The intent data market is projected to grow from roughly $1.5 billion today to over $4.5 billion by 2033. Every sales and marketing team has heard the pitch: "We detect which accounts are researching topics related to what you sell, so you can reach out at the right time."
The problem: most teams buy intent data, pipe it into their CRM, and find it noisy, expensive, and hard to act on. Bombora tells you "Acme Corp is surging on cloud security." Great — but which person? What stage are they at? Should you call or email? The signal is account-level, topic-level, and pre-outreach. It tells you who to target, not how interested they actually are.
Meanwhile, your sales team sends proposals, case studies, and decks to prospects every day. When a prospect spends 4 minutes on your ROI page and forwards the deck to their CFO, that's intent data too. But nobody calls it that.
This post breaks down first-party, second-party, and third-party intent data — what each type actually tells you, what it costs, and why the highest-quality buying signals are hiding in a source nobody includes in the conversation.
What is intent data?
Intent data is any signal that indicates a prospect's likelihood to buy. In B2B, it traditionally comes in three flavors: third-party (aggregated from publisher networks), second-party (shared from review platforms), and first-party (collected from your own properties). The distinction matters because each type operates at a different level of fidelity, cost, and timing in the buying cycle.
Most "intent data explainers" stop there. We won't.
Third-party intent data: the industry standard
What it is: Aggregated behavioral signals from publisher networks showing which companies are researching topics related to your product. Bombora, 6sense, ZoomInfo, and TechTarget are the major providers.
How it works: Bombora's Data Co-op tracks content consumption across 5,000+ B2B publisher sites. When employees at Acme Corp read significantly more articles about "cloud security" than their historical baseline, Bombora flags a "surge" on that topic. Your sales team gets an account-level signal: Acme Corp is in-market for cloud security.
Where it's valuable: Top-of-funnel account identification, ABM campaign prioritization, and discovering accounts you didn't know were researching your category.
What it costs
Third-party intent data is not cheap. Based on verified contract data from Vendr and published pricing analyses:
| Platform | Typical annual cost | What you get |
|---|---|---|
| Bombora | $25,000–$80,000/yr (Vendr median: $24,750) | Topic-level surge data, account-level only |
| 6sense | $50,000–$140,000/yr (Vendr median: $55,211) | Predictive intent + account identification |
| ZoomInfo (Advanced) | $24,000–$45,000/yr | Intent signals bundled with contact data |
| G2 Buyer Intent | $55,000–$70,000/yr (base + add-on) | G2 profile and comparison activity |
And that's just the license fee. MarketBetter estimates the total cost of ownership — including activation tools, implementation, and RevOps resources — at $73,000–$200,000+ per year.
The limitations
The frustration data is striking. Forrester's 2023 Global B2B Intent Data Survey found that more companies expected benefits than achieved them — across every benefit category, and especially in sales use cases and revenue growth. Forrester analyst Brett Kahnke put it directly: "Despite all the benefits of intent data, too often the reality doesn't meet the expectations. This is particularly true in sales."
The structural limitations:
- Account-level, not individual. You know "Acme Corp" is surging, not who at Acme. Identifying specific contacts within surging accounts was cited as the #1 execution challenge in Forrester's survey.
- Topic-level, not solution-level. They're researching "cloud security" broadly, not evaluating your specific product.
- Noisy. 6sense has 131 mentions of inaccurate contact data and 70 mentions of accuracy issues in verified G2 reviews. One G2 reviewer noted: "From an intent perspective, it is not the end all be all or the crystal ball. It is directional."
- Expensive for uncertain ROI. Only 24% of companies report "exceptional ROI" from intent data (Intentsify/Ascend2, 2024). 37% can't measure ROI at all.
- Lagging. Most third-party intent data is delayed by days or weeks. By the time a surge is detected, the prospect may already be in conversations with competitors.
Demandbase — a major intent provider — acknowledges on their own blog: "A single search on a term does not mean an account is ready to buy (or even more likely to buy). They may not even know who you are!"
Second-party intent data: the middle ground
What it is: Behavioral signals from another platform's first-party data, shared with you through a commercial relationship. The clearest examples: G2 buyer intent (who viewed your G2 profile or compared you to competitors), TrustRadius downstream intent, and review platform activity data.
Gartner Digital Markets defines it as "behavioral data collected by an organization that has a direct relationship with the user, like a software review site."
Where it's valuable: Higher signal quality than third-party because the behavior is specific to your category or product. When someone compares you to a competitor on G2, that's a stronger signal than "someone at their company read articles about your category."
The limitations:
- Still account-level in most cases — you see the company, not the individual
- Limited to platforms you're listed on
- Requires paid relationships with each platform ($40,000–$50,000/year for G2 Buyer Intent alone)
- Coverage is narrow — only captures buyers who use review sites during their evaluation
First-party intent data: what everyone says it is
What it is today: Signals from your own digital properties. Website visits, pricing page views, content downloads, webinar registrations, email engagement, chatbot interactions, form fills.
Why it's considered the gold standard:
- Individual-level, not just account-level — you know exactly who
- High accuracy — this person actually did this thing on your property
- Free — you already own the data via your website analytics and marketing automation
- Real-time — no delays from third-party aggregation
The definition gap nobody notices:
We checked the exact definitions of "first-party intent data" from eight major vendors: Foundry, IntentData.io, Lift AI, Influ2, Clearbit/HubSpot, Demandbase, 6sense, and Bombora. Every single one defines first-party intent data as some combination of website visits, email engagement, content downloads, CRM activity, and marketing automation data.
None of them — not one — include shared document engagement, proposal tracking, or post-outreach content engagement in the definition.
This isn't a coincidence. The first/second/third-party classification wasn't created by Gartner or Forrester (neither has published a formal taxonomy). It was created by vendors whose products center on pre-outreach signals. The taxonomy reflects what they sell, not the full landscape of buying signals.
The missing first-party source: shared content engagement
When you share a tracked proposal, case study, or deck with a prospect, and they engage with it, that is first-party intent data. You created the content. You shared it directly. The engagement happened on your tracked link. It's your data.
But it doesn't show up in your website analytics. The prospect never visited your website. They clicked a link in an email, viewed your content on a hosted page, and your document tracking tool captured the engagement. This data lives in a completely different system from your website analytics, marketing automation, or CRM — so nobody includes it in the "first-party intent data" conversation.
Why this data may be the highest-quality intent signal available
| Signal type | Level | Timing | Specificity | Example |
|---|---|---|---|---|
| Third-party (Bombora) | Account | Pre-outreach | Topic ("cloud security") | "Acme Corp is surging on your topic" |
| Second-party (G2) | Account | Pre-outreach | Category (your G2 profile) | "Acme Corp compared you to Competitor X" |
| First-party website | Individual | Pre/during outreach | Page-level (your pricing page) | "Sarah at Acme viewed your pricing page" |
| First-party shared content | Individual | Post-outreach | Page + time + forwarding | "Sarah spent 4 min on your ROI page, then forwarded the deck to 2 colleagues" |
The data supports this hierarchy. Qwilr analyzed over 1 million proposals and found that proposals viewed for more than 4 minutes had a 41% acceptance rate — compared to just 3.5% for proposals viewed less than 1 minute. That's an 11x difference based purely on engagement time.
When at least 2 additional unique users viewed a proposal within the first 5 days, the acceptance rate nearly doubled (Qwilr, 2025). Gong's analysis of 1.8 million opportunities found that closed-won deals have twice as many buyer contacts as lost deals, and multi-threading boosts win rates by 130% in deals over $50K.
Shared content engagement captures exactly these signals: who's engaged, how deeply, and whether the evaluation is expanding to new stakeholders.
Five buying signals your intent platform can't see
1. Per-page time analysis
Your prospect spent 30 seconds on your company overview but 4 minutes on the ROI calculator. That tells you more about their decision criteria than any discovery call note. When Proposify analyzed roughly a million proposals, they found winning proposals are viewed an average of 2.5 times — and 43% of won proposals close within 24 hours of opening.
The pattern of which pages get attention, not just whether the document was opened, is the signal.
2. Forwarding detection
Your contact shared the deck with two new people internally. One read the technical specs, the other read only pricing and timeline. You now know the evaluation has expanded beyond your single contact — and you know who's playing what role.
This is champion validation in its most direct form. You don't need to ask "who else is involved in this decision?" — you can see it.
3. Return visits
The prospect viewed your proposal on March 5. Went quiet for three weeks. Came back on March 28 without you sending a follow-up. Something changed internally — a budget conversation, a competitor demo that went badly, a new quarter.
A return visit is the strongest buying signal in long B2B sales cycles. No third-party intent platform can detect this kind of re-engagement because the behavior happens on your content, not on a publisher network.
4. Drop-off points
If every prospect drops off on page 7 of your 12-page deck, page 7 is killing your deal. That's content intelligence, not just intent — and it's feedback you can act on immediately by fixing the content.
Qwilr's data found that proposals with fewer than 6 content blocks had a 66% higher conversion rate than longer proposals. Shorter, more focused content doesn't just read better — it closes better.
5. Bot-filtered engagement
In enterprise sales teams, 15–40% of apparent document "views" come from email security scanners — Microsoft SafeLinks, Proofpoint, Mimecast, Google Safe Browsing. These scanners click links, load pages, and generate fake engagement data that inflates your analytics.
If your intent data includes bot traffic, your signals are contaminated. Third-party intent data aggregated across publisher networks has no way to filter this at the individual session level.
When to use which type
This isn't an either/or decision. Each type of intent data serves a different stage of the buying journey:
- Third-party intent: Top of funnel. Identify accounts you didn't know were researching your category. Feed into ABM campaigns and territory planning.
- Second-party intent: Mid-funnel. Validate that accounts are evaluating your specific category — especially useful when they compare you to competitors on review platforms.
- First-party website intent: Capture demand when prospects research on their own. Pricing page visits, feature page deep-dives, return visits.
- First-party shared content intent: Post-outreach deal intelligence. Understand engagement depth, stakeholder involvement, and buying timeline on active deals — the pipeline you're already working.
The critical gap: third-party intent tells you who to call. Shared content intent tells you when to call, what to say, and who else needs to be in the conversation.
How to start capturing shared content intent data
You don't need a $50K platform or a six-month implementation. The mechanics are straightforward:
1. Stop sending attachments. Every PDF attached to an email is a dead signal. Switch to tracked links — the recipient clicks, views in a browser, and you get per-page engagement data.
2. Track per-page engagement, not just opens. An "opened" notification tells you almost nothing. Per-page time data tells you what the buyer cares about, where they lose interest, and whether they read the sections that matter.
3. Set up real-time alerts on active deals. When a prospect you sent a proposal to two weeks ago re-opens it unprompted, that's a signal worth acting on within hours, not days.
4. Watch for multi-stakeholder expansion. When your document gets forwarded internally, the deal is progressing through the buyer's organization. New viewers from the same company domain — especially viewing different sections — means the evaluation has expanded.
5. Log engagement data alongside your CRM. Shared content intent data is most valuable when it sits next to your traditional pipeline data — close dates, deal stages, activity history. The engagement context makes every other signal more actionable.
Tools like HummingDeck capture this data automatically — per-page time tracking, forwarding detection, return visit alerts, and three-layer bot filtering — so every signal in your dashboard represents a real person engaging with your content.
The bottom line
The intent data market keeps growing because the underlying need is real: sales teams want to know who's interested and when to engage. But the current taxonomy has a blind spot. It defines first-party intent data as website behavior and ignores the engagement data from content you share directly with prospects — even though that data is individual-level, page-level, time-aware, and predicts deal outcomes with greater precision than any third-party signal.
Your proposals, decks, and case studies are already generating first-party intent data every time a prospect opens them. The question is whether you're capturing it.