THE SHORT ANSWER
Lead qualification assesses whether a person or account plausibly fits the offer and is ready for an appropriate next step. Lead scoring turns selected signals into a prioritization rule. Both should use explicit definitions, known data limits and feedback from real outcomes.
Separate fit from readiness
| Dimension | Question | Possible evidence |
|---|---|---|
| Fit | Can this offer serve the need well? | Use case, segment, constraints |
| Intent | Is the person actively evaluating? | Relevant enquiry, comparison or requested conversation |
| Behaviour | What have they actually done? | Meaningful product, content or sales interaction |
| Timing | Is there a real decision window? | Stated trigger, deadline or current project |
| Budget | Can the economics work where price matters? | Range, funding path or procurement fit |
| Authority/access | Can the right people participate? | Buying role, influence or path to decision makers |
Budget and authority matter in some considered B2B purchases and much less in a simple consumer transaction. Choose criteria from the buying context, not from a fashionable acronym.
Evidence & context: OpenStax, Rice University
MQL and SQL are local agreements
A marketing-qualified lead usually means marketing evidence justifies a defined next step. A sales-qualified lead usually means sales has accepted or verified readiness for its process. The terms vary widely, so dashboards must include their actual rules.
The handoff should specify response time, ownership, accepted evidence and a reason for rejection. Otherwise teams can optimize their own count while customer follow-up deteriorates.
Use scores to prioritize, not pronounce truth
Rule-based scoring assigns known points or categories to signals. Predictive scoring estimates an outcome from historical data. Rules can be understandable but arbitrary; predictive systems can inherit past selection, missing-data and bias patterns.
- Keep fit and intent visible rather than hiding everything in one number.
- Penalize stale or contradictory evidence.
- Test whether high scores actually progress and create suitable customers.
- Review who is systematically deprioritized.
- Allow people to override a score with a recorded reason.
Example: route the next action
A small-business owner who requests a pricing discussion for the supported use case may deserve prompt human follow-up. A student downloading an introductory guide may be valuable to educate but inappropriate for a sales call. The difference is the next useful action, not one person's worth.
Use lead nurturing for leads that need time, and revisit the ideal customer profile when fit criteria are unclear.
Sources & further reading
- The Business-to-Business Market
OpenStax, Rice University. Open educational material on organizational buyers and buying situations. Actual B2B decision roles and procurement requirements vary by customer and purchase.
- Customer Relationship Management
OpenStax, Rice University. Open educational material on managing customer relationships and value over time. CRM software and lifecycle messaging do not themselves create retention.
Examples and exercises are illustrative unless attributed to a source. No independent expert review is claimed.
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