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Grade a lead A–F on firmographic fit alone, the classic grading matrix.
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- Claude, via MCP
How do you grade a lead from A to F?
Rate fit on five weighted criteria: industry (25), company size (20), budget (20), authority (20) and geography (15). Yes scores full weight, partly scores half, no scores zero. The total out of 100 maps to a grade: 90+ is A, 75 to 89 B, 60 to 74 C, 40 to 59 D and under 40 F.
Grade C is a marginal fit. These are usually worth nurturing rather than routing straight to sales, the gap is almost always talking to a decision-maker.
Grading measures fit (who they are); it says nothing about intent. Combine with the Lead Scoring Logic Architect for the classic grade × score routing matrix.
About this calculator
Lead grading is the classic marketing-automation concept most teams half-remember: a letter grade, A through F, based purely on firmographic and demographic fit, with no behavior or engagement in the mix at all. That deliberate narrowness is the point, this calculator answers "is this the right kind of company and contact" completely separately from "are they engaged," so the two questions don't get muddled together in one score.
How to use it
- Rate five fit criteria as Yes, Partially, or No: right industry/vertical, right company size, budget confirmed or implied, talking to a decision-maker, and serviceable geography.
- Read the resulting letter grade, A through F, and the fit score out of 100 it's based on.
- Check the weakest criterion, the lowest-scoring input dragging the grade down.
Methodology
Each criterion carries a fixed weight: industry 25, company size 20, budget 20, authority 20, geography 15, totaling 100. A Yes answer scores full weight, Partially scores half weight, No scores zero.
The fit score is the sum of weighted points divided by total possible weight (100), expressed as a percentage. That percentage maps to a letter grade: 90+ is A, 75-89 is B, 60-74 is C, 40-59 is D, below 40 is F.
The weakest criterion is simply whichever input has the lowest point value among the five, surfaced separately so you know exactly which fit dimension to investigate before routing the lead further.
This grade is fit-only by design, it says nothing about engagement, intent, or how actively the prospect is evaluating a purchase. A grade-A lead who has never opened an email is still a cold lead; the classic grade × score matrix pairs this fit grade with a separate behavioral score (see the Lead Scoring Logic Architect) before a routing decision is made.
Fit score and letter grade
Fit score = 25 × Industry + 20 × Size + 20 × Budget + 20 × Authority + 15 × Geography (each criterion: Yes = 1, Partly = 0.5, No = 0) Grade: A ≥ 90, B 75 to 89, C 60 to 74, D 40 to 59, F < 40
- Industry
- Is the company in an industry you serve well?
- Size
- Does headcount or revenue sit in your target range?
- Budget
- Is there evidence the company can afford your product at its normal price?
- Authority
- Is the contact a decision-maker or a strong influencer on the purchase?
- Geography
- Is the company where you can sell, deliver and support?
A grade measures fit only: who the lead is, not what they have done. Pair it with a behavioural score (visits, form fills, replies) to decide routing. Salesforce describes the same split in its lead scoring and grading guidance: the grade shows how well the prospect matches your ideal customer, the score shows interest.
Worked example: a mid-size manufacturer's marketing manager
A lead arrives from a manufacturing company, an industry the firm serves well. The company is a little below the target size, budget is unclear, the contact is a marketing manager who will not sign, and the company is in a city the firm serves.
- Industry yes = 25 × 1 = 25.
- Size partly = 20 × 0.5 = 10.
- Budget partly = 20 × 0.5 = 10.
- Authority no = 20 × 0 = 0.
- Geography yes = 15 × 1 = 15.
- Fit score = 25 + 10 + 10 + 0 + 15 = 60, which is a C. Weakest criterion: authority.
- If the contact introduces the head of operations who owns the budget, authority becomes yes and the score rises to 80, a B.
A C with a clear gap is a lead to work with a specific aim: find the decision-maker. Combine the grade with engagement in the lead scoring logic architect, so a C-grade lead showing strong intent still gets attention while an A-grade lead with no activity goes to nurture. Use the grades to set the MQL rule in the MQL calculator.
What grade should a lead need before sales calls?
Decide with sales, using past deals. Grade a sample of last year's closed-won and closed-lost deals with this model:
- If most wins were A or B, route A and B leads to sales and nurture the rest.
- If many wins were C, your criteria may be too strict, or one criterion (often budget) is hard to judge early.
- If losses are spread evenly across grades, the criteria do not predict outcomes and need changing.
The grade bands are the tool's defaults. The right cut-off is the one your own win history supports.
Lead grading in India vs the US
Company size is hard to judge in India from a form alone, because many firms do not publish headcount or revenue. GST registration, LinkedIn company pages and the website are practical checks. Geography often means city tier: if you deliver in person, a lead in a city you do not serve should score low even if everything else fits. Budget is frequently uncertain early, so "partly" is a fair default until the first call.
US firmographic data is easier to obtain from enrichment tools, which makes size and industry quick to grade automatically. Authority is the harder criterion, because job titles vary. Build a title list that maps to authority levels and review it each quarter. For the cost of enrichment against its benefit, see the data enrichment value predictor.
Common lead grading mistakes
- Mixing behaviour into the grade, which double-counts it when you also score engagement.
- Setting weights from opinion instead of from closed-won and closed-lost deals.
- Scoring budget "no" when it is simply unknown. Use "partly" until you know.
- Grading once at lead creation and never updating it after the first call.
- Routing on grade alone, so engaged mid-fit leads never reach sales.
Sources
- Get started with lead grading, Salesforce Trailhead. Accessed 2026-10-19.
Go deeper
FAQ
Grading measures only who the prospect is, industry, size, budget, authority, geography, into a letter grade. Scoring (the Lead Scoring Logic Architect) measures both fit and behavior together into a numeric 0-100 score with a routing recommendation. The two are meant to be used together, not as substitutes for each other.
Generally no, a poor fit grade means the prospect isn't a real match for what you sell regardless of how engaged they seem, so routing them to a rep wastes the most expensive resource in the funnel. Suppress or route to a self-serve or lower-touch track instead.
Mark it Partially or No rather than guessing Yes, since an inflated grade based on assumed budget or authority will misroute leads that later turn out to be a poor fit. Discovery calls exist specifically to convert these unknowns into confirmed Yes/No answers.
The calculator uses fixed weights, but the method works with any weights. If your wins depend more on one criterion, give it more weight in your CRM's grading rules and keep the total at 100.
No. Keep them but exclude them from sales routing and paid retargeting. Some are useful for brand reach, and a few will change role or company and become good fits later.
Numbers looking off?
If the model says one thing and the pipeline says another, that gap is usually where the revenue is. A 30-minute call finds it.
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