Intent Data Buying Guide for GTM Engineers
Intent data promises to tell you which accounts are in-market before they raise their hand. Some vendors deliver on that promise. Most don't. This guide separates signal from noise.
What Intent Data Measures
Intent data tracks digital research behavior across the B2B web. When someone at a target company reads three articles about CRM migration, downloads a vendor comparison PDF, and visits G2's CRM category page, that cluster of activity generates an intent signal. The theory: companies actively researching a topic are more likely to buy a solution in that category.
Three types of digital behavior generate intent signals. Content consumption covers articles, whitepapers, and video views across publisher networks. Web research spikes track when a company's search volume for specific topics jumps above their baseline. Review site activity captures product page visits, comparison views, and profile interactions on sites like G2 and TrustRadius.
The critical distinction: intent data tells you a company is researching a topic, not that they're ready to buy. A company spiking on "CRM migration" might be starting a 12-month evaluation, or an intern might be writing a blog post. The signal is directional, not deterministic. GTM Engineers who treat intent as a prioritization input (not a trigger for immediate outbound) get better results.
First-Party vs Third-Party Intent
First-party intent comes from your own properties: website visits, content downloads, product trials, pricing page views. You control the data quality. You know exactly what pages were visited and for how long. The limitation is volume. Your website captures intent from prospects who already know you exist, which skews toward later-stage buyers.
Third-party intent comes from external content networks, publisher co-ops, and review platforms. Bombora's Data Co-op aggregates consumption data from 5,000+ B2B websites. 6sense combines third-party signals with AI predictions to identify accounts showing research behavior across the web. The advantage: you catch buyer research activity before they ever visit your site.
The tradeoff is transparency. Third-party intent providers rarely disclose exactly which websites generated a signal. You're trusting their data co-op methodology and matching algorithms. Some vendors match IP addresses to companies (which breaks down with remote work). Others use cookie-based tracking (which is eroding). The best use both methods and layer in additional signals like hiring patterns and technographic changes.
For most GTM Engineering teams, the right approach combines both. Use first-party intent (website visitor identification via Clearbit Reveal, HubSpot tracking, or similar) as your highest-confidence signal. Layer third-party intent on top to expand your view of in-market accounts you haven't reached yet.
Vendor Comparison
Four vendors dominate the B2B intent data market. Each has a different data methodology, coverage footprint, and integration approach.
6sense Surge Data. 6sense combines third-party content consumption signals with proprietary AI models that predict buying stage. Their "Revenue AI" platform assigns accounts to buying stages (awareness, consideration, decision, purchase) based on signal patterns. Strongest for enterprise accounts with 500+ employees. Pricing starts around $60K/year for the platform, with intent data as a core module. Best integration path: direct CRM sync with stage-based alerts. The AI predictions add genuine value when you have enough historical data to train the model. For smaller companies with thin CRM history, the predictions are less reliable.
Bombora Company Surge. Bombora operates the largest B2B intent data co-op, aggregating content consumption from 5,000+ publisher websites. Their "Company Surge" score measures when a company's research volume on a topic exceeds their normal baseline. Strongest for topic-level intent across broad market segments. Pricing runs $24K-$72K/year depending on topic count and account volume. Best integration path: Bombora feeds into most major platforms (6sense, Demandbase, HubSpot, Salesforce) as a data layer. The pure data approach (no AI predictions) means you control the interpretation, which GTM Engineers often prefer.
G2 Buyer Intent. G2 captures intent from its 80M+ annual software review visitors. When someone from a target account views product profiles, reads reviews, or compares vendors on G2, that activity generates an intent signal. The signal quality is high because G2 visitors have strong purchase intent by definition. Pricing is bundled with G2 marketing solutions (typically $30K-$60K/year). Best integration path: webhook alerts to Slack or CRM. The limitation: coverage is narrow. G2 only captures intent for companies evaluating software categories listed on their platform.
TrustRadius Buyer Intent. Similar model to G2 but with deeper enterprise buyer coverage. TrustRadius intent signals come from product research, review reading, and comparison activity on their platform. Their buyer intent data integrates with most marketing automation platforms. Pricing is comparable to G2. The differentiator: TrustRadius skews toward larger enterprise buyers, so if your target market is mid-market to enterprise, their signal coverage may be stronger than G2's.
Integration Patterns
Raw intent data is useless sitting in a dashboard. The value comes from routing signals into systems where they trigger action.
CRM enrichment. The baseline integration: push intent scores as account-level fields in your CRM. Add a "Surge Score" or "Intent Level" field to the Account object in HubSpot or Salesforce. Update it daily via API sync. Sales reps see intent context alongside their existing account data. This is table-stakes. Every vendor supports it.
Lead scoring models. Intent signals become scoring inputs. An account showing surge behavior on your target topic gets +20 points. An account on G2 comparing you to a competitor gets +30. Layer these signals with first-party engagement (email opens, website visits) and firmographic fit (right industry, right size) for a composite score. The tools index covers scoring platforms in detail.
Trigger-based outbound. The highest-impact pattern: use intent spikes to trigger automated outbound sequences. When Bombora flags a surge on "data enrichment" for a target account, automatically enroll that account's decision-makers in a personalized outbound sequence via your sequencing tool. The message references their likely research area without being creepy about it. "We work with companies evaluating their enrichment stack" works. "We noticed you read three articles about data enrichment this week" does not.
ABM campaign targeting. Feed intent-qualified account lists to LinkedIn Ads, Google Ads, or programmatic display campaigns. Show ads to companies actively researching your category. This reduces wasted ad spend by focusing budget on accounts that are in-market rather than spraying across your entire TAM.
Pricing and ROI Calculation
Intent data platforms fall into three pricing tiers.
Entry tier ($24K-$40K/year): Bombora standalone data feed, G2 intent basics, TrustRadius intent. You get the raw signals and basic integrations. No AI predictions, no orchestration layer. Good for teams that have their own scoring infrastructure and just need the data.
Mid tier ($40K-$80K/year): Bombora with expanded topics, G2 with marketing solutions, 6sense essentials. Includes some automation, better reporting, and more integration options. This is where most mid-market B2B companies start.
Enterprise tier ($80K-$120K+/year): 6sense Revenue AI full platform, Demandbase One, combined multi-source intent with orchestration. AI-driven predictions, automated campaign triggers, full-stack ABM capabilities. Worth it only if you have the sales volume and ACV to justify the spend.
ROI math: If your average deal size is $50K ARR and intent data helps you close 2 additional deals per quarter, that's $400K in annual revenue lift against $24K-$120K in platform cost. The math works for companies with $30K+ ACV. Below that, the platform cost often exceeds the incremental revenue, especially in the first year while you're calibrating signal quality.
When Intent Data Is Worth It vs When It's Noise
Intent data works when: You sell to a defined market with $30K+ ACV. Your sales cycle is 60+ days (enough time for research behavior to surface). You have the infrastructure to act on signals within 48 hours. You're running outbound at scale (1,000+ accounts) and need a prioritization layer.
Intent data is noise when: Your ACV is under $10K (the math doesn't close). Your market is too niche for intent co-ops to have meaningful coverage. You can't act on signals quickly (if it takes your team two weeks to follow up on a surge alert, the signal has decayed). Your total addressable account list is under 500 (at that size, just work the whole list).
The honest assessment: most B2B companies that buy intent data underuse it. They get the dashboard, check it occasionally, and never build the automation infrastructure to turn signals into action. If you're going to invest in intent data, commit engineering resources to building the integration layer. Otherwise, you're paying for a reporting tool.
Start with a 90-day pilot on one intent source. Measure signal-to-meeting conversion rate against your baseline outbound. If intent-flagged accounts convert at 2x+ your cold outbound rate, expand. If they don't, the data isn't matching your market well enough to justify the spend.
Source: State of GTM Engineering Report 2026 (n=228). Salary data combines survey responses from 228 GTM Engineers across 32 countries with analysis of 3,342 job postings.