Create advanced Works with: Any AI

Lead Qualification Scorecard for CRM Lead Scoring Rules

Table output Has example

Create a lead qualification scorecard with fit and intent criteria, point values, thresholds and review rules to apply in a CRM.

The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.

[VERIFY] is an editorial flag, not a blank to fill. Wherever the prompt shows [VERIFY], check that item against a reliable source before you use it.

Help me build a lead scoring and qualification scorecard. Who our best customers are (size, industry, role, problem): [BEST_CUSTOMER_PROFILE]. Signals we see before a deal (page visits, replies, form fields, events): [BUYING_SIGNALS]. Past wins and losses in a few lines: [PAST_WINS_AND_LOSSES]. Capacity of the sales team for new leads: [SALES_CAPACITY]. CRM or marketing tool used: [CRM_TOOL].

Produce: a fit score table with the columns Criterion, Values and points (for example 0, 5, 10), Evidence needed; an intent score table with signals and decay rules so that old activity counts for less; negative scoring for poor fit; thresholds for marketing qualified, sales accepted and nurture with the arithmetic that shows how a sample lead scores; a feedback loop where sales rejects leads with a reason code list; and a quarterly review method comparing score bands with actual win rates, with the arithmetic to calculate the win rate per band.

Include a short section on bias: scoring rules should be tested against outcomes, and should not use personal characteristics that are irrelevant or protected. Add a manual override rule and a one-page explanation for the sales team.

Scoring features, limits and automation depend on your CRM and plan; mark each as [VERIFY]. Do not invent historical results; any point values and thresholds are starting hypotheses to adjust with real data. Data protection rules apply to behavioural tracking and profiling, so check local rules [VERIFY].

Add a worked example with invented figures: a lead from a 150-person manufacturer with a director title, 3 pricing page visits and a webinar attendance, and compute the total score against a threshold of 60.

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Optional: type your details and the prompt above updates. Nothing is saved or sent.

Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.

Invented points; replace with data from your own wins and losses.
Fit: company size 100 to 250 employees = 15; industry manufacturing = 10; director title = 15. Fit total = 40.
Intent: pricing page visits 3 x 5 = 15; webinar attendance = 10. Intent total = 25.
Negative: free email address = 0 (not applicable), competitor = 0. Negative total = 0.
Total = 40 + 25 + 0 = 65, above the threshold of 60, so mark as marketing qualified.

Decay rule: intent points lose 50 percent after 30 days with no activity, so the same lead scores 40 + 12.5 = 52.5 a month later and drops back to nurture.
Review: if the 60 to 79 band has 9 wins from 60 leads (15 percent) and the 80 plus band 8 wins from 20 (40 percent), raise the threshold.

• scorecard
• lead-scoring