The False Comfort of Retention Metrics
š„¹What most brands miss about true repeat-purchase behavior, and more!

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š„¹The False Comfort of Retention Metrics
Retention is one of the most dangerous metrics in DTC. Not because itās wrong, but because itās misunderstood. High retention in a low-purchase-velocity brand isnāt a success; itās a stall in motion, hiding in your cohorts.
Hereās the trap:
Your 60-day repurchase curve looks āhealthyā because most customers havenāt hit the window to buy again. If youāre selling wellness bundles, supplements, or even fashion pieces that naturally turn every 45ā75 days, your Month 1 āretentionā stat is just a function of time delay, not brand love.
And if you let that false confidence compound, itāll inflate your LTV model, throw off your ad budgets, and mislead product expansion planning.
Itās a fake positive, and it costs real money.
Step back and segment by velocity tier
Instead of treating retention as a uniform outcome, start dissecting it by SKU-classed reorder velocity.
- Which products turn in 15 days?
- Which needs 60+ days for depletion or desire?
- Which purchases are planned repeaters vs. impulse repeats?
This recalibration alone can kill your hero illusion. The supplement SKU that looks like a rockstar in your 90-day retention graph may actually just be⦠untouched inventory sitting in a customerās pantry.
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This one change fixes everything downstream
Once your retention model reflects reality:
- Winback campaigns stop targeting customers too early.
- Product teams stop interpreting demand as brand affinity.
- Finance stops forecasting LTV from delayed cycles.
You regain control of repurchase design instead of guessing behavior. You finally match retention actions to the customerās actual timeline, not the timeline your dashboard was built to support. Because retention isnāt about who comes back.
Itās about knowing when they could come back, and who truly chose to.
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