Cohort analysis is a statistical technique used to evaluate the behavior and characteristics of a group of individuals over time. It is commonly applied in business and marketing to comprehend how customer behavior changes throughout their relationship with a company. By examining data from specific cohorts, businesses gain insights into customer retention, engagement strategies, and areas for growth.

In its simplest form, cohort analysis involves dividing individuals into distinct subgroups, or cohorts, based on common characteristics or behaviors. For example, businesses might categorize customers by the month of their first purchase. This segmentation enables comparison between different cohorts, providing valuable insights into customer behavior changes.

Cohort analysis addresses essential questions such as:

  • How effective are our customer retention efforts after the first purchase?
  • What factors influence customer retention in specific cohorts?
  • Are specific customer segments showing higher or lower retention rates?
  • How do customer behaviors change within each cohort over time?

Cohort Analysis Benefits

Once defined, cohorts are analyzed to understand their behavior over time, revealing insights into customer loyalty and purchase patterns. Businesses can compare metrics like average purchase amount and second purchase rates across various cohorts, allowing them to identify trends and patterns.

Cohort analysis offers the advantage of controlling external factors influencing customer behavior, such as economic downturns. 

By isolating such effects, you can understand their true impact on the business and adapt strategies or processes accordingly.

Types of Customer Cohorts

Several types of cohort analysis exist, including:

  • Time-based Cohorts: segmented based on acquisition time, revealing retention differences across various periods.
  • Acquisition Cohorts: focus on customers acquired through different channels like organic search, paid advertising, social media, etc.
  • Product-specific Cohorts: highlight customer engagement with specific products, indicating bestsellers and products causing churn.
  • Customer Segmentation Cohorts: groups customers based on demographics, behavior, or purchase history, helping prioritize efforts.
  • Behavioral Cohorts: segmented by specific actions like cart abandonment or multiple purchases, guiding targeted strategies.
  • Loyalty Program Cohorts: focus on customers engaged with loyalty programs, enabling measurement of program impact on retention and engagement.

Conducting Cohort Analysis Step By Step

Cohort retention analysis is a meticulous and iterative process essential for unlocking valuable insights into customer engagement and loyalty. Let’s break down the steps to perform a comprehensive cohort analysis that yields actionable results.

Step 1: Define the Period

Begin by defining the timeframe you want to analyze for cohort retention. The duration can vary based on your business and customer nature, but selecting a relevant period is crucial to capture meaningful trends.

Step 2: Create Cohorts

Divide your customers into distinct groups or cohorts using predefined types or tailor-made categories that align with your objectives. Strive for a balance between statistical significance and granularity to capture meaningful behavioral differences.

Step 3: Choose Key Metrics

Identify key metrics for measuring retention within each cohort, whether it’s tracking Net Promoter Score (NPS) for recommendations or retention rates for overall loyalty. Select metrics that align with your business goals and accurately represent customer behavior.

To get you started, here’s a list of possible metrics to focus on:

  • Repeat Purchase Rate: indicates customer loyalty and retention effectiveness, aiding personalized marketing efforts.
  • Average Order Value (AOV): understands spending behavior variations across cohorts, guiding personalized strategies.
  • Customer Lifetime Value (CLV): reveals cohorts with higher long-term value, ensuring focused retention efforts.
  • Purchase Frequency: identifies high and low-frequency cohorts, enabling targeted retention strategies.
  • Average Customer Lifespan: evaluates the average duration of customer lifecycle within each cohort, indicating campaign effectiveness.
  • Customer Engagement Metrics: Includes website visits, time spent, open email rates, and click-through rates, uncovering behavioral patterns.

Step 4: Track Cohort Activity

Monitor the behavior of each cohort over time by meticulously collecting data on their interactions with your business. Data sources can include transaction records, return forms, or customer engagement metrics.

Ensure robust data collection mechanisms are in place for accurate tracking.

Step 5: Calculate Retention Rates

Calculate retention rates by dividing the number of active customers within each cohort by the total number of customers or users initially in the cohort.

For example, in monthly retention analysis, calculate the percentage of customers active each subsequent month after their initial interaction. This quantitative measure assesses how effectively cohorts retain customers over time.

Step 6: Visualize Data

Utilize visualization tools to represent your data through line graphs, bar charts, or heat maps. Visualizations facilitate easy comparison of retention rates across different cohorts over time, making trends and patterns visually discernible. Clear visualizations also aid in effectively communicating insights from your cohort retention analysis.

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Step 7: Analyze Across Cohorts

Delve into the data across cohorts to identify variations and insights. Look for factors or events that may have influenced retention, such as pricing changes, marketing campaigns, or customer support initiatives. Leverage customer surveys and interviews to gain qualitative insights, complementing your quantitative data analysis.

Step 8: Derive Actionable Insights

Conclude the cohort retention analysis by identifying cohorts with higher or lower retention rates. Dive deep into potential reasons behind these differences, revealing the underlying truths. These insights are the cornerstone for strategic decision-making, enabling you to design targeted initiatives aimed at improving retention rates effectively.

Unlocking the Potential of Cohort Analysis for Customer Retention

Cohort analysis offers clarity in these complex scenarios, providing insights that guide the path to customer retention. 

Here, we delve into four strategic approaches that leverage cohort analysis to maximize Customer Retention Rate (CRR) and foster enduring customer relationships.

1. Tailored Offers for Targeted Retention

Utilizing cohort analysis, you can glean invaluable data about customer preferences and purchasing habits. Identify high-value customers and discern their favored products or services. 

Armed with this knowledge, craft personalized offers—from enticing coupons to free shipping and discounts—designed to retain existing customers. 

By tailoring your incentives, you create a compelling reason for customers to stay loyal to your brand.

2. Loyalty Programs: Fostering Lasting Connections

In an era where choices abound, customer loyalty means stability. 

Implementing loyalty programs enhances customer retention by instilling a sense of belonging and appreciation. 

Incorporate elements of gamification, rewards, tier programs, and loyalty points to add allure to your offerings. 

Cohort analysis, with its ability to pinpoint receptive customers, aids in targeting those most likely to engage with and benefit from loyalty initiatives.

3. Reactivation Campaigns: Reviving Dormant Connections

Identifying idle customers is an opportunity rather than a setback. Cohort analysis enables you to discern intervals between purchases, unveiling critical insights. 

Armed with this knowledge, craft reactivation emails tailored to individual customer timelines. A strategic nudge can reignite interest, guiding dormant customers back into the fold. 

Precision in timing is key, ensuring your efforts resonate with the right audience at the opportune moment.

4. Proactive Problem-Solving: Anticipating and Addressing Issues

Cohort analysis equips you with the ability to pinpoint the exact moment a user’s journey concludes on your website. 

Armed with this information, proactively resolve issues, preventing future occurrences and potential customer losses. 

Timely interventions and seamless resolutions demonstrate your commitment to customer satisfaction, instilling confidence and loyalty.

Building Your Cohort-Driven Retention Strategy

Embarking on a cohort-driven retention strategy might sound daunting, but with a structured approach, it becomes a powerful tool for business growth. 

Follow these steps to orchestrate an effective retention strategy tailored to your unique customer landscape:

Identify High and Low-Retention Cohorts

Analyze cohort retention data to pinpoint groups with high and low retention rates. Focus on significant customer segments or those with potential for enhanced value, aligning with your business goals.

Uncover Cohort Characteristics

Delve into customer demographics, purchase behavior, engagement patterns, and other relevant data points within high and low-retention cohorts. This deeper analysis sheds light on the factors influencing retention within each group.

Identify Key Retention Drivers

Identify the key factors contributing to high retention rates within successful cohorts. These drivers could range from product features and customer support to personalized experiences and communication channels. Tailor strategies based on these insights.

Address Low Retention Factors

Identify gaps leading to low retention rates and develop initiatives to address these issues. From product enhancements to personalized messaging, implement changes that enhance the customer experience and boost loyalty.

Personalized Engagement Strategies

Leverage cohort analysis insights to customize marketing campaigns, communication strategies, and customer support initiatives. Monitor the impact of these strategies through A/B testing and customer feedback, refining your approaches continuously.

Sustained Value and Engagement

Remember, retention strategies extend beyond the initial acquisition phase. Continuously provide value, nurture relationships, and maintain open communication to enhance engagement and foster lasting customer loyalty.

Long-Term Monitoring for Success

Keep a vigilant eye on cohort retention over the long term. Monitor the effectiveness of your strategies and adapt as needed. By staying proactive and customer-focused, your business can ensure sustained success and enduring customer satisfaction.


Your customers are at the heart of your success; understanding them is the key to your growth.

Cohort analysis is a powerful tool that helps you uncover insights into customer behavior, loyalty, and how it evolves over time.

These valuable insights are the foundation on which you can create personalized experiences and targeted strategies that speak directly to your audience.

Need a helping hand? 

Omniconvert’s Reveal makes cohort analysis easy, simplifying complex data and allowing you to understand your customers better and refine your business strategies.


What Is Meant by Cohort Analysis?

Cohort analysis is a statistical technique used to evaluate the behavior and characteristics of a group of individuals over time.

It involves dividing a group of individuals into distinct subgroups, or cohorts, based on a common characteristic or behavior and then analyzing their behavior over time.

What Is Cohort Analysis (With Example)?

A business might use cohort analysis to understand how customer behavior changes over the course of their relationship with the company.

The business might divide its customers into cohorts based on the month in which they made their first purchase and then analyze the average purchase amount and the percentage of customers who make a second purchase for each cohort.

By comparing these metrics across different cohorts, the business can identify trends and patterns that can inform its marketing and retention strategies.

What Is a Cohort and a Cohort Analysis?

Cohort analysis is a type of observational study, which means that it involves observing and analyzing data without manipulating or intervening in the behavior of the individuals being studied.

This allows researchers to identify trends and patterns in the data that may not be apparent through other methods of analysis.

How Do You Do a Cohort Analysis?

To do a cohort analysis, follow these steps: identify the group of individuals that you want to study and divide them into distinct subgroups, or cohorts, based on a common characteristic or behavior; collect data on the behavior and characteristics of the individuals in each cohort.

Analyze the data for each cohort and compare the results across different cohorts; use the insights gained from the analysis to inform your business or marketing strategies; and continue to monitor and update the data as needed.

Why Do We Do Cohort Analysis?

Cohort analysis is often used in business and marketing to understand how customer behavior changes over the course of their relationship with a company.

It allows businesses to control for external factors that may influence customer behavior and to identify opportunities for growth and improvement.

By analyzing data from a cohort of individuals, businesses can gain valuable insights into how to retain and engage their customers, as well as identify potential areas for growth and improvement.

What Type of Study Is a Cohort Analysis?

Cohort analysis is a type of observational study, which means that it involves observing and analyzing data without manipulating or intervening in the behavior of the individuals being studied.

This allows researchers to identify trends and patterns in the data that may not be apparent through other methods of analysis.