Template

Lead Scoring Model Template

A practical lead scoring framework covering fit signals (firmographic, demographic) and engagement signals (behavioral, intent). Includes point values and MQL threshold guidelines.

Template Updated February 2026 Free

Get the Template

Download the CSV file. Open in Google Sheets, Excel, or any spreadsheet tool. Customize the fields for your team.

⬇ Download Scoring Model
CSV format — works with Google Sheets, Excel, Numbers

Scoring Dimensions

Effective lead scoring weights two independent dimensions: fit (who they are) and engagement (what they've done). Most broken scoring models collapse these into one score, making it impossible to tell the difference between a perfect-fit prospect who hasn't engaged and a poor-fit visitor who downloaded everything.

Fit Score (0-100)

  • Company size — Match to your ICP employee count range (+25 for exact match, +15 for adjacent, 0 for outside range)
  • Industry — Target industries (+20), adjacent (+10), excluded (0)
  • Title/role — Decision maker (+25), influencer (+15), individual contributor (+5)
  • Geography — Serviceable market (+15), stretch market (+5)
  • Technology — Uses your integration partners (+15 per match)

Engagement Score (0-100)

  • Content consumption — Pricing page visit (+20), case study (+15), blog (+5), resource download (+10)
  • Email engagement — Open (+2), click (+5), reply (+15)
  • Product signals — Free trial signup (+30), demo request (+25), feature page visits (+10)
  • Decay — Subtract 5 points per week of inactivity (cap at -30)

Setting Your MQL Threshold

The MQL threshold should be set by working backward from your sales team's capacity and historical conversion data. A common starting point: Fit ≥ 60 AND Engagement ≥ 40.

Review the threshold monthly. If sales rejects more than 20% of MQLs, your threshold is too low. If your MQL volume drops below what the team can work, it's too high. The goal is a rejection rate under 15%.

Checklist

Define ICP criteria (company size, industry, geography, technology)
Map title/role hierarchy for your buyer personas
Assign fit scores for each dimension (total = 100)
List engagement events with point values
Set inactivity decay rate and cap
Define MQL threshold (Fit + Engagement minimums)
Configure in your marketing automation platform
Set up weekly MQL quality review with sales
Establish monthly threshold adjustment cadence

Get the Template

Download the CSV file. Open in Google Sheets, Excel, or any spreadsheet tool. Customize the fields for your team.

⬇ Download Scoring Model
CSV format — works with Google Sheets, Excel, Numbers

Frequently Asked Questions

What's a good MQL-to-SQL conversion rate?

30-40% is strong. Below 20% means your scoring model is too loose. Above 50% might mean you're being too restrictive and leaving pipeline on the table. Track this weekly and adjust.

Should I use a single score or a fit/engagement matrix?

Always use two separate scores. A single combined score hides the difference between a great-fit prospect who hasn't engaged yet (nurture them) and a poor-fit contact who's very active (don't waste sales time). The matrix approach makes routing decisions clearer.

How often should I recalibrate lead scoring?

Monthly threshold reviews, quarterly model reviews. Pull your closed-won deals from the last quarter and check: did the scoring model predict them? If high-scoring leads aren't converting, the model needs adjustment.

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