# Weekly Linear tickets from Algolia zero-result searches

> Every Monday, last week's biggest zero-result Algolia searches become ranked Linear tickets your merchandising team can act on today.

- Workflow type: agent
- Services: Algolia, Linear
- Categories: Operations, Product
- Published: 2026-07-17

## What it does

- Pulls last week's zero-result searches from your Algolia index every Monday morning
- Ranks queries by weekly search volume so the top offenders sit at the top of the batch
- Files one Linear ticket per query into your merchandising team with a short brief on the likely cause (missing product, missing synonym, or content gap)
- Skips queries that already have an open ticket with the same title so nothing gets duplicated

## What you'll need

- An Algolia account with Analytics enabled and an API key that can read analytics
- A Linear workspace and the team ID of the merchandising team where new tickets should land
- A rough sense of your weekly search volume so you can pick a sensible minimum threshold

## Prompt

Every Monday at 9am, pull the top zero-result searches from Algolia for the past 7 days using Algolia's Analytics: Top Searches with No Results. Filter the results to queries whose weekly search count is at or above a configurable minimum threshold (default: 5), then sort the remaining queries by volume descending so the top offenders come first.

For each unique query in the ranked list, first check Linear for an existing open issue in the merchandising team whose title matches the query exactly (using Linear's Search Issues, scoped to the target team and to non-completed workflow states). If a matching open issue is found, skip that query to avoid duplicates.

Otherwise, call Linear's Create Issue in the merchandising team. Use the query text as the issue title. In the description, write a short markdown brief that includes: the query text, the weekly search volume, and a one-line hypothesis on the likely root cause. Pick the hypothesis from three buckets: missing product (the query looks like a product or brand name that we do not carry or have not indexed), missing synonym (a plausible variant of something we do carry, such as a plural, misspelling, or category alias), or content gap (a broader informational query where our catalog copy or landing pages do not yet cover the topic). Note that the hypothesis is a starting point for the merchandiser to confirm.

Expose two knobs the user can tune without editing the workflow: threshold (the minimum weekly search volume before a query becomes a ticket, default 5) and teamId (the Linear team the tickets are filed against, defaulting to the merchandising team). Log a brief summary at the end of each run listing how many queries were considered, how many tickets were created, and how many were skipped as duplicates.

## How to customize

- Adjust the minimum weekly search volume before a query becomes a ticket
- Point the workflow at a different Linear team if merchandising is not the right owner
- Change the run cadence (daily on a busy storefront, biweekly on a slow one) or narrow it to a specific Algolia index

## FAQ

### What counts as a zero-result search?

Any query a shopper typed into your Algolia-powered search box that returned no matches from your index. Algolia tracks these automatically as long as Analytics is enabled on the application.

### Why send these to Linear instead of Notion or Slack?

Zero-result queries are usually merchandising or catalog problems (a missing product, a missing synonym, a content gap), not writing projects. Linear tickets make them ownable, prioritizable, and closeable by the team that actually fixes them.

### How does the agent decide the likely root cause?

It looks at the query itself. A plausible product or brand name that returns nothing suggests a missing product or a missing synonym. Broader informational phrases suggest a content gap. The hypothesis is written into the ticket so your merchandiser can confirm before acting.

### Will it re-open tickets I already closed?

No. Before creating anything, the agent looks for an open Linear issue whose title matches the query and skips it. Closed tickets stay closed unless the same query returns above threshold and there is no open ticket for it.

### Can I run this against more than one Algolia index?

Yes. Point the workflow at a specific index name, or clone the workflow per index so each catalog can have its own threshold and its own Linear owner.

Use this prompt in General Input: https://www.generalinput.com/prompts/weekly-linear-tickets-from-algolia-zero-result-searches