Buyer intent is evidence that an account is researching, evaluating or preparing to buy a solution to a problem you solve. It shows up as behavior: visits to pricing and comparison pages, content downloads, review-site activity and third-party "topic surges". Intent tells you whether an account is looking, not why or when it will decide.
Teams that treat every surge as a trigger end up spending SDR time on accounts that were only curious. Intent gets more useful once it is paired with the business event behind it. Even then it raises the odds of a conversation; it does not promise a purchase or a date.
What are the types of buyer intent data?
| Type | Source | What it tells you | Typical weakness |
|---|---|---|---|
| First-party behavioral | Your site, product, emails | This account engaged with your content | Anonymous unless de-anonymized |
| Third-party topic intent | Data co-ops, publisher networks | Accounts consuming content on a topic | Same feed sold to everyone |
| Review and comparison activity | Review sites, comparison pages | Active, often late-stage evaluation | Competitors see it too |
| Declared intent | Forms, demo requests, replies | The account told you | Rare, and it comes late in the journey |
The buyer intent data guide covers how each type is collected and priced. Business events such as hiring, funding and leadership changes are not intent data in the vendor sense, but they explain why intent appears. They are covered in the buying signals pillar.
First-party vs third-party intent data: which matters more?
First-party intent data is behavior on properties you own. It is specific to you but covers only accounts that already found you. Third-party intent data is behavior observed across other publishers and aggregated by a vendor. It reaches accounts that have never heard of you, but it is broader, less specific and may be visible to competitors. Many teams start with first-party data, because it is free to collect and easier to trust, and add third-party data only after testing it against closed-won accounts. The buyer intent data guide has the full comparison.
Why is intent alone a weak predictor?
There are three reasons.
Intent is easy to share. Third-party feeds are built from publisher and data-co-op networks that can overlap, so a competitor who buys a comparable feed may see a similar surge at about the same time. If the feed is your only edge, you may not have one. What separates conversion from waste is how fast and how well you act on the surge.
Topic is not product. An account surging on "sales automation" might be evaluating a sequencer, hiring a RevOps lead, writing an internal memo, or being spammed by three vendors who triggered the surge themselves. Without the account context, the surge is uninterpretable.
Intent has no timing. A surge tells you the account is reading now. It does not tell you whether the budget cycle closed last week or whether the new leader who will make the decision has started yet. Timing comes from business events and their sequence, which is the subject of the revenue timing guide.
How is buyer intent scored, in short?
Scoring works when it combines behavioral evidence with causal evidence and lets both decay over time. Business events carry the most weight, first-party engagement comes next, and third-party intent is capped so it can lift a borderline account but never put an event-free account at the top. How to score buyer intent sets this out as a working rubric of 25 signals. A high score means an account deserves attention first; it is not a forecast of when, or whether, it will buy.
How do you use intent data?
The usual failure is a sequencer set to fire a generic email at every surging account, which produces the "Hi {FirstName}, I noticed you were researching…" email that buyers have learned to ignore. Using intent data well takes five steps:
- 01Attach the intent to an account and an event
Find the business event that explains the interest. If there isn't one, the account goes to a watch list, not a sequence.
- 02Identify who inside the account is likely behind it
A surge in a 200-person company often maps to a function. Map the buying committee for that function rather than emailing the CEO.
- 03Write to the event, not to the surge
For example, 'You've added four SDR roles since your new VP started' is a message about their situation. 'I saw you were researching sales tools' is a message about your data.
- 04Route by stakes
An economic buyer at a high-probability account gets a human thread. A technical evaluator at a mid-probability account gets a shorter drafted message that a person approves, with replies handed to a person.
- 05Measure reply rate by trigger, not by campaign
If intent-only triggers reply at a fraction of the rate of event-plus-intent triggers, the scoring model should be re-weighted.
How does PravRaha treat buyer intent?
PravRaha starts from business events at the account, not from intent data. We treat intent as a confirming signal at most, and it never triggers outreach on its own. The Messaging agent drafts against the business event, so the first sentence of the email references the event rather than the fact that the account was observed. The platform page describes how each agent uses signals.
Related guides on intent and timing
- →The business events behind intent: buying signals
- →Data types and vendors: buyer intent data
- →A scoring rubric: buyer intent signals and scoring
- →When to act: revenue timing
See how the loop runs inside PravRaha.
Signals, intelligence, prediction, timing, decision-makers and action, as one system rather than eight tools.