What is Intent Data? First, Second and Third-Party Explained
Intent data is evidence that a person or company is researching something related to what you sell. It might be your own website visits (a company viewing your pricing page three times this week), activity on a review site (comparing vendors in your category), or a third-party provider’s estimate that an account’s reading on a topic like “SOC 2 compliance” has spiked. Sales and marketing teams use intent data to decide which accounts to focus on now, rather than waiting for a form fill.
Why intent data matters
B2B buyers do most of their research before they speak to anyone.
- ~70% of the purchasing process is complete before buyers engage with sellers 6sense Buyer Experience Report, 2024
- 85% of buyers have largely set their purchase requirements before reaching out to sellers 6sense Buyer Experience Report, 2024
- 11 people in the average B2B buying group 6sense Buyer Experience Report, 2024
These are figures from a vendor that sells intent data, so treat them as directional. The pattern, though, matches what most B2B sales teams see: by the time someone fills in your form, the shortlist is largely set. Intent data is an attempt to see that research phase and show up during it, before a lead ever reaches the MQL vs SQL handoff.
How intent data works
| Type | Source | Example signal | Strength | Weakness |
|---|---|---|---|---|
| First-party | Your website, emails, product, CRM | A target account visits pricing and a case study twice in a week | Accurate, yours, cheapest | Only shows people already aware of you |
| Second-party | Another company’s first-party data, shared by agreement, such as review sites | An account compares vendors in your category on a software review platform | Close to purchase | Limited coverage, paid |
| Third-party | Data providers aggregating activity across many publisher sites | An account’s reading on your topics is well above its normal level | Wide reach, early signal | Modeled, noisy, privacy questions |
Most providers resolve anonymous visits to a company through IP and other signals, then report topics and a surge score at account level, not individual names.
Example: prioritizing a target account list
A hypothetical B2B cybersecurity firm has 300 target accounts and two salespeople. They combine three signals each week:
- Fit: account matches the ideal profile (size, industry, region).
- First-party intent: pricing, comparison or case study visits in the last 14 days.
- Third-party intent: surge on topics like “penetration testing” and “SOC 2”.
| Tier | Rule | Accounts this week | Action |
|---|---|---|---|
| 1 | Fit + first-party + third-party | 9 | Personal outreach from sales within 48 hours |
| 2 | Fit + one intent signal | 31 | Targeted ads and a Thought Leader Ad sequence |
| 3 | Fit, no intent | 260 | Light nurture only |
Two salespeople can properly work 9 accounts a week. They can’t work 300.
Intent data is only useful if someone acts on it this week. A common mistake is buying a third-party feed, pushing every surging account into the CRM and then changing nothing about how sales works. Start with your own first-party signals, such as pricing and case study visits, because they're free and specific. Add a paid feed only when sales has the time to follow up on it.
How to use intent data
-
Start with first-party
Track high-intent pages: pricing, comparisons, case studies, integrations. It's free and the most accurate signal you have.
-
Define your topics
List 10–20 topics your buyers research before buying, in their words, not your product names.
-
Add a provider if needed
Test second- or third-party data against a target list for one quarter before signing a long contract.
-
Combine with fit
Intent without fit is noise. Feed it into your lead scoring model as an engagement signal.
-
Tier and act
Map each tier to a clear action, owner and response time.
-
Measure the lift
Compare meetings and pipeline from intent-prioritized accounts against the rest.
Myth vs fact
- MythIntent data tells you exactly who is ready to buy.
- FactMost intent data is a modeled, account-level estimate. It suggests where research is happening, not who is deciding or when. Use it to prioritize, then qualify through conversation.
Intent data is most useful inside an account-based marketing program, where you already know which accounts matter.
Frequently asked questions
What is the difference between intent data and lead scoring?
Lead scoring ranks known leads using fit and engagement. Intent data is one input to it, and can also flag accounts before you know anyone there. Many teams add intent signals as extra points in their scoring model.
Is intent data legal under GDPR?
It depends on how it's collected and used. Account-level data is less sensitive than individual tracking, but any personal data needs a lawful basis and transparency. Ask providers how they collect data and get consent, and involve your privacy lead.
Is third-party intent data worth the cost for a small business?
Often not at first. Most small B2B teams get more from first-party signals and a tight target list. Test a provider when you have more good-fit accounts than your team can contact and need a way to prioritize.
What are examples of intent signals?
Pricing page visits, repeat visits to case studies, competitor comparison research, review site activity, webinar attendance, job postings for related roles and a surge in reading about topics related to your product.