SmartHelping / Historical Cohort Analysis / Excel
Cohort Modeling
Turn customer transactions into a clear view of retention, churn and spending over time. Analyze up to five years of historical data with cohort visualizations, a dashboard and customer lifetime value metrics.
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See the template in action
Follow the transaction data through the cohort analysis.
Watch the original walkthrough to review the data layout, retention analysis and layer-cake spending chart. Open the screenshots below for a closer look at the workbook.
Dashboard and metrics update
See the added dashboard and customer metrics.
This update adds a dashboard, customer lifetime value, and additional churn and spending visualizations to the template.
What the template includes
See how customer groups perform over time.
Use historical transaction data to review customer retention and spending by monthly cohort.
Up to 60 months of historical data
Analyze as much as five years of customer transaction history using a simple input structure built around customer IDs, transaction dates and purchase amounts.
Average monthly retention curve
Review average customer retention over time, with a best-fit curve to help estimate retention rates based on the historical pattern.
Layer-cake spending visualization
See monthly customer spending by cohort in a stacked area chart. Each layer represents a cohort so you can compare its contribution with the rest of the customer base.
Monthly churn in counts and percentages
Review average monthly churn as both a customer count and a percentage, supported by the template’s churn visualizations.
Retention by monthly cohort
Compare the average retention of each monthly cohort to see which customer groups retain more strongly over time.
Dashboard and customer lifetime value
Use the added dashboard, customer lifetime value metric and spending visuals to bring the cohort analysis into a broader view of customer performance.
Three inputs, one calculated cohort column
Start with a simple transaction table.
Enter your historical records in the three input columns. The fourth column uses a formula to identify the cohort month for each customer.
CustomerID
Enter the customer identifier for each transaction so the workbook can group purchases belonging to the same customer.
Purchase / Transaction Date
Enter the date associated with each purchase or transaction for the monthly cohort analysis.
Purchase Amount
Enter the amount of each purchase to support the cohort spending summaries and visualizations.
Calculated cohort month — column D
The fourth column uses MINIFS to determine the cohort month from each customer’s earliest transaction date in the data. Preserve this formula column when entering data or adding extra fields.
Retention, spending and customer behavior
Use historical patterns to inform the next decision.
Cohort analysis shows how different groups of customers behave over time. It gives recurring-revenue businesses a way to investigate retention changes, compare spending patterns and revisit forecasting assumptions.
Investigate churn
Look for when retention weakens and which monthly cohorts underperform. Use those patterns to guide further investigation into the product, service or customer experience.
Review customer spending
Compare the revenue contribution of newer and older cohorts. Historical spending patterns can help inform assumptions about repeat purchases, upgrades and future customer value.
Track changes over time
Use repeated cohort reviews as benchmarks when assessing new features, marketing efforts or retention initiatives. Compare the observed results with your operating and financial assumptions.
How to use the template
Move from transaction records to a cohort review.
Prepare the transaction history
Organize up to 60 months of records into customer ID, transaction date and purchase amount columns.
Keep the cohort formula intact
Retain the formula in column D so each customer’s cohort month continues to calculate from the transaction history.
Review the cohort outputs
Compare retention, monthly churn, layer-cake spending and customer lifetime value using the dashboard and visualizations.
Use the findings in your planning
Investigate differences between cohorts and use the historical patterns to refine customer-retention initiatives and revenue-forecast assumptions.
Extend the analysis
Compare a customer segment with the full customer base.
For a more detailed analysis, adapt the workbook to compare product categories, campaign groups or other customer segments.
Add product or campaign fields
Add extra metadata columns for product categories, marketing campaigns or other customer attributes while preserving column D and its cohort formula.
Adapt the summary formulas
Duplicate the cohort summary tabs and adjust their formulas to include only records that meet the category or metadata criteria you want to analyze. This requires workbook customization.
Need help adapting the analysis? Contact Jason for custom financial modeling work.
Who this template is for
For teams with customer transaction history to analyze.
SaaS and recurring-revenue operators
Review how long customer groups remain active, how their spending develops and whether newer cohorts are performing differently.
Finance, product and marketing teams
Use the historical analysis to inform forecasting assumptions, identify groups for further investigation and benchmark changes in customer performance.
Also available in these bundles
Need more recurring-revenue modeling tools?
This template is included in the SaaS / Recurring Revenue bundle and the Super Smart Bundle.
SaaS / Recurring Revenue Models
Explore financial models and analysis tools for SaaS, subscriptions and recurring-revenue businesses.
View the SaaS bundleSuper Smart Bundle
Access the complete public SmartHelping template collection across industries and financial-analysis needs.
View the Super Smart BundleQuestions before you buy
A few useful details.
How much historical data can I analyze?
The template supports up to 60 months, or five years, of historical customer transaction data.
Which fields do I need to enter?
The three inputs are CustomerID, Purchase / Transaction Date and Purchase Amount. A fourth column calculates the cohort month using a MINIFS-based formula.
What does the layer-cake chart show?
It displays monthly customer spending in a stacked area chart, with one layer for each cohort. This shows how each cohort contributes to spending over time.
Does the template include the dashboard update?
Yes. The added dashboard, customer lifetime value metric, and churn and spending visualizations are included in the template. The update video above walks through those additions.
Can I analyze a specific product category or campaign?
Yes, with customization. Add the relevant metadata without overwriting column D, duplicate the cohort summary tabs and adjust the formulas to filter for the category or campaign you want to review.
Make customer history easier to interpret
See retention and spending by cohort.
Get the Cohort Modeling Template for $75 and analyze historical customer performance with retention curves, spending charts and a dashboard.
