22 Feb Advanced Cohort Analysis In Google Analytics
With the Cohort Analysis report now available in Google Analytics, you can investigate how users acquired in a given time frame behave, convert, and spend on your site over time.
You can find the Cohort Analysis technique under Analysis in Google Analytics for app+web. It promises to offer better ways to explore user behavior trends. Since it has both app+web functionality, it can also show a deduplicated view of your customers across platforms, depending on your setup.
The Cohort technique goes beyond the limitations of the Cohort report for the web by introducing a few customizations that help base your cohorts on a broader set of data. When building the analysis, you should also keep in mind that app+web has a different base data model, so expect to notice a difference compared to your standard Analytics library tracking.
Exploring Cohort Analysis
You can customize Cohort Analysis by going beyond the acquisition date criteria for building cohorts. You will see the default view of the analysis when you open the report, but you manipulate the selectors to make the most of this powerful feature.
Benefits Of Cohort Analysis
Determine trends in user behavior and retention over time. It will allow you to see how likely users acquired on a specific date range are to keep visiting your site after a few weeks, compared to the users who purchased during special promotion periods.
– Identify how changes to your content increased engagement or decreased engagement over time. For example, you may notice that a group of visitors who first opened your site/app during a week where you made of navigation/layout improvements tend to return more than those who haven’t seen the new changes to your website or app.
– Further explore problems with the site/app or user experience looking at the retention rate, which may be a good indicator of whether users were satisfied with their experience on a day they first arrived.
– Track the effect of short-term marketing campaigns and promotions. Evaluate the performance of promotions since you can see when you were running the advertisements and derive insights based on results.
– Calculate the churn rate of your customers, and understand how it impacts overall KPIs. You can also minimize or even eliminate the impact on KPIs by re-engaging with existing customers or acquiring new ones.
– Determine the best moment to remarket to your visitors, since you’ll know when they’re likely to abandon.
Building Cohort Analysis: Step-By-Step
1. Select Technique.
To start building a cohort report, select the Cohort Analysis technique in the Analysis hub or select Cohort Analysis in the left-hand navigation page:
2. Select Inclusion Criteria
You can now specify what criteria are evaluated by including a user in a cohort- a key difference from the standard Cohort report in Analytics. In addition to the existing Acquisition Date, it can also be Session, Transaction (an eCommerce conversion), and Conversion (any).
Only the first occurrence of a session, transaction, or conversion gets counted for a user during the date range specified for the analysis. So, if a user made several transactions in the specified period, they will only be included in the first cohort they qualify for.
This updated customization allows you to look deeper into the behavior of users who interacted with the site/app within a given date range or converted or spent money, irrespective of their acquisition date. This is extremely useful since an acquisition date may impact user behavior and retention, and it can also change after a subsequent visit or a transaction.
3. Select Return Criteria
This defines which users are evaluated and included in the cohort outside of the initial time frame. It also has Session, Transaction, and Conversion values. So, if a cohort granularity is Weekly, the inclusion is a transaction, and the return criteria are Session, the cohort includes all the users who made a transaction on a specified week and who visited the site/app in any of subsequent weeks.
This setting also offers the opportunity to explore different criteria combinations. For example, you may want to explore:
– Users who have a repeated session (return criteria) depending on the time frame in which they first converted (inclusion criteria);
– Visitors who converted in a repeated session (return criteria) depending on the date range they first arrived (inclusion criteria);
– Customers who spent money with your business during a repeated visit (return criteria) depending on the time frame in which they first converted (inclusion criteria);
4. Select Cohort Granularity
Google Analytics for app+web now offers to build cohorts based on the date range you’ve specified for the analysis (in the Variables pane), and it breaks it down into Daily, Weekly, or Monthly cohorts. Just keep in mind that the date range follows calendar weeks (Sun-Sat) and months.
5. Select Breakdown dimension
You can add one of many Analytics web- or app-specific dimensions to see how cohorts perform across different dimension values. There is a limitation, though: you can only view up to 15 dimension values.
6. Select Value
This new technique allows you to define a metric that shows in the cohort table. This is an improvement compared to the existing Analytics report. You can measure your cohorts against different app- and web-specific metrics, including sessions, page/screen views, or number of events:
The new Cohort Analysis opens up a more extensive range of opportunities to explore your user base, behavior, conversion trends, and retention. As a result, you’ll get a better level of detail for analysis benefits of either app-specific or aggregated datasets from multiple platforms or data streams.
To learn more about how you can use Google Analytics to understand the behavior of users on your website and app, read our blog on Custom Attribution Modeling in Google Analytics.