Most lead-qualification frameworks come from sales. BANT (Budget, Authority, Need, Timeline) was published by IBM in the 1960s for an outside sales motion. MEDDIC (Metrics, Economic buyer, Decision criteria, Decision process, Identify pain, Champion) was developed for enterprise software sales in the 1990s. CHAMP, ANUM, GPCTBA/C&I — all sales frameworks.
These frameworks ask questions a marketing team can't answer at the point of lead capture. "What is the customer's budget?" — a marketer typically doesn't know. "Who is the economic buyer?" — usually unknown until sales engages. "What's the timeline?" — the lead hasn't been asked.
Marketing needs a different framework. One that works with the data marketers actually have at lead capture, before sales touches the lead. This article gives you that framework.
Why sales frameworks fail marketers
The core mismatch is timing. BANT-style questions are answered through conversation — a sales rep has the lead on a call. Marketing-side qualification has to happen before the call exists, often from form data alone.
Three things go wrong when marketing teams try to apply sales frameworks:
1. They score on data they don't have. Budget and authority require disclosure that doesn't happen at form fill. Marketing ends up scoring N/A on the most important factors.
2. They wait for sales to qualify. This makes marketing a contact-list management function rather than a lead-quality function. If marketing's job is to deliver MQLs (Marketing Qualified Leads), the qualification has to happen at the marketing layer, not the sales layer.
3. They build sophisticated score models on weak signals. Lead-scoring software multiplies weak signals (page views, email opens) into impressive-looking scores that don't predict conversion. Sales rejects the high-score leads. Marketing loses credibility.
The fix isn't to abandon scoring. It's to score on data marketing actually has, using a framework designed for marketing's position in the funnel.
The marketing-native qualification job
Marketing-side qualification answers three questions:
- Is this lead the right kind of company? (ICP fit)
- Is this lead actually interested? (Intent signal)
- Is this lead from a channel that historically converts? (Source quality)
These three are answerable from data that lives in a marketing CRM at the moment of capture. No conversation required. No sales-team disclosure required. The data is structural.
If a lead scores well on all three, it's an MQL — ready for sales engagement. If it scores poorly on any one, it's a lower-priority lead that needs nurture or removal.
The framework: 3 dimensions, 3 levels each
Each dimension has three levels — let's call them Strong, Acceptable, and Weak. A lead's score is its combination across the three dimensions. The framework produces a 3×3×3 grid: 27 possible cells.
Dimension 1: ICP fit (firmographic alignment)
Strong: Company matches your target industry, size, and geography. Person has a title in the buying committee for your product.
Acceptable: Company is adjacent to ICP but plausibly a fit (e.g., a slightly larger or smaller company than your sweet spot). Person has a title that influences buying.
Weak: Company doesn't match ICP (wrong industry, too small/too large, wrong geography). Person doesn't influence buying (junior IC, intern, student).
How to assess at capture: Email domain (work vs. free), company size (estimate from domain or self-reported), industry (from form field or domain lookup), title (from form field).
Dimension 2: Intent signals (behavioral evidence)
Strong: Lead took a high-commitment action — booked a demo, downloaded a comparison guide, viewed pricing page, requested a custom proposal.
Acceptable: Lead took a moderate action — downloaded a content piece, attended a webinar, subscribed to newsletter with additional fields.
Weak: Lead took a low-commitment action — subscribed to newsletter with email only, downloaded a TOFU piece without further engagement.
How to assess at capture: The form they filled out matters more than what they did after. A demo-request form is Strong intent; a newsletter signup is Weak intent. Don't conflate the two.
Dimension 3: Source quality (channel performance)
Strong: Source has a 90-day track record of converting at or above your average MQL-to-customer rate.
Acceptable: Source is established but has variable quality — converts above your floor but below your top performers.
Weak: Source is new (no track record), historically below your floor, or known to attract irrelevant leads (e.g., aggregator sites, broad-spectrum content).
How to assess at capture: Tag every lead with source at capture time. Calculate per-source conversion to MQL and to customer monthly. Categorize sources into Strong/Acceptable/Weak based on the latest 90-day window.
The MQL threshold
A lead qualifies as MQL if it scores Strong on at least 2 dimensions, and not Weak on any dimension. This gives you four MQL-qualifying patterns:
- Strong / Strong / Strong (premium MQL)
- Strong / Strong / Acceptable
- Strong / Acceptable / Strong
- Acceptable / Strong / Strong
Everything else is a non-MQL — either needs nurture (if two Acceptable dimensions) or removal (if Weak on any dimension).
This threshold is conservative deliberately. False-positive MQLs (leads that look qualified but aren't) damage marketing-sales trust faster than false-negative MQLs (leads we missed). Tune later, but start strict.
The MQL → SQL handoff
MQL is a marketing decision. SQL (Sales Qualified Lead) is a sales decision — sales has accepted the lead and is actively working it.
The handoff fails when:
- Marketing hands off without context (just an email and a name)
- Sales has no SLA on accepting/rejecting MQLs (leads rot in queue)
- Rejection feedback doesn't flow back to marketing (same low-quality patterns repeat)
The handoff works when:
- MQL is delivered with full context: source, intent signal, ICP details, qualification reasoning
- Sales accepts or rejects within 24 hours (or escalation triggers)
- Rejection includes a reason code that marketing can act on (wrong ICP, wrong timing, bad data)
- Marketing reviews rejection patterns monthly and adjusts source priorities
A CRM that supports this handoff has source, intent, and qualification fields as first-class objects. Most marketing CRMs (including QUST) do; most contact-list tools (including Mailchimp) don't.
Common mistakes
Over-engineering the framework. Tweaking weights, adding sub-dimensions, building elaborate score formulas. The framework above is intentionally simple. Complex frameworks fail because they require disciplined data entry that teams don't maintain.
Scoring deals, not leads. Deal characteristics (budget, timeline) come from sales conversation. They belong in the sales qualification framework, not marketing's. Marketing's framework operates on data available before the conversation.
Ignoring source quality. Source is the most diagnostic dimension because it's structural. If 90% of your converting customers come from organic search and 80% of your leads come from a paid channel that converts at 1% — your source-quality scoring will fix more problems than any other lever.
Treating MQL as a permanent label. A lead can be MQL today and disqualified tomorrow if a Weak signal emerges (e.g., title was misrepresented, company is much smaller than disclosed). Statuses move both directions.
Scoring leads you've never converted. If you have no customer data, you don't have source-quality data. Start with the first two dimensions only (ICP fit + intent) and add source quality after 30-60 days of conversion data.
Spreadsheet template
The framework runs in a spreadsheet without any software. Columns:
- Lead ID / email
- ICP fit: Strong / Acceptable / Weak
- Intent: Strong / Acceptable / Weak
- Source quality: Strong / Acceptable / Weak
- MQL? (formula: AND(at least 2 Strong, none Weak))
- Status (New, MQL, SQL, Disqualified, Customer, Lost)
- Source (text)
- Notes
A team of 1-3 marketers can run this in a spreadsheet for several months before a CRM becomes necessary. The CRM upgrade is worth it when:
- Lead volume exceeds ~50/week (manual entry becomes the bottleneck)
- You need automation (status change → notification)
- Multiple people need to update the same record
- Reports need to run automatically rather than manually
A CRM that supports this framework natively (QUST does — lead, source, status, custom fields) saves about 5-10 hours/week at moderate lead volume.
