Intent Data
Intent data refers to behavioral signals that indicate a prospect’s likelihood of purchasing a product or service. These signals come from content consumption, search activity, technology adoption patterns, and engagement across digital properties. Marketers use intent data to prioritize accounts, personalize outreach, and time their campaigns to match buyer readiness.
What is Intent Data?
Intent data captures the digital footprints that buyers leave as they research solutions. When a company’s employees repeatedly visit pages about CRM software, download comparison guides, or attend related webinars, those actions generate intent signals. Aggregated together, these signals suggest the company is actively evaluating options in that category.
There are three primary types. First-party intent data comes from a brand’s own properties: website visits, form fills, content downloads, and product usage patterns. Second-party intent data is another organization’s first-party data, shared through a partnership or data cooperative. Third-party intent data is collected across thousands of websites by vendors like Bombora, G2, and TrustRadius, then sold to marketers who want visibility into accounts they don’t yet touch.
The core formula for prioritizing accounts with intent data is straightforward:
Intent Score = (Topic Relevance x Signal Strength x Recency) / Baseline Activity
Topic relevance measures how closely the consumed content matches the seller’s category. Signal strength reflects volume and depth of engagement. Recency weights recent activity higher than older behavior. Baseline activity normalizes for companies that consume large volumes of content regardless of purchase intent.
Intent Data in Practice
Bombora processes content consumption signals from over 5,000 B2B websites through its Data Co-op, covering more than 12,000 intent topics. Enterprise buyers use these signals to identify which accounts are surging on topics relevant to their solutions, often weeks before those accounts fill out a form.
6sense combines intent data with predictive analytics to assign buying stage labels to accounts. According to 6sense’s own benchmark data, companies using their platform saw a 2x increase in pipeline conversion rates and a 35% reduction in deal cycle length by focusing on accounts showing active research behavior.
G2 captures buyer intent from over 80 million annual visitors to its software review platform. When a prospect compares products in a category, views pricing pages, or reads reviews, G2 packages those signals and delivers them to vendors in near real-time. Vendors on G2’s platform report identifying 2.5x more qualified accounts than through inbound alone.
ZoomInfo integrates intent data into its sales intelligence platform by combining Bombora’s Co-op data with its own first-party signals from over 150 million professional contacts. Their customers use intent-triggered workflows to automate outreach when target accounts begin researching relevant topics.
Why Intent Data Matters for Marketers
Most B2B buying journeys are 70% complete before a prospect contacts a vendor. Intent data closes that visibility gap by surfacing accounts early in their research phase. This allows marketing teams to allocate budget toward accounts with genuine purchase interest rather than spraying campaigns across an entire addressable market.
For account-based marketing programs, intent data acts as the prioritization layer. Instead of treating all target accounts equally, marketers can tier their efforts based on which accounts are actively in-market. This improves both conversion rates and cost efficiency.
The shift toward cookieless tracking makes intent data more valuable. As third-party cookies disappear, intent data from content consumption and review platforms provides an alternative signal source that doesn’t rely on individual user tracking.
Related Terms
FAQ
What is the difference between intent data and engagement data?
Engagement data measures how a known contact interacts with a brand’s own content (email opens, webinar attendance, page views on owned properties). Intent data is broader. It captures research activity across the open web, often from anonymous visitors and accounts that have never interacted with the brand directly. Engagement data tells a marketer what known leads are doing. Intent data reveals what unknown accounts are researching.
How accurate is third-party intent data?
Accuracy depends on the vendor’s data collection methodology and the size of their content network. Industry benchmarks from Demand Gen Report suggest that 62% of B2B marketers using third-party intent data rate its accuracy as “good” or “excellent” for account-level targeting. Accuracy drops significantly at the individual contact level, which is why most vendors sell intent data as account-level signals rather than person-level data.
Intent data vs. lead scoring: which should marketers use?
They serve different purposes and work best together. Lead scoring evaluates individual contacts based on demographic fit and behavioral engagement with a brand’s own properties. Intent data evaluates accounts based on research behavior across external sources. Combining both creates a model where marketers can identify in-market accounts (intent) and then prioritize the best-fit contacts within those accounts (lead scoring).
How quickly does intent data go stale?
Most intent data providers recommend acting on signals within 7 to 14 days. Research from Bombora shows that the correlation between intent signal spikes and actual purchase behavior drops by roughly 50% after three weeks. Marketers who build automated workflows triggered by real-time intent signals consistently outperform those who review intent reports on a weekly or monthly basis.