AI Lead Scoring Template (Salesforce + HubSpot)

Most AI lead scoring vendors sell a black box. The pitch is roughly: hand us your CRM data, we'll produce a score, trust the model. That's commercially attractive but commercially fragile — the moment a sales rep asks why a hot lead scored low, the trust collapses, and the scoring quietly stops being used inside three months.

This template inverts the pattern. The AI scoring lives in an Excel-first model where every variable is visible, every weight is tunable, and the reason a lead scored 87 versus 64 can be explained in one sentence. The model itself is calibrated against the same UK SME deal-velocity benchmarks WayaNerd uses in its production AI customer support deployments — it's not theoretical, it's tuned to UK B2B procurement patterns where average sales cycles run 47–112 days, not the 18-day cycles you'd see in US SMB SaaS.

The practical workflow: drop in 12–18 months of your historical pipeline data, the model produces calibration weights for your business, you can either keep the model in Excel (perfectly viable for sub-£10M ARR) or import the calibrated rules into Salesforce or HubSpot using the included CSV / JSON mappings. Most teams keep Excel for the first 90 days, validate the model against actual outcomes, then migrate to CRM. The Excel-first phase is where trust gets built.

The reviewer checklist is the part most teams skip. Sales scoring that hasn't been signed off by sales-ops, the head of sales, and a sample rep cohort fails on adoption. The checklist takes 90 minutes to complete and saves the 6 weeks of awkward conversations that happen when the scoring goes live without it.