Cohort analysis can provide you with insights that are not possible with split tests. Split testing compares two samples of a population based on different data to obtain a specific result. Cohort analysis also uses location and time criteria.
For example, you believe that a red CTA button increases conversion compared to a blue one. To test the assumption, a split test is organized, during which some people see a block with a red button, while others go to a page with a blue one. This test showed that the page with the red button showed better conversion.
To verify the indicators, you move outlook email list on to cohort analysis. Now you divide all customers into segments depending on location and time of acquisition. As a result, it turns out that the red button was more often responded to by people who paid for the product in the summer, and they also lived by the sea. In all other groups, the reaction was not so obvious.
A further detailed study of the cohort – the one attracted by the red button – reveals the reason for this reaction. Interestingly, customers living on the coast are so accustomed to blue shades (they are constantly surrounded by them) that the presence of red influenced their choice.
For other categories of buyers, the presence of one or another color did not play a special role. Therefore, without a cohort study, the conclusions could be incorrect.
It should be said that such analysis is used not only to refine split testing, it is also suitable for a more in-depth study of user behavior and actions and allows for a more accurate assessment of the effectiveness of interaction with them.
But you shouldn't give up on split tests either, one method logically complements the other. Cohort analysis has many advantages, but in essence it is also a regular sequential study, when you spend some time observing how visitors react to replacing elements on a website page. And how the conversion changes.
Analyzing the effectiveness of two methods simultaneously will allow you to form a more realistic picture of your business project and you will understand where improvements need to be made.
Cohort Analysis to Improve Conversion
-
- Posts: 274
- Joined: Mon Dec 23, 2024 3:42 am