78% of Keywords Never Produced an Inquiry: Your Cost per Inquiry Is Understated 28%
TL;DR
One store's keyword ledger: of 1,641 keyword-week records, 1,277 (78%) produced zero inquiries while consuming ¥8,962 — 27% of total spend. The average over "keywords that did produce" comes to ¥32; the blended cost that counts every yuan of spend is ¥41 — a 28% understatement. The only correct formula is total spend ÷ total inquiries: not one yuan of zero-inquiry spend may vanish from the denominator.
The situation: the cost you see is the survivors' cost
Keyword reports are organized per keyword, so your eyes land on keywords that produced inquiries — those have a cost to show. Zero-inquiry keywords display no cost, and so they quietly exit your field of view.
Their spend, however, left the account in full. This audit came out of a keyword-level check while building AI Operations.
The data: the missing 27%
| Metric | Value |
|---|---|
| Keyword-week records | 1,641 |
| …with zero inquiries | 1,277 (78%) |
| Spend on zero-inquiry records | ¥8,962 (27% of total) |
| Total spend / total inquiries | ¥33,417 / 824 |
| Naive average over inquiring keywords | ¥32 |
| Blended cost (total ÷ total) | ¥41 |
The naive average only bills the survivors — (technical note: this is textbook survivorship bias in ad data. Counting only producing samples donates the non-producing samples' spend for free; with 27% of the money missing from the denominator, the cost "improves" by two to three tenths.)
What it's worth: what 28% understatement does
The understatement is not cosmetic — it cascades:
- Acquisition budget: budget set at ¥32 while reality is ¥41 leaves a ¥9-per-inquiry hole — across 824 inquiries, about ¥7,400
- Product go/no-go: a product line judged against an understated keyword cost reads "still viable" while truly underwater
- Pricing and margin: acquisition cost is the hidden floor of B2B quotes; a floor 28% too low cannot carry real deal prices
Disciplines for operators
- One base formula: cost = total spend ÷ total inquiries. Any "average" that excludes zero-inquiry samples is void on sight.
- Keep a separate zero-inquiry watchlist, sorted by accumulated spend — this is the main battlefield of "check five: truly zero inquiries"; words that burn past a reasonable cost with nothing to show get stopped without ceremony.
- Quality weighting is layer two: once the base is right, weight purchase-ready inquiries (pricing asks, sample requests, volume) above casual ones. No universal weights exist — derive them from your own deal path and freeze them, so months stay comparable.
- The target line comes from your own history: normal months (holidays excluded) define the band — the method is in A Real Store-Wide Efficiency Alert, From a 40-Week Ledger.
One line to remember
Cost = total spend ÷ total inquiries. Zero-inquiry spend never disappears from the denominator; quality weighting is always layer two.
FAQ
What is the right way to calculate B2B ad inquiry cost?
Total spend ÷ total inquiries — no exceptions. Leave zero-inquiry spend out of the denominator and the cost reads two to three tenths too low.
Should zero-inquiry keywords be paused?
Check accumulated spend and observation window first: spend clearly above a reasonable cost with still zero inquiries means stop; freshly added keywords deserve a full settlement cycle.
Is quality-weighting inquiries still worth doing?
Yes — as a second layer. Fix the base formula first (zero-inquiry spend must not vanish from the denominator), then grade purchase-ready vs casual inquiries.
That base-formula discipline is built into AI Operations — LLM-powered analysis that automatically surfaces market trends, user behavior, and sales data to drive strategy. One notch wrong on the cost formula, and everything downstream is wrong.
CCLEE
Independent developer, 24 years in e-commerce, focused on grounding AI in real business scenarios.
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