ROI Cohort Analysis: How to Measure and Use it in App Media Campaigns

In the realm of data analysis, it is of paramount importance to examine data within the appropriate context to drive both user engagement and app-generated revenue. Thus, cohort analysis becomes crucial in identifying the optimal path to optimize your campaigns. 

So, what is cohort analysis, and why is it important? 

 When we talk about cohort analysis, we are referring to a segmented analysis of user groups with common goals or characteristics. These characteristics can include a region or language, items most purchased within a specific time frame, acquisition date, and more. 

 In the context of apps, cohort analysis is an extremely effective tool for gaining more detailed insights into how specific user groups engage and behave within your app over time. It even helps refine Key Performance Indicators (KPIs) for performance measurement. 

 One significant advantage of cohort analysis is that it allows you to compare similar data to identify trends. Thus, this type of analysis enables you to answer crucial questions such as: 

• Who is engaging with your app? 
• When do users tend to drop off from using your app, and why? 
• How much of your revenue comes from new users versus older ones? 
• What is the best time to re-engage your users? 
• Which media channels bring in more users with a positive ROI? 

 Therefore, this type of analysis is essential for optimizing user acquisition (UA) campaigns, improving retention, and estimating Lifetime Value (LTV) more efficiently. 

Some uses of cohort analysis in app advertising campaigns 

 By identifying trends, cohort analysis provides the necessary insights for optimizing active app advertising campaigns and making real-time changes with agility, making your actions more efficient. This is a proven method to increase engagement and revenue, helping you identify the right path to expand your app's UA KPIs and retention. 

 Still have doubts about how cohort analysis can improve your revenue campaign results? Here are some practical examples: 

• Cohort analysis allows you to discover which channels, campaigns, and ad sets within a campaign capture the most qualified users. By providing insights into all revenue streams, cohort analyses can answer questions like "which media channel drove more in-app purchases?" or "which campaign generated the highest revenue per user in region X?" and so on. 

• You can use this analysis to identify relevant patterns for scheduling a remarketing campaign. For the e-commerce sector, remarketing campaigns often include KPIs such as the number of users making in-app purchases, revenue from purchases, or the percentage of re-engaged users. However, to get a complete view of user behavior, KPIs, and success metrics - cohort reports can be used to offer a multidimensional analysis. 

• Cohort analyses are used to discover friction points in onboarding, initial steps, paywalls, or challenging levels. They do this by examining data from these churn-prone areas in your app and comparing it with monthly user retention. Identifying and eliminating these friction points found through things like in-app events, is essential to increasing retention.  

• Figuring out how to fix a problem or improve a feature can be as challenging as diagnosing it. So, instead of rushing to make significant changes to your product, perform A/B tests of these modifications within your cohorts to understand what works and what doesn't. With this data, you can introduce changes to your product with more confidence. 

What are the next steps for efficient and successful campaigns? 

All the analysis and performance tracking of KPIs require a strong collaboration between brands and their partners. To do this, it is essential to establish criteria, best practices, and a framework for choosing and testing these partners. We suggest you: 

•  Define clear objectives: Before initiating a partnership, it is essential to define the objectives you want to achieve, whether it is increasing revenue, acquiring more users, or improving engagement. 
•  Monitor and analyze performance: Closely monitor the data and metrics provided to assess the performance of advertisements. This will allow for adjustments and optimizations as necessary. 
•  Ensure a positive user experience: Verify that ads do not compromise the user experience. Avoid overly intrusive ads or those that negatively impact app performance. 

With all this being said, choose a partner that provides continuous ad performance monitoring and optimization consultation to identify opportunities. 

This approach enables advertisers to achieve more significant results and reach their goals more efficiently. 

ClearPier specializes in growth and performance for apps. They provide clients with comprehensive campaign management while also focusing on data-driven performance, safe traffic, and full transparency.