Lead qualification: what it is, the main frameworks and a scoring example

This page is for SDRs, sales managers and marketing ops teams who need a shared, written way to decide which leads go to sales, which get nurtured and which get dropped. It covers the process, the main frameworks in brief and a scoring model with real arithmetic.

What lead qualification means

Lead qualification is the work of deciding whether a lead should get a seller's time. It answers two questions:

• Fit: does the company match your ideal customer profile, and is this person involved in buying? This can usually be checked from data before anyone talks.
• Readiness: do they have a problem you solve, and a reason to act in the next few months? This usually needs a conversation.

A lead that fits but isn't ready goes to nurturing. A lead that's ready but doesn't fit is the hard case: often it's better served by a partner, a self-serve option or a polite no. Marketing typically qualifies for fit and engagement (a marketing qualified lead), and sales confirms readiness in conversation (a sales qualified lead). The MQL vs SQL entry explains the hand-off.

How to qualify a lead, step by step

1. Check fit against your profile. Industry, size, location and the person's role. Drop clear mismatches before scoring anything else.
2. Score engagement. Replies, pricing page visits, event attendance, proposal requests.
3. Route by score. Above the threshold goes to a seller within an agreed time; below goes to nurturing or no action.
4. Qualify in conversation. Confirm the problem, who's involved in deciding, what it's worth to them and the timing.
5. Decide and record why. Advance it, nurture it or disqualify it, with a reason anyone can read later.

Qualification frameworks compared

MEDDIC was created in 1996 at the engineering software company PTC by Dick Dunkel, according to MEDDICC, the company that now teaches it. BANT and CHAMP have no confirmed single author. All three ask the same core questions in a different order: is there a real problem, who decides, is there money, and when.

A useful split: use BANT or CHAMP to decide whether a lead becomes an opportunity, and MEDDIC to decide whether an opportunity is likely to close.

Worked example: a fit and engagement score

Illustrative example. The company, leads and results are invented to show the arithmetic.

Northstar Business Travel (northstar.example) manages corporate travel for companies with frequent staff travel. Its scoring model gives up to 60 points for fit and 40 for engagement, with deductions for clear mismatches:

Routing rule: 70 or more goes to a seller within one business day; 40 to 69 goes to nurturing; under 40, no action.

Lead C shows why fit and engagement are scored separately. It's the keenest lead of the three and the worst fit: a company that size rarely needs managed travel. Northstar sends it a self-serve booking option instead of a seller's time.

Lead A in conversation. The SDR uses CHAMP. Challenges: travel between offices doubled after the third office opened. Authority: the finance director owns the budget; the COO signs. Money: they spend heavily on travel and want to cut hotel costs. Prioritization: they want a policy in place before January. All four confirmed, so Lead A becomes a sales qualified lead and the SDR books the account executive with a note covering each point.

Checking the model. A score is only useful if it predicts outcomes. Northstar compares last quarter's leads by band:

The top band converts four times as often as the middle, so the threshold is doing its job. If the bands converted at similar rates, the points would need reweighting. The free lead scoring calculator lets you build and test a model like this.

Disqualify early

Qualification includes saying no. In Ebsta's 2024 benchmark report, built from 4.2 million opportunities at 530 companies, top performers were 366% more likely to close an opportunity at the discovery stage instead of carrying it in hope, and deals were 324% more likely to be won when MEDDPICC (an extended MEDDIC) was completed by the time the solution was presented. These are correlations, not proof, but they match practice: the deals you drop early free time for the ones you can win.

Common reasons to disqualify, written as a rule so reps apply them the same way:

• The company is outside your profile on size, industry or location.
• No one you've spoken to can describe the problem in their own words.
• There's no path to the person who approves the money.
• The timing is more than two quarters away (nurture instead).
• They need something you don't do.

Checking fit by hand is slow at volume. Bebop finds companies that match a plain-language description of your best customers and explains why each one fits, so the fit check is done before a lead reaches a seller.

Common mistakes

• One score for everything. Mixing fit and engagement lets an eager poor-fit lead outrank a quiet ideal one.
• Qualifying on budget first. Many buyers don't have a budget until they've agreed there's a problem. Lead with the problem.
• Never checking the model. If score bands convert at the same rate, the score is noise.
• No written reason for disqualification. Without it, you can't tell a bad lead source from a bad week.
• Treating qualification as a single event. Requalify when the deal stalls or the champion leaves.

Next step: build and test your own model with the free lead scoring calculator.