Examples of Cohort Analysis
The dog box subscription example showcases a common marketing scenario. However, cohort analysis is a powerful tool applicable across various industries. Here are some additional examples:
E-commerce Platform
- Goal: Top up Customer Lifetime Value (CLTV).
- Cohorts: One can be cohorts set up based on a customer’s first purchase amount(elementary). g. Track purchase frequency (5-10 orders) and average order value (>$50) separately for each group of customers (<$25, $25-$50, $51-$100). Study how these metrics vary between the cohorts during the entire time period. In addition to this, creating of such insights shows which segments should be focused by promotion and loyalty programs in order to drive consumers who are repeat.
Saas Company
- Goal: Generate revenue from the free trial users. The former can be used for generating revenue and the latter can be used for expansion. The combining and segmentation will help in increasing customer lifetime value as well.
- Cohorts: Validate cohorts through membership in free trial and link those features to the same. g. , basic features vs. advanced features). Filtrate that aspects which are responsible for high conversion rates of free subscriptions to paid ones. This helps establish what a product should be and how the free trial experience should be designed, creating a perfect customer journey with no hiccups whatsoever.
Mobile Gaming App
- Goal: Improve user engagement.
- Cohorts: Construct cohort which is represented by the customers’ in-app purchase history (ie). g. , spending vs. non-spending users). Analyze how many times infrequency do these cohorts log in, do they complete their daily quests, and what social features do they use. This can give the merchants an insight into the segments with low engagement where they can develop appropriate measures to enhance customers’ in-app experience, thus, contributing to an increase in revenue.
Streaming Service
- Goal: Personalize content recommendations.
- Cohorts: Determine to what extent the audiences belong to explicit definitions (for example by using viewing habits). g. Markets now segment not only the audience itself but also the individual experience with specific movies that may have different genres (action movie viewers, comedy viewers). Analyze on which genres of movies are watched by the peoples of each group the most. This offers a means to deliver contents specific to users conditioning and therefore the likelihood of users being satisfied and adhering to the network is improved.
What is Cohort Analysis and How does It Works?
In Data analytics, extracting actionable insights is crucial for informed decision-making. Cohort Analysis stands as a powerful tool in this realm, providing a nuanced understanding of user behavior over time.
This article aims to demystify Cohort Analysis, elucidating its significance and demonstrating how it effectively groups data by specific characteristics.
Table of Content
- What is Cohort Analysis?
- Why use Cohort Analysis?
- When to Use Cohort Analysis
- Types of Cohort Analysis
- How does cohort analysis work?
- Importance of Cohort Analysis
- Steps to Conduct Cohort Analysis
- 1. Define Goals and Questions
- 2. Choose Cohort Definition
- 3. Identify Relevant Metrics
- 4. Gather Your Data
- 5. Analyze the Cohorts
- 6. Take Action
- Examples of Cohort Analysis
- Python Implementation – Cohort Analysis
- Benefits of Cohort Analysis
- Challenges in Cohort Analysis
- Cohort Analysis- FAQs