An approach engineered for impact

Maximize customer lifetime value with Measurly’s state-of-the-art AI model suite.

A powerful suite of advanced models, working together to maximize customer lifetime value.

Advanced Segmentation

Clusters your entire customer base based on their preferences and behaviors, while mapping out a path to increase their engagement, retention, and lifetime value. 

Our models take into account the thousands of behaviors and experiences of your users, clustering them into segments that define how each group interacts with your product. We enhance these segments with predictive lifetime value and churn probability to identify and prioritize which groups to focus on first.

By uncovering insights and patterns in customer behavior and preferences, our approach helps you gain a deeper understanding of your customers, enabling more effective engagement strategies.

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Predictive Lifetime Value (LTV)

Estimates the future revenue potential of your users until their natural churn point. 

Based on a forward-looking approach that estimates the probability of customers making each subsequent transaction, and arrive at a future ‘infinite’ lifetime value with a given accuracy score. The power of using our predictive LTV model over a backward-looking timegated LTV is the quick feedback loop. Launching new products or changing prices will immediately be seen in the accuracy of each customer’s lifetime value, allowing for real-time optimization and better decision-making. 

This approach provides a deeper understanding of your customers, helping you maximize the value of your customer base and enabling sustainable growth.

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Recommendation Algorithm

Influence your customers’ engagement potential by proactively recommending your products and services throughout their buying journey.

Complemented by Advanced Segmentation, our algorithm recommends complementary services to your customers based on your business model and their buying frequency. Our Collaborative filtering model is ideal for businesses with one or similar services, as it recommends products and services that similar users have enjoyed. Our Content-based filtering model is ideal for businesses with multiple products or services that are complementary, recommending products that are similar and complementary for up-sell opportunities.

This approach helps you to better understand your customers’ preferences and needs proactively, enabling you to offer targeted and personalized recommendations that can drive higher engagement, retention, and revenue growth.

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Retention Model

Predicts the probability that each customer comes back within a dynamic time period. 

This model links the probabilities of each customer returning with the leading indicators of why they may churn, providing you with a menu of options to improve retention.

This unlocks the ability to tailor your communications to each customer, targeting the specific reasons they are at risk of leaving your product.

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Behavioral Model

Analyzes historical customer interactions and behaviors to gain a deep understanding of each customer’s unique preferences, needs, and decision-making processes.

Every customer has unique needs, preferences, and behaviors that shape their experience with your product. Our behavioral model captures these individual differences and enhances the dimensions of every other model.

By describing how and why each user interacts with your product, the behavioral model provides insights that allow you to create targeted campaigns. This personalized approach leads to increased engagement, open rates, and conversion rates for each customer segment, helping you maximize your marketing efforts.


Sentiment Model

Uses natural language processing to break down all of your users’ rich texts, such as reviews, biographies, and user profiles, and clusters them into distinct groups. 

This approach provides insights into how customers feel about your products or services and their unique needs and preferences. 

This data can then be used in conjunction with churn and engagement modeling to influence the end customer segment, predictive LTV profile, and recommended products and services. 

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Engagement Model

Uses historical customer interactions and behavior to predict the likelihood of future purchases or engagements.

By analyzing past customer interactions and the frequency of these engagements, we estimate the total number of interactions or orders a customer is likely to make in the future, helping you make informed decisions to improve operations and increase profits. 

This information allows companies to create targeted marketing strategies, optimize pricing, and improve customer experience.  

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How it Works

Engineered for impact

Fancy data models are nothing without thorough data feature selection and a robust marketing strategy designed to drive meaningful results. Our approach brings together data science and growth marketing to answer the “so what?” from your customer data and help you drive tangible outcomes that impact your bottom line.


We deep-dive into your data to get a deep understanding of each customer and what influences their conversion.


Our learning process fuels the AI models we train to predict future customer interactions and optimal ways to influence their journey.


Connection with your marketing tools allow you to capitalize on opportunities to grow customer engagement through real-time campaigns.


Explore how our models drive meaningful results to customer engagement.

Supercharge customer engagement with Measurly.

Book a demo or schedule a strategy call to learn how Measurly can help your business grow.