Cohort Analysis is a technique used to analyze characteristics of a cohort (a group of customers distinguished on a common characteristic) over time. It is actually another type of customer segmentation which extends the analysis over a defined period.
One of the frequently applied use case in sales function is to segment customer base based on some set of characteristics. The criteria could be to categorize them into groups who are likely to continue buying, who are likely to defect or who have already defected (went inactive).
Once these groups are formed, some of the common applications for analysis would be to:
- Study customer retention – use the results to learn about conversion rates of certain groups and accordingly focus marketing initiatives (may be try to focus on customers who could be retained)
- Forecast transactions for cohorts/individual customers and predict purchase volume
- Bring more business – Identify groups for upselling and cross-selling
- Estimate marketing costs by calculating lifetime value of a customer by cohort
- Improve customer experience based on individual customer needs across websites and stores
Using Running total for duplicate SUM(Sales)
We can see that Corporate is performing best
Looking at the year on year percent difference in Sales
Using bar charts to look at the quarterly performance. We can further drill down to more granular levels to check monthly and daily performances
Looking at every day sales with “Running Sum” and “Moving Average” of Sales
Editing calculations at the date level with “Previous value” as 30 – for the 30 day moving average
And using filters to see the data for particular years
At Tableau Public: