What signals does Warmly use for intent scoring?

First-party (website visits, email engagement, chat, content) and third-party (LinkedIn Contact Posts with AI extraction, Glassdoor leadership signals, G2 competitive intel, Hiring Trends with strength scoring, Bombora intent topics, News signals, technographics). All combined with ML-optimized weights.

How is this different from 6sense intent?

6sense is black-box — you get a score but no explanation. Warmly shows exactly which signals contributed what. Plus, we combine first-party signals that 6sense can't see.

How do the scoring weights work?

Our ML model weights signals based on what's most predictive for B2B buying behavior — first-party signals like pricing page visits are weighted higher than passive signals.

How quickly do scores update?

First-party signals (website) update in real-time. Third-party signals update within hours of detection. No weekly batch processing.

Do I need Bombora separately?

Bombora intent is included with Warmly. No separate contract or integration required.

How does Bombora topic scoring work?

Bombora topics relevant to your category (sales intelligence, buyer intent, etc.) are automatically matched and scored. The model identifies which topics correlate with your ideal customers.

How does scoring connect to orchestration?

Intent scores trigger actions: high score sales alert, medium score nurture, low score hold. TAM Agent uses scores for prioritization.

What's the difference between fit and intent?

Fit (ICP Tiering) tells you if an account matches your ideal customer profile. Intent tells you if they're actively researching. Best results come from combining both: 'Tier 1 + High Intent.'

Can I see historical intent trends?

Yes. View intent score changes over time to identify accounts trending up (entering buying cycle) or down (disengaging).

ML INTENT SCORING

Know Who's Ready — Before They Tell You

Intent scoring shouldn't be a black box. Warmly's ML-powered scoring combines all signals and explains every score. See who's in-market and act while they're hot.

ML Intent Scoring is a transparent system that combines first-party signals (website visits, email engagement) with third-party signals (Bombora intent, job postings) to identify accounts actively researching your solution — with full explainability showing exactly why each account scores the way it does.

See Intent Scoring in Action

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4.8/5 based on G2 reviews for intent data transparency

What is ML Intent Scoring?

ML Intent Scoring identifies accounts showing buying signals

First-party signals

Website visits, email engagement, chat conversations

Third-party signals

Bombora intent, job postings, technographics

Combined scoring

All signals weighted and unified

Transparent

See exactly why a score is what it is

Real-time

Scores update as signals arrive

Score ranges

90-100

Urgent — Buying now, engage immediately

70-89

High — Active research, prioritize outreach

50-69

Medium — Early interest, nurture

Below 50

Low — Not in market yet

Best for

Teams wanting to prioritize accounts by readiness

Sales orgs tired of guessing who to call

Companies replacing black-box intent providers

Black-Box Intent

Warmly Intent

Score: 72! (no explanation)

Score: 72 — here's exactly why

"High intent" label

Specific signals with contributions

Third-party only

First-party + third-party

Batch updates (weekly)

Real-time streaming

No Trust

Don't know why 72 is high

Black-box scores provide numbers without explanation — reps have no reason to trust them

Result: Sales ignores intent data completely

No Action

What's different for 72 vs 71?

Without context, reps can't prioritize or personalize their outreach

Result: All "high intent" accounts treated identically

Stale Data

Old signals count the same

Week-old Bombora data mixed with signals from 90 days ago

Result: Reach out after the buying window closes

Signal Category

Specific Signals

Website behavior

Visit frequency and recency, pages viewed (pricing = high intent), time on site, multiple visitors from same account, return visits

Engagement

Email opens and clicks, content downloads, webinar attendance, chat conversations, form submissions

Signal Category

Specific Signals

Bombora Intent

Topic surge (researching your category), competitor research, solution research, buying stage keywords

Job Signals

Job postings (hiring for relevant roles), job changes (new decision-makers), layoffs (budget constraints)

Technology Signals

New tech adoption, competitive tech changes, technology spend changes

Company Signals

Funding announcements, M&A activity, leadership changes

Champion

Who they are

Mid-level with direct pain point, has influence but not final authority, motivated to solve the problem

How we identify

Title patterns indicating user-level management, job descriptions mentioning relevant responsibilities, engagement signals

Why they matter

Will advocate internally and push the deal forward

Decision-Maker

Who they are

Has budget authority for this purchase, VP/C-level for your deal size, may not be most visible

How we identify

Org chart position relative to champion, title + company size patterns, historical deal data

Why they matter

Final say on vendor selection, signs the contract

Influencer

Who they are

Shapes evaluation criteria, technical or operational expert, often includes procurement/legal

How we identify

Related functions (IT for tech purchases, legal for contracts), reporting relationships to decision-makers

Why they matter

May have veto power, sets requirements you must meet

Approver

Who they are

Signs off on procurement, may be finance, legal, or executive, often the final hurdle

How we identify

Role patterns (CFO for big deals, procurement for all deals), company size and process patterns

Why they matter

Can kill deals at the last minute if not engaged early

Example: Acme Corp — Score 87

Signal

Value

Weight

Contribution

Website visits (7 days)

1.5x

+18

Pricing page view

Yes

2.0x

+30

Bombora surge topics

1.0x

+15

Job posting (SDR)

Yes

0.8x

Email engagement

2 clicks

1.2x

+10

Recency bonus

This week

1.5x

Total

What this means

Reps know what to reference in outreach

Marketing knows which signals drive scores

RevOps can tune based on what converts

First-Party Signals

Third-Party Signals

Recency Factors

Website visits weighted by page type (pricing = high value)

LinkedIn Contact Posts • AI-extracted initiatives, pain points, urgency

Recent signals (7 days) weighted highest

Email engagement indicates active interest

Glassdoor Signals • Leadership complaints predict vendor evaluation

30-day signals provide context

Chat conversations show buying urgency

G2 Product Reviews • Switching intent, competitor frustrations

90-day lookback for trend analysis

Content downloads show research stage

Hiring Trends • Role counts with signal strength scoring

Email engagement

Bombora Surge • Topic intent at account level

Total

News Signals • Funding, partnerships, exec hires

Signal coverage:75% of ICP companies have 3rd party signals | 49% have LinkedIn insights | 42% have Glassdoor signals

Comparison

Traditional Intent

Warmly Intent

Batch updates (weekly)

Real-time streaming

Old signals count same

Recency weighting

Third-party only

First, second, and third party

Yesterday's score

Score as of now

When a visitor hits your pricing page, their score updates immediately.

Intent Scoring Powers Your Entire GTM Motion

TAM Agent Feature

How ICP Tiering Connects

Dynamic Audiences

Filter by intent score range ("Intent 80+")

Al ICP Tiering

Combine fit (tier) + intent for full prioritization

Buying Committee

High-intent accounts get committee identification priority

Outbound Orchestration

Score threshold triggers automated sequences

Nurture Campaigns

Medium-intent accounts enter personalized nurture

LinkedIn Ads

Target high-intent accounts with awareness campaigns

Higher conversion on high-intent accounts

More pipeline from intent- sourced leads

Faster identification of ready buyers

More Deals, Same Team Size

"Warmly has allowed us to increase our pipeline targets by twenty percent without increasing headcount."

David Chase

Sales Leaders / CROs

Marketing That Converts

"We’ve doubled our average contract value, and our sales team freaking loves using it."

Charles Fox

Marketing / Demand Gen

Revenue Outcomes

"Warmly sourced MQLs closed fifty percent higher and thirty percent faster than our other sources."

Stephanie Armand

RevOps

Building transparent, explainable intent scoring

Current intent provider is a black box

Full transparency — see every signal contribution

No way to validate intent accuracy

Track correlation between scores and conversions

Teams don't trust the data

Explainability builds confidence across org

Can't explain scores to stakeholders

Clear breakdown of why each account scored high

Result: "Finally have intent data I can defend. When sales asks why an account is 87, I can show them exactly why."

Prioritizing campaigns by buyer readiness

ABM programs spray budget everywhere

Focus on accounts showing actual buying signals

No differentiation between warm and hot

Score ranges enable precise segmentation

Can't prove intent data drives pipeline

Full attribution from signal to score to conversion

Third-party intent only (missing website)

First-party + third-party unified view

Result:"Shifted 70% of ABM spend to 80+ intent accounts. Pipeline per dollar tripled."

Knowing which accounts to call first

All accounts look the same in CRM

Score-based prioritization surfaces ready buyers

No context for personalization

Signal breakdown tells you what they're researching

Reps don't trust marketing's "hot leads"

Transparent scores with explanations build trust

Outreach timing is random

Real-time scores enable immediate response

Result:"My team starts every day with the intent dashboard. They know exactly who to call and what to say."

Connect your data

Connect your CRM and add website tracking pixel

Scores populate automatically

Entire TAM scored in real-time

Automate actions

Trigger outreach on score thresholds

Book a Demo

Know Who's Ready — Before They Tell You

What is ML Intent Scoring?

Example: Acme Corp — Score 87

Intent Scoring Powers Your Entire GTM Motion

More Deals, Same Team Size

Marketing That Converts

Revenue Outcomes

Common Questions

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