Capture no-result demand
Record what the customer was trying to find when search, filters or configuration produced no valid result.
- Evidence
- Established practice. Widely and independently practised across commerce. Nothing here is a Specify discovery; these are the ideas most likely to be uncontroversial and least likely to be exciting.
- Difficulty
- Small. Difficulty is an initial editorial assessment of how much work an idea usually takes, not a guaranteed estimate for your systems. A change that is small in one storefront can be significant in another because of where the data lives.
The commercial problem
Most storefronts record what was bought. Very few record what was looked for and not found. The result is a business that knows its bestsellers precisely and its unmet demand not at all.
Why it matters
Demand that produced no result is the cheapest market research a business can obtain, because the customer has already done the work of describing what they wanted. Discarding it is a choice, usually an unexamined one.
Where it applies
- Site search returning zero results
- Filter combinations that empty the grid
- Configurators reaching an invalid state
- Enquiry forms abandoned before submission
Suggested implementation
- Log the query or the filter state, the page it happened on, and the time. Nothing about the person is required for this to be useful.
- Group by what was asked for rather than by frequency of the exact string, so twenty phrasings of one requirement count as one requirement.
- Review it on a fixed cadence with somebody who knows what production can actually do.
- Separate 'we could have sold this' from 'we will never sell this' explicitly, and keep both.
Risks and constraints
- It becomes a dashboard nobody opens. The review cadence matters more than the collection.
- Recording free-text queries can capture personal data if customers paste it in. Treat the log as personal data and set a retention period.
- High-frequency nonsense and bot traffic will dominate raw counts unless filtered.
What to measure
- Volume of no-result events, as a baseline rather than a target
- How many distinct requirements appear more than a threshold number of times
- How many recorded requirements the business turns out to be able to serve
How this relates to Specify
This is what the Opportunity Ledger structure is for: converting lost demand into something a business can act on.
Related ideas
Start with evidence
Or start with one of your own enquiries
The complimentary Enquiry Audit takes one real customer enquiry and shows what a structured reading of it produces. It runs on this site and costs nothing.