Lihi Lotker, Author at Coho AI

Unraveling the Layers: Hyper-Personalization as the Pinnacle of User Engagement

The Journey from Personalization to Hyper-Personalization in the Digital Age

In the pre-internet era, the scope of personalization was somewhat limited by the amount and type of information businesses could gather about their customers. The brick-and-mortar stores of yesteryears had their own methods of recognizing loyal customers.

The Beginning of Advanced Personalization

The rise of the internet fundamentally changed the game. Suddenly, businesses had access to a wealth of information about their customers’ preferences, behaviors, and interactions, all logged in digital format, ready for analysis. Every click on a webpage, every item added to an online shopping cart, every “like” on a social media post – these actions produced data points that, when aggregated and analyzed, provided a granular view of the customer’s behavior and preferences.

This digital transformation enabled companies to move beyond the traditional methods of personalization. E-commerce giants, for example, could now track and analyze the browsing history of their users, allowing them to recommend products with greater accuracy. Similarly, content platforms could curate and suggest media based on viewing or reading histories.

Artificial Intelligence and Predictive Analytics: Ushering in Hyper-Personalization

However, this was just the beginning. As technologies advanced, especially with the integration of Artificial Intelligence and Machine Learning, the amount of actionable data skyrocketed. Not only could businesses track what users were doing, but with predictive analytics, they could also forecast future actions, tastes, and preferences with a degree of precision previously thought impossible.

This evolution ushered in the era of hyper-personalization. Now, businesses could tailor user experiences not just based on past behaviors but also in real-time. For instance, if an online shopper looked at a product but didn’t make a purchase, they could be retargeted with a tailored ad or a special discount for that very product as they browsed other sites. Streaming services could adjust content suggestions based on time of day, viewing history, and even current global events.

In essence, the digital revolution transformed personalization from a game of educated guesses based on limited data to a sophisticated, data-driven strategy that considers myriad factors to create deeply individualized user experiences.

Technological Drivers Behind Hyper-Personalization

As industries veer towards more individualized interactions, understanding the technology propelling this shift becomes essential. At the core of this evolution are AI and machine learning, which are reshaping how businesses interact with and understand their customers.

Diving Deeper into AI and Machine Learning

Artificial Intelligence (AI) and machine learning stand out as the primary catalysts for the current hyper-personalized age. They have the remarkable ability to digest, analyze, and make sense of immense data pools in real-time. This capability provides businesses with insights at an unprecedented rate, facilitating more informed decisions about user preferences and predicting future behaviors.

Machine learning, a subset of AI, further refines this process by continuously learning and adapting to new data. Over time, these systems can autonomously improve, making their predictions more accurate and their personalization techniques more precise.

Comparative Dynamics: Hyper-Personalization vs. Personalization:

Here’s a more in-depth look at how traditional personalization stacks up against the advanced realm of hyper-personalization:

Aspect	Personalization	Hyper-Personalization
Data Utilized	Demographics, Previous Purchases	Real-time Behavior, Emotions, Current Context
Technology Drivers	Basic Algorithms, Cookies	AI, Machine Learning, IoT
Outcome	Generic Recommendations, Broad Segmentation	Individualized Experiences, Dynamic Content & UI Adjustments
Scope	Reactive (Based on Past Actions)	Proactive (Predictive Modeling of Future Actions)

Harnessing Real-Time Data Analytics

Real-time data analytics stands as another pillar supporting the hyper-personalization framework. In the digital age, actions on the web, from clicks to scrolls, are tracked. This constant influx of real-time data, when paired with AI, can power instantaneous personalized interactions, creating experiences that feel bespoke for every user.

The power of real-time analytics lies in its capacity to capture the user’s present context, going beyond past behaviors. For businesses, this means being able to present the user with relevant content or product recommendations precisely when they are most likely to engage or convert.

Industry Case Studies: Leading the Charge in Hyper-Personalization

Netflix: A Tailored Viewing Experience

When you think about personalized content recommendations, Netflix probably tops the list. But there’s so much more beneath the surface. Beyond merely suggesting shows or movies, Netflix harnesses advanced algorithms to learn from your viewing habits. If you consistently pause a certain genre or skip episodes of a specific series, the platform notices. Over time, Netflix doesn’t just offer show suggestions but also modifies its interface. Ever noticed how the artwork for movies or shows might change occasionally? That’s hyper-personalization at work. It’s not about merely pushing content but shaping an entire experience tailored to your viewing preferences.

Amazon: Crafting a Unique Shopping Expedition

Amazon, the e-commerce behemoth, takes hyper-personalization to another level. Each user’s journey on Amazon is like a fingerprint – unique and distinctive. Start with product recommendations, which are based on an amalgamation of your viewing history, past purchases, wish lists, and more. Dive deeper, and you’ll notice the dynamic pricing strategies, where prices might subtly shift based on demand, user interest, and browsing history. Even the homepage layout is tailored! For instance, if you’ve been browsing fitness equipment lately, expect to see deals and promotions related to that on your next visit. It’s not just about selling a product; it’s about creating a personalized shopping narrative for each user.

Spotify: The Sound of Personalization

In the realm of music streaming, Spotify emerges as a paragon of hyper-personalization. Users worldwide laud the platform’s “Discover Weekly” playlist – a curated selection based on individual listening habits, song skips, and favorites. Furthermore, Spotify’s real-time contextual playlists, such as “Rainy Day Blues” on a drizzly evening, showcase the platform’s commitment to enhancing the overall user experience through mood and environment-based curation.

E-Commerce Platforms: A Global Shift Towards Individual Experiences

While giants like Netflix, Spotify and Amazon dominate discussions around hyper-personalization, they aren’t the only players in the game. E-commerce platforms, both big and small, are recognizing the profound impact of tailoring experiences. By leveraging real-time data analytics, these platforms can track nuanced details such as how long a user hovers over a product, the path they take through the site, or even their scrolling speed. Armed with this data, websites can dynamically adjust. Imagine an e-commerce site reshuffling product placements based on your browsing history or showcasing a pop-up deal just when you’re about to leave. It’s not science fiction; it’s the new reality of online shopping, ensuring users feel seen, understood, and catered to at every click.

The Future of Hyper-Personalization

Bridging the Gap Between Physical and Digital

With advancements in technology, the once distinct boundaries between the physical and digital worlds are becoming increasingly intertwined. Wearable technology, like fitness trackers and smartwatches, are becoming essential tools for many in their daily lives. Imagine a day when after an intense workout, your fitness tracker communicates with your refrigerator, suggesting a protein-packed smoothie recipe. Or consider the potential of the Internet of Things (IoT) – where seemingly ordinary devices are embedded with technology, enabling them to communicate and interact over the internet. In the near future, cars might not just be modes of transportation but could become personalized environments. Imagine your vehicle detecting increased stress levels via your smartwatch and automatically playing calming music or adjusting the lighting to help you relax.

Ethical Concerns in a Hyper-Personalized Era

The future indeed appears promising, but it’s not devoid of concerns. As businesses gain access to an ever-growing amount of personal data, the potential for misuse or unintended breaches increases exponentially. It’s essential that companies prioritize not just the potential of hyper-personalization, but also the ethics that must underpin its use. Ensuring transparency about data collection processes, prioritizing user rights, and allowing users greater control over their data will be paramount. Moreover, continuous education for teams is essential to ensure they understand the implications of their actions and the responsibility that comes with handling such extensive user data.

In Conclusion

The Dawn of a New Engagement Era

Hyper-personalization is not just another buzzword; it signifies a seismic shift in the way businesses perceive and interact with their users. No longer are customers seen as mere statistical entities; they are understood in their uniqueness, with tailored experiences crafted to resonate deeply with their individual preferences and lifestyles.

Challenges & Opportunities Ahead

While the benefits of hyper-personalization are vast, the challenges it presents are equally significant. From navigating the complex terrain of data privacy laws to ensuring that personalization feels organic and not invasive, businesses have their work cut out for them. However, those willing to invest the time, resources, and heart into understanding hyper-personalization’s intricacies will not just stay relevant – they’ll lead. The future belongs to businesses that can transform their user engagements from mere interactions to profound, transformative experiences.

As we stand at the cusp of this exciting new era, it’s clear that the future of user engagement is not just personal – it’s hyper-personal.

The Evolution and Future of Customer Segmentation

Introduction

Customer segmentation continues to be a cornerstone strategy for businesses, providing invaluable insights for targeted engagement and product development. Initially limited to optimizing marketing campaigns, segmentation has expanded its horizons, now playing a crucial role in enhancing user experience and guiding product development. But what exactly does the future hold for customer segmentation, especially with advancements in AI? This article will explore the dual purpose of customer segmentation, its future trajectory with AI, and delve into the types of segments commonly used in the industry.

Let’s dive into how customer segmentation serves dual purposes: improving user experience and making products better. Along the way, we’ll see how AI is revolutionizing the field and go over the different types of customer segments out there.

What is Customer Segmentation?

Customer segmentation is the practice of dividing a company’s customer base into specific groups based on various attributes like demographics, psychographics, and behavioral patterns. By doing this, businesses aim to allocate resources more efficiently, target marketing campaigns, and provide personalized experiences.

The Dual Purpose of Customer Segmentation

Traditionally a cornerstone for marketing efforts, customer segmentation now serves a dual function:

Understanding User Interactions: Businesses today are increasingly interested in how users interact with their products. Metrics like frequency of usage, feature interaction, and time spent on the platform provide valuable insights. Analyzing this data allows for data-driven product development and refinement.
Delivering Unique Experiences: Identifying different customer segments enables companies to offer tailored user experiences. This could manifest as personalized recommendations, customer-specific offers, or even unique user interfaces.

Types of Segments

As the purpose of segmentation has diversified, so have the types of segments. Here are some common types:

Demographic Segmentation: This is the most basic form, dividing customers by age, gender, income, etc.
Psychographic Segmentation: This type considers psychological aspects like lifestyle, values, and attitudes.
Behavioral Segmentation: Here, customers are segmented based on their behavior such as usage frequency, loyalty, and spending.
Geographical Segmentation: This type focuses on location-based categorization.
Temporal Segmentation: This newer form considers the time at which a customer interacts with a product, seasonal purchasing patterns, etc.
Value-Based Segmentation: This focuses on the customer’s lifetime value, segregating high-value customers from low-value ones for targeted efforts.

The Future of Customer Segmentation: The Role of AI

Auto-Segmentation Through AI

One of the most exciting developments in the realm of customer segmentation is the application of AI for auto-segmentation. These algorithms can sift through extensive data sets, identifying patterns that might take human analysts months to spot. Machine Learning models can perform real-time analysis, flagging bottlenecks or pain points for immediate action, thus accelerating product development cycles.

Predictive Segmentation

Beyond just identifying existing patterns, AI algorithms can predict future changes within segments. Predictive segmentation can forecast how customer behaviors and preferences will evolve over time, allowing businesses to adapt proactively rather than reactively.

Advanced Types of Segmentation

AI’s computational power allows for more intricate segmentation types, such as sentiment analysis, real-time segmentation based on incoming data, and even predictive lifetime value segments. These nuanced categories can provide deeper insights into user interaction and facilitate hyper-personalized experiences.

Ethical Considerations

As AI takes on a larger role in customer segmentation, ethical considerations, particularly around data privacy and consent, will become increasingly significant. Businesses will need to ensure that their use of AI for segmentation complies with privacy regulations like GDPR, and that data is handled in a transparent and secure manner.

Conclusion

The future of customer segmentation is not just promising; it’s transformative. With the dual purpose of improving user experience and guiding product development, segmentation has become a multidimensional tool that, when powered by AI, has limitless potential. Advanced types of segments, real-time and predictive analysis, and ethical considerations are the key areas to watch out for. As we continue to move into an era of data-driven decision-making and personalized experiences, AI-powered customer segmentation will likely become a staple in business strategy, altering the way we understand and engage with consumers.

With these advancements, customer segmentation is set to become not just a business strategy, but a comprehensive tool for sustained competitive advantage.

Product-Led Growth 101: A Glossary of Essential Terms

In 2023, according to Open View Partners, only one-fifth of SaaS companies have seen a growth rate of at least 75% year-on-year. However, PLG leaders have still managed to grow at twice the rate of traditional SaaS companies. The adoption of PLG has expanded across the software landscape, and tracking product-qualified leads (PQLs) or accounts (PQAs) has boosted the likelihood of fast growth by 61%.

By now, you’re likely familiar with the concept of product-led growth (PLG), which was extensively covered in a past article. But to truly master the verbiage of product-led growth and effectively implement its principles, it’s quite essential to be well-versed in the associated terminology.

Although you may already know some bits about PLG, a little guidance to catch up with the intricacies of product-led growth might help:

Understanding the Market

Addressable Market : The specific segment or group of potential customers that a product or service can effectively target and serve.
Blue Ocean Companies: Innovative organizations that create new markets and demand, making the competition irrelevant.
Red Ocean Companies : Businesses in saturated markets aiming to outperform competitors.
Total Addressable Market (TAM): The total revenue opportunity for a product, accounting for potential future expansion.

User Engagement & Experience

Activation Barriers: Obstacles or hurdles that prevent users from fully adopting and engaging with a product or service.
‘A-Ha’ Moment: The point at which a user realizes the value and benefits of a product or service, often leading to increased engagement and continued usage.
User Experience (UX): Users’ overall experience and satisfaction when interacting with a product or service.
User Journey: The path or stages users go through when interacting with a product, often involving steps like activation, discovery, conversion, and scaling.
Stickiness: Refers to the degree of engagement and loyalty that users have towards a product.
Time To Value (TTV): The amount of time it takes for a user to derive value or achieve their desired outcome from using the product.
Self-Serve: A model that allows users to onboard and use a product or service independently, without assistance.

Product Development & Features

Enterprise Product Development (EPD): The comprehensive process of bringing a product from its conceptualization to its launch within a company.
Feature Adoption Rate: The rate at which users adopt and utilize specific features of a product.
Workflow: The sequence of tasks and processes an organization follows to complete a specific project or achieve specific goals.
Product-Market Fit: The alignment between a product and its target market.

Growth Strategies & Models

Bottom-Up Selling: Emphasizes simplicity and fast acceptance.
Marketing-Led Growth: Focuses on acquisition through marketing efforts.
Sales-Led Growth: Relies on sales teams and human intervention for growth.
Growth Loops: A framework for driving growth by creating a cyclical process for continuously engaging users.
Freemium Model: A pricing model with free basic features, but advanced features require payment.
Go-To-Market (GTM): Launching and promoting a new product to customers.
Value Metric: A measurement companies use to assess the value generated in exchange for their product.
Value-Based Pricing: A pricing strategy largely relying on the customer’s perceived product value.
Channel: The marketing and distribution channels that are scalable and cost-effective for product-led growth, such as word-of-mouth, content marketing, or low-cost CPC advertising.
Sales Cycles: The time it takes for a customer to move through the sales process, from initial contact to making a purchase.

Customer Metrics & Analytics

Advanced Analytics: Tools that uncover insights through data analysis.
Average Revenue Per User (ARPU): The average amount of revenue generated per user or customer.
Churn Rate: The rate at which customers or users discontinue or unsubscribe from a product or service.
Customer Lifetime Value (CLV): The predicted revenue a customer will generate over their relationship with the company.
Effort Analysis: Quantitative method to understand users’ difficulty navigating through each step of a digital experience.
Net Promoter Score (NPS): A metric used to measure customer satisfaction and loyalty.
Product Qualified Leads (PQL): Leads that have demonstrated an interest and derived value from the product, suggesting a higher likelihood of becoming customers.
Product Qualified Accounts (PQA): Accounts that have actively used and gained substantial benefit from the product, signaling a potential for conversion or growth.
Segment Analysis: Grouping users based on their behaviors to identify patterns.
Time-Based Cohort Analysis: Examines user behavior and engagement patterns over different time periods.

Models & Frameworks

Fogg’s Behavior Model: States that Motivation, Ability, and a Prompt must converge simultaneously for a behavior to occur.
Hook Model: Focuses on creating strong user habits through triggers, actions, rewards, and investments.
RICE Framework: A framework used to prioritize projects or initiatives based on their potential impact, effort required, confidence level, and resources available.
Customer-Centric: A strategy prioritizing exceptional customer experiences by placing the customer at the core of products, ideas, philosophy, and operations.
SaaS (Software-as-a-Service): Software delivery model where applications are accessed through the internet and provided on a subscription basis.

Top 5 Must-Read Books for Product-Led Growth Enthusiasts

Henry Truman once said that “Not all readers are leaders, but all leaders are readers.” No matter how many technological advancements we will live to see, there is one medium that will never become outdated – Books. There is nothing, absolutely nothing, quite like a good book. No matter the wave of technological advancements, one medium will always hold its relevance – Books. Nothing can quite replace the depth and breadth of knowledge that a well-written book can provide.

Whether you’re aspiring to master the art of PLG or attain the competency to lead growth-focused teams in your organization, these five books are absolutely essential. Each one of them carries a treasure trove of knowledge, lessons, and frameworks that, when applied correctly, will provide a strategic advantage in crafting successful PLG initiatives.

Here is your top 5 must-read list –

1. “Product-Led Growth: How to Build a Product That Sells Itself” by Wes Bush

Mastering the Art of Onboarding

Kicking off our list is the influential work by PLG expert, Wes Bush. “Product-Led Growth: How to Build a Product That Sells Itself” is a seminal guidebook in the realm of product-centric organizations, offering comprehensive, deep-dive insights into the creation of a product that inherently generates demand. Bush paints a vivid picture of the transformational shifts that modern-day organizations need to embrace, underlining the cardinal role that onboarding, customer satisfaction, and feedback play in propelling a product-led growth model.

In this exhaustive treatise, Bush stresses the importance of elevating the product as the heart and soul of your business. He highlights the significance of captivating customers right from their initial interaction and maintaining that engagement throughout their journey with your product. The power of a strong first impression cannot be overstated. Bush expounds on how successful onboarding can transform a casual user into a loyal advocate. It’s not just about familiarizing users with your product, but also about demonstrating value quickly and creating an experience that’s hard to abandon.

Customer Satisfaction as a Growth Driver

Equally noteworthy is the book’s exploration of customer satisfaction and its undeniable role in growing a product-focused business. Bush argues that it’s not enough for a product to meet the needs of a customer. It should go a step further, exceeding expectations and providing delight with every interaction. In this way, the product itself becomes a driver of growth.

The Cardinal Role of Feedback in PLG

The critical role of feedback in the PLG paradigm is also examined in-depth. Bush asserts that a PLG company is always listening, constantly collecting user feedback to refine and improve its product. By incorporating feedback loops, organizations can create products that evolve along with the needs of their customers, ensuring long-term user engagement and loyalty.

“Product-Led Growth: How to Build a Product That Sells Itself” is not just a book but a rich repository of knowledge, strategies, and actionable insights that are indispensable to constructing a thriving, product-focused business. By the time readers turn the last page, they are equipped with a deep understanding of PLG and the practical knowledge needed to implement its principles in their own organizations. This book is not just a masterclass in PLG but a blueprint for building a business that is capable of driving sustainable, customer-centric growth.

2. “The Product-Led Organization: Drive Growth by Putting Product at the Center of Your Customer Experience” by Todd Olson

Leveraging Customer Feedback for Growth

Todd Olson’s insightful work, “The Product-Led Organization: Drive Growth by Putting Product at the Center of Your Customer Experience”, elucidates a structured approach to transforming into a product-led organization. The book underscores the criticality of placing the product at the core of the customer experience and propounds efficient methodologies to realize this ambition. Drawing from a wealth of personal experience, Olson offers invaluable insights into embracing a product-centric mindset, deeply understanding customer needs, and synchronizing various organizational teams around the central premise of the product.

An important aspect Olson explores in his book is the power of customer feedback. He elaborates on how product-led organizations leverage feedback not just for remedial action, but also for continuous product improvement. He believes that customer feedback, both positive and negative, is an essential ingredient in the process of refining a product and creating an offering that hits the mark every time.

Importance of Data-Driven Insights

The book further stresses the significance of data-driven insights to enhance the customer journey and foster growth. It offers advice on establishing effective metrics, tracking user behavior, and using these insights to make informed decisions that elevate the user experience. Olson explains how data can be a powerful tool for improving user experience and delivering a product that effectively solves customer problems and fulfills their needs.

“The Product-Led Organization: Drive Growth by Putting Product at the Center of Your Customer Experience” is more than just a book; it is a well-crafted guide and a vital resource for anyone aiming to adopt a PLG approach. With its practical insights and actionable strategies, this book lays the groundwork for building and nurturing a truly product-led organization.

3. “Onboarding Matters” by Donna Weber

Donna Weber’s “Onboarding Matters” is an enlightening read, particularly for SaaS businesses looking to leverage a product-led growth model. Weber, through her years of experience and expertise in customer success, articulates the critical role of effective onboarding to the success of freemium products and businesses. She strongly believes that successful user activation largely relies on excellent onboarding procedures, and that a seamless and engaging onboarding experience is the linchpin of converting free users into paying clients.

Customizing Onboarding Experiences

One of the unique aspects that Weber covers in this book is how different user personas may require tailored onboarding experiences. She sheds light on the intricacies of onboarding for B2B SaaS solutions, arguing that they are more complex than those for consumer-oriented services. She contends that there is no one-size-fits-all onboarding method and hence, emphasizes the need for a flexible and adaptable approach to onboarding that caters to the unique needs of different user personas.

Weber’s Orchestrated Onboarding: A Game-Changer

Weber goes a step further to introduce the concept of “Orchestrated Onboarding,” a recurring theme throughout the book. According to her, a well-orchestrated onboarding process not only facilitates seamless internal communication but also provides an open channel for engaging with customers. The ultimate goal of orchestrated onboarding, as Weber suggests, is to deliver a unified customer experience by eliminating the silos between departments.

Weber’s ability to weave her experiences into practical advice makes this book an invaluable resource for B2B growth teams, particularly those in the SaaS domain. Her detailed explanations, clear-cut strategies, and the emphasis on putting the customer at the center of the onboarding process make this book a must-read for those looking to improve their onboarding process and, consequently, their customer retention rates.

Furthermore, Weber highlights the role of a smooth onboarding process in allowing new customers to realize the return on their investment. She underscores that the perceived value of your product is directly related to how effectively new users are onboarded and integrated into the product experience.

This nuanced view on the role of onboarding in driving customer satisfaction and product success is what sets Weber’s “Onboarding Matters” apart, making it a must-read for anyone looking to delve deeper into the intricacies of customer success in the realm of product-led growth.

4. “Monetization Innovation” by Madhavan Ramanujam & Georg Tacke

The Undervalued Power of Monetization and Pricing

Madhavan Ramanujam and Georg Tacke’s “Monetization Innovation” is a must-read for anybody involved in growth, especially those working in the B2B SaaS and Product-Led Growth (PLG) industries. Despite being critical components of the business model, monetization and pricing often don’t receive their due attention. However, in the context of B2B SaaS and PLG businesses, the pricing structure and strategy bear even more significance.

To stimulate customer acquisition and minimize entry barriers, it is essential to offer a free version or trial of your product. However, this necessitates the formation of precisely calibrated price tiers and compelling feature bundling to incentivize upgrades.

Pricing Strategy as a Catalyst for Customer Acquisition

The authors articulate that the success of PLG can largely be attributed to its dual focus on easing entry points and facilitating upgrade inducements.

“Monetization Innovation” does a stellar job at dissecting and laying out the fundamentals of pricing and monetization. It walks the reader through an expansive spectrum of topics: devising strategy, blueprinting a model, conducting customer interviews, interpreting quantitative data, and much more. Aspiring to harness newer avenues of revenue generation, this book serves as an essential reservoir of knowledge.

Ramanujam and Tacke also stress on the importance of understanding and leveraging this dual emphasis for RevOps and sales executives. By aligning their sales strategies with well-defined price tiers, they can effectively shepherd prospects through the sales funnel. This alignment, prioritizing customer experience, yields increased conversion rates and cultivates loyalty among existing customers.

Thus, “Monetization Innovation” emerges as an imperative read for individuals and organizations that aim to thrive in a product-led business environment, equipping them with the crucial understanding of the monetization dynamics and the prowess to execute successful pricing strategies.

5. “The Lean Product Playbook” by Dan Olsen

Bridging the Gap between UX Design and Lean Methodologies

Dan Olsen’s book, “The Lean Product Playbook”, stands as an invaluable guide to constructing products that customers truly appreciate. Offering a systematic approach, Olsen outlines the process to attaining Product-Market Fit. The book serves as a thorough manual for applying lean methodologies in the realm of product development, propelling the readers to deeply understand customer needs, create a compelling value proposition, and grasp the importance of validated learning through progressive product enhancements.

Achieving Product-Market Fit: A Lean Approach

By combining user experience (UX) design with lean startup methodologies, Olsen paints a comprehensive picture of ideation, prototyping, user testing, and analytics. He places a strong emphasis on data-driven decision-making and evidence-based adjustments, establishing the book as an indispensable resource for anyone striving to create a product-led organization.

Leaders and entrepreneurs will find in “The Lean Product Playbook” the knowledge and practical guidance they need to navigate the intricate paths, avoid common pitfalls, and maximize the promising opportunities in the product-led growth landscape. This book equips its readers with a broad understanding of lean product development, preparing them to propel their business towards substantial growth.

With its focus on combining UX design with lean startup methodologies, it covers essential topics such as ideation, prototyping, user testing, and analytics. This book is an indispensable resource for those looking to create a product-led organization, providing the knowledge and practical guidance needed to navigate the challenges and maximize the opportunities in the world of PLG. By investing time in this book, leaders can equip themselves with a holistic understanding of lean product development, preparing them to drive their business to new heights.

In conclusion, all these books are uniquely beneficial in providing insightful guidance to build a successful product-led organization. They cover a range of aspects from the fundamental understanding of PLG to practical strategies, monetization, customer onboarding, and achieving product-market fit. Each book offers different perspectives, which when combined, provide a comprehensive understanding of PLG. Reading these books can significantly enhance one’s knowledge and skills in the PLG domain, preparing them to drive their organization towards becoming truly product-led. However, it’s worth noting that while these books offer valuable insights and guidance, it is the diligent application of these learnings that will ultimately pave the path towards success.

Leveraging User Behavior for Better Lead Scoring in a PLG Model

Without analytics, tech teams rely on insufficient demographic data or vanity metrics, hindering their ability to personalize services and understand customer preferences. So far, Openprise estimates that only 35% of revenue operations leaders possess full confidence in their capability to score leads accurately.

User behavior insights in a product-led growth (PLG) model lead to more accurate lead scoring, better resource allocation, and increased revenue generation. Adopting PLG strategies and aligning investments with user needs and market goals drives sustainable growth and profitability. Analyzing user behavior enables businesses to make informed decisions, enhance the user experience, and maximize their data’s potential for success.

How to Deploy User Behavior & Analytics?

User behavior denotes all the actions a user performs on a website or mobile app. It includes factors like time on the page, the number of pages visited, how people interact with different features, and also friction they encounter while using the product, etc.

Behavioral analyses help companies gain detailed metrics and segmentations to identify bottlenecks within their software or service, gauge customer reactions to investment messages, assess satisfaction with feature changes, determine the effectiveness of ads, analyze the conversion journey timeline, and improve the overall success of their product for customers. However, utilizing behavioral analysis effectively can be challenging, often due to the company’s lack of clear vision.

Exploring the Advent of User Data

McKinsey estimates that businesses capitalizing on customer data insights enjoy 85% greater revenue growth and over 25% higher gross margin than their competitors. As a result, businesses have begun to utilize behavioral data, ushering in a period of hyper-personalization in which firms compete to get a more nuanced knowledge of customer interactions.

Measures of user behavior on a website or mobile app, such as the amount of time spent there, the number of pages seen, the number of times a feature is used, and the amount of difficulty experienced by the user, are all considered part of user behavior. In a product-led growth (PLG) paradigm, organizations may improve their lead-scoring procedures by analyzing and understanding user behavior, resulting in more precise identification and prioritization of new customers.

ProductLed found that 91% of B2B SaaS businesses have already adopted the PLG strategy and want to boost expenditures in PLG efforts this year. This exemplifies the increasing appreciation for the value of exploiting user behavior inside a PLG framework.

Deploying User Behavior Data for Lead Scoring & PLG

Although various factors beyond your product alone influence user behavior, Lead scoring is improved as businesses learn how customers interact with a product. The possibility of a lead becoming a paying client may be estimated using data on user behavior as signs of interest, engagement, and intent. Considerable insight into a lead’s interest and propensity to buy may be gleaned from their use patterns, feature preferences, and engagement with marketing material.

Hence, pursuing better data-driven choices and more efficiently deploying sales resources is possible by analyzing user behavior in a PLG model. Sales teams may increase their conversion rate and revenue creation by focusing on the leads with the highest potential of converting into customers.

Leveraging behavioral data is a critical but overlooked component for measuring the effectiveness of Key Performance Indicators (KPIs) and making necessary adjustments. In PLG companies, the product serves as the primary source of data collection, w essential for driving growth and generating revenue. By analyzing this data effectively, companies can uncover valuable insights that guide their expansion and success.

3 Pillars of Efficient Product-led Growth

Gainsight outlines that “product experience data combines a wider data set, such as user sentiment, that allows teams to pull insights about intent, quality of user’s customer journey, and effective ways to expand each user’s product adoption.”

Hence, forward-thinking businesses may learn more about a lead’s potential for conversion based on their activities in using a PLG model to score leads based on their behavior. Particularly in sectors where customer interactions can be tracked and analyzed in great detail, this method enables more efficient prioritization of sales efforts and improved decision-making. According to Open View Partners, 3 pillars empower viable PLG:

Pillar 1: Design for the end user –

Designing for end users means prioritizing their needs and understanding the problems they want to solve. Successful product-led growth businesses put the needs of real people first and commit to continuously improving their products to effectively address those needs. Companies can create a user-centric experience that drives satisfaction and loyalty by listening to users and making consistent enhancements.

Pillar 2: Deliver value before capturing value –

In a give-and-take relationship with users, providing value upfront before expecting anything in return is essential. Product-led companies focus on delivering value quickly, often through free trials, freemium models, or open-source offerings. The key is for users to experience the product’s value first-hand, either by solving their problem quickly or by reaching a pivotal “aha” moment. By simplifying the initial product experience and removing barriers, companies ensure users can easily access and recognize the product’s core value.

Pillar 3: Invest in the product with go-to-market intent –

The upfront investment in creating software can yield substantial long-term benefits. PLG companies understand that the cost of delivering value to additional customers is significantly lower than that of professional services. This includes gathering comprehensive product data to track user behavior, establishing a growth function that enhances distribution and value capture, and conducting go-to-market experiments to optimize the user journey. Companies can drive sustainable growth and profitability by aligning product investments with acquisition, conversion, and expansion goals.

Bottom Line

Acquiring clarity on the desired user path, a clear product roadmap, achievable goals, understanding market demands and product change requirements, and specific objectives such as revenue generation or increasing customer satisfaction are essential.

Thus, those interested in leveraging user behavior data to improve lead scoring companies must define their expectations and ideal user paths before analyzing data, as generic data alone cannot magically solve unidentified problems. With predefined expectations, teams can identify deviations from the ideal path and make necessary adjustments to enhance the user experience and lead scoring, improving the PLG model.

Free trials, when used effectively, help users understand the potential benefits of a product or service without any initial financial commitment, thereby reducing entry barriers and making the decision process smoother. From a business perspective, free trials can significantly drive user growth and conversion rates.

Optimizing Free Trial Strategies: A Blueprint for SaaS Businesses

The significance of free trials in SaaS-based businesses is immeasurable. As a compelling strategy in the toolkit of a product manager, free trials serve a dual purpose: They act as a customer acquisition tool and as a solid building block in establishing long-lasting customer relationships.

Free Trial Benchmarks

For SaaS businesses to effectively acquire customers and generate revenue, free trial benchmarks are crucial. In order to evaluate the success of your own trial initiatives, you must understand the typical conversion rates and performance metrics associated with free trials.
Typically, in the dynamic SaaS industry, free trial conversion rates ranged from 1% to 10% a decade ago, with most businesses falling within the 2%-5% range. As this industry has evolved in recent years, benchmarks have gone up to 20%, 40% and even higher.
Which shows why it’s important to recognize that the landscape of the SaaS industry is constantly evolving, and customer expectations are evolving alongside it which means your company can’t just set and forget free trials and must evolve with it as well
It is crucial to acknowledge that the SaaS industry is in a constant state of evolution, accompanied by evolving customer expectations. Because of this, companies cannot afford to adopt a “set it and forget it” approach to free trials. In order to remain relevant and meet their customers’ needs, they must proactively adapt and evolve

Choosing the Right Free Trial Type

There are primarily three types of free trials, and choosing the right one depends on your product, your goals, and your audience.

Time-Limited Trials

The first type, time-limited trials, provide full access to all features for a specific duration, usually between 7 to 30 days. This model gives users an immersive experience of the product, with the aim of showcasing its full potential and driving the users towards a purchase decision.

Feature-Limited Trials

Feature-limited trials restrict access to certain advanced or premium features while giving free access to the basic ones. This approach works best when your product has unique features that distinguish it from competitors.

Usage-Limited Trials

Usage-limited trials, on the other hand, offer unlimited time access but limit the usage, for instance, the number of projects that can be created or the amount of storage available. This model can be effective in products where long-term usage is crucial for realizing the product’s value.

Cracking the Code: Free Trial Metrics

Next comes a critical component of a free trial strategy: metrics. Monitoring the right metrics helps businesses understand user behavior, gauge the trial’s effectiveness, and make data-driven decisions to optimize the trial process.

Key Metrics to Monitor

When it comes to tracking performance, there are three free trial key metrics to keep a close eye on:

Number of Sign-ups: This metric provides a snapshot of how many users are interested in trying your product. It serves as the starting point of your funnel.
Activation Rate: This percentage measures the users who take a meaningful action (like completing a project or achieving a milestone) during the trial period.
Conversion Rate: This is arguably the most crucial metric. It measures the percentage of trial users who become paid customers, thereby directly impacting your revenue.

How to Calculate These Metrics

Calculating these metrics is straightforward yet essential as tracking any other key KPIs . The activation rate can be calculated by dividing the number of users who achieved a meaningful action by the total number of users who signed up for the trial.

The conversion rate is calculated by dividing the number of users who converted to paid customers by the total number of users who signed up for the trial. This key metric helps you understand the efficacy of your free trial in converting users to paid customers.

Essential Aspects Often Overlooked

There are often-overlooked aspects in managing a successful free trial strategy:

Smooth User Onboarding

Ensure user onboarding is as smooth as possible. The easier it is for users to get started, the higher the chance they will explore your product in depth.

Guidance for Achieving Outcomes

Provide users with guidance on how to achieve meaningful outcomes with your product. This could be via email, in-app messages, or a dedicated support team.

Monitoring User Engagement

It’s not just about sign-ups and conversions, pay attention to user engagement during the trial period. This can give insights into potential roadblocks or opportunities for improvement.

Best Practices for Optimizing Your Free Trial Strategy

Maximizing the impact of your free trial requires a strategic approach that extends beyond simply monitoring metrics. Below are some tried-and-true best practices to optimize your free trial strategy:

Personalize the trial experience

Tailor the free trial experience to match the user’s needs, preferences, or use cases.

Communicate value constantly

Regularly highlight the benefits and value your product brings to the user during the trial period.

Use a combination of trial types

Depending on the user persona, you may want to offer different types of trials (time, feature, or usage-limited) to cater to different user expectations and requirements.

Test and iterate

Regularly test different aspects of your trial strategy (duration, type, communication, etc.) and iterate based on the results.

Proactively engage with the users

Don’t wait for the user to reach out. Proactively ask for feedback, provide support, and address any potential issues the users might face.

Wrapping Up

Free trials are a pivotal part of any SaaS business. It’s not just about offering a glimpse of your product, but about fostering a relationship with potential customers. From choosing the right trial type to closely monitoring metrics and fine-tuning the process, a well-executed free trial strategy can drive user growth and revenue while setting the foundation for long-term customer relationships.

Navigating the Shift From Sales-led to product-led

The world of business is filled with paradigms, models, and frameworks, each promising a path to success. But few shifts in thinking have been as transformative as the one from sales-led to product-led growth. It’s not merely a change in focus or a new buzzword; it’s a foundational alteration in how B2B companies approach growth, where products become the primary drivers, reshaping strategies, customer interactions, and even the cultural fabric of organizations.

While product-led growth (PLG) has captured the imagination of many and has become a dominant model, it is essential to underline that it is not a universal solution. The decision to adopt PLG or a hybrid model integrating both sales and product-led strategies must be finely tuned to the unique needs, strengths, and goals of a company. The path to PLG may include leveraging sales teams for upsells or handling complex deals, recognizing that traditional methods still have their place in the modern business landscape.

Since 2020, Pendo found that 89% of product leaders perceive their companies as being product-led. Gartner predicts that by 2025, 75% of SaaS providers will implement product-led growth techniques to foster growth and expansion among their existing customer base. This revolution places products at the forefront, serving as the primary growth driver within these organizations. It signifies a fundamental change in perspective, highlighting the critical role that products play in shaping the overall success and trajectory of the company.

Product-led Growth versus Sales-led Growth

We already discussed that different models fit different companies, but to understand the shift from product-led growth towards sales-led growth, we should assess the main differences between these two major growth avenues.

Emphasizing Product Experience

Product-led sales prioritize the product experience as the primary driver of sales, whereas traditional sales methods focus on relationship-building and outreach efforts.

Sales Processes

Product-led growth follows a product-centric and often self-service sales process, whereas traditional sales methods emphasize face-to-face interactions and sales pitches.

Sales Cycle Time

Businesses with a product-led approach have a significantly shorter sales cycle, as customers can use the product to understand its value and make informed buying decisions. In contrast, traditional sales methods often involve a longer sales cycle due to the need for relationship-building and decision-making.

Lead Generation

Lead generation for product-led sales relies on the product itself. However, traditional sales methods mostly rely on external lead sources like events, cold calls, and email campaigns.

Exploring the Benefits of Product-led Growth

Quite frankly, product-led growth empowers businesses to unlock new possibilities, seize opportunities, and deliver exceptional value to customers at every stage. Why should the most innovative businesses consider product-led sales? Well, these benefits make the case for its unprecedented potential:

Diminishing Customer Acquisition Costs (CAC)

All product-led growth organizations have lower CAC since they don’t need to invest much in marketing and advertising. As word-of-mouth promotes your product, new people will sign up for the free or low-cost versions and eventually upgrade to the paid versions.

Enhanced Product Feedback

Listening to the customer experience will lead you to spend more time gathering feedback now that your product will be front and center.

Improved User Retention

Users who try a product and don’t like it tend to quit using it. However, product-led businesses aim to provide user-friendly solutions to actual issues. Therefore, your firm will retain more customers if it prioritizes the product above everything else.

Greater Median Enterprise Value

OpenView reports that “the median enterprise value (EV) of PLG companies is 2X higher than the public SaaS index as a whole.” Companies with a strong focus on their products tend to create solutions that better serve their customers. Customers will return and may even tell others about your goods if you do a good job.

Faster Revenue Growth

According to Bain, companies that primarily rely upon PLG have a higher success rate in exceeding the Rule of 40 and the more ambitious Rule of 50. The Rule of 40 states that a company should have a combined revenue growth rate and EBITDA margin of at least 40%. Similarly, the Rule of 50 sets a higher bar with a combined rate of 50%.

Challenges of Implementing Product-led Sales

Notwithstanding the possibilities introduced by product-led sales, several challenges prevail:

Addressing Implicit Biases

When analyzing usage data, it’s essential to acknowledge and address the implicit biases that product teams may have. By fostering a culture of self-awareness and encouraging diverse perspectives, you can ensure that interpretations and actions are based on objective observations rather than preconceived notions.

Embracing User Unpredictability

Users can be unpredictable, and their behavior may not always align with your expectations. Free trial experiences may introduce randomness into the data, with varying engagement and conversion levels. By anticipating and accounting for these variations, you can better understand user behavior and tailor your strategies accordingly.

Leveraging Human Elements

Whereas PLG primarily accentuates data integration and automation, it’s essential to recognize and leverage the human elements of intelligence, experience, and behavior. Hence, most enterprises should incorporate the expertise and insights of their team members to complement the data-driven approach. Subsequently, this synergy of human intelligence and data-driven insights will drive PLG success.

Strategies for Implementing PLG

Without a doubt, embracing a product-led approach entails a bold transformation, redefining every aspect of your business strategy, organizational structure, infrastructure, and policies. These four PLG strategies mandate a paradigm shift in mindset, paving the way for innovative ways of operating and collaborating throughout the entire product life cycle:

Growth Loops

Growth loops are replacing traditional sales and marketing funnels. Funnels create silos and one-directional flow, while growth loops emphasize cross-functional collaboration and continuous growth over time. They leverage existing customers to bring in new customers through low-effort referrals and viral strategies.

Hook Model

The Hook Model focuses on creating habit-forming products. By understanding triggers, actions, variable rewards, and investments, you can design products that engage users and keep them returning. This model addresses emotional needs and patterns, allowing your product to become a part of users’ everyday lives.

BJ Fogg Behavior Model

This type emphasizes the importance of onboarding, engagement, and product design. It considers three factors: ease of use, value proposition, and prompts. You can drive user behavior and foster long-term engagement by making your product easy to use, communicating its value effectively, and providing timely prompts.

RICE Prioritization

RICE is a framework for prioritizing product launches, updates, and experiments. It evaluates ideas based on Reach, Impact, Confidence, and Effort. Quantifying these factors allows you to make data-informed decisions, reduce bias, and effectively prioritize your backlog. RICE helps ensure that both product improvements and PLG strategies receive appropriate attention.

Considering the Shift: Is Product-Led Growth Right for You?

The shift from sales-led to product-led growth is more than a strategic reorientation; it’s a complex transformation that may fundamentally alter the way your organization operates. Before embarking on this journey, carefully evaluate whether your product can become the centerpiece of your growth strategy. Consider your target market, the nature of your offerings, and your organizational strengths. Assess how PLG aligns with your long-term vision and how it might interact with existing sales strategies. Engage with stakeholders, including sales and product teams, to gauge readiness and alignment. Most importantly, recognize that PLG is not a one-size-fits-all solution, and the hybrid approach may present an appealing middle ground. Whether fully embracing PLG or blending it with traditional sales efforts, the decision should be deliberate, informed, and tailored to your unique business landscape.

Mastering the Growth Game: A Guide to Diverse Sales Strategies

James Cash Penney, JCPenney’s founder, once said, “No company can afford not to move forward. It may be at the top of the heap today but at the bottom of the heap tomorrow if it doesn’t.”

To propel their expansion and drive revenue, companies employ various growth motions. From sales-led growth to product-led growth, founder-led growth, and marketing-led growth, each strategy offers unique advantages and challenges. Let’s delve into the particularities of these strategies alongside their benefits, challenges, and best use cases.

Sales-led Growth

Sales-led growth is a strategy emphasizing sales processes and people to increase revenue. In a sales-driven growth strategy, the sales staff takes center stage, and their efforts significantly influence the company’s overall success. Although the marketing department still has some say in how the brand is portrayed, the sales division ultimately determines the company’s success or failure.

SFE Partners indicates that “With a sales-led go-to-market strategy, salespeople can target specific accounts or segments of leads to find change-makers in an organization.” In contrast to product or marketing-led approaches, salespeople may give high-value information to best fit prospective customers much sooner using this method.

Advantages of Sales-led Growth

Usually, businesses prioritize acquisition, transaction closure, and revenue development when sales teams are in charge. This approach empowers the sales force to steer company results and build lasting customer connections. According to Substack, “The sales team can help customers understand the product better and provide personalized solutions.” Companies like Oracle and Microsoft have taken this strategy to heart by maximizing their sales force’s impact.

Challenges of Implementing Sales-led Growth

Most enterprises may have internal divisions if sales are the driving force behind expansion. Potentially neglected by this approach are customer service and customer success, both essential to expanding a firm. When departments work in silos, it may dilute the quality of leads and the sales funnel’s effectiveness and reduce the likelihood of deals being closed. There has to be harmony between the sales, marketing, and support departments.

Best Use Cases for Sales-led Growth

Sales-led growth is most efficient when the sales force is heavily involved in generating revenue and client acquisition. It works effectively for companies that depend on consultative selling strategies, complicated sales cycles, or a high volume of one-on-one customer encounters. Sales-driven expansion is generally successful in sectors where human relationships and networking are crucial, such as corporate software and high-value B2B products.

Product-led Growth

Gainsight found that a majority 58% of companies already embrace this innovative growth motion. It’s not just limited to a specific size or product type, as organizations of all scales have jumped on the PLG bandwagon, with 40% having an annual contract value (ACV) exceeding $25K. Besides, 91% of these companies plan to further invest in PLG, with an ambitious 47% aiming to double down on their existing investment.

Product-led growth is all about making a great product people love using and spreading the word about using viral loops to expand your business. The focus is on the product rather than promotion or advertising, which may save costs. Products like Slack, Netflix, and Zoom have found success because of the way their users interact with the platform.

Advantages of Product-led Growth

It has been demonstrated that PLG companies grow 25% quicker than their competitors and are more likely to double their year-over-year revenue growth, as per the findings of Openview Partners.

Companies can acquire users organically through viral loops, such as inviting users or being part of online communities. Once the viral coefficient takes effect, the product’s scalability and automation reduce reliance on traditional marketing and sales distribution channels. In addition, PLG offers lower customer acquisition costs (CAC) by leveraging the product’s inherent virality.

Challenges of Implementing Product-led Growth

Although PLG has great potential, it might still require some early marketing to find the right audience and boost visibility. Putting all of one’s faith in the product alone may be questionable to spur expansion since additional marketing and sales assistance may be required. In addition, it might be difficult to strike a balance between promoting product self-service and offering comprehensive assistance to business clients.

Best Use Cases of Product-Led Growth

SaaS businesses of all sizes, as well as collaborative or communicative software, may benefit greatly from PLG. It does well in markets where a superior customer experience significantly impacts new customer acquisition and business expansion. PLG works best for products that have the potential to become viral, in which consumers may spread the word about the product in an organic way and generate a network effect. Often, a PLG approach is useful for start-ups and enterprises who want to shorten sales cycles, expedite user onboarding, and emphasize product experience.

Founder-led Growth

Peculiar in its reliance on the personal brand and influence of the company’s founder or CEO, “founder-led growth” is a unique growth strategy. When a firm or product becomes successful due to the founder’s name recognition and reputation, the company or product is said to have experienced “founder-led growth.” Steve Jobs and Elon Musk are just two business leaders whose charm, vision, and hands-on approach helped their firms explode in success.

Purdue’s Krannert School of Management’s research highlights that S&P 500 companies where the founder remains actively involved as notable public figures generate 31% more patents than their counterparts. Founder-led companies demonstrate a fearless attitude towards risk-taking by making bold investments to revitalize and adapt their business models, showcasing their commitment to shaping the future through inventive strategies.

Advantages of Founder-led Growth

Founder-led growth capitalizes on the personal branding and reputation of the founder, which can attract attention, investments, and customer loyalty. The founder’s influence creates a unique selling proposition and can generate trust and excitement around the company and its products. The founder’s vision and leadership can inspire and align employees with the company’s goals.

Challenges of Founder-led Growth

As the name outrightly suggests, successful founder-led expansion is highly dependent on the founder’s persona, connections, and reputation. Thus, it may be quite difficult to duplicate this approach if the founder’s influence is diminished. Unforeseen risks may arise if the founder departs or suffers a reputational setback since the company’s success may become reliant on them. Besides, expanding a company beyond the founder’s capabilities is difficult and calls for good delegation and a solid leadership team.

Best Use Cases of Founder-led Growth

When a company’s founder has a substantial personal brand and influence in their field or niche, they are in a prime position to drive growth. Start-ups and technology-based businesses where customers share the founder’s vision and drive are common examples. This may be effective for companies dependent on the founder’s experience and reputation, such as consulting firms, coaching enterprises, and those that rely on the founder as a thought leader.

Marketing-led Growth

Marketing-led growth is driven by marketing efforts, where customers are acquired through various marketing channels and strategies. Examples include content marketing, videos, blogs, eBooks, and other forms of engaging content. In other words, the overarching focus is on attracting customers through valuable content and building a differentiated brand narrative.

Accenture indicates that the key to achieving marketing-led growth lies in the seamless collaboration and integration of diverse customer data. The foundation of this process is built upon four layers encompassing client experience, work orchestration, ecosystem connectivity, and data & applied intelligence. Organizations can optimize each layer to enhance customer experiences, streamline internal workflows, foster connections with external partners, and leverage data-driven intelligence to fuel their marketing-led growth initiatives.

Advantages of Marketing-led Growth

With marketing as the core engine of expansion, businesses can update their brand stories, set themselves apart from competitors, and provide customers with valuable content. Without a doubt, it arises as a great tool for being noticed by customers, increasing brand awareness, and bolstering your reputation. Upgrades, social shares, recommendations, and customer reviews may all improve with this tactic.

Challenge of Marketing-led Growth

There are two main problems with marketing-driven growth. First, for efficient lead nurturing and customer understanding, seamless lead sharing between the marketing and sales departments must be seamless. Second, there is the risk of putting too much emphasis on client acquisition and not enough on customer retention.

Best Use Cases of Marketing-led Growth

Marketing-led growth is well-suited for service brands aiming to establish themselves as market leaders through organic growth. It is particularly effective in businesses with sustainable models that prioritize customer retention. Marketing-led growth is beneficial for sectors where customers seek quick self-help solutions and where content-driven engagement can effectively showcase the product or service’s value.

Growth Matters – Key B2B insights w/ Leore Spira, Head of RevOps @ Buildots

Today’s salespeople juggle an array of tools – from prospecting and CRM to outreach tools and meeting schedulers. Coupled with a comprehensive infrastructure for lead generation, lead-scoring systems, and sales-related data, it’s a challenging landscape to navigate.

As we continue our Growth Matters series, we’re focusing on demystifying this complexity. To guide us through these treacherous waters, we’ve invited a seasoned RevOps specialist, to guide us through these intricate waters.

Please join us in welcoming Leore Spira, Head of Revenue Operations at Buildots. Her extensive experience and expertise will help us delve deeper into these challenges and provide insights into navigating them successfully. Welcome, Leore!

Explore her insights on RevOps fundamentals, data’s role, essential tools, and future trends.

Let’s start with the basics – what is the purpose of RevOps, and what are some key components of a successful RevOps strategy?

RevOps (Revenue Operations) is a strategic approach to aligning sales, marketing, and customer success teams within an organization to optimize revenue generation and customer experience. The purpose of RevOps is to drive growth and increase revenue by streamlining holistic processes, improving collaboration, and leveraging data to make informed decisions.

The key components of a successful RevOps strategy include:

1. Alignment:

RevOps requires a strong alignment between GTM, e.g. sales, marketing, and customer success teams. This includes clear communication and collaboration to ensure that all teams are working towards the same goals.

2. Data-driven approach

RevOps relies heavily on data to make informed decisions. A successful RevOps strategy includes collecting and analyzing data from various sources to gain insights into customer behavior, sales performance, and marketing effectiveness.

3. Process optimization

RevOps aims to streamline and optimize sales, marketing, and customer success processes. This includes identifying inefficiencies and implementing solutions to improve productivity, efficiency, and effectiveness.

4. Technology integration

RevOps requires the use of technology to support its processes and data-driven approach. A successful RevOps strategy includes integrating and leveraging technology and building the optimized tech stack such as CRM systems, marketing automation, and analytics tools.

5. Continuous improvement

RevOps is a continuous process of improvement. A successful RevOps strategy involves regularly monitoring performance metrics and adjusting processes and strategies to achieve better results over time.

How can RevOps help B2B companies better understand and serve their customers throughout the entire customer lifecycle?

RevOps can help B2B companies better understand and help their customers throughout their lifecycle by providing a holistic view of the customer journey.

Here are some ways RevOps can help:

1. Collect and analyze customer data

RevOps collect and analyze data from various sources, such as CRM systems, GTM tech stack, marketing automation tools, and customer feedback, to gain insights into customer behavior, relationship, and preferences. This data can be used to identify trends, anomalies, and patterns, as well as to personalize the customer experience journey and process.

2. Align sales, marketing, and customer success teams

RevOps align these teams to ensure that they are all working towards the same goals or KPIs and that there is a consistent approach to customer engagement throughout the customer lifecycle. This can help avoid gaps and inconsistencies in the customer experience.

3. Optimize processes

RevOps can optimize processes such as lead generation, lead nurturing, sales cycle, churn rate, or customer onboarding to ensure that they are efficient and effective. This can help minimize the time it takes to convert a prospect into a customer and reduce churn rates.

4. Provide insights and recommendations

RevOps provide insights and recommendations based on data analysis and performance metrics to help teams make informed decisions about better helping their customers. This can help teams identify areas for improvement and prioritize initiatives that will have the most impact on customer satisfaction and retention.

By leveraging RevOps strategies and tools, B2B companies can better understand and support their customers throughout their journey. This can lead to increased customer satisfaction, loyalty, a great relationship, and revenue growth.

What role does data play in driving RevOps success, and how do you ensure you gather and maintain quality data?

Data plays a critical role in driving RevOps success, as it provides insights into the customer journey performance and effectiveness. To ensure that data is of high quality, B2B companies must have a robust data management strategy and infrastructure in place.

Here are some key steps to gathering and maintaining quality data for RevOps success:

Define your data management strategy: Establish a clear strategy for data management that outlines the processes and tools needed to collect, store, and analyze data. This strategy should also define data ownership and access rights.
Standardize data collection: Define and standardize data collection processes to ensure that data is consistent and accurate across all systems and teams. This includes defining data fields, naming conventions, and data entry protocols.
Implement data governance: Implement data governance policies and procedures to ensure data accuracy, completeness, and security. This includes establishing data quality standards, data privacy policies, and data access controls.
Use technology to automate data processes: Utilize technology such as CRM or GTM systems, marketing automation tools, and analytics platforms to automate data processes and improve data accuracy and completeness.
Continuously monitor and improve data quality: Regularly monitor data quality and implement processes for data cleansing and enrichment to ensure that data is accurate and up-to-date.

By following these steps, companies can ensure that they gather and maintain high-quality data hygiene in the systems that can be used to drive RevOps success. This includes providing insights to GTM leadership and management, which can help the company to optimize its revenue generation and customer experience and support its decision-making process with data.

What are some essential tools and technologies that B2B companies should consider when implementing a RevOps strategy?

B2B companies should consider a range of tools and technologies when implementing a RevOps strategy.

Here are some essential tools and technologies to consider:

CRM systems: A CRM (Customer Relationship Management) system is a critical tool for managing customer journey data and interactions across the customer lifecycle. It enables B2B companies to track customer interactions, manage accounts, contacts, leads, and opportunities, and analyze customer data to make data-driven decisions.
Marketing automation tools: enable companies to automate repetitive marketing tasks, such as lead nurturing, email marketing, and social media management. They can help improve the efficiency and effectiveness of marketing campaigns and ensure that leads are properly nurtured throughout the funnel.
Sales enablement tools: help sales teams to be more efficient and effective by providing them with the right content and information at the right time. They can include tools such as content management systems, sales training and coaching tools, and sales performance analytics platforms.
Analytics tools: enable companies to collect and analyze data from various sources, such as website analytics, customer feedback, customer relationship, health and engagement score, and sales performance metrics. They can provide valuable insights to support scaling the processes and revenue.
Collaboration tools: such as project management software, communication platforms, and file-sharing tools, can help improve collaboration and communication across teams, which is essential for successful RevOps implementation.

Overall, companies should consider a range of tools and technologies to support their RevOps strategy, depending on their specific needs and goals. These tools and technologies can help improve efficiency, productivity, effectiveness, and collaboration across sales, marketing, and customer success teams, leading to better revenue generation and customer experience.

At what stage should companies start investing in RevOps?

RevOps can be beneficial for companies at any stage of their growth, whether they are startups, SMBs, or large enterprises. However, the exact timing of when to invest in RevOps may vary depending on the company’s specific circumstances and goals.

Here are some common scenarios:

Rapid growth: If a company is experiencing rapid growth, it may need to optimize its revenue generation and customer experience processes to keep up with demand. Implementing a RevOps strategy early can help streamline processes, improve collaboration, and leverage data to make informed decisions.
Sales and marketing misalignment: If sales and marketing teams are misaligned, a RevOps strategy can help align them and ensure that they are working towards the same goals. This can help avoid gaps and inconsistencies in the customer journey and improve overall revenue generation and funnel.
Churn reduction: If a company is experiencing high churn rates, it may need to improve its customer experience processes. RevOps can help optimize customer onboarding, support, and success processes and leverage data to identify areas for improvement.
Technology adoption: If a company is adopting new technologies such as CRM systems, marketing automation tools, or analytics platforms, a RevOps strategy can help ensure that these tools are integrated properly and used effectively to optimize revenue generation and customer experience.

You’ve been doing Rev/SalesOps for years! How has the role of this department evolved over the years, and what do you see as the future trends in this field?

Over the years, the role of Rev/SalesOps has evolved from being primarily focused on sales process optimization to a more holistic approach to revenue generation and customer experience (e.g. full funnel and customer journey).

Here are some key trends that have shaped the evolution of Rev/SalesOps:

Data-driven decision-making: Rev/SalesOps has become increasingly data-driven, with a focus on collecting and analyzing data to gain insights into customer behavior and relationship throughout the funnel, sales performance, and marketing effectiveness. This has enabled Rev/SalesOps teams to make informed decisions and optimize revenue processes.
Collaboration and alignment: Rev/SalesOps has become more focused on collaboration and alignment across GTM teams, i.e., sales, marketing, and customer success teams. This has helped to avoid gaps and inconsistencies in the customer journey and improve the overall revenue generation funnel.
Technology adoption: Rev/SalesOps has become more reliant on technology to support its processes and data-driven approach. This has led to the adoption of different tools to increase efficiency and data enrichment.
Customer-centric approach: Rev/SalesOps has become more focused on a customer-centric approach, with a greater emphasis on optimizing the customer experience throughout the customer lifecycle. This has led to a greater focus on customer success and retention (land and expand methodology) in addition to revenue growth.

In terms of future trends, here are some areas that are likely to shape the evolution of Rev/SalesOps:

Artificial Intelligence and Machine Learning: The use of AI and machine learning is likely to become more prevalent in Rev/SalesOps, particularly in areas such as sales forecasting/prediction, lead/account scoring, and customer segmentation and health.
Sales Enablement: Rev/SalesOps is likely to become more focused on sales enablement, providing sales teams with the tools and information they need to be more effective and efficient in their roles.
Sales Process Automation: Rev/SalesOps is likely to continue to automate and streamline sales processes, making them more efficient and effective.
Customer Experience Optimization: Rev/SalesOps is likely to become even more focused on optimizing the customer journey throughout the customer lifecycle, with a greater emphasis on customer success, growth playbooks, health, relationship, and retention.

What are some key performance indicators (KPIs) that companies should track to measure the success of their RevOps initiatives?

Tracking key performance indicators (KPIs) is essential to measure the success of RevOps initiatives. Here are some KPIs that companies should consider tracking:

Revenue growth: Revenue growth is the ultimate goal of RevOps, and tracking this metric can help companies measure the productivity and efficiency of their RevOps strategy and GTM teams.
Sales cycle length: The length of the sales cycle is a key indicator of the efficiency of the sales process. Tracking this metric can help companies identify bottlenecks and areas for improvement.
Customer acquisition cost (CAC): CAC is the cost of acquiring a new customer and is an important metric for tracking the efficiency of marketing and sales efforts.
Customer lifetime value (CLTV): CLTV is the total value of a customer over the course of their relationship with the company. Tracking this metric can help companies identify opportunities for upselling and cross-selling.
Win rate: Win rate is the percentage of deals won versus the total number of deals pursued. Tracking this metric can help companies identify areas for improvement in the sales process and adjust their strategy accordingly.
Customer satisfaction (CSAT) and Net Promoter Score (NPS): CSAT and NPS are metrics used to measure customer satisfaction and loyalty. Tracking these metrics can help companies identify areas for improvement in the customer experience, the relationship with the product, and address issues before they become major problems.
Marketing/Sales attribution: Marketing/Sales attribution is the process of assigning credit for a sale or conversion to a specific marketing/Sales touchpoint or campaign. Tracking this metric can help companies identify which marketing efforts are most effective in driving revenue.

Can’t let you go before asking about AI. How do you see it impacting the RevOps world, and what possible impacts do you think it will have?

AI has the potential to significantly impact the RevOps world in a variety of ways. Here are some possible impacts on RevOps:

Sales forecasting and prediction: AI can help improve the accuracy of sales forecasting and pipeline prediction by analyzing historical data and identifying patterns and trends.
Lead or account scoring: AI can help automate lead scoring by analyzing customer data and behavior or type of relationship to determine which customers or prospects are most likely to convert or grow.
Sales process automation: AI can automate repetitive tasks and processes, such as data entry and scheduling, freeing up sales reps to focus on more high-value tasks.
Churn prediction: by analyzing customer behavior and engagement data, AI can help predict which customers are at risk of churning and enable RevOps teams to take proactive measures to retain those customers. AI can identify patterns in customer data that may indicate dissatisfaction, such as reduced engagement, decreased activity, or negative feedback. Based on these insights, RevOps teams can take targeted actions to improve the customer experience and address issues before they lead to churn. This can also help improve customer retention rates and ultimately drive revenue growth.
Customer segmentation: AI can help segment customers based on various criteria, such as purchase history, behavior, and preferences, to personalize the customer journey and messaging.
Chatbots: AI-powered chatbots can help automate customer support and provide instant answers to common customer queries or desires.
Sales coaching: AI can provide insights and recommendations to sales reps, such as personalized coaching and training, to help them improve their performance and close more deals.
Marketing personalization: AI can analyze customer data to provide personalized marketing messages and offers based on customer preferences and behavior.

Overall, AI has the potential to revolutionize the RevOps world by improving the accuracy of forecasting, automating tasks and processes, and providing personalized insights and recommendations. However, it is important for companies to ensure that they have the necessary infrastructure and data management strategies in place to effectively leverage AI for RevOps.

Understanding the Key Differences and Synergies between RevOps vs SalesOps

Velocify maintains that high-performing companies are twice as likely as underperforming companies to describe their sales process as “closely monitored” or “strictly enforced or automated.” In fact, companies that align people, processes, and technology across their sales and marketing teams experience up to 36% more revenue growth and up to 28% more profitability, as concluded by Forrester.

SalesOps and RevOps have emerged as critical business paradigms that achieve these aspects, but their benefits are usually hindered by the confusion surrounding their differences. Moving forward, we aim to address the most poignant differences between SalesOps and RevOps, exploring their objectives, responsibilities, and impact on the customer journey.

Exploring the Responsibilities of RevOps & SalesOps

According to Gartner, sales operations is a crucial strategic function that supports, enables, and drives effective sales objectives, strategies, and programs.

BCG estimates that RevOps has enhanced the digital marketing ROI from 100% up to 200%. To achieve this, RevOps encompasses the following:

– Operations management (managing and optimizing resources, sales ops, marketing ops, customer success ops, and project management)
– Enablement (providing support to sales, marketing, and customer success teams through sales enablement, learning management, and performance management)
– Data analysis and insights (gathering data, providing insights for day-to-day operations and strategic planning)
– Tools (managing technology across sales, marketing, and customer success)
– Sales operations play an increasingly vital role in sales success, as Salesforce indicates that 89% of sales professionals emphasize its importance in growing their business. In this pursuit, SalesOps integrates:
– Data management (measuring and evaluating sales data)
– Forecasting (predicting future sales growth and needs)
– Sales tactics (using data analysis and forecasting to create sales strategies and objectives)
– Sales team support (providing support and training to sales representatives)
– Lead generation (attracting and converting prospects into leads)
– Sales incentives/commissions calculation (identifying and managing value for stakeholders)

Uncovering the Different Objectives of RevOps vs SalesOps

For businesses, efficiency is synonymous with success. RevOps and SalesOps share a primary goal: improving operational efficiency. However, their objectives differ based on their specialized areas. Adithya Krishnaswamy, Head of RevOps and Growth at Everstage, postulates, “RevOps was an evolution of Sales Ops when people realised it wasn’t just sales that needed operations anymore.”

SalesOps concentrates on enhancing sales operations, including customer relationship management, order processing, forecasting, and budgeting. It aims to drive efficiency within sales processes to maximize revenue. In other words, SalesOps ensures that the sales team is equipped with the necessary resources and tools to close deals, retain customers, and increase revenue.

Conversely, RevenueOps takes a broader approach by including SalesOps and other related functions like finance and customer success operations. RevenueOps analyses the entire revenue generation process and seeks to optimize it. It aligns sales and marketing operations to drive revenue growth by identifying and fixing inefficiencies throughout the customer journey.

RevOps vs SalesOps Impact on Customer Journey

Well, the success of a business is contingent upon its capacity to establish and sustain favorable connections with its clientele. SalesOps and RevOps are both pivotal in improving the customer experience, albeit through distinct approaches.

The SalesOps department is dedicated to enhancing the quality of engagements between sales personnel and clients. The department is committed to removing any impediments that may impede the customer’s journey, guaranteeing that each sales funnel stage is optimized and effective. SalesOps teams are responsible for devising innovative strategies that enhance customer satisfaction and foster revenue generation.

RevOps endeavor to enhance customer conversion rates by furnishing a smooth and uninterrupted experience throughout all phases of the purchaser’s expedition. The comprehensive scope of this entails implementing inbound marketing strategies aimed at capturing the interest of prospective clients, as well as the execution of post-sale endeavors that foster brand loyalty and advocacy. RevOps strategies are formulated to maximize revenue generation by improving customer experience.

While SalesOps and RevOps may have distinct aims and objectives, forward-thinking businesses can integrate them. Sales Operations is commonly perceived as a sub-domain of the RevOps department in numerous organizations, facilitating seamless integration and data sharing between the two teams. Thus, the information gathered by Sales Operations can support Revenue Operations in their forecasting endeavors. In contrast, the data obtained by Revenue Operations can serve as a valuable resource for sales tactics and decision-making.

How to Know When to Deploy SalesOps vs RevOps

As businesses expand, it is crucial to consistently assess their operations and tactics to guarantee they are achieving their objectives. In this pursuit, it is advisable to determine the company’s needs and decide which is more beneficial for you: SalesOps or RevOps:

It might be time to deploy SalesOps if:

– Your company needs someone dedicated to sales operations, especially if you’re a smaller or newer company looking to drive growth.
– Your sales team spends too much time organizing, planning, and strategizing instead of selling, which can be solved by a SalesOps team that simplifies the sales process.
– Your company is in the early stages, and you need to drive revenue before expanding your team further.
– Your sales reps need extra training to reach their full potential.

Conversely, it is advisable to integrate RevOps if:

– Your company is encountering hurdles when it comes to increasing revenue.
– You lack cross-departmental visibility and communication, which can be solved by implementing a RevOps framework.
– Your processes are outdated and need modernization, and RevOps can help automate and streamline your operations.
– You can’t tell what’s working and what’s not, and RevOps provides a bird’s eye view of the entire customer lifecycle to identify problems.
– You don’t have a long-term growth strategy; a RevOps team can help develop and implement one.

Mastering Sales Metrics: Decoding PQLs and PQAs for a Winning Sales Strategy

The sales environment today is constantly changing, so it’s important to stay informed and adaptable. In order to ensure your sales team succeeds, understanding key concepts such as Product Qualified Leads (PQLs) and Product Qualified Accounts (PQAs) can be critical. Rather than being methodologies, PQLs and PQAs are essential elements of the sales process. This post explores PQLs and PQAs, their relevance in different scenarios, and their relationship to your sales team’s work. Knowing the differences between them and knowing when to use them will help your sales team succeed.

PQLs and PQAs vs MQLs and SQLs

Understanding MQLs and SQLs

To fully grasp the value of PQLs and PQAs, it’s important to compare them with other widely-used concepts in the sales world: Marketing Qualified Leads (MQLs) and Sales Qualified Leads (SQLs). MQLs are prospects identified by the marketing team as having the potential to become customers based on their interactions with marketing materials. SQLs, on the other hand, are leads that the sales team deems ready for a direct sales approach based on their level of interest and intent.

PQLs and PQAs: A Different Perspective

While MQLs and SQLs focus primarily on the level of engagement with marketing materials and sales readiness, PQLs and PQAs take a more product-centric approach. PQLs are prospects who have actively engaged with the product or service itself, while PQAs are organizations with multiple PQLs, signaling a high level of interest and potential for conversion.

Defining PQLs and PQAs

What are Product Qualified Leads (PQLs)?

Product Qualified Leads (PQLs) are potential customers who have demonstrated a clear interest in your product or service by engaging with it in a meaningful way. Examples of PQL engagement include signing up for a free trial, using a freemium version of your product, or attending a product demonstration. PQLs have shown a higher likelihood of conversion compared to traditional leads because they have firsthand experience with your offering.

What are Product Qualified Accounts (PQAs)?

Product Qualified Accounts (PQAs), on the other hand, are entire organizations or business units that display a strong potential for conversion. PQAs often consist of multiple PQLs within the same organization, indicating a high level of interest and engagement with your product or service. By targeting PQAs, you can focus on nurturing relationships with key decision-makers and stakeholders, increasing the chances of closing a deal.

Identifying the Relevance of PQLs and PQAs

When to Focus on PQLs

PQLs are particularly relevant when your sales team is dealing with individual users or smaller organizations. In these cases, it is essential to identify and engage with prospects who have shown genuine interest in your product. By focusing on PQLs, your sales team can prioritize high-quality leads and allocate resources more effectively.

When to Focus on PQAs

PQAs become more relevant when targeting larger organizations or enterprises. In these scenarios, your sales team needs to consider multiple stakeholders and decision-makers within the same account. Focusing on PQAs allows you to engage with an entire organization, ensuring you address the needs and concerns of all relevant parties, which can lead to more significant deals and long-term business relationships.

Integrating PQLs and PQAs into Your Sales Team’s Work

Developing a PQL and PQA Mindset

To successfully integrate PQLs and PQAs into your sales team’s workflow, it’s essential to adopt the right mindset. This involves understanding the differences between PQLs and PQAs, recognizing their value, and knowing when to prioritize each one.

Aligning Sales and Marketing Efforts

Both PQLs and PQAs require close collaboration between sales and marketing teams. Marketing efforts should focus on driving product engagement and identifying PQLs, while the sales team should concentrate on nurturing these leads and converting them into customers. In the case of PQAs, both teams need to work together to engage with multiple stakeholders and decision-makers within the organization.

Leveraging Technology and Data

To effectively identify and manage PQLs and PQAs, your sales team should use technology and data to track engagement, monitor progress, and make informed decisions. Customer Relationship Management (CRM) systems, marketing automation tools, and data analytics can help you collect and analyze information about your leads and accounts, allowing your team to prioritize their efforts and optimize their strategies.

Utilizing Product-Led Revenue Platforms for PQL and PQA Management

Product-led revenue platforms can play a crucial role in helping your sales team adopt the PQL and PQA mindset, align with marketing efforts, and make data-driven decisions. These platforms consolidate essential information, enable you to track product engagement, and identify PQLs and PQAs. Additionally, they provide customized scoring based on product usage and other factors, allowing your team to prioritize leads and accounts more effectively.

By integrating a product-led revenue platform into your sales and marketing processes, you can ensure that your team has a centralized system to manage PQLs and PQAs effectively. These platforms not only streamline workflows through playbooks and automation but also promote better communication and collaboration between sales and marketing teams, leading to a more efficient and successful sales process.

Conclusion

Understanding the distinctions between PQLs, PQAs, MQLs, and SQLs is essential for sales success. By adopting a product-centric mindset and knowing when to focus on PQLs or PQAs, your sales team can better prioritize their efforts, allocate resources effectively, and ultimately drive more conversions. Utilizing product-led revenue platforms can significantly enhance your team’s ability to identify and manage PQLs and PQAs by fostering alignment, encouraging data-driven decision-making, and promoting seamless collaboration between sales and marketing teams. Additionally, these platforms offer customized scoring, playbooks, and automation, streamlining your workflows and further optimizing your sales process. Embracing these concepts and strategies will ensure long-term success and growth for your organization.

The Power of Analytics: Transforming B2B Sales and Revenue Generation Strategies

From Data to Dollars: Leveraging Analytics to Maximize B2B Sales and Revenue Growth

Caroly Fiona once said, “The goal is to turn data into information, and information into insight.” To complement this adage, these insights can be translated into your revenue. As per a recent publication by McKinsey, the implementation of data analytics is poised to offer numerous benefits. This innovative approach involves utilizing computer systems and processes to perform analytical tasks with minimal human intervention, improving quality, safety, speed, and output while reducing errors.

Data analytics is paramount for B2B sales organizations as it furnishes valuable insights into the efficacy of various sales channels. The process of data analytics involves leveraging unstructured data to extract valuable insights that can inform business decisions and drive strategic outcomes. Algorithms are used for analysis and tailored to meet specific objectives, allowing sales teams to leverage historical performance data to pinpoint lucrative strategies and effectively target high-value customers.

Sigma Computing reports that although many businesses recognize the value of big data, over 63% of employees are concerned that they cannot get insights from their solutions in a timely manner. For many businesses, the greatest challenge is likely to obtain data insights before they become obsolete. In this vein, Forrester emphasizes that up to 73% of all data is never deployed for analytical purposes.

Exploring the Core Data Types

B2B enterprises are gaining access to an expanding data pool. Certain data sets can prove to be highly valuable in providing crucial insights into your enterprise. Alternative forms of data may not hold the same level of significance. In the realm of B2B enterprises, key categories of data contain significant value for generating data-driven insights: customer data and sales data.

Customer Data – Fundamental customer data includes details such as the organization’s name, physical address, geographical location, and scale, among others. Although rudimentary, this information can still be highly valuable, particularly when integrated with sales data. Customer engagement and behavior can provide valuable insights into how your customers engage with your brand and navigate your website or online store.

Sales Data – Sales data refers to the numerical information that tracks the performance of a company’s sales activities. This data is typically used to analyze trends, identify growth opportunities, and make informed business decisions. Sales data provides valuable insights into customer behavior, including purchasing patterns and timelines. In the context of business-to-business (B2B) sales, the sales data can provide valuable insights into the performance of your sales agents and other sales personnel.

Effective Market Segmentation

Without a doubt, the strategic development of market segmentation is a crucial determinant of the success of novel products or services, as it enables the effective targeting of products to diverse market segments. Data analytics-driven customer segmentation can aid businesses in crafting highly personalized and efficient marketing campaigns that directly cater to their customers’ unique needs and concerns. By leveraging real-world data insights, your enterprise can enhance its revenue generation capabilities across diverse segments by delivering innovative products and services.

Leveraging big data analytics to gain insights into consumer behaviour directly impacts an organization’s revenue. Organizations that leverage such data possess a competitive edge over their rivals as they can furnish appropriate offerings that cater to their clientele’s specific needs and preferences.

As per the study conducted by McKinsey Global Institute, organizations that rely on data-driven approaches are more likely to obtain customer acquisition, retention, and profitability. Specifically, such organizations are 23 times more likely to acquire customers, six times more likely to retain customers, and 19 times more likely to achieve profitability.

At a fundamental level, this enables employees to redirect their focus towards higher priority responsibilities. Implementing automation technology enables enterprises to effectively manage large volumes of data, encompassing critical aspects such as data acquisition, refinement, duplication, and repository upkeep.

Predictive Analytics & Forecasting

Resource allocation, trend forecasting, and action identification are integral components of effective management. The processes of forecasting and budgeting are integral components of routine business operations that demand a substantial amount of time and effort. The process of forecasting entails the estimation of future trends by analyzing past data. Predictive analytics represents a distinct approach to data analysis.

Furthermore, integrating various inputs in predictive analysis and forecasting enables the prediction of future trends with greater detail and nuance than conventional historical forecasting techniques. Predictive analysis offers valuable insights that would allow managers to enhance their agility and adaptability to dynamic market conditions, thereby reducing inefficiencies and maximizing revenue optimization.

Descriptive & Diagnostic Analytics

Any enterprise must comprehensively assess its operational efficacy to discern its strengths and areas of improvement for future growth. Descriptive analytics is a fundamental data analysis technique involving the systematic collation, organization, and presentation of various historical data types. By leveraging advanced techniques such as data aggregation and mining, descriptive analytics can effectively uncover patterns and trends within historical data. The resultant data sets can be effectively showcased through Business Intelligence (BI) incomprehensible visual aids such as graphs, diagrams, and charts.

After the initial evaluation, the diagnostic analysis represents the subsequent rational progression in this course of action. Descriptive analysis addresses the question of “what occurred?” while diagnostic analysis explains “why did this event occur?”. Various methodologies, including drill-down, data discovery, data mining, and correlations, are employed to extract the interrelationships among diverse datasets. The process of diagnostic analysis not only involves the identification of trends, but also strives to unveil the interrelationships among various parameters.

Bottom Line

B2B businesses can acquire a deeper understanding of their consumers and the sales funnel as a whole by evaluating data from channels as diverse as customer relationship management (CRM), web analytics, and marketing automation. With this knowledge, B2B organizations can better tailor their sales strategy and customer service to boost conversion rates and revenue. Businesses may better deploy their time, money, and other resources by identifying the most successful marketing efforts.

B2B enterprises may monitor their sales activity and see patterns in their income streams using analytics. This may help them generate data-driven choices and change tactics, including expanding into new areas or adjusting prices. Maintaining momentum and making necessary adjustments with the advent of data analytics may empower B2B teams to accomplish their revenue goals.

RevOps: The Game-Changer for B2B Customer Acquisition and Retention

Considering escalating customer acquisition expenses and dwindling conversion rates, enterprises must devise effective strategies to acquire, retain and expand their customer portfolio. Well, the average cost merchants incur for acquiring a new customer has significantly increased over the last decade. SimplicityDX concluded that in 2013, merchants experienced a loss of $9 per new customer, whereas presently, the loss has surged to $29, indicating a substantial 222% rise.

For those who want to enhance their customer acquisition process, RevOps arises as the most consistent and innovative solution.

Matching Customer Expectations with RevOps

The RevOps shift has garnered significant attention as a crucial strategy for fostering interdepartmental collaboration and delivering a seamless customer journey. As per the findings of a research conducted by Salesforce, customers anticipate uniformity in their interactions with a company across various departments. Nevertheless, it frequently appears that individuals are confronted with disparate divisions instead of cohesive entities.

Moving forward, the RevOps department is uniquely positioned to bridge the gap and deliver a cohesive customer journey that not only meets but surpasses customer demands. Gartner Inc. anticipates that a RevOps framework will be adopted by 75% of the most rapidly expanding enterprises worldwide by 2025. Enterprises comprehend that a proficiently executed RevOps approach can propel revenue expansion and augment customer contentment.

In the same vein, recent research conducted by ActiveCampaign regarding the influence of customer experience automation has revealed that automation technology has the potential to enhance customer acquisition and retention rates substantially. The research findings indicate that enterprises that have incorporated automation technology into their operations have witnessed a significant increase of up to 110% in their lead generation and a remarkable 94% surge in their conversion rate.

Leveraging Key Metrics for Customer Acquisition

RevOps teams are uniquely positioned to craft a frictionless customer journey by identifying and addressing the gaps in your sales and marketing processes. By using data-driven insights to evaluate and optimize the customer journey, RevOps teams can help your business achieve better customer acquisition and retention rates, drive revenue growth, and stay competitive in today’s marketplace.

To streamline processes, RevOps teams need to understand how efficient and accurate the existing processes are. Key metrics like Customer Lifetime Value (CLV) and Customer Acquisition Cost (CAC) can be used to evaluate how much revenue your operations generate across departments throughout the customer journey. RevOps teams can identify and remove bottlenecks by analyzing these metrics to maximize value and profits.

Customer Lifetime Value (CLV) measures how much a customer is worth to your business from the moment they first start using your product or service until they stop. CLV isn’t based solely on the customer’s first purchase but on how effective upsells and renewals are. A low CLV limits how much you should spend to acquire new customers and should be a key consideration in your marketing and sales strategies.

Customer Acquisition Cost (CAC) indicates how much you must invest in marketing and sales to acquire a new customer. A good CAC for your brand depends on the CLV and customer churn. A high CAC should alert your RevOps team that your branding is inconsistent, your ad placements are off, or you’re targeting the wrong clients.

How Deploying RevOps Diminishes Customer Acquisition Costs

Companies who want to deploy an effective RevOps strategy should incorporate a customer acquisition cost goal into their comprehensive strategic plan to elevate their operations. However, the objective in question changes, contingent upon variables such as the industry, the value of the customer’s lifetime, and the expansion aspirations of the company. If the expenses associated with customer acquisition persistently surpass the desired threshold, it may be prudent to undertake a comprehensive reassessment of the RevOps approach.

One potential strategy is to comprehensively evaluate and refine the marketing and sales methodologies currently employed. When paid advertising fails to yield the intended outcomes, it may be judicious to investigate alternative marketing channels. RevOps teams can leverage data analytics to discern the most efficient channels and allocate resources accordingly.

In the event that the objective for customer acquisition cost proves to be persistently unachievable, it may become imperative to revise the target to a more pragmatic figure. RevOps teams must periodically assess their customer acquisition cost objective and make necessary modifications to ensure its congruence with the organization’s overarching objectives and available resources.

Effective team communication is critical in attaining the desired customer acquisition cost. RevOps teams must collaborate with sales, marketing, and customer success teams to foster a cohesive approach towards achieving organizational objectives. Effective inter-team communication and feedback mechanisms can facilitate the identification of potential areas for enhancement and streamline strategies to minimize customer acquisition expenses.

Prioritizing Customers: Proven Strategies for Successful Upselling and Retention

In the rapidly evolving world of SaaS, staying ahead of the competition requires a deep understanding of your customers, product, and market. However, with unlimited data and platforms to choose from, it can be overwhelming to figure out where to start.

To help you get started, empowering product teams with the tools they need to deliver value to their users, increase conversion rates, and drive growth is of paramount importance. Leveraging the power of product-led change with enterprise sales efficacy gives every team a clear understanding of what they need to do to achieve maximum impact.

In this blog post, we’ll explore the key strategies and processes that drive successful upsells and retention. We’ll cover important topics such as defining your ideal customer, building a growth flywheel playbook, and understanding the importance of customer observability.

Whether you’re a seasoned SaaS veteran or just starting, these strategies will help you prioritize your customer base and drive growth for your business.

Product-led revenue: The importance of customer observability

Product-Led Growth (PLG) is a business model focusing on building and growing a product-driven company. It is designed to increase customer engagement and drive revenue through product usage and customer satisfaction. One of the critical components of a successful PLG strategy is customer observability, which allows you to track and understand how customers interact with your product.

Forbes understands the ever-growing importance of PLG, especially for technical products, as the world of AI, sales, and marketing are becoming blurred and combined.

Customer observability provides valuable insights into the customer journey, allowing you to identify areas of improvement and optimize the customer experience. By understanding how customers engage with your product, you can make informed decisions about product development, marketing, and sales strategies. This leads to increased customer satisfaction, higher conversion rates, and, ultimately, increased revenue.

The Benefits of Customer Observability

Improved Customer Experience: By understanding the customer journey, you can identify areas of improvement and optimize the customer experience. This leads to increased customer satisfaction and loyalty.

Increased Conversion Rates: Learning how customers interact with your product allows you to make informed decisions about product development, marketing, and sales strategies, leading to higher conversion rates so that you can be there at the most meaningful moment.

Better Product Development: Customer observability provides valuable insights into the customer journey, which can inform product development decisions and lead to creation of products that better meet customer needs.

The importance of customer observability in driving product-led revenue cannot be understated. AI platforms combine product-led growth efficiency with enterprise sales efficacy, helping every team understand exactly what needs to be done and where their efforts need to be focused on achieving maximum impact. With proper systems and processes in place, you can gain a deeper understanding of your customers and confidently drive product-led growth.

The key to successful upsells and retention

In the competitive landscape of modern SaaS, understanding your customers and what they need is essential to success. By defining your Product Qualified Lead, you can prioritize your customer base and focus on the right customers, leading to increased revenue and customer satisfaction.

A PQL is a crucial component of product-led growth and helps businesses understand who their most valuable customers are, their needs, and how to reach them effectively. By focusing on your PQL, you can make the most of your resources and direct your efforts toward growth initiatives.

Here’s what you can expect from defining your PQL:

Prioritize your customer base: By understanding your PQL, you can prioritize your customer base and focus on the right customers, driving successful upsells and retention.
Drive growth and success: By focusing on your PQL, you can drive growth and success by efficiently and effectively using your resources.
Improve customer satisfaction: You can improve customer satisfaction by understanding your customers and their needs, leading to increased revenue and growth.

Defining your PQL is valuable in unlocking the potential for successful upsells and retention. You can drive growth and success while improving customer satisfaction by prioritizing your customer base and focusing on the right customers.

Growth Flywheel: Build a Playbook for Success

Now that you have clearly defined your lead and sales strategy, you can start implementing your growth flywheel.

A growth flywheel is a (mostly) autonomous system that drives growth through a series of interconnected actions. The goal of a growth flywheel is to create a virtuous cycle that continually drives development and improvement, allowing your business to scale and succeed. One of the pivotal components of a successful growth flywheel is having a playbook that outlines the strategies and processes that drive growth.

The Importance of a Growth Flywheel Playbook

Below are the benefits of implementing a well-put-together growth flywheel for your team. Remember that skill can be trained, with the right processes, regardless of where your staff member starts from.

Consistency: A growth flywheel playbook ensures that all teams follow the same processes and strategies, leading to consistent and predictable growth.
Alignment: By having a shared understanding of what drives growth, teams can work together more effectively and achieve better results.
Scalability: A well-defined growth flywheel playbook allows you to scale your growth efforts, making it easier to drive growth as your business grows.

Constructing and Scaling Your Growth Flywheel Playbook

Building a successful growth flywheel playbook requires a deep understanding of your customers, product, and market. Start by defining your target customer and the value you offer them. Then, identify the key growth drivers, such as customer acquisition, engagement, and retention. Finally, define the strategies and processes to drive growth in these areas.

A growth flywheel playbook is a living document, constantly evolving as you learn and grow. Continuously monitor and adjust your growth flywheel to ensure it drives the desired results.

By building a growth flywheel playbook, you can drive consistent and predictable growth, align your teams, and scale your business for success.

The Future of Product-Led Growth

Product-led growth (PLG) is a business model that prioritizes the customer experience and focuses on building and growing a product-driven company. It has proven to be a successful approach to driving revenue, increasing customer engagement and satisfaction, and driving growth. The critical components of a successful PLG strategy are customer observability, defining your ideal customer (Product Qualified Lead), and implementing a growth flywheel playbook.

In the rapidly evolving world of SaaS, staying ahead of the competition requires a deep understanding of your customers, product, and market. With the power of advanced AI technologies, companies can now clearly understand what they need to do to achieve maximum impact. Customer observability provides valuable insights into the customer journey, allowing businesses to make informed decisions about product development, marketing, and sales strategies. Defining your PQL is crucial in unlocking the potential for successful upsells and retention.

Implementing a growth flywheel playbook is also essential in driving consistent and predictable growth. A well-defined growth flywheel playbook ensures that all teams follow the same processes and strategies, leading to better results and scalability as the business grows.

In conclusion, the future of product-led growth is bright. With the right tools and strategies, businesses can prioritize the customer experience and drive growth, leading to increased revenue, customer satisfaction, and success. Companies that embrace PLG and adopt these key strategies will continue to stay ahead of the competition and drive success in the fast-paced world of SaaS.

Unlocking the Secret to Product-Led Growth: The Power of Understanding the Invisible Customer Journey

When it comes to driving growth for your business, it’s easy to focus on the obvious metrics, such as website traffic and conversion rates. But have you ever stopped to consider the invisible journey that a customer travels to make their decision to convert? The hidden factors that influence a customer’s decision-making process can be just as important as the obvious ones.

From the first time a customer interacts with a brand, they go through an invisible journey that shapes their perception of a brand and the likelihood of doing business with the company again in the future. This invisible journey is the culmination of subtle cues and touchpoints that ultimately drive product-led growth.

What is Product-Led Growth (PLG)?

Product-led growth (PLG) has become a buzzword in the business world as more companies recognize the power of letting their products speak for themselves. PLG is about creating an experience-driven product that resonates with customers and drives them through the entire customer journey. This is why a deeper understanding of customer needs and preferences is crucial for businesses looking to optimize their PLG strategy.

Think of it like a game of chess. You may have all the right pieces on the board, but if you don’t understand the subtle tactics and strategies at play, you’ll never be able to outmaneuver your opponent. Similarly, businesses may have a great product and a solid marketing strategy, but without understanding customer behavior and insights, they’ll never be able to optimize their growth potential fully.

Decoding the customer journey

So, what does the customer journey look like in practice? Let’s say you’re a SaaS company that specializes in project management software. While your website may be getting plenty of traffic, you notice that many users are dropping off at the pricing page.

By digging deeper, you discover that many of these users are small businesses that are hesitant to commit to long-term contracts. With this information, you can adjust your pricing strategy to offer more flexible options, resulting in a significant increase in conversions.

But the customer journey doesn’t end at the pricing page. To fully optimize growth, it’s crucial to analyze why small businesses are dropping off at other stages. It could be that the information or resources on the website are insufficient or that the user interface is confusing. To address these issues, you can improve the website’s design and user experience to increase conversion rates.

Consider A/B testing different pricing options and website designs to see which ones have the best impact on conversions. Additionally, reach out to small businesses that have dropped off at the pricing page through email or phone to understand their specific concerns and answer any questions they may have. This will help you enhance the customer experience and foster closer relationships with prospective clients.

Leveraging the Customer Journey for PLG Success

With a clear understanding of the customer journey, it’s time to put this information to work. Here are some ways to optimize your PLG strategy using the customer journey:

Mapping the customer journey

Identify the critical stages of the customer journey, including awareness, consideration, purchase, and post-purchase.

Identifying pain points and opportunities

Analyze each stage of the customer journey and identify areas for improvement in the user experience.

Streamlining the onboarding experience

Ensure the onboarding process is easy to understand and provide resources and support to help customers get started.

Building a feedback loop

Ask for customer feedback at key stages in the customer journey and use that information to iterate and enhance the product.

Optimizing for retention

Recognize the factors that influence customer retention and concentrate on improving them.

Analyzing customer data

Use customer data and analytics to track behavior and identify aspects of the product that are promoting growth and engagement.

Personalizing the experience

Use consumer data to personalize the experience and develop targeted marketing strategies to engage different customer segments.

Continuous testing and optimization

Keep testing and refining all aspects of the customer journey, from the onboarding process to the in-app experience. Doing this will help you enhance the overall user experience and drive growth.

Unlock Your PLG Strategy with the Invisible Customer Journey

In conclusion, unlocking the power of the “invisible journey” is key to driving growth for businesses. By gaining a deep understanding of customers and their behavior, businesses can improve customer retention, increase acquisition, and enhance conversion rates. By utilizing consumer data to personalize the experience, businesses can develop targeted marketing strategies that effectively engage different customer segments. Continuous testing and optimization of the customer journey is critical, from the onboarding process to the in-app experience. This helps businesses enhance the overall user experience and drive growth.

The customer journey is a complex and ever-evolving process, and businesses need to stay ahead of the curve to succeed. Rather than relying on assumptions and guesses, businesses should embrace the “invisible journey” to make data-driven decisions and adopt best practices that foster growth. Embracing the power of the “invisible journey” will empower businesses to take control of their growth strategy and achieve long-term success.

Fueling the future of product-led revenue – Announcing our $8.5M seed funding

We are thrilled to announce the securing of an $8.5M seed funding round led by Eight Roads, TechAviv, and a select group of angel investors, including company co-founder Ariel Maislos.

This funding will allow us to further develop our platform and grow the team as we work to bring you the best tools for converting your customer usage data into revenue.

Our platform allows you to have complete visibility of where your customers are in their customer journey by analyzing their engagement with your product in real-time. We believe that this technology has the potential to revolutionize the industry and make a real impact on the lives of our customers.

“SaaS companies are in a unique position where they can actually measure the value their users extract from their products. By correlating this information with data coming from CS, sales, and support, we create a customer observability platform, which is crucial to generating sustainable and proactive revenue growth. Securing our funding is a huge step toward our platform’s capability to help businesses succeed in a tough and unpredictable market. Especially when KPIs are now more focused on sales efficiency and NRR. As revenue teams need more product insights, we aim to provide an out-of-the-box solution to a problem which companies tried to solve internally until now.”

Itamar Falcon, CEO of Coho AI.

We would like to express our gratitude to all of the investors, customers, and employees that joined us on this journey!

Stay tuned for more developments in the near future!

Read the full story as it was shared by TechCrunch.

From Good to Great: How Customer Health Scores Drive Customer Success

As a customer success professional, one of your primary goals is to ensure that your customers are successful in achieving their desired outcomes using your product or service. This requires a proactive approach to identifying and addressing potential issues or challenges that your customers may face. One effective tool for doing this is a customer health score, which is a quantitative measure of a customer’s overall health and success with your product or service.

In this blog post, we will delve into the importance of customer health scores for customer success teams and how they can be used to drive customer success. We will also discuss some best practices for creating and using customer health scores, as well as how they can be integrated into a customer success strategy.

What is a customer health score

A customer health score is a metric that measures the overall health and success of a customer with your product or service. It is typically a numerical score or rating, with a higher score indicating a healthier and more successful customer.

There are various ways to calculate a customer health score, but it typically takes into account a combination of factors such as usage and adoption of the product, customer satisfaction, and any potential risks or issues that the customer may be experiencing. Some customer success teams may also consider other factors such as the customer’s business outcomes or the value they are receiving from the product.

The purpose of a customer health score is to provide a quick and easy way to assess the overall health of a customer, which can help customer success teams prioritize their efforts and identify potential issues or risks before they become major problems.

Why are customer health scores important for Customer Success teams?

While many companies still don’t use customer health metrics, it’s a missed opportunity that could be a significant growth engine. Here are 4 reason why:

Prioritizing efforts

With a customer health score, customer success teams can quickly assess the overall health of their customers and prioritize their efforts accordingly. This allows them to focus their time and resources on the customers who are most in need of assistance or are at the greatest risk of churning.

Identifying potential issues early

A customer health score can help customer success teams identify potential issues or challenges before they become major problems. This allows the team to proactively address these issues and prevent them from escalating.

Driving customer success

By regularly monitoring and improving a customer’s health score, customer success teams can help ensure that the customer is successful in achieving their desired outcomes using the product or service. This can lead to increased customer satisfaction and loyalty, which can ultimately drive revenue and growth for the company.

Providing a common language

Customer health scores provide a common language for customer success teams to use when discussing the overall health and success of their customers. This can help teams communicate more effectively and ensure that everyone is working towards the same goals.

Best practices for creating and using customer health scores

When creating and using customer health scores, it’s important to keep the following best practices in mind:

Choose the right metrics

The metrics that you choose to include in your customer health score should be relevant to your product or service and should accurately reflect the overall health and success of your customers. Be sure to consider a variety of factors such as usage, satisfaction, and potential risks.

Regularly review and update the score

Customer health scores should be regularly reviewed and updated to ensure that they are accurate and relevant. This may involve adding or removing metrics, adjusting the weighting of different metrics, or making other changes as needed.

Involve the customer in the process

When developing and reviewing customer health scores, it’s important to involve the customer in the process. This can help ensure that the metrics chosen are relevant to the customer’s needs and goals and that the customer is aware of their overall health and success.

Use the score as a starting point for improvement

A customer health score is not a static metric – it should be used as a starting point for continuous improvement. Customer success teams should work with customers to identify areas for improvement and develop action plans to address these areas.

Leverage data and analytics

Customer health scores should be based on data and analytics, rather than subjective opinions or assumptions. This helps ensure that the score is objective and accurate and can be used to drive meaningful actions and improvements.

By following these best practices, customer success teams can effectively create and use customer health scores to drive customer success and improve the overall health and success of their customers.

Integrating Customer Health Scores into a Customer Success Strategy

Incorporating customer health scores into your customer success strategy is an important step in driving customer success and ensuring that your customers are achieving their desired outcomes.

Set up regular check-ins with customers

Customer health scores should be regularly reviewed and discussed with customers. During these check-ins, customer success teams can review the customer’s health score and discuss any potential issues or challenges that the customer may be facing.

Use customer health scores to guide customer success plans

Customer success plans should be tailored to the specific needs and goals of each customer. Customer health scores can be used to guide the development of these plans and to identify areas where the customer may need additional support or resources.

Use customer health scores to drive cross-functional collaboration

Customer success is often a cross-functional effort, involving teams such as sales, marketing, and product development. .Having a single source of truth can be used to drive collaboration across these teams and ensure that everyone is working towards a common goal.

Leverage automation and technology

There is a variety of technologies available that can help automate the process of tracking and managing customer health scores. These tools can help customer success teams save time and focus on more high-value activities, such as working with customers to address their needs and drive success.

Takeaways

Customer health scores are a crucial tool for customer success teams as they help prioritize efforts, identify potential issues early, drive customer success, and provide a common language for teams to use.

By regularly reviewing and updating customer health scores and integrating them into a customer success strategy, CS teams can build stronger, more loyal customer relationships and drive revenue and growth.

Want to know more about how you can incorporate customer health score into your daily work? Contact us!

Maximizing B2B SaaS Revenue with NRR: Why It Matters and How to Do It

In times of recession, businesses are more likely to cut costs wherever possible, including by canceling subscriptions to non-essential services. This means that B2B SaaS companies need to focus on retaining their existing customers in order to continue generating revenue. NRR allows companies to track their success in doing so and make any necessary adjustments to their retention strategies.

Winning at revenue growth also relies on revenue retention. Revenue retention will give you the keys to unlocking all other aspects of revenue growth strategy.

These users prop up all outreach to new customers showing that your brand has a high-level of trustworthiness for long-term relationships.

Revenue growth can seem like a no-brainer, but when it comes to revenue retention, it can feel like a shot in the dark. So, what is net revenue retention, and why does it matter so much?

Net revenue retention, abbreviated NRR, is a metric used to boost business growth.

What is NRR?

Net Retention Rate (NRR) is a key metric for any B2B software as a service (SaaS) company, but it becomes particularly important in times of economic recession. NRR measures the percentage of a company’s existing customers that continue to use and pay for its services from one period to the next.

Industry leaders describe NRR as “net dollar retention.”

Net dollar, or net revenue retention, the company considers upgrades, downgrades, and customer churn to analyze the business customer base.

NRR breaks down into monthly segments called monthly revenue retention, or MRR. MRR is a rough estimate of the revenue that comes from your user base each month.

Why is NRR important?

Experts believe NRR is now more important than ever before.

With the current economic slump, it is now more important than ever before to retain customer bases.

Estimates state that a business can deliver 20 percent growth yearly with the existing customer base.

Growth happens without adding a single new user. Why? Because a stable customer base has expansion opportunities. We’ll talk about that in a minute. First, we’ll define the logic and the math that backs NRR.

Know what churn looks like

When factoring NRR, you will also want to look at churn cases. Churn is the rate at which customers end relationships with your brand.

If a customer cancels a subscription, this may not be the same thing. They may still access your free version of the product, and yet not be paying for a subscription for whatever reason.

Churn distinguishes between these cases and cases where a customer has broken a connection with your brand forever.

The math of NRR

Net Revenue Retention requires some simple math. Use the NRR equation:

(Contraction MRR – (Churn MRR + Expansion MRR)) / Starting MRR

Alright, so math sucks. Let’s break this down.

To find your NRR, you will add your growth to your starting MRR. Subtract downgrades and churn from this new MRR. Now divide the new MRR by your starting MRR. Last, multiply the MRR you got from the division by 100%. This final result is your NRR.

How to use your NRR

You might be wondering why we put you through the math. Trust us, it’s worth it.

Simmering it down, NRR is the tool we use to gauge business growth potential from our existing user base. These are more than just fancy calculations. We’re solving for where our growth potential is so we can strategize the best ways to influence that growth to happen.

Industry leaders say that a good NRR is going to show growth of over 100%.

When the NRR passes the 100% mark, we see growth instead of a static revenue retention rate. An NRR of 100% shows that our annual revenue retention, or ARR, has either grown or remained the same.

Ideally, we want the NRR number to be 109%. This shows that we are retaining a good revenue income and also growing by roughly 9%.

Recognize the room to grow

While 9% is ideal, we have found that a business can grow by 20% per year by keeping a healthy net revenue retention.

Using NRR gives us insights into how to upsell our subscription base.

Because NRR can show us who is already engaging with a paid version of the product, we can use these metrics to estimate who will be open to an upsell. Upselling happens when your current customer base is open to the value offer for a higher-cost subscription.

Invest time in expansion opportunities

Remember a little while ago when we said NRR was good for expansion opportunities? We’ll bring it full circle now. Upselling is one of the expansion opportunities we can explore through NRR math.

KPIs for the upsell

We need a little bit from our data rather than solving for growth rates. KPIs take over here. Informed KPIs give us the data groups and tools for seeing the value our users are looking for in an upgrade. We sell from there.

Building the upsell

Setting data priorities straight empowers the upsell process. As we explore upselling, we work towards expansion revenue goals. Expansion revenue is any revenue that expands from initial customer contact. We call it expansion revenue because we’re exploring an expanding relationship with our customers.

Upselling is one of two primary expansion catalysts. The second catalyst is cross-selling. Cross-selling introduces customers to new features or add-ons within their existing plans.

Prevent churn

Remember that data can alert you to positive growth opportunities, but it can also show you areas where improvement is key. To avoid churns and “drop off,” you need to know your data and streamline the upsell and cross-sell to work naturally with where the customer is in their relationship with you.

Marketing leaders remind us that no one likes to be “sold to.” A customer with an issue is more likely to have a negative reaction to expansion measures if they feel that their current needs are not being met. However, addressing this is relatively simple. When in doubt, return to your user data flows.

Know your data

We talked about KPIs a little while ago. Here is where they get all-important. Without a clear use for data, teams fumble around product management funnels in the dark.

This is why actionable, AI-led product growth modeling is important. Here we point a laser to the KPI and hone in on data that is essential for reaching those KPI-based goals.

Make your data work for the customer

Whether you upsell or cross-sell, make data work for the customer. Boost your pipeline to understand the customer user-experience flow. Then, use this information to work in natural upsell and cross-sell opportunities.

Coho’s AI-enhanced product-led growth insight tool will notify the team when a customer reaches a milestone.

Notification helps teams to optimize the flow of selling prompts in a way that flows with the customer journey and needs. Is a customer outgrowing their current subscription? It’s time for an upsell. Is the customer running into a few roadblocks based on the need for one additional feature? Cross-sell to them.

Coho AI enables personalized selling based on usage insights.

Takeaways

Customers are people. Data helps us relate to them in ways that are as diverse as they are. With better insights into the flow of their needs and wants, we can use the NRR to optimal advantage.

Coho AI believes that product-led revenue growth is people-led revenue growth. AI empowers human interaction in mass numbers in ways that other growth models never could.

Bottom line: the NRR is vital to underlying our core community of users. By building on this, you will invest in the life and future of not only your product but also your brand community. In an economy driven by uncertainty and a deep need for connection, this makes daylight to dark difference between you and your competition.

How to turn your company into a Product-led company

Did you know that investors have found that product-led companies are twice as likely to grow fast than other models?

A June study published by TechCrunch discovered that product-led growth models are “2x more likely to grow quickly than sales-led” growth models. To tap into this rapid growth opportunity, you’ll want to know how to transform your current growth model to follow product-led growth. Today we’ll show you how it’s done.

Understand your user journeys

First, you’ll need to understand the path your users take through your product. Data that tracks the user journey through your product is essential here.

By tracking user data, you are observing user interaction with your product. This gives you a clear oversight into a user’s path, what went well and what may have triggered difficulty. With this oversight, you can start honing in on improvements.

Major companies such as Tesla gather user data to hone in on the “product experience” of their brand. By collecting feedback, Tesla ensures that it engages with real users to constantly improve the product experience. Tesla has been credited with “transforming car buying” into an ongoing experience rather than a one-off purchase.

Create product experiences that push time-to-value

Now that you’ve got a clear idea of the customer’s path, you’ll want to cut down the obstacles a customer faces using your product. Customers essentially search for a quick problem-solving solution when shopping for products. By trimming down obstacles, you can invest in the speed at which your product solves your customer’s problem.

This rate of problem-solving speed is called “time to value”. When you reduce the obstacles a product user faces to reach their ideal solution, you accelerate the time-to-value ratio. Creating product experiences that push this speedy solution arrival time is an essential part of driving home a PLG model.

User Guiding blog summarized PLG as the growth model where the product is the core of the business, and customers are the core of understanding the product. Customer experience and engagement steer data gathering to build a stronger core.

Steer users to natural conversions with value

PLG modeling focuses on honing and empowering customer-to-product relationships. Steer users to conversions by letting them understand the true value of your product on their own. A free product with many key value features entices the user to experience the product further. This leads to a natural conversion to a higher value tier within your product.

But while many companies have adopted this model and do let their users take the product for a ride before they buy it, they still treat the conversion stage as “one size fits all”, instead of following the actual user journey their users go through and offer them to purchase a plan only once they hit an actual milestone and are ready to make the purchase.

Introduce new features based on customer usage

As you steer natural conversions through value, you will want to gradually work in new features and experiences. Using user data to hone this usage-based feature building guarantees that you are adding features customers are eager for, based on their needs.

UserGuiding blog explains user data led feature adding works because the data “comes up” with new features based on user behavior, and conveys to the user their needs and expectations.

Base pricing around customer needs

In order to become a full-fledged PLG model, you need to scale into flexible pricing packages that allow customers to subscribe according to their preferences. With flexible pricing, customers don’t feel pressured into making time-based commitments, and they can choose the plan that fits their needs the most.

Because PLG needs to deliver value and customer experience instantly, breaking down hesitation barriers is key to unblocking the user pathway to conversion.

Strategize the upsell

PLG experts advise strategizing the upsell after the product has delivered value. Users with access to a demo product already have experience with your product. A PLG company needs to base upselling on features that stand out as added value on top of the current experience.

By focusing on delivering experience-driven products, PLG models break down barriers to monetization. When the time comes for a paid version, the user knows the current product value and is more willing to pay for added value.

Overview

These steps are starting places. While product-led growth is easy to implement, there are also many intricate parts that make up a successful PLG growth model. These steps can set you up with an efficient PLG growth model to build from.

Want to learn more? Follow our team of PLG visionaries at Coho for more insights or contact us.

Common misconceptions about Product-led growth

It’s no secret that product-led growth strategies, abbreviated PLG, are all the rage right now. As a result of PLG’s go-to-market models, B2B sales have been permanently altered, making it an essential growth leader for modern companies. However, common misconceptions about PLG encourage growth leaders to dismiss it as a fad.

PLG misconceptions cost businesses who fail to understand the marketing and sales significance of product-led strategy. We’ve narrowed down a few of these common myths so you know why they cost you, and how to avoid them.

Myth 1: You won’t need a sales team

Product-led growth marketing is the strategic arm of product-led companies. “Product-led” means that the company uses its resources to hone the power and appeal of the product it offers so that it can convert sales on its own merits.

A product-led growth model still needs a sales team because sales teams can help identify key customers, wrote Forbes Council Member Vanessa Dreifuss.

Myth 2: Your buyers will be entirely self-sufficient

While a solid product-led growth model will seek ways to empower the self-sufficiency of the user experience, the buyer won’t be entirely self-sufficient.

The PLG growth go-to-market enables customers to be highly self-sufficient but does eliminate the need for customer support. Customer experience support teams measure their success in their response time to customers, and the efficient support of the customer’s voice.

Myth 3: PLG will drive revenue by itself

PLG is often mistaken for a revenue-driving strategy by itself. Contrary to this belief, Darrow explained that PLG streamlines the potential conversion from free demos to paid subscriptions. PLG by itself doesn’t drive revenue or target the right user.

Targeting the best users and closing sales requires smart use of KPI data and the combined effort of team support, which we’ll get into more below.

Myth 4: You won’t need marketing

A PLG-led growth model still needs a marketing push. Believing that PLG can take care of itself without any push from marketing costs teams because they rely too broadly on PLG, and essentially don’t understand the outcomes PLG can generate. The basic outcomes from PLG are: 1) Acquisition and 2) Conversions.

PLG provides a pipeline to draw in customers and streamline their product-interaction process. The same rules of marketing that apply to previous growth model leaders still apply to PLG because marketing drives brand awareness and other outcomes that boost PLG’s efficiency.

Go-to-market research finds that PLG works best when it is aligned with the revenue marketing team efforts.

Myth 5: Self-service is the only buying experience customers want

While it’s true that the modern buyer wants the convenience of self-service, they still need help with sales questions sometimes. The sales teams help to make products better by addressing customer needs.

In the same way that PLG speeds up the buyer’s journey process, sales teams accelerate closing deals. Sales teams in a PLG supportive role can “supercharge” sales growth.

How To Implement PLG The Right Way

You can take the next step towards an informed PLG implementation by dispelling common misconceptions. Here’s where Coho comes in. Our platform helps you target and optimize key KPIs and orchestrate your customer journey flow.

With Coho’s platform, teams can apply data to their PLG growth model, generating the correct hand-in-glove use of team support for the streamlined user journey.

Streamlined data, focusing on key customer retention paths, support the tactical implementation of PLG. By honing in on focal points in the data, a team can eliminate redundant data gathering and focus on data streamlining their revenue funnels.

Want to learn more? Contact us today.