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Structured Prompts for GTM Data Workflows

Structured GTM prompts define the evidence, decision criteria, output fields, and handling of unknowns. Version and test them as part of the workflow they control.

George Rekouts

George Rekouts

· updated October 6, 2026

Structured Prompts for GTM Data Workflows

A casual question is useful for exploration. A prompt that decides which accounts enter a sales campaign needs a more explicit specification.

Treat the prompt as one component of the workflow: define what it receives, what it must decide, and how you will check the result.

Define inputs and decision rules

“Find good prospects” leaves the criteria open. Describe the business activity and hard requirements, then identify the evidence the model should use.

Separate observation from inference. A homepage can state that a company sells managed IT services. It may not reveal its budget or current buying plans.

Example: a bounded qualification prompt

Using only the supplied company profile and homepage text, determine whether the company sells managed IT services to other businesses. Return fit, not fit, or insufficient evidence. Include the supporting sentence. Do not classify a hardware retailer as a fit unless the text also describes the required service.

This prompt defines the source, criterion, exception, and uncertainty state. It still needs testing on representative companies.

Specify the output contract

Decide which fields the next step requires: company identifier, decision, supporting evidence, and review status. Validate those fields before writing the result to a CRM or campaign list.

Use code or database operations for exact exclusions, record counts, and deduplication. Natural language instructions should not be the only control protecting those invariants.

Version and evaluate changes

Keep a reference set with clear matches, clear mismatches, and ambiguous examples. Run it when changing the prompt, model, or source preparation.

Track disagreements rather than optimizing only for output format. A well-formed answer can still be wrong.

DiscoLike combines structured company retrieval with DiscoGen research. Explore the API and build a small validation workflow before applying the prompt to a large list.


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