Every customer, read by what they will do next.
Who buys once, who comes back, who pays full price and who waits for a discount, with the dollars each group holds.
Customers
61,480 customers, by what they do
| Pattern | Customers | Forward CLV | Each |
|---|---|---|---|
| One-Timers | 43,65071% | $1.18M | |
| Repeat Buyers | 17,83029% | $3.03M | |
| Brand Championsof Repeat | 4,1207% | $1.71M | |
| Promo Loyalistsof Repeat | 5,96010% | $640K |
Repeat buyers are 29% of the base and hold 72% of its Forward CLV. The two groups inside them are where the full-price and promo playbooks start.
Four patterns, not one average.
Shopify shows what sold. Tacet groups every customer by how they buy: once, again, at full price, or only on a discount. Each group is a playbook’s audience, or a reason to rest.
One-Timers
43,650
71% of customers · $1.18M of Forward CLV · $27 each
Bought once. Most will not buy again; the ones who might are the second-purchase playbook's audience.
Repeat Buyers
17,830
29% of customers · $3.03M of Forward CLV · $170 each
Bought at least twice. They hold 72% of Forward CLV.
Brand Champions
Inside Repeat Buyers
4,120
7% of customers · $1.71M of Forward CLV · $415 each
Repeat buyers at full price, among the top tenth by Forward CLV. Recognition, never a coupon.
Promo Loyalists
Inside Repeat Buyers
5,960
10% of customers · $640K of Forward CLV · $107 each
Repeat buyers who wait for a discount. The promo-weaning playbook reads whether they would pay full price.
Promo reliance. 16.4% of net revenue was sold on a discount. 5,960 of the customers behind it would likely have paid full price.
Subscription targets. 1,240 steady repeat buyers on a tight rhythm, worth a subscription offer.
Cohorts on true first-purchase dates.
In a 12-month export, 31% of September's “new” customers had bought before. These rows start every customer at their true first order.
Customers · Cohorts
| First order | New | M0 | M1 | M2 | M3 | M4 | M5 | M6 | M7 | M8 | M9 | M10 | M11 | Paid back |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Oct 2025 | 1,612 | – | 10% | 16% | 19% | 22% | 24% | 26% | 27% | 28% | 29% | 29% | 30% | Month 5 |
| Nov 2025 | 2,240 | – | 10% | 15% | 18% | 20% | 22% | 24% | 25% | 26% | 26% | 27% | not yet | Month 6 |
| Dec 2025 | 2,905 | – | 9% | 13% | 16% | 18% | 20% | 21% | 22% | 23% | 24% | not yet | not yet | Month 7 |
| Jan 2026 | 1,380 | – | 10% | 15% | 19% | 22% | 24% | 25% | 26% | 27% | not yet | not yet | not yet | Month 5 |
| Feb 2026 | 1,295 | – | 10% | 16% | 20% | 22% | 25% | 26% | 27% | not yet | not yet | not yet | not yet | Month 5 |
| Mar 2026 | 1,540 | – | 11% | 17% | 21% | 23% | 26% | 27% | not yet | not yet | not yet | not yet | not yet | Month 4 |
| Apr 2026 | 1,466 | – | 10% | 16% | 19% | 22% | 24% | not yet | not yet | not yet | not yet | not yet | not yet | Month 5 |
| May 2026 | 1,510 | – | 10% | 15% | 18% | 21% | not yet | not yet | not yet | not yet | not yet | not yet | not yet | Month 6 |
| Jun 2026 | 1,602 | – | 10% | 16% | 19% | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | Month 5 |
| Jul 2026 | 1,488 | – | 10% | 15% | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | Not yet |
| Aug 2026 | 1,574 | – | 9% | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | Not yet |
| Sep 2026 | 1,724 | – | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | not yet | Not yet |
9 of the last 12 months of new customers have paid back their acquisition spend. March 2026 paid back in month 4.
Measured history, not a model. Nothing on this table forecasts. Each cell is the share of that month’s new customers who had placed a second order by then.
Why the date matters. Count a returning customer as new and every cohort looks younger and better than it is, and the forecast built on it runs high.
See your own customers by what they will do next, free, by tomorrow morning.
One customer: then, and next.
Every line on the statement traces to customers, and every customer has a page: what they have contributed, what they are expected to, when they are due, and what they are likely to buy next.
Then is measured, next is expected. Contribution to date comes from orders and refunds. Forward CLV is a 12-month expectation, after product cost and expected returns, never a promise.
The reorder clock is the customer's own. Every 74 days for this one, read from their own gaps, not a store average. Due now means due now for them.
The same figures sit on the Klaviyo profile. So a segment, a flow or a campaign can use them, and your team never leaves Klaviyo to act.
Customer 20417
Then
- $412.60
- Contribution to date
- 1 of 11
- Units returned
Next
- $188.40
- Forward CLV, 12 months
- 81%
- Chance still active
- 4%
- Return propensity
Reorders Every 74 days Due now since 25 Oct
Most likely next Field Coat Wax
| 12 Aug 2026 | Waxed Field Coat | $168.00 |
| 3 Jun 2026 | Field Coat Wax × 2 | $32.00 |
| 20 Feb 2026 | Merino Base Layer × 21 returned | $74.00 |
| 9 Nov 2025 | Trail Boot | $142.00 |
On the Klaviyo profile
- tacet_forward_clv = 188.40
- tacet_reorder_stage = Due now
- tacet_return_band = light
- tacet_pattern = Brand Champion
Forward CLV is what this customer is expected to contribute over the next 12 months. The reorder stage and the return band beside it are the same values a Klaviyo segment reads.
Due, past due, well past due.
Every repeat buyer has a reorder point of their own, worked out from their rhythm. Tacet sorts the ones who are past it into three bands, and each band is a playbook stage.
Due now
1,742
customers, holding $298,100
At their own reorder point this week.
Past due
1,366
customers, holding $241,900
Past it, and still likely to buy.
Well past due
1,943
customers, holding $272,400
Fading. The win-back playbook's audience.
5,051 customers, $812,400 of Forward CLV, past their own reorder point and in no flow. The reminder brings forward an order they were going to place.
See the reorder playbookRead-only on your store.
Tacet reads Shopify and never writes to it. Customer data is limited to name and email, plus orders and refunds.
Nothing sends without your GO.
Your admin switches every playbook on. It sends from your own Klaviyo, under your sender.
Every result measured against customers who didn't get it.
A group is held back from every playbook. Results are read in profit, after product cost, discounts and refunds.
See your customers by what they will do next.
Your customer P&L, free, the morning after you connect Shopify.