If your reps don’t trust your lead scoring, they ignore it. Then they cherry-pick “hot” accounts that were never buying. Then pipeline dies quietly. Classic.
Fit vs intent scoring fixes that because it matches how deals actually happen: some accounts can buy (fit). Some accounts are shopping right now (intent). You need both.
TL;DR
- Fit = static. “Should we ever sell to them?”
- Intent = dynamic. “Are they in-market this month?”
- Use a 2-axis scorecard. Keep it dumb. Keep it visible.
- Trigger actions off thresholds: enrich, email, call, hold, disqualify.
- Add anti-signals so “noise intent” doesn’t hijack the queue.
- Audit weekly or reps will call it “BS” by day 10.
Fit vs intent scoring (definitions your team won’t argue about)
Fit scoring (static)
Fit is what stays mostly true for 6-18 months.
Fit answers:
- Are they your ICP?
- Can they afford it?
- Do they have the problem you solve?
- Does your product even make sense in their environment?
Fit data sources:
- Firmographics (industry, headcount, geo)
- Technographics (tools installed)
- Org structure (team size, roles)
- Business model (B2B vs B2C, PLG vs enterprise)
- Constraints (compliance needs, data residency)
If your fit scoring changes every week, you built intent scoring by accident.
Intent scoring (dynamic)
Intent is what changes week to week.
Intent answers:
- Are they actively evaluating solutions?
- Did something happen that forces a project now?
- Are they showing buying motion, not just curiosity?
Intent data sources:
- Hiring, job posts
- Tech installs and migrations
- Funding, mergers
- Leadership changes
- Compliance deadlines
- Site behavior (only if you can trust it)
- Outbound engagement (replies, forwards, meeting link clicks)
Most B2B buying happens before sellers hear about it. 6sense research reports buyers typically wait until roughly 70% through their journey to engage sellers, and buyers initiate first contact more than 80% of the time. That’s why you need intent signals that fire before a form-fill. Source: 6sense 2024 Buyer Experience research and announcement content. 6sense newsroom post and 6sense report page
Also, buyers increasingly prefer self-serve and rep-free motion early. Gartner found 61% of B2B buyers prefer a rep-free buying experience. Translation: your “call them because they downloaded a PDF” playbook is tired. Gartner press release (June 25, 2025)
The simple model sales teams actually trust: a 2-axis scorecard
Your scoring fails when you mash everything into one number. One number hides trade-offs.
A two-axis model makes the trade-off obvious:
- Fit score (0-100)
- Intent score (0-100)
Then you map accounts into four quadrants:
- High fit, high intent = go now
- High fit, low intent = nurture and watch
- Low fit, high intent = trap (don’t waste time)
- Low fit, low intent = ignore
This is the model reps trust because it matches their instincts. It just forces consistency.
Copy-paste template: Fit score (0-100)
Use 5 factors. Keep it boring. Boring ships.
Fit factors and weights
1) Firmographic ICP match (0-30)
- Industry match: 0-10
- Headcount range: 0-10
- Geo and language coverage: 0-10
2) Role coverage (0-15) Do you have the right people to sell into?
- Economic buyer present: 0-5
- Champion role present: 0-5
- Technical approver role present: 0-5
3) Tech environment fit (0-20)
- Required integrations present: 0-10
- Disqualifying tech conflicts absent: 0-10
4) Pain profile (0-20) Use observable proxies, not vibes.
- Clear motion problem you solve: 0-10
- Clear workflow gap you replace: 0-10
5) Ability to pay (0-15)
- Estimated ACV aligns to your pricing floor: 0-10
- Procurement maturity (if needed): 0-5
Fit score thresholds
- 80-100: ICP Core
- 60-79: ICP Adjacent
- 40-59: Edge case
- 0-39: Not ICP
Disqualify rules (hard gates) If any of these are true, fit becomes 0:
- Wrong customer type (example: you only sell B2B, they are pure consumer)
- Unserviceable geo or compliance requirements
- Required integration missing and non-negotiable
- Company too small to ever hit minimum ACV
Hard gates prevent “one excited intern clicking around” from stealing rep time.
Copy-paste template: Intent score (0-100)
Intent needs two things:
- A list of signals you can actually collect
- A decay model so old signals stop lying
Intent scoring rules (simple, rep-readable)
- Score each signal once.
- Add a time decay multiplier.
- Subtract anti-signals.
Time decay multiplier
- Signal in last 7 days: x1.0
- 8-14 days: x0.7
- 15-30 days: x0.4
- 31-60 days: x0.2
- Older than 60 days: ignore
This stops your CRM from celebrating a funding round from last year.
Operational intent signals (use now, no data science required)
1) Hiring and job posts (0-25)
Hiring is budget plus urgency. Not always. Often enough.
Score ideas:
- Hiring for the exact function your product impacts (example: SDR Manager, RevOps, Sales Ops): +10
- Hiring multiple roles in that function (2+ postings): +5
- Hiring senior leader in function (Director/VP): +10
Caveat: job posts can be “evergreen.” That’s why you need anti-signals.
2) Tech installs and migrations (0-20)
Tech change creates project windows.
Score ideas:
- New install of adjacent tool you integrate with (example: they add a CRM, data warehouse, outreach tool): +8
- Rip-and-replace motion (public migration notes, job post mentions, stack change): +12
3) Funding, M&A, budget events (0-15)
Money creates initiatives. Sometimes it creates chaos. Still a signal.
Score ideas:
- Seed/Series A-C within 30 days: +10
- Growth equity / large round (category dependent): +12
- Merger or acquisition: +8
4) Leadership changes (0-15)
New leaders buy. Also, new leaders “review the stack.”
Score ideas:
- New VP/Head in your target function within 30 days: +12
- New CEO in growth stage: +8
- New RevOps leader: +10
5) Compliance deadlines and regulatory triggers (0-15)
Deadlines create non-negotiable buying.
Score ideas:
- Public compliance deadline that matches your solution: +15
- Vendor risk or security initiative announced: +10
6) Site behavior (0-15, only if reliable)
Most site behavior data is a liar in a trench coat. Use it only when you can tie it to identity with confidence.
Score ideas:
- Pricing page view by known account, 2+ times in 7 days: +10
- Integration docs view by known account: +8
- Security page view by known account: +6
- Multiple visits by multiple people from same account: +12
If you only have anonymous traffic guesses, cap this category at 5 and move on with your life.
7) Outbound engagement signals (0-20)
Engagement is intent. It is also politeness, curiosity, or boredom. Score accordingly.
Score ideas:
- Positive reply (not a brush-off): +15
- “Not now, check back in X months” with a time window: +10
- Meeting link click plus follow-up activity: +8
- Multiple stakeholders replying or forwarding: +12
The anti-signals list (prevents false positives)
This is where trust gets built. Reps hate scoring because it overvalues junk.
Anti-signals (subtract points)
- Student research / consultants / vendors sniffing around: -15
- Job posts older than 60 days with no change: -10
- “Evergreen hiring” language like “always hiring” careers pages: -8
- Competitor installs that lock you out (hard conflict): -25 or hard disqualify
- High activity from one person only (single-thread risk): -5
- Spammy engagement (open spikes, bot clicks): -15
- Unsubscribe: -20
- Reply is a hard no (“removed,” “never,” “stop contacting”): -30 and suppress
Also add a simple rule: if intent is high but fit is low, do not “chase heat.” Heat on the wrong stove still burns time.
The 2-axis matrix: what to do at each threshold
Here’s the part teams actually use. Actions. Not theory.
Your score bands
-
Fit A: 80-100
-
Fit B: 60-79
-
Fit C: 40-59
-
Fit D: 0-39
-
Intent Hot: 70-100
-
Intent Warm: 40-69
-
Intent Cool: 15-39
-
Intent Cold: 0-14
Action table (copy-paste)
A fit + Hot intent
- Action: Enrich + multi-thread + call within 5 minutes of task creation
- Channel: email + phone + LinkedIn
- Goal: meeting booked in 7 days
- Add: 2nd stakeholder within 48 hours
A fit + Warm intent
- Action: Enrich + outbound sequence
- Channel: email-first, call on day 2-3
- Goal: meeting booked in 14 days
- Watch: new intent signals
A fit + Cool intent
- Action: Hold + light nurture
- Channel: low-frequency email, retargeting if you run it
- Goal: stay present without burning domain reputation
A fit + Cold intent
- Action: Park
- Re-check: monthly
B fit + Hot intent
- Action: Enrich, qualify fast
- Channel: email plus one call
- Goal: confirm need, confirm buyer role coverage
- If they convert: keep
- If they don’t: downgrade
B fit + Warm intent
- Action: Sequence
- Goal: generate explicit pain confirmation before spending call time
B fit + Cool or Cold intent
- Action: Nurture
- Goal: wait for better intent
C fit + Hot intent
- Action: Disqualify or route to “edge-case” rep
- Reason: these accounts produce long cycles and small deals
- Exception: strategic logo or expansion land
D fit (any intent)
- Action: Disqualify
- Don’t be the team that “books meetings” with companies that cannot buy.
Example scorecards (realistic, not fantasy)
Example 1: Perfect target, real buying motion
Account: 250-person B2B SaaS, US, sales-led motion.
Fit
- Firmographic ICP: 26/30
- Role coverage: 12/15
- Tech fit: 16/20
- Pain profile: 18/20
- Ability to pay: 12/15
Fit total: 84 (Fit A)
Intent
- Hiring SDR Manager posted last week: +10 x1.0 = 10
- New RevOps hire announced: +10 x1.0 = 10
- Pricing page visits from known account, 3 visits: +10 x1.0 = 10
- Positive reply: “Who handles this?”: +15 x1.0 = 15
Intent subtotal: 45 - No anti-signals
Intent total: 45 (Warm)
Action: enrich, sequence, call on day 2. Multi-thread by day 3.
Example 2: Huge intent spike, terrible fit
Account: 12-person agency, multiple “sales automation” reads.
Fit
- Too small for pricing floor: hard gate
Fit total: 0 (Fit D)
Intent
- Lots of content consumption: doesn’t matter
Action: disqualify.
This is how you stop celebrating garbage meetings.
Example 3: Strong fit, fake intent
Account: 800-person manufacturer. One intern clicks around.
Fit
- Firmographic: 24/30
- Role coverage: 8/15
- Tech fit: 14/20
- Pain profile: 10/20
- Ability to pay: 15/15
Fit total: 71 (Fit B)
Intent
- One person hits 8 pages in 10 minutes: +12
- Anti-signal: single visitor, bot-like pattern: -15
Intent total: 0
Action: hold. Don’t chase.
Implementation steps (one afternoon, not a quarter)
Step 1: Pick your ICP inputs (30 minutes)
Write down:
- 3 industries you close fastest
- 2 headcount bands
- 2 stack requirements
- 2 deal-killer disqualifiers
If you can’t do this, scoring is not your problem. Positioning is.
Use Chronic’s ICP Builder to formalize this so the scoring doesn’t drift every time someone loses a deal and panics.
Step 2: Build the scorecard in a spreadsheet (60 minutes)
Tabs:
- Fit factors
- Intent signals
- Anti-signals
- Action table
- A “reason codes” dropdown (more on that later)
Keep weights visible. Hidden weights are how you get “the system is rigged” comments.
Step 3: Wire the actions into your workflow (60 minutes)
Your model is useless until it triggers work.
Minimum triggers:
- If Fit A/B and Intent Hot/Warm: create task + enroll in sequence
- If Fit D: suppress
- If Intent signal appears: auto-enrich missing fields
Chronic handles this end-to-end:
- Pull leads and accounts
- Enrich contacts via Lead Enrichment
- Score with AI Lead Scoring
- Write the sequence copy with AI Email Writer
- Move it through a real Sales Pipeline
No tool soup. No “export CSV and pray.”
Fit vs intent scoring: how to use third-party intent data without getting scammed
Third-party intent can work. It can also create a fake sense of certainty.
Bombora’s Company Surge intent scoring, for example, describes “surge” as increased interest over a recent window compared to a baseline window. That baseline-relative concept matters because it reduces raw-volume bias. Read their own explanations before you buy. Rollworks help doc summarizing Bombora Company Surge methodology and Bombora core concepts on intent topics
Rules if you use third-party intent:
- Never let intent override fit.
- Require 2 signals. Example: Bombora surge + hiring post.
- Decay aggressively. If the signal isn’t recent, it’s just history.
The weekly audit that stops reps from calling it “BS” on day 10
Your scoring model dies in one of two ways:
- It floods reps with junk.
- It “misses” deals reps think were obvious.
A weekly audit prevents both. Put it on the calendar. Friday morning. 30 minutes. No excuses.
What to review (every week)
Pull the last 7 days of worked accounts.
Track:
- Meetings booked by quadrant
- A fit + hot/warm intent should dominate.
- Meeting show rate by quadrant
- If A fit + hot intent no-shows, your intent signals are noise.
- Reply rate by intent band
- Intent hot should reply more. If not, weights are wrong.
- Time-to-first-touch
- Hot intent needs speed. If reps wait 2 days, scoring won’t save you.
- Reason codes on disqualifications
- If “not ICP” appears too often on Fit A/B, your fit criteria is lying.
The “reason codes” trick (stops opinion wars)
Force a single dropdown when a rep overrides the score:
- Wrong persona
- No budget
- Already has competitor under contract
- Too small
- Timing not now
- Bad data
- Other (requires note)
Now you can fix the model with evidence, not group therapy.
What to change (and what not to change)
Change:
- Weights that correlate with bad meetings
- Anti-signals that catch recurring false positives
- Thresholds that overload the team
Do not change:
- ICP definition every week
- The model because a VP “has a feeling”
- Intent weights because one whale account did something weird
If you want a tighter signal framework for outbound in 2026, pair this scoring model with Chronic’s post on relevance and signals. It lays out what actually gets replies now. Relevance beats personalization
Common pitfalls (the ones that quietly kill pipeline)
Pitfall 1: Treating opens as intent
Opens are not intent. Apple MPP and bots made sure of that.
Use:
- Replies
- Meeting link clicks
- Multi-stakeholder engagement
- Specific page views tied to known identity
Pitfall 2: No decay
Old intent is dead intent. If you don’t decay it, you build a museum.
Pitfall 3: One number scoring
One number encourages gaming. Two axes encourage thinking.
Pitfall 4: No anti-signals
Without anti-signals, the loudest noise wins.
Pitfall 5: No operational actions
A score that doesn’t trigger work is a dashboard. Dashboards do not book meetings.
If deliverability is your current bottleneck, fix that before you “score harder.” Sending more to the wrong people just burns domains faster. Use a weekly tracking dashboard and SOP. Deliverability dashboard template and deliverability-first outbound SOP
FAQ
What’s the difference between fit vs intent scoring?
Fit scoring measures how well an account matches your ideal customer profile using mostly static attributes like industry, size, and tech stack. Intent scoring measures short-term buying motion using dynamic signals like hiring, funding, leadership changes, and outbound engagement.
What’s a good starting weight split for fit vs intent?
Start with 50/50 conceptually, but do not merge into one number. Keep separate scores and use a quadrant action table. If you must prioritize, prioritize fit for routing and intent for timing.
Which intent signals are most reliable in 2026?
Operational signals beat vanity signals:
- Hiring and role changes tied to your use case
- Tech installs and migrations that create project windows
- Compliance deadlines that force action
- Outbound replies and multi-thread engagement
Be cautious with generic website “interest” unless identity resolution is solid.
How do we stop false positives from hijacking the queue?
Add anti-signals with negative points and hard gates. Examples: bot-like site activity, evergreen job posts, student or consultant traffic, unsubscribes, and disqualifying tech conflicts. Then require at least two intent signals before calling something “hot.”
How often should we audit and adjust the scoring model?
Weekly. Review meetings booked, show rate, reply rate, and rep overrides with reason codes. Make small weight and threshold changes based on outcomes, not opinions. If you wait monthly, reps will already be freelancing.
Do we need third-party intent data providers like Bombora or 6sense?
Not required. You can run a solid model with hiring, tech change, funding, leadership changes, and outbound engagement. Third-party intent can add coverage, but only if you treat it as one signal among many and enforce fit gates and time decay.
Ship the template, run the audit, earn rep trust
Copy the scorecards. Pick your weights. Add decay. Add anti-signals. Wire actions to thresholds.
Then do the weekly audit. Every Friday. Same time. Same report.
That’s how fit vs intent scoring turns into meetings. Not arguments.