What is cohort analysis?
A cohort is a group of people who share a common characteristic or experience within a defined time frame. For instance, users who signed up for a service in January 2024 or customers who made their first purchase during a specific marketing campaign. Cohort analysis involves tracking these groups over time to evaluate their behavior and identify trends.
Unlike traditional analytics, which might focus on overall user metrics, cohort analysis breaks down data into smaller, more meaningful segments. This approach makes it easier to identify patterns that could be masked by aggregated data.
Benefits of cohort analysis
Improved customer retention
Cohort analysis helps businesses understand customer retention rates by analyzing how different groups of users engage with a product or service over time. For instance, it can reveal whether customers acquired through a specific channel have higher or lower retention rates compared to others.
Better marketing strategies
By identifying which marketing campaigns attract high-value customers, it allows businesses to allocate resources more effectively. It can also help determine which cohorts respond best to specific promotional strategies.
Product optimization
It can uncover how users interact with a product, revealing pain points or features that drive engagement. This information is invaluable for product teams looking to improve user experience.
Enhanced revenue insights
Analyzing cohorts based on purchase behavior can provide insights into customer lifetime value (CLV) and revenue trends. Businesses can identify which cohorts contribute the most to revenue and focus efforts accordingly.
Types of Cohort analysis
- Acquisition cohorts: This type focuses on users grouped by the date they started using a service or product. For example, you might analyze how retention rates differ between users who signed up in January versus February.
- Behavioral cohorts: Behavioral cohorts group users based on actions they’ve taken, such as purchasing a specific product, completing a tutorial, or engaging with a feature. This type of analysis helps understand how specific behaviors influence outcomes.
How to conduct cohort analysis
- Define your cohort: Determine the criteria for creating your cohort. This could be based on acquisition date, customer behavior, or demographic attributes.
- Choose a metric to analyze: Decide on the KPIs you want to evaluate. Common metrics include retention rate, conversion rate, and average revenue per user (ARPU).
- Visualize the data: Cohort analysis is often presented in a table or chart format, such as a retention curve or heatmap. These visualizations make it easier to spot trends and compare cohorts.
- Interpret the results: Look for patterns and anomalies in the data. For example, if a particular cohort has a significantly higher retention rate, investigate what factors contributed to its success.
Tools for cohort analysis
Several analytics tools can help automate and simplify cohort analysis, like Google Analytics, Shopify Analytics, or NestAds.
NestAds is an ad tracking and marketing attribution software that centralizes data from all the platforms you’re working with, such as TikTok, Facebook, Google, Klaviyo, and more. Within NestAds’ Business Intelligence, you can see cohort analysis with the cost of acquisition.
Combined with marketing insights from NestAds’ features, you get deep insights into how you should implement retention marketing for your customers, which customer segments to focus on, and which marketing campaigns are working best. By using NestAds, you get the most comprehensive and actionable view for optimizing your strategies for better results.
Use cases for cohort analysis
- E-commerce: Identify which customer acquisition channels lead to the highest repeat purchases.
- SaaS: Track user retention and engagement to optimize subscription models.
- Mobile apps: Analyze app usage patterns to improve features and reduce churn.
