Qualify a Lead

Outcome

A supported decision allocates attention without pretending that sparse data proves fit.

Why It Matters

A score is not buyer reality. False positives waste attention; false negatives can deny a useful relationship.

Use When

Use after a relevant signal, before a material sales commitment.

Inputs

Bring source and consent, observed situation, offer boundary, fit criteria, exclusions, owner, and unknowns.

Recipe

1. Verify provenance and permission. 2. Separate observed facts from enrichment and inference. 3. Check problem, fit, authority, timing, and exclusion criteria. 4. Mark missing facts unknown. 5. Choose pursue, nurture, refer, or decline.

Human and AI Control

AI may research public facts and organise evidence. Humans own sensitive inference, contact, fit judgment, and decline.

Output and Handoff

Return the decision, cited evidence, unknowns, rationale, owner, and next permitted action.

Evidence, Transfer, and Stop

Measure later fit and outcome separately from outreach volume. Stop on prohibited data, weak provenance, or consent ambiguity.

Next

When fit is established, secure buyer commitment.