Qualification should make the next decision easier. It is not a score invented inside a marketing tool; it is a shared operating rule for deciding what deserves attention, what needs more context and what should be declined.

Start with the decision, not the fields

Define the action the model must support: immediate sales follow-up, assisted research, nurture, partner routing or rejection. A field is useful only when it changes that action.

Separate company fit from current intent. A relevant organisation may not be in an active buying situation, while a high-intent response may still be outside the serviceable market.

Use four observable dimensions

Fit covers sector, geography, company type, technical constraints and the problems you can genuinely solve. Intent covers the behaviour and request that indicate active evaluation. Timing covers urgency and dependencies. Readiness covers whether a practical next step is possible.

Avoid false precision. A small number of clear levels — strong, uncertain and weak — is usually easier to audit than a score with dozens of hidden weights.

Design the handoff rule

For every combination, define owner, response target, required context and fallback. A strong fit with unclear timing might receive a useful diagnostic resource; strong fit and active timing should reach a named owner immediately.

Capture the reason behind every route. This is what allows marketing to improve targeting and sales to challenge a rule with evidence.

Review outcomes, not just form completion

Compare qualified status with accepted opportunity, progression, loss reason and eventual value. A model that labels many records as qualified but creates no accepted pipeline is not working.

Review the edge cases monthly. Most learning appears in records that sales accepted despite a low score, or rejected despite a high score.

Implementation checklist

  • The next action is defined before fields are chosen.
  • Fit and intent are evaluated separately.
  • Every route has an owner and response target.
  • Disqualification reasons are explicit and reviewable.
  • Pipeline outcomes are fed back into the model.
A good qualification model is understandable, reversible and connected to real outcomes. Its purpose is not to prove that marketing produced a large number; its purpose is to help the organisation act consistently.