The Retention Report shows whether repeat customers are profitable, not just active. It combines orders, costs, and acquisition spend so you can:
See customer lifetime value after product, shipping, and payment costs.
Find channels that bring customers who never return.
Time win-back flows based on real reorder behavior.
This guide explains every tab, metric, and calculation.
Before you start: period and refunds
Date range. The report defaults to the last 365 days. Lifetime value and repeat-purchase windows need a long period. A short range may end before customers have had time to order again. Change the range with the date picker in the top bar. It is shared with Cohort Analysis.
Refund attribution. The selector in the top right controls when refunds reduce revenue:
Refund Date (default): the refund reduces revenue on the day it was issued.
Order Date: the refund reduces revenue on the day the original order was placed.
Ignore Refunds: the report shows gross revenue without subtracting refunds.
Use Refund Date for a cash-flow view. Use Order Date when you want each cohort's true net revenue. Use Ignore Refunds only to compare gross numbers.
Demo mode: the date range and refund selector are locked to the sample data.
Overview tab
CLV:CAC trend
This chart compares customer lifetime value with the cost of acquiring a new customer over time.
Above 1.0 means a customer is worth more than they cost to acquire.
CAC includes paid acquisition only. Retention and email costs are excluded, so this measures paid-media efficiency rather than blended customer cost.
Headline KPIs
Metric | What it means |
Repeat purchasers | Share of customers who placed 2 or more orders. |
Avg orders per customer | Average number of orders per customer. A rising value means better retention. |
New-customer AOV | Average order value on a customer's first order. |
Returning-customer AOV | Average order value on repeat orders. Bundles and cross-sells can increase it. |
Products per order | Average number of products in each order. |
Profit KPIs
Venon uses your real costs to show profit, not just revenue:
CM2 (contribution profit) = net revenue − product costs − shipping costs − payment fees. This is profit before ad spend.
CM3 (net profit) = CM2 − ad spend. This is what remains after acquisition costs.
Metric | What it means |
Avg Contribution Profit (CM2) | CM2 per customer over their lifetime, before ad spend. |
Avg Net Profit (CM3) | CM3 per customer after ad spend. |
Contribution Margin (CM2) | CM2 as a share of net revenue. |
CM2 per Order | Average contribution profit per order. |
Cost accuracy: if product costs are missing, COGS uses a default estimate. Complete your cost settings for more accurate profit numbers.
Expected Next Order
This section estimates when the next order is due and when a customer moves from active to at risk to lost. Use it to time win-back flows.
Avg to 2nd order: the typical time between the first and second order.
Avg interval (repeat): the typical time between later repeat orders.
Start win-back: the median. 50% of repeat customers have reordered by this point.
At risk after: the 75th percentile.
Lost after: the 90th percentile. By this point, 9 in 10 repeat customers have already reordered.
AOV over time: new vs returning
This chart shows daily average order value for first orders and repeat orders separately. A rising returning-customer line means repeat customers are spending more per order over time.
Repurchase & LTV tab
First-to-second purchase curve
This curve shows the cumulative share of customers who placed a second order within each time window. When the curve flattens, most repeat buyers have already converted. That point is your practical win-back deadline.
Average days between orders
This shows the typical gap between each order and the next: first to second, second to third, and so on. Use these gaps to send reminders shortly before customers normally reorder.
Period LTV, revenue & profit
This section shows lifetime value per customer at each maturity window, cumulative revenue, and CM2 after product, shipping, and payment costs. Windows run from 30 days to 365 days.
Why can the 365-day total cover less revenue than a shorter window? Fewer customers are old enough to have a full 365-day history. The total therefore covers a smaller group even when lifetime value per customer keeps rising. This is data maturity, not a performance drop.
LTV by first purchase
This table groups customers by the product they bought first and ranks those products by 365-day net LTV (CM2), not revenue. A lower-revenue product with strong margins can be a better acquisition product than a higher-revenue product with high costs.
The table also shows 90-day, 180-day, and 365-day LTV, margin, and repeat rate for each first product.
Channels tab
Retention by channel
This table splits retention metrics by the channel that first brought in each customer. Use it to find channels that generate first orders but few repeat purchases.
Columns include customers, share of total, new-customer AOV, repeat rate, and average days to the second order.
Aliases for the same platform are merged. For example, google and google-ads roll up to Google, while facebook and meta-ads roll up to Meta. Combined metrics are weighted by customer count.
Where the numbers come from
Orders, revenue, AOV, and repeat behavior: Shopify order history, calculated per customer.
CM2: net order revenue minus product costs, shipping costs, and payment fees.
CM3: CM2 minus ad spend.
CAC and ad spend: connected platforms such as Google, Meta, and TikTok.
Channel attribution: first-touch. Each customer is credited to the channel that first brought them in.
Numbers are most accurate when cost settings are complete and ad platforms are connected.
Quick FAQ
Why do longer windows sometimes show fewer customers?
Only customers old enough to have reached that window are included. This keeps each maturity window comparable.
Is CAC blended or paid-only?
Paid-only. It measures acquisition efficiency and does not include retention or email costs.
Why is a channel missing or grouped?
Aliases for the same platform are merged, and unattributed traffic is grouped separately. First-touch attribution means each customer appears under only the channel that first acquired them.