Contents
What is cohort analysis
Cohort analysis is a powerful tool for studying consumer behavior that allows marketers to delve into the dynamics of groups of users who performed a specific action within a given time frame. This research focuses on narrow groups of people, called cohorts, which helps to uncover patterns that remain unnoticed when analyzing general data. For example, users who signed up for a newsletter between May 1 and May 30 can be grouped into one cohort, allowing for a more detailed analysis of their behavior.
Goals of cohort analysis
Cohort analysis plays an important role in evaluating the effectiveness of marketing campaigns and helps to create a complete picture of business promotion results. It can be used to:
- Identify patterns that contribute to improving customer experience;
- Determine which traffic sources provide the highest number of conversions;
- Adjust promotion strategies based on the data obtained.
Additionally, cohort analysis allows for a more accurate identification of weaknesses and shortcomings in marketing efforts, as well as understanding how different user groups respond to company initiatives.
Differences between cohort analysis and segmentation
Despite their similarities, cohort analysis and segmentation have fundamental differences. Audience segmentation divides users into groups based on common characteristics, such as age, gender, or interests, and analyzes their behavior over time. In contrast, cohort analysis focuses on studying the behavior of users with the same experience who performed the same action during the same period. For example, if an online store operates in several CIS countries, segmentation may show that Russians make more purchases, but to understand the reasons for this, cohort analysis is necessary, which will reveal how different traffic sources influence customer behavior.
Steps of cohort analysis
Cohort analysis includes several key steps:
- Defining the metric: it is important to establish key performance indicators, such as conversions, number of purchases, or average check.
- Forming cohorts: users are grouped based on a common characteristic, such as registration time or purchase made.
- Comparing cohorts and analyzing metrics: after forming cohorts, their behavior should be analyzed to identify differences.
It is important to consider that metrics can be actionable, reflecting real results, or vanity metrics that do not affect business financial performance. Cohort analysis helps to identify which metrics matter for business growth and how they can be used to improve results.
Examples of using cohort analysis
Cohort analysis finds applications in various areas of business. For example, it can be used for:
- Evaluating the effectiveness of advertising campaigns;
- Tracking repeat visits;
- Conducting A/B testing;
- Identifying loyal customers;
- Analyzing the effectiveness of different versions of mobile applications.
Each of these cases demonstrates how cohort analysis can help identify problems and determine successful strategies. For instance, during A/B testing, users can be divided into groups and their behavior on different versions of a web page can be observed. This will help to understand which version attracts more customers and increases conversion rates.