How much revenue does each acquisition cohort generate over time?

MetricCumulative revenue per acquisition cohort, indexed to that cohort's first-order revenue

Unitx of cohort month-0 revenue, cumulative

Triangular grid showing cumulative revenue per customer from each acquisition cohort. Newer cohorts have shorter rows. Read column-by-column to see how much each cohort contributes over time. Build by summing per-customer revenue per month, grouped by signup month. Example: Jan 25 cohort cumulative $42/customer at M5; Mar 26 cohort $18 at M2.

Non-subscription DTC and online retail, blended verticals, 12-month cohort window, 2023 to 2026 data. Indexed so month 0 equals 1.0x, meaning a 1.4x cohort earned 40 cents of incremental revenue per dollar of first-order revenue across the following 12 months. · No Tier 1 publisher reports cohort revenue stacking as a published quantile distribution, so these bands are derived, not lifted. Derivation: 12-month repeat purchase rate (Metrilo 28.2%, Rivo 28.2%, Bluecore 16.5%, BS and Co 18.8%) multiplied by observed orders-per-repeater and the repeat-order AOV premium (Bluecore reports active buyers place 57.6% more orders and spend 69.2% more than new buyers). The four repeat-rate sources disagree by a factor of 1.7 because Bluecore uses a narrower window and a retailer-weighted sample while Metrilo uses a self-selected DTC panel of 65 brands, so the median band is wide on purpose. Treat the shape as the signal and the level as indicative. Bottom-30 cohorts are effectively single-purchase cohorts where stacking is a rounding error.

Category split omitted: No two independent Tier 1 or Tier 2 sources publish cumulative cohort revenue multiples split by vertical, so any category table would be a repeat-rate table wearing a different label.

Every cohort band is roughly the same thickness at month 0 and adds almost no height afterwards, so the stack grows only because new cohorts are bolted on the bottom rather than because old cohorts thicken.

Jan cohort contributes $180k in month 0 then $14k, $9k, $7k in the following three months, reaching 1.09x by month 12. Total revenue is up 30% year on year but the month-12 multiple has been flat at 1.1x for six consecutive cohorts, which means growth stops the moment spend stops.

• Time the second-order push to the actual repeat window rather than the dashboard average. Median time to second purchase is 15 to 35 days across DTC, while the mean reads 50 to 100+ days because a long tail of late returners drags it (Eightx, 2026). A flow built on the mean fires after the decision window has closed.
• Run a post-purchase sequence of 3 to 4 emails instead of an order confirmation alone. Practitioner data puts the lift at 8 to 15 percentage points of repeat purchase rate, which on a 1.15x cohort is worth roughly 0.2x to 0.3x of additional month-12 multiple at typical repeat AOV.
• Separate the stack by acquisition channel before spending against it. Coupon and deal-site acquired customers run 40% to 60% below average LTV while organic search runs 20% to 40% above (Kissmetrics synthesis), so a flat blended stack hides two cohorts with opposite economics.
• Move the highest-frequency SKU into a replenishment or subscription offer. Subscription conversion is the only lever that reliably moves DTC cohorts into the 2x+ band, with subscription and replenishment models reported at 40% to 60% retention against 25% to 30% for standard repeat buyers.

1. MetriloReport: Customer retention and DTC brands · 2022 · n=65 DTC brands, self-selected panel of Metrilo customers Average repeat purchase rate 28.2%, and close to 60% of revenue comes from existing rather than first-time customers metrilo.com ↗
2. Bluecore2024 Customer Growth Benchmarks Report · 2024 · n=100+ omnichannel retailers and DTC brands, full 2023 calendar year 74% of customers buy once and never return; average repeat purchase rate 16.5% bluecore.com ↗
3. Bluecore (via GlobeNewswire release)Retailers With the Highest Identification Rates See 53% Higher Repeat Purchase Rates · 2024 · n=100+ retailers across apparel, sporting goods, health and beauty, toys, footwear, home, jewelry Active buyers placed 57.6% more orders and spent 69.2% more than new buyers, which is the mechanical driver of cohort stacking after month 0 globenewswire.com ↗
4. BS and CoRepeat Purchase Rate Benchmarks · 2026 · n=156,110+ customers across 10+ verticals, 365-day lookback, agency-managed DTC brands Repeat buyers are 18.8% of customers and 19.6% of revenue at aggregate level, roughly 1:1, which caps stacking for the median brand bsandco.us ↗
5. EightxNew vs Returning Customer Revenue Split Benchmarks · 2026 · Shopify merchant population aggregates plus Eightx client cohorts Shopify-wide, repeat buyers are about 21% of customers and about 44% of revenue; established DTC brands with a working retention stack sit closer to 60% returning revenue eightx.co ↗
6. DigitalAppliedCustomer Lifetime Value Benchmarks 2026 · 2026 · Aggregated 2025 and early 2026 published datasets, cross-industry Ecommerce cohort repeat-purchase decays to 52% by month 3 and 28% by month 12, unlike contractual SaaS curves which flatten digitalapplied.com ↗
7. Lifetimely (AMP)Lifetimely benchmarks and LTV cohort reporting · 2026 · Predictive model trained across 45,000+ Shopify stores and $100B+ in GMV Cohort reporting is segmented by first-purchase date, first product, channel and geography, with cumulative revenue and repurchase rate tracked per cohort lifetimely.io ↗