Drew AI can analyze customer lifetime value (LTV) and cohort behavior, helping you understand how much customers are worth over time and how different acquisition cohorts perform.
What is cohort analysis?
Cohort analysis groups customers by when they made their first purchase (their acquisition month) and then tracks their behavior over time. This reveals patterns like:
How much revenue each cohort generates at 30, 60, 90 days and beyond
Whether newer cohorts are more or less valuable than older ones
How long it takes for customers to make a repeat purchase
Which acquisition channels bring the highest-value customers
LTV metrics Drew AI can calculate
Drew AI accesses your full order history to calculate LTV at multiple time windows:
30-day LTV: Revenue per customer within their first 30 days
60-day LTV: Revenue per customer within their first 60 days
90-day LTV: Revenue per customer within their first 90 days
6-month LTV: Revenue per customer within their first 180 days
1-year, 2-year, 3-year LTV: Long-term customer value
These metrics are calculated from actual Shopify order data, not projections.
Example questions to ask
"Show me LTV by acquisition cohort."
"What is our average customer LTV at 90 days?"
"Compare the LTV of customers acquired in Q4 vs. Q1."
"Which monthly cohort has the highest repeat purchase rate?"
"What is our customer retention rate month over month?"
Types of cohort analysis
Drew AI supports several ways to cohort your customers:
LTV Cohorts: Group customers by acquisition month. The most common analysis type.
Product Cohorts: Group by the first product a customer purchased. Useful for understanding which entry-point products lead to the highest LTV.
Location Cohorts: Group by shipping location. Helpful for geographic expansion decisions.
Custom Cohorts: Group by order tags or customer tags. Useful for analyzing specific campaigns or customer attributes.
Retention analysis
Beyond LTV, Drew AI can analyze customer retention — how many customers come back to make a second, third, or fourth purchase, and how long it takes. This is essential for understanding your repeat purchase rate and optimizing retention marketing.
Example questions:
"What is our customer retention rate?"
"How long does it take the average customer to make a second purchase?"
"What percentage of customers make a repeat purchase within 90 days?"
Visualizations
Drew AI often presents cohort data as heatmaps showing LTV growth over time, making it easy to spot trends at a glance. It can also generate line charts showing retention curves or LTV growth by cohort.
Need help? Reach out to support@datadrew.io or use the in-app chat.
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