Why Traditional B2B Intent Data Is Too Late (and What to Do Instead)

Why most intent signals arrive late

Most "intent data" tools tell you who is already in-market. When teams rely only on website and G2 data, they chase buying intent after a shortlist is set and competitors are in the mix.

If you're leading Sales, Marketing, RevOps, or an early-stage SaaS, you've probably been pitched B2B intent data that fires on signals like:

• Users visiting your website or pricing page
• Prospects interacting with your LinkedIn posts
• Accounts researching you on G2 or review sites
• Buyers downloading your whitepapers, eBooks, or case studies

These are valuable, but they are late-stage intent signals. By the time they pop, the account-based sales team is competing for attention instead of shaping the problem.

The problem with late-stage B2B intent data

• Competitors see the same activity, so your outreach lands alongside theirs.
• The buying group often defined the problem alone, so conversations tilt to features and price.
• Reps fight to stand out in crowded inboxes instead of guiding the evaluation.
• Account-based marketing (ABM) stays reactive, and account-based sales loses the chance to influence requirements.

Traditional B2B intent data is necessary, but it is not enough to win the deal.

What early intent signals look like

Imagine spotting buying intent before someone types your name into Google. Early intent signals show where attention and budget are shifting:

• New priorities and investments highlighted in leadership interviews or board updates
• Hiring patterns that reveal strategy shifts in RevOps, data, customer success, or security
• Customer complaints that surface recurring pain in support communities and reviews
• Use cases and problems they suddenly discuss in blogs, resource centers, or LinkedIn posts
• Subtle changes on their website that hint at new ICPs, packaging, or product bets

These early intent signals give teams room to reach out first, shape the problem statement, and position as a trusted advisor.

How ConnectCurator.ai finds proactive intent data

Instead of waiting for clicks on your assets, ConnectCurator.ai looks outward to capture proactive intent data that maps to your offers.

• News and announcements: product launches, partnerships, funding, and market expansions.
• Hiring patterns: roles and departments being staffed that signal new priorities.
• Customer complaints and feedback: signals from users that expose gaps and friction.
• Owned content and messaging: themes across websites, case studies, and LinkedIn posts.

Each signal is evaluated against your solution so you get curated insights like "This target account is ramping up RevOps and data hires — prioritize a pipeline visibility play." Less noise, more context you can act on.

From raw signals to account-based plays

ConnectCurator.ai delivers early intent signals directly into the systems your teams already use.

• Slack: real-time alerts with why it matters and a suggested outreach angle.
• HubSpot: mapped fields, account timelines, and views to prioritize accounts showing movement.
• Account-based sales and marketing: ready-to-send messaging so reps can reach out before competitors.
• Customer success coverage: upsell and churn watchlists built from proactive intent data.

Your GTM motion shifts from reactive lead chasing to proactive, account-based engagement grounded in buying intent.

What this means for different leaders

Proactive intent beats reactive triggers

Most teams have some B2B intent data. The real edge comes from early intent signals that surface before prospects hit your site or G2 profile.

ConnectCurator.ai shows you which accounts are getting ready to move, why it matters, and how to engage with account-based sales and marketing plays.

Want to see this in action? Watch the demo or view pricing to start enriching accounts.