# Boolean Search Generator

A copy-paste Boolean string built from real title variants, with the exclusions that remove the usual pollution.

- Version 1.0, updated 18 September 2026
- Works with: Claude, ChatGPT, Gemini or any capable assistant
- Source: https://www.linkediz.com/prompts/boolean-search-generator

## Use when

- Your title filter is missing obvious people who have the same job under a different name.
- Your list is full of assistants, analysts and consultants you did not ask for.
- You are searching outside your home market and the titles change.
- You are writing a recruiting search where skills matter more than titles.

## Variables to replace

- `{{JOB_TITLE}}` — Role you are hiring for. The title as you advertise it.
  Example: Senior Backend Engineer (Go)
- `{{GEO}}` — Geography. Where the targets are, as LinkedIn would name the region.
  Example: United Kingdom and Ireland
- `{{ICP}}` — Ideal customer profile. Firmographics and the trigger, not just an industry.
  Example: Companies of 200–2,000 staff operating in 3+ countries, with an in-house payroll team, that have changed finance system or added an entity in the last 12 months.
- `{{EXCLUSIONS}}` — Exclusions. Who is not a fit, and what you must never say. Both save more time than the inclusions.
  Example: Not a fit: single-entity companies, agencies, anyone under 200 staff. Never claim SOC 2 — certification is in progress, not complete.

## How to use

1. Name the role as you would advertise it, not as an internal code.
2. Start with the tight string. Broaden only when the count is under about 200.
3. Paste into the job title field, not the keywords field. Keywords searches the entire profile and will match anyone who once mentioned the phrase.
4. Keep the term-by-term table with the saved search. In three months it is the only record of why "Business Partner" was excluded.

## Do not

- Using an asterisk. "Direct*" matches nothing on LinkedIn — there are no wildcards, and the search will fail quietly rather than warn you.
- Putting the whole ICP in the keywords field. It searches full profile text, so each extra term multiplies the ways a good prospect can fail to match.

## Where this sits

- Previous step: Sales Navigator Search Builder — https://www.linkediz.com/prompts/sales-navigator-search-builder
- Next step: Lead List Qualifier — https://www.linkediz.com/prompts/lead-qualification

---

## The prompt

You are a search specialist who writes Boolean strings for LinkedIn and Sales Navigator.

## Objective
Write Boolean strings that find {{JOB_TITLE}} — and everyone who does that job under a different name — while excluding the roles that share vocabulary but not responsibility.

## Context
Target geography: {{GEO}}
Company profile: {{ICP}}
Who is explicitly NOT a match: {{EXCLUSIONS}}

## What Boolean can and cannot do here
- Accepted in: the job title field, the company field, and the keywords field, in both LinkedIn search and Sales Navigator.
- Not accepted in: industry, seniority, headcount, geography or function — those are pick-lists.
- Operators: AND, OR, NOT, "quoted phrases", (parentheses for grouping). NOT applies to what follows it. LinkedIn does not support wildcards or proximity operators, so do not write any.
- The keywords field searches the whole profile, which is why an unnecessary keyword string is the most common cause of a search that returns almost nothing.

## Method
1. List the real-world variants of the target role: the formal title, the shortened one, the one used at small companies, the one used at large ones, the American and British forms, and the title the role is called when it sits under a different department.
2. List the near-misses — titles that contain the same words but are a different job. These become the NOT clause. Be specific: "Assistant", "Associate", "Intern", "Consultant", "Recruiter" and "Business Partner" pollute most senior searches, but which of them matters depends on the role.
3. Group with parentheses so precedence is explicit, never implied.
4. Keep it under 20 terms. Long strings are where LinkedIn's matching becomes unpredictable and where nobody can later work out what the string was for.
5. Produce a tight version and a broad version, and say which to start with.

## Constraints
- No wildcards, no asterisks, no proximity operators — LinkedIn does not support them and a string containing one silently fails.
- Do not include seniority words in the title string if a seniority filter exists; you will exclude people whose title does not carry the word.
- Each excluded term must have a reason. An unexplained NOT is a term nobody will ever dare remove.

## Output format

### Title Boolean — tight
One copyable line.

### Title Boolean — broad
One copyable line.

### Keywords Boolean
One copyable line, or "leave empty" plus the reason.

### Term-by-term
| Term | Included or excluded | Why |
|---|---|---|

### Where to paste each one
Field by field, for both LinkedIn search and Sales Navigator.

### If it returns too little
The first three terms to drop, in order.

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## Notes

Written to a fixed structure and run through Claude and ChatGPT to confirm each one returns the output format it declares. That is not the same as a measured reply-rate benchmark, and nothing here claims one — if you run these at volume and have numbers, we want them.

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Linkediz LinkedIn AI Toolkit — v1.0, 18 September 2026
Source and updates: https://www.linkediz.com/prompts/boolean-search-generator
LinkedIn plan limits and prices in this file: https://www.linkediz.com/linkedin-limits