A Beginner’s Guide to Cohort Analysis in Marketing

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Key Takeaways

Cohort analysis is a powerful technique for segmenting customers based on shared characteristics or behaviors, providing valuable insights into customer trends and preferences.

Improved customer retention is a significant benefit of cohort analysis, enabling businesses to identify loyal customer groups and tailor retention strategies effectively.

Cohort analysis also contributes to enhanced product development by guiding businesses in understanding how different customer segments interact with their products or services.

Better campaign performance is another advantage of cohort analysis, as it helps marketers optimize their strategies by identifying which campaigns resonate most with specific customer cohorts.

By leveraging cohort analysis, businesses can allocate resources more efficiently, refine messaging, and personalize promotions to maximize ROI and overall campaign effectiveness.

Incorporating cohort analysis into your marketing approach can lead to data-driven decision-making, improved customer experiences, and ultimately, business growth and success.

Are you looking to understand your customer data better and improve marketing strategies? Welcome to “A Beginner’s Guide to Cohort Analysis in Marketing.” We’ll explore how cohort analysis can transform businesses.

Ever thought about how grouping customers by behavior and traits can enhance marketing? Let’s see how cohort analysis can boost your grasp of customer trends, improve retention, and enhance campaign performance.

What is Cohort Analysis?

Cohort analysis is a powerful marketing tool. It helps businesses track specific customer groups over time. By grouping them based on similarities, like their first purchase date or how they were acquired, it reveals insights into retention, engagement, and performance.

Types of Cohorts

  • Acquisition Cohorts: This groups customers by their acquisition date. It uses their first interaction or purchase with the company. By studying these cohorts, we can spot trends in customer acquisition, find valuable customer groups, and shape marketing strategies to attract similar customers later.
  • Behavioral Cohorts: These groups customers based on their actions or behaviors. For instance, their product usage, engagement, or subscription renewals. This analysis shows how different customer groups interact with the product or service. It helps identify retention strategies and tailor marketing to boost satisfaction and loyalty.

4 Steps to Conduct Cohort Analysis

Step 1 – Setting Up Cohort Groups

To start a cohort analysis, first, create separate cohort groups. These groups share a common trait, like the first product interaction month or location.

This step divides customers, aiding in understanding their behavior over time. It also helps in developing focused marketing strategies.

Step 2 – Data Collection and Preparation

After defining cohort groups, the next step is to gather and prepare data for analysis. First, collect key metrics. These include when customers were acquired, their purchase history, engagement, and retention rates. Ensuring data is accurate and consistent is crucial. It helps in drawing meaningful insights from cohort analysis.

Step 3 – Performing the Analysis

First, we identify cohort groups and organize data. Then, we start the analysis. We compare key metrics among cohorts over time. This reveals customer behavior and trends. It also helps assess marketing or product changes. Finally, we use tools and techniques to gain insights from the data.

Step 4 – Visualizing Cohort Data

Using visuals for cohort data boosts understanding and decisions. Marketers commonly use line charts. They show how metrics change after acquiring customers.

Also, cohort retention curves clearly display customer retention over time. These visuals help marketers spot areas for improvement. They can then enhance strategies and grow the business.

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Key Metrics to Track

Conversion rates

In cohort analysis, conversion rates are key. They show how well marketing strategies work. This metric tracks the percentage of users moving from signups to purchases.

By studying cohort data, marketers can discover which groups are more likely to convert. Then, they can adjust campaigns, improving returns and gaining more customers.

Retention Rates 

Retention rates, another crucial aspect of Cohort Analysis, measure the percentage of active users who continue engaging with a product or service over time.

By segmenting users into cohorts based on their sign-up or acquisition dates, marketers can identify trends in user behavior and implement retention strategies to reduce churn and foster long-term customer relationships.

Customer Lifetime Value (CLTV) 

Cohort Analysis enables marketers to calculate Customer Lifetime Value (CLTV) accurately. By tracking the revenue generated from cohorts over their entire lifecycle, businesses can understand the value each cohort brings and allocate resources effectively. CLTV insights derived from Cohort Analysis guide strategic decisions, such as investment in customer retention or acquisition initiatives.

Engagement Metrics

Engagement metrics encompass various indicators, including website visits and time spent on apps, that reflect user interaction and interest. Cohort Analysis enhances the understanding of engagement patterns across different user groups, enabling marketers to refine content, optimize user experiences, and drive meaningful interactions. By monitoring these metrics within cohorts, businesses can adapt their marketing strategies for enhanced user engagement and satisfaction.

Tools for Cohort Analysis

Google Analytics

Google Analytics is popular in marketing for cohort analysis. It tracks user actions and groups them by criteria like when they joined, their location, or site actions. This tool helps businesses understand customer loyalty, engagement, and marketing campaign impact.


Mixpanel is a powerful platform for analyzing user groups and behavior. Specifically, it tracks how different groups behave over time. It offers detailed reports and visuals.

These help businesses see how their marketing strategies affect customer segments. Also, it’s great for improving marketing. Marketers can study user retention, product use, and marketing’s impact.


Amplitude is a top analytics tool for mobile and web apps. It shines in cohort analysis. This feature lets businesses make custom groups. They can use parameters like user behavior, demographics, and life stages.

Marketers then use these insights. They learn about user involvement, conversion rates, and how to enhance journeys. This guides their decisions and marketing strategies.

Benefits of Cohort Analysis in Marketing

Improved Customer Retention

Cohort analysis significantly boosts customer retention in marketing. First, it sorts customers by behavior and traits. This reveals what keeps them happy. Also, it pinpoints loyal groups. Companies then create strategies to keep these segments. Finally, it helps meet customer needs, lower churn, and build lasting relationships.

Enhanced Product Development

Cohort analysis significantly boosts product development in marketing. It involves studying customer groups. This process helps companies understand how these groups use products or services.

By knowing this, they can tailor improvements and innovations to suit each group better. Also, cohort analysis uncovers patterns and preferences. This leads to more focused development and better products.

Better Campaign Performance

Cohort analysis plays a crucial role in improving campaign performance for marketing initiatives. By examining the behavior and response of customer cohorts to various campaigns, businesses can optimize their marketing strategies for better results.

This analysis helps in understanding which campaigns resonate most with specific customer segments, allowing for personalized and effective targeting. With cohort analysis, marketing teams can allocate resources more efficiently, refine messaging, and tailor promotions to maximize ROI and overall campaign effectiveness.


Cohort analysis helps marketers. It reveals customer patterns, boosts retention, and guides product development. Also, it enhances campaign performance. By grouping customers with similar traits, businesses can make smart, data-driven choices.

These choices lead to better marketing and improved outcomes. Adding cohort analysis to marketing strategies is key. It provides insights that foster growth and success in competitive markets.


What is a cohort analysis example?

A cohort analysis example involves tracking a group of users who signed up in January and observing their behavior over subsequent months to understand retention and engagement trends.

How do you perform cohort analysis in Excel?

To perform cohort analysis in Excel, create a pivot table with user data segmented by acquisition date and activity, then use formulas to calculate retention rates over time.

How is cohort analysis done in Python?

In Python, cohort analysis can be done using libraries like pandas and matplotlib to process user data, create cohorts, and visualize retention metrics with detailed plots.

Where can I find a cohort analysis template?

Cohort analysis templates are available online, often as Excel or Google Sheets files, providing pre-formatted tables and charts to input your data and analyze cohorts easily.

How is cohort analysis used in research?

In research, cohort analysis is used to study specific groups over time, assessing changes in behavior or outcomes based on different interventions or conditions.

What is cohort analysis in marketing?

Cohort analysis in marketing involves grouping customers by shared characteristics or signup dates, then tracking their interactions and behaviors to improve retention and campaign effectiveness.

How do you use cohort analysis in Tableau?

In Tableau, cohort analysis is performed by creating calculated fields to define cohorts and using visualization tools to display retention and engagement trends across different time periods.

Can you do cohort analysis in Power BI?

Yes, cohort analysis in Power BI is done by importing user data, creating custom measures and calculated columns to define cohorts, and using visualizations to track their behaviors over time.

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