Rank Crowds by Cost or ROI? Same Cost, 4× Apart in ROI
TL;DR
July data from 18 audience packages in one store: two crowds with inquiry costs just 10% apart (¥38.9 vs ¥43.0) ran 4× apart in ROI (5.30 vs 1.25). Inquiry cost and ROI answer different questions — cost per inquiry says whether the traffic was bought expensively; ROI says whether the buyers were worth it — and either ruler alone, used in an environment month, will mislead you.
The situation: ranking by one metric produces fiction
The comfortable way to read a crowd report is to sort it: by inquiry cost, cut the priciest; by ROI, cut the worst. In July's real data, those two sorts disagree completely. This reconciliation came out of a crowd-report audit while building AI Operations.
The data: one ruler prices traffic, the other grades it
Across crowds (one month, 18 packages): inquiry costs spread ¥32–44, yet near-identical costs carried ROI from 1.25 to 5.30 — "store new-buyers" at ¥43.0 cost only 10% more than "cross-border buyers" at ¥38.9, and returned a quarter of the ROI. Inquiry cost measures what it takes to pull in one interested buyer; what those buyers then purchase, and at what value, is invisible to it.
Across months (the same store, seven months): January–June crowd inquiry costs held at ¥16–21 with ROI 8.4–18.5; in July, spend tripled (×3.1), cost doubled to ¥39, and ROI collapsed to 4.0. All 18 packages breached together — July was an environment month (platform competition, market-wide moves), not one crowd suddenly failing.
| View | Subject | Inquiry cost | ROI | Note |
|---|---|---|---|---|
| Across crowds (July) | Cross-border buyers | ¥38.9 | 5.30 | Highest ROI among the 18 packages |
| Across crowds (July) | Store new-buyers | ¥43.0 | 1.25 | 10% pricier, a quarter of the ROI |
| Across crowds (July) | All 18 packages | ¥32–44 | 1.25–5.30 | Costs bunch in a narrow band; ROI fans out 4× |
| Across months (Jan–Jun) | Store-wide crowds | ¥16–21 | 8.4–18.5 | The normal-environment watermark |
| Across months (July) | Store-wide crowds | ¥39 (about doubled) | 4.0 | Spend ×3.1; all packages breached together |
(Technical note: the report's ROI uses 15-day-attributed GMV — while measured attribution back-fill runs as late as day 29 after week end, see Is 16 Days Enough for Marketplace Ad Data?. That ROI only counts what landed inside 15 days: systematically low for long-cycle B2B buyers, and still drifting between months as the ledger finishes posting.)
What it's worth: the mis-pruning ledger
Repricing by a single ruler in an environment month is wrong in both directions: June's good environment (ROI 18.5) inflates every crowd and hides the ones that genuinely need fixing; July's bad environment (ROI 4.0) condemns them all — including crowds that were merely dragged down by the month. Separating "environment" from "crowd" is what makes pruning precise: what deserves cutting deserves it in good months too; nothing gets cut for the weather.
Disciplines for operators
- Read both rulers together: inquiry cost prices the traffic; ROI grades it. Similar costs with multiples-apart ROI is an audience-selection problem — repricing cannot fix it.
- No rankings in environment months: when store-wide crowd spend and costs move together (as in July), cross-audience comparisons are void that month.
- Discount the ROI: 15-day-attributed ROI runs systematically low for B2B and drifts until settlement closes (when the platform locks the period's numbers and stops back-filling) — it has not earned the "sole benchmark" chair.
- Reprice on consecutive trends: single months are noise; three months in one direction with real magnitude is a trend. The full monthly procedure lives in The 1688 Crowd Premium Monthly Method.
The judgment order for developers
The discipline above ships as an automated pipeline in the crowd report. A comparable month = a finalized month (16 days after month-end, the attribution cutoff) with spend in that month; for cost-trend math, months with zero inquiries are filtered out as well. Checks run in dependency order, later checks overriding earlier conclusions:
| Order | Check | Trigger | Outcome | Override relation |
|---|---|---|---|---|
| 1 | Finalized-month filter | Only finalized months are judged (16 days after month-end) | Months still in progress are excluded whole | Runs before everything |
| 2 | Whitelist split | Crowd not on the operable whitelist (crowds that can actually be repriced) | No data, no judgment | Domain gate |
| 3 | Low-spend grouping | Finalized final-month spend below 0.10 × the median spend of operable crowds | Grouped separately, no advice | Before trend; untouched by freeze |
| 4 | Trend check | Two consecutive comparable months with spend but zero inquiries → cut candidate; the 2 moves across the latest 3 cost-comparable months point the same way with cumulative change ≥ 0.20 → raise/cut; fewer than 3 months → insufficient | Three-way directional call | Zero-inquiry outranks magnitude |
| 5 | Market-freeze overlay | Store-wide inquiry cost moves more than 0.40 month-over-month | Every directional call above flips to frozen | Overrides all directional calls, zero-inquiry cuts included |
| 6 | Execution-state filter | Marked stopped → stopped; premium already 0 → no cut advice | Re-judged by execution facts | Runs last, overrides directional calls |
(Technical note: the environment check sits after the trend check, not before — each crowd gets its own direction first, then the store-wide overlay flips directional calls to frozen; an environment month freezes the advice without swallowing state groups like low-spend or insufficient data. The freeze trigger is the inquiry-cost ratio, not spend: if spend doubles and inquiries double with it, cost hasn't moved and month-over-month self-comparison still works — freezing only when the efficiency baseline itself shifts. The 0.40 threshold comes from the measured split — normal months move 0.5%–27.6%, structure months 98%–116% — and 0.40 sits mid-band. And the 15-day ROI is display-only in this pipeline; it never enters the judgment.)
One line to remember
Inquiry cost prices the traffic; ROI grades it. No rankings in environment months; reprice on consecutive trends.
FAQ
Should audience performance be judged on ROI or inquiry cost?
Both, always: inquiry cost is the price of the traffic, ROI is its quality. Either one alone gets bent out of shape by environment months or single big orders.
Why can similar-cost audiences differ 4× in ROI?
Inquiry cost only says whether the traffic was expensive, not whether the buyers convert. Audiences with different order sizes and paths turn the same inquiry price into very different GMV.
What to do in a month when all crowd costs jumped together?
Call it an environment month — when store-wide crowd spend and costs double together, no cross-audience repricing; return to each crowd's own trend after the environment recovers.
That "two rulers + environment detection" method for crowd reports is built into AI Operations — LLM-powered analysis that automatically surfaces market trends, user behavior, and sales data to drive strategy. A crowd report deserves more than one sort button.
CCLEE
Independent developer, 24 years in e-commerce, focused on grounding AI in real business scenarios.
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