Cohort Analysis in ScaleXP

Cohort analysis helps you track customer behavior over time by grouping customers
based on when they started using your product or service. You can analyze retention,
revenue growth, and customer value trends with just a few clicks.

How to add a new Cohort Analysis

• Navigate to Dashboards
• Click Add a Chart
• Select Cohort
• Use the left side panel to select the type of cohort analysis you want, and relevant date range

To change the name of the chart, use the toggle at the top for "Chart Name & Settings"..

Types of cohort analysis in ScaleXP

1. Customer or Logo Retention

The percentage of customers who remain active over time, starting from their first month with your company.
Use case: See how well your onboarding or product updates are helping retain
customers.
Calculation Methodology: Customers are grouped by the month they started
(Month 0). For each subsequent month, the chart shows the percentage of that
original cohort still active.
Example:
100 customers joined in January (Month 0).
80 are still active in February (Month 1).
60 in March (Month 2).
Cohort row:
Month 0: 100%
Month 1: 80%
Month 2: 60%

2. Lifetime Value (LTV)

The cumulative revenue generated per customer over time, starting from their sign-up
month.
Use case: Evaluate the ROI of marketing campaigns by measuring customer
value over time.

Calculation Methodology: Sum the total revenue from the cohort and divide it
by the number of customers in that cohort. This is done cumulatively across
months.
Example:
50 customers joined in February.
Revenue:
- Feb: £1,000
- Mar: £2,000
- Apr: £1,500
Total revenue = £4,500
LTV = £4,500 / 50 = £90 per customer by Month 2

3. Net Revenue Retention (NRR)

The percentage of recurring revenue retained from a cohort, including expansion,
contraction, and churn.
Use case: Understand whether existing customers are expanding their use of
your product.
Calculation Methodology: Start with the cohort's Month 0 revenue. Then
calculate revenue in each following month (including upsells and downsells).
Express each month's revenue as a percentage of Month 0.
Example:
March cohort: £10,000 in March (Month 0)
April: £11,000 → 110%
May: £9,000 → 90%
June: £10,500 → 105%
Cohort row:
Month 0: 100%
Month 1: 110%
Month 2: 90%
Month 3: 105%

4. Average Revenue per Customer (ARPC)

The average monthly revenue per customer in a cohort.
Use case: Spot declining revenue per customer, which may signal a need to
improve pricing or engagement.
Calculation Methodology: For each month, divide total revenue from the cohort
by the number of active customers in that month.

Example:
April cohort:
- April: £2,000 from 20 customers = £100
- May: £1,800 from 18 customers = £100
- June: £1,200 from 15 customers = £80
Cohort row:
Month 0: £100
Month 1: £100
Month 2: £80

Related articles

Intro to cohort analysis
New to cohort analysis? Start here to learn what it is, how it works, and why it's important.

Common issues in cohort analysis: How to correct & fix errors in cohort analysis 
Learn about common data issues that might affect your cohort results, like inconsistent
customer IDs or missing revenue.