What is Cohort Analysis?

Cohort analysis is an analytical technique that groups customers (or orders, or products) that share a common characteristic and tracks their behavior over time. The most common cohort dimension is acquisition date: grouping all customers acquired in January together and tracking their purchasing patterns over subsequent months. This reveals trends that aggregate metrics hide, such as whether newer customers are more or less valuable than older ones.

Why It Matters

Aggregate metrics like “average order value” or “repeat purchase rate” blend all customers together, masking important trends. Cohort analysis separates the data to reveal whether your business is improving or deteriorating over time. If January’s cohort has a 40% repeat purchase rate at 6 months but June’s cohort is at 25%, something changed—and you need to investigate what.

How It Works

• Define Cohorts: Group customers by a shared attribute: first purchase date, acquisition channel, first product purchased, or geographic region.
• Track Over Time: For each cohort, track metrics like repeat purchase rate, average order value, total lifetime spend, and churn rate at regular intervals (monthly, quarterly).
• Compare Cohorts: Plot cohorts against each other on the same timeline. Newer cohorts should ideally perform as well as or better than older ones.
• Identify Drivers: When cohort performance varies, investigate the cause. Did marketing change? Did product quality shift? Did a new competitor enter the market?

How Nventory Helps

Nventory’s order data enables cohort analysis by tracking customer purchase history across all channels. The system provides the foundation data needed to build cohort models that reveal how customer behavior evolves over time and how operational changes impact repeat purchasing patterns.