Metric Definition
Retention over time
Track from
Customer cohort analysis
Customer cohort analysis groups customers by their acquisition period and tracks their purchasing behaviour over subsequent time intervals. It reveals how retention, order frequency, and revenue evolve for each cohort as they mature, exposing trends that aggregate metrics hide.
7 min read
What is customer cohort analysis?
Customer cohort analysis divides your customer base into groups based on when they were acquired and tracks how each group behaves over time. The January cohort includes everyone who made their first purchase in January. You then track what percentage of that cohort purchases again in month two, month three, and beyond.
This approach is essential because aggregate metrics can mask deteriorating customer quality. Your overall customer repeat rate might look stable at 30%, but cohort analysis could reveal that recent cohorts are repeating at only 20% while older cohorts with higher rates are propping up the average. Without cohort analysis, you would not detect the decline until it hit revenue.
Cohort analysis also enables causal investigation. If the March cohort retains significantly better than the February cohort, you can investigate what changed: a new acquisition campaign, a product launch, a seasonal effect, or an improved onboarding experience. This makes cohort analysis a diagnostic tool, not just a reporting view.
Segment cohorts by acquisition channel in addition to time. A cohort acquired via organic search may retain at twice the rate of one acquired via paid social, revealing that channel quality matters as much as timing.
Key cohort dimensions to track
| Dimension | What to track | Why it matters |
|---|---|---|
| Retention curve | Percentage purchasing in each subsequent period | Reveals how quickly customers lapse |
| Revenue per cohort | Cumulative revenue generated by each cohort | Shows long-term value by acquisition period |
| Order frequency | Average orders per customer within each cohort | Indicates purchasing cadence trends |
| AOV progression | How average order value changes over time | Reveals whether customers trade up or down |
| Cohort LTV | Projected lifetime value per cohort | Enables accurate acquisition budget setting |
How to improve cohort performance
- 1
Optimise the first 30 days aggressively
The first month after acquisition is when the highest proportion of customers lapse. Design a strong post-purchase sequence with delivery updates, product tips, and a compelling reason to return within 30 days.
- 2
Compare cohorts by acquisition source
Identify which channels produce cohorts with the best retention curves and shift acquisition budget accordingly. A channel that costs more per acquisition but produces longer-retaining customers is often more profitable.
- 3
Test retention interventions by cohort
Apply different retention strategies to different cohorts and compare outcomes. This controlled approach reveals which interventions actually improve retention versus those that merely correlate with it.
- 4
Detect declining cohorts early
Set alerts when a new cohort underperforms the previous cohort at the same maturity point by more than a defined threshold. Early detection gives you time to investigate and adjust before the revenue impact compounds.
- 5
Use cohort LTV to set acquisition budgets
Each cohort generates a predictable revenue curve. Use mature cohort data to project LTV for newer cohorts and set maximum acquisition cost targets that ensure profitability at the cohort level.
Related metrics
Customer Lifetime Value
CLV / LTV
SaaS Metrics
Metric Definition
CLV = Average Revenue Per User × Gross Margin × Average Customer Lifespan
Customer lifetime value (CLV) is the total revenue a business can expect from a single customer account over the entire duration of their relationship. It quantifies the long-term financial worth of acquiring and retaining a customer, making it one of the most important metrics for sustainable growth.
Customer Repeat Rate
Loyalty signal
Ecommerce & Marketplace MetricsMetric Definition
Customer Repeat Rate = (Customers with 2+ Orders / Total Unique Customers) x 100
Customer repeat rate measures the percentage of customers who return to make more than one purchase within a defined period. It is the simplest and most direct indicator of whether your product, pricing, and post-purchase experience are strong enough to earn a second transaction.
New vs Returning Customers
Customer composition
Ecommerce & Marketplace MetricsMetric Definition
New vs returning customers measures the proportion of orders and revenue coming from first-time buyers versus repeat purchasers. It reveals whether growth is driven by acquisition, loyalty, or a sustainable balance of both.
Order Frequency
Buying cadence
Ecommerce & Marketplace MetricsMetric Definition
Order Frequency = Total Orders / Total Unique Customers (in period)
Order frequency measures the average number of orders a customer places within a defined time period. It captures how deeply your store has been woven into a customer's purchasing habits and is one of the three core levers of customer lifetime value alongside average order value and customer lifespan.
See how your customer quality evolves over time
Build a metric tree that tracks cohort retention, spending, and LTV so your team can detect changes early and invest in the acquisition sources and retention strategies that produce lasting customers.
