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Customer Language Keyword Research

Turn real audience language into testable search patterns

Extract user jobs, entities, and supported modifiers from interviews, reviews, tickets, discussions, and sales notes while preserving the evidence trail.

What the Agent prepares

  • Audience phrase and user-job table
  • Evidence-labeled query patterns
  • Confidence, ambiguity, and validation list

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Make the next search decision from evidence, not assumptions

Extract user jobs, entities, and supported modifiers from interviews, reviews, tickets, discussions, and sales notes while preserving the evidence trail.

The Agent separates observed data, interpretation, missing evidence, and unknowns before recommending a page, experiment, investment, or stop decision.

Use it for

Audience-language research

Preserve customer nouns and verbs before normalizing terminology.

Query pattern mapping

Combine one job, entity, and only evidence-supported modifiers.

Intent separation

Keep similar wording separate when it implies a different outcome.

Example task

Map these support tickets into query patterns

What the Agent prepares

  • Audience phrase and user-job table
  • Evidence-labeled query patterns
  • Confidence, ambiguity, and validation list
Completed query evidence map linking customer sources to three prioritized search patterns

How it works

01

Define the decision

Fix the audience, market, task, scope, and success condition.

02

Inspect the evidence

Apply the Skill method and test competing explanations and missing data.

03

Choose the next action

Return a bounded recommendation, validation step, and stop rule.

Customer language excerpt separated into task, object, and supported condition with source evidence

Evidence-led search planning with explicit limits

  • The Agent does not retrieve current rankings or market data unless a verified data tool is connected.
  • It does not invent search volume, ranking outcomes, customer demand, proof, traffic, links, or revenue.
  • A human reviews claims, market evidence, privacy, accessibility, legal, brand, and publishing decisions.

Frequently asked questions

What should I provide?

Share the market, audience, decision, time window, raw query or page evidence, metric definitions, and constraints.

Can I use exported data?

Yes. Include the platform, date, filters, geography, device, units, and collection method.

Does it guarantee rankings?

No. It prepares a testable recommendation and exposes unknowns; it does not promise traffic or ranking outcomes.

Ready to put this Agent to work?

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Failed or incomplete first runs are refunded