Lead Grade
A letter-based classification (A/B/C/D) representing how well a lead fits the ICP, often paired with a numerical score for engagement.
A lead grade is a letter-based classification (typically A through D, or A through F) representing how well a lead fits your Ideal Customer Profile (ICP). Grades are usually paired with a numerical lead score: the score measures engagement, the grade measures fit.
The grade-and-score model originated with Pardot (now Marketing Cloud Account Engagement) in the late 2000s. The thinking: a single number can’t distinguish “highly engaged but wrong-fit” (a researcher, competitor, or student) from “perfect fit but quiet” (a strategic account that’s not actively browsing). Two dimensions can.
How a lead grade is calculated
Lead grades are firmographic and demographic, not behavioral. Inputs typically include:
- Title and seniority (Director and above usually grade higher than IC roles)
- Function (RevOps, Marketing Ops, Demand Gen for a marketing tool; Engineering for a dev tool)
- Company size (within target headcount band)
- Industry (matching closed-won verticals)
- Geography (in a region you can serve)
- Email type (corporate domain vs freemail)
Each signal nudges the grade up or down. A perfect-fit lead lands at A; a clear non-fit lands at D or F. The boundaries are usually score-based under the hood — grade A might be 90+ profile points, grade B is 70–89, and so on — but the letter abstracts that for sales-facing UX.
Lead grade vs lead score
| Lead Grade | Lead Score | |
|---|---|---|
| Measures | Fit to ICP (firmographic) | Engagement (behavioral) |
| Format | Letter (A–D) | Number (0–100 typical) |
| Updates on | Profile changes (title update, company growth) | Activity (page views, downloads, demo requests) |
| Decays? | Rarely | Usually |
| Origin | Pardot | Various (HubSpot Score, Marketo Lead Score, Eloqua) |
A lead with grade A and score 90 is the unambiguous priority. A lead with grade D and score 90 is a researcher or competitor — high engagement but no real buying intent. A lead with grade A and score 20 is a marketing target — fit is there but engagement isn’t yet.
When the grade-and-score model breaks
The two-dimensional model is a real upgrade over a single score, but it has limits:
- Profile fit and account fit are different things. A senior RevOps director (high profile fit) at a 5-person startup (low account fit) shouldn’t get a single fit grade. A modern model splits them.
- Deal context matters. A lead at an account with an active opportunity is a different play than the same lead at an account with no open opp. Grade and score don’t capture this.
- Decay applies to the wrong dimension. Most systems decay the score (engagement) but not the grade (fit). In practice, fit can change too — a contact gets promoted, a company gets acquired, a title shifts.
When to use grades vs scores
Grades win for sales-facing UX. “This is an A-3” is faster to read than “score 87, fit 76, engagement 92.” Scores win for analytics: you can plot conversion rates by score decile. Most modern stacks use both — a numerical score for the analytics layer, a letter grade for the rep’s queue.
Related at kenbun
kenbun’s scoring model uses four numerical dimensions (engagement, profile fit, account fit, deal context) and exposes both the dimensions and a tier classification (Hot, Warm, Nurture, Disqualified) so sales gets the readable grade and analytics gets the granular numbers.