Introduction
Cohort analysis has become an important analytical tool as companies search for more detailed insights into their consumer base. It offers useful information on client behaviour over time, especially when done in Microsoft Excel. We will show you how to perform a cohort analysis in Excel in this post, giving you a useful tool for making data-driven decisions.
Cohort analysis: What is it?
A subset of behavioural analytics called cohort analysis divides up a given data set into groups of related individuals for examination. Within a predetermined timeframe, these groupings, or “cohorts,” frequently have similar qualities in common. Cohort analysis is a useful tool for organizations to understand their audience and modify strategy because it can help with trends and patterns.
Why Use Cohort Analysis in Excel?
Excel continues to be a preferred option for many firms despite the development of more complex data analysis tools. It is available, comparatively simple to use, and incredibly adaptable. Excel is a notable option for cohort analysis because of its data segmentation and pivot table features.
Step-by-step Excel Cohort Analysis
· Gather Your Data in Step 1
Collecting your data is the first stage in an Excel cohort analysis. The user’s acquisition date and past behaviour, such as their transaction history or website visits, should be included in this data.
· Define Your Cohorts in Step 2
Define your cohorts next. Cohorts are typically collections of users who have something in common, usually the date of acquisition.
· Create a pivot table in Step 3
You may now make a pivot table once you have gathered your data and determined your cohorts. Choose your data, then select “PivotTable” on the “Insert” tab in Excel.
· Organize Your Data in Step 4
Create your pivot table with the cohort as the row labels (for example, the acquisition date) and the period (for example, the month of purchase) as the column labels. The behaviour you are tracking should be represented in the value field.
· Analyse your data in Step 5
You can examine your data after setting up your pivot table. Keep an eye out for recurring patterns or trends.
Example of How to Use Cohort Analysis in Excel?
Let’s take a look at a situation where a business wishes to keep tabs on the spending habits of customers it recruited in a certain month. Assume you have data on a user that contains their acquisition month (the month they made their first purchase), purchase month, and total monthly spending.
· Gather Your Data in Step 1
Let us say we have a spreadsheet with the information below:
· Define Your Cohorts in Step 2
In this instance, the cohorts will be the users organized by the month of acquisition. For instance, a cohort would consist of all consumers who made their first purchase in January 2023.
· Create a pivot table in Step 3
• Select the header row as well as the complete dataset.
• Select “PivotTable” from the “Insert” menu by selecting the “Insert” tab.
• Make that the appropriate data range is chosen in the ‘Create PivotTable’ dialog box. Click “OK” after deciding whether to add the pivot table to a new or existing worksheet.
· Organize Your Data in Step 4
• Move the ‘Rows’ box’s ‘Acquisition Month’ field there.
• Move the ‘Columns’ box’s ‘Purchase Month’ field there.
• Move the ‘Amount Spent’ field from the ‘Fields’ box to the ‘Values’ box. Make sure the setting is “Sum of Amount Spent” to obtain the monthly average spend for each cohort.
The total amount spent for each cohort in each purchase month should now be visible in your pivot table (grouped by acquisition month).
· Analyse your data in Step 5
You can now begin examining your data.
• You can observe that clients recruited in a particular month tend to spend more money over their initial few months.
• One prevalent pattern in many firms is a tendency where expenditure decreases with time for each cohort.
Conclusion
Excel cohort analyses are a potent tool for gaining an understanding of your consumers’ behaviour. You may comprehend how many elements affect customers’ interactions with your company over time by segmenting them into relevant groups. Cohort analysis may appear difficult at first, but if you master it, it will be a vital tool in your toolbox for data analysis.
Keep in mind that this is only a simple example. You might have more information to consider and more intricate cohort definitions in a real-world situation. Additionally, you might wish to compute data for your cohorts like retention rate, average spend per user, etc. using sophisticated Excel tools.
