B2B Lead Qualification Scorecard
Score B2B leads using BANT criteria, engagement, and fit metrics. Enter values for instant results with step-by-step formulas.
Worked Examples
Example 1: Enterprise Prospect - Strong Fit
Problem:Enterprise company (200+ employees). Budget availability: 70% (confirmed budget exists). Authority: 80% (VP-level contact). Need/pain: 75% (clear problem identified). Timeline: 60% (Q2 decision). Engagement: 65% (demo + content). ICP Fit: 70% (right industry, slightly small).
Solution:BANT score: (70×0.25 + 80×0.25 + 75×0.3 + 60×0.2) × 1.2 (enterprise multiplier) = 87. Total with engagement/fit: (87×0.6 + 65×0.2 + 70×0.2) = 79. Win probability: 71%. Expected deal: $50K.
Result:79/100 | Warm Lead | 71% win probability | $35.5K weighted value
Example 2: SMB Prospect - High Engagement, Low Fit
Problem:Small business (25 employees). Budget: 40% (unclear). Authority: 90% (founder). Need: 85% (urgent pain point). Timeline: 80% (immediate). Engagement: 90% (multiple demos, active trial). ICP Fit: 45% (too small for typical deal).
Solution:BANT: (40×0.25 + 90×0.25 + 85×0.3 + 80×0.2) × 0.9 (small multiplier) = 65. Total: (65×0.6 + 90×0.2 + 45×0.2) = 66. High engagement but low fit and budget concerns.
Result:66/100 | Warm Lead | Caution: Budget and fit risks | Qualify budget before investing time
Example 3: Mid-Market - Perfect Timing
Problem:Medium company (100 employees). Budget: 85% (approved). Authority: 75% (director, needs VP approval). Need: 90% (critical pain). Timeline: 95% (must decide this month). Engagement: 80% (active evaluation). ICP Fit: 85% (ideal segment).
Solution:BANT: (85×0.25 + 75×0.25 + 90×0.3 + 95×0.2) × 1.0 = 86. Total: (86×0.6 + 80×0.2 + 85×0.2) = 85. Hot lead with strong signals across dimensions.
Result:85/100 | Hot Lead | 77% win probability | Prioritize for immediate follow-up
Frequently Asked Questions
What is BANT qualification?
BANT = Budget, Authority, Need, Timeline. Classic B2B qualification framework developed by IBM. Budget: Can they afford it? Authority: Can they decide? Need: Do they have a problem we solve? Timeline: When do they need a solution? All four elements needed for a qualified opportunity.
How accurate is lead scoring?
Well-implemented lead scoring improves sales efficiency 30-50%. Accuracy depends on historical data quality and regular model refinement. Score models should be validated against actual conversion rates quarterly. Start simple and iterate—complex models without good data underperform simple ones.
When should a lead be passed to sales?
MQL to SQL handoff typically at 60-70 score threshold depending on sales capacity and deal value. But context matters—hot timeline with moderate score might warrant engagement while high score with no timeline can wait. Coordinate marketing and sales on handoff criteria and regularly review.