How accurate is person-level identification?

Accuracy varies by traffic source. Email-sourced traffic (clicked from campaigns) has highest resolution. Direct and organic traffic relies on matching methods. Expect 20-40% person-level resolution on typical B2B traffic.

Is this GDPR/CCPA compliant?

Yes. Warmly uses compliant identification methods. We don't use fingerprinting or non-consensual tracking. Person-level data is handled according to applicable privacy regulations.

What if the visitor is already in my CRM?

Even better. Warmly matches against your CRM contacts, increasing identification rates. When a known contact visits, you see their full history.

What's the difference between account-level and person-level?

Account-level tells you 'someone from Acme visited.' Person-level tells you 'Sarah Chen, VP Sales at Acme, visited your pricing page.' Person-level enables direct follow-up.

Can I see historical data?

Yes. Once installed, Warmly retroactively enriches existing sessions where possible. New visitors are identified in real-time going forward.

How do chat conversations become signals?

Every chat message is analyzed for intent signals. Keywords, questions, objections, and sentiment feed into intent scoring and can trigger automations.

1st Party: Web Intent

Know Who's On Your Site — Right Now

First-party web intent starts with knowing who. Warmly identifies visitors at the person level — name, email, title, company — and tracks every page, click, and conversation. Your data, your visitors, real-time.

See Visitor Identification in Action

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What are 1st Party Web Intent Signals?

1st party signals come from your owned channels — primarily your website

Person-level visitor identification

Know the individual, not just the company

Page-by-page behavior

What they viewed, how long, in what order

Chat conversations

Full transcripts and intent signals from AI chat

Form submissions

Conversions and micro-conversions tracked

Return visit detection

Know when someone comes back

How identification works

IP-to-company matching (account-level baseline)

Cookie matching with known visitors

Email pixel matching

LinkedIn data graph matching

CRM and marketing automation sync

Best for

Teams wanting to engage visitors while they're on-site

Sales wanting instant alerts for key accounts

Marketing wanting to personalize experiences

Anonymous Traffic Is Wasted Traffic

The typical website analytics stack

Account-level identification only (IP to company)

Anonymous visitor sessions

No connection to CRM contacts

Data arrives in daily batches

The problems

You know the company, not the person

Can't follow up without a name

No real-time action

Data arrives after they've left

No context

What pages? What intent? How urgent?

Missed opportunities

Hot buyers browse anonymously and leave

Warmly changes this with person-level, real-time identification.

Multiple Methods, Maximum Coverage

Resolution rates:

Account-level: 90%+ of B2B traffic

Person-level: 20-40% of B2B traffic (varies by traffic source)

Complete Context, Not Just a Name

When Warmly identifies a visitor, you get:

Identity

Full name

Email address (when available)

Job title

LinkedIn profile

Company and company data

Behavior

Pages viewed (with time on page)

Session duration and frequency

Navigation path

Scroll depth and engagement

Return visit history

Context

Traffic source and referrer

Campaign attribution

Previous chat conversations

CRM history (if contact exists)

Intent score

What They Say Matters More Than What They Click

Chat conversations are first-party signals too:

From AI chatbot

Questions asked (buying signals)

Objections raised

Features mentioned

Competitors referenced

Timeline and budget discussed

From live chat

Human conversation context

Handoff transcripts

Meeting requests

Example chat signals

"We're evaluating tools this quarter" → High intent "What's your pricing for 50 users?" → High intent "Just browsing" → Low intent "Can you integrate with Salesforce?" → Technical evaluation

These signals feed into intent scoring and trigger automations.