The most common WhatsApp retention setup is a single reminder sent 30 days after every order: "Time to restock?" It's easy to build and it's wrong for almost every product in the catalog, because 30 days is a guess, not a signal. A single-person household finishing a 250g jar of ghee and a five-person household finishing the same jar are not on the same clock — sending both the identical message on day 30 means one gets it two weeks too late, after they've already rebought elsewhere, and the other gets it two weeks too early, while half the jar is still full.
Why fixed-interval reminders underperform
A flat interval treats every product and every customer as identical consumption rates. In practice, consumption rate is the single biggest variable in whether a reorder message lands at the right moment: a honey jar and a bag of loose-leaf tea don't run out at the same pace, and a household that ordered two jars in one basket doesn't run out at the same pace as a household that ordered one. Send too early and the message reads as spam and trains customers to ignore future ones. Send too late and the customer has already reordered from a competitor, or just replaced the habit.
What consumption-based timing actually tracks
- Pack size vs. typical usage rate — a per-category estimate of how long a given pack size actually lasts, built from repeat-purchase intervals in your own order data, not a guess.
- Quantity ordered— two jars in one order roughly doubles the runway before a reminder makes sense; the flow should read basket quantity, not just "an order happened."
- Category-specific decay — a spice blend used a few times a week lasts differently than one used daily; each product category needs its own consumption curve, not one store-wide number.
What this looks like in practice
On a catalog of honey, ghee, and herbal tea, that means three different timers, not one: honey and ghee run on a longer curve and get a WhatsApp nudge closer to day 45–50, while a fast-moving tea blend gets one closer to day 20. Order quantity shifts each of those forward or back per customer. The message itself also gets sharper when it's timed correctly — "still have ghee left, or ready for the next jar?" lands very differently on the actual day someone's jar runs low than it does two weeks early or late.
The fix, in order
Start with repeat-purchase intervals already sitting in your order history — for customers who did reorder the same product, how many days actually passed. Use that to build a per-category (ideally per-SKU) consumption estimate instead of one flat number. Wire the WhatsApp flow to trigger off that estimate, adjusted by quantity ordered, and re-tune it every quarter as real reorder data accumulates — the estimate gets more accurate the more orders it's built from.
This is the exact process behind our Get Repeat pillar — read the full breakdown on the Get Repeat page.