Rodok
Abderrazzak AbouyaalaIntent signals are clues that a company or a person is moving toward a purchase. There are three main kinds: intent data (anonymous research, usually company-level), buying signals (visible changes like a new leader or a hiring push) and trigger events (dated moments that open a window to sell). They differ in who you see and what they cost.
The words get used interchangeably, which is why teams end up paying for the wrong thing. This guide separates them, explains first-party vs third-party intent, and gives a plain answer on when each is worth the money.
What are intent signals?
An intent signal is any evidence that a buyer is closer to a decision than they were last month. You'll also see them called buyer intent signals or buying intent signals; they mean the same thing. In B2B, that evidence comes from three places:
- Your own channels: someone visits your pricing page, replies to an email, uses a feature in a trial.
- Other companies' channels: a company's employees read a lot about a topic across publisher websites.
- Public changes: a new VP of Sales starts, a team posts four job openings, a founder asks LinkedIn for tool recommendations.
All three are "intent" in the loose sense. But they answer different questions. The first tells you who's already looking at you. The second tells you which accounts might be researching your category. The third tells you who has a fresh reason to buy, and usually who to talk to.
Intent data vs buying signals vs trigger events
| Intent data | Buying signals | Trigger events | |
|---|---|---|---|
| What it is | Research activity on a topic, often across many websites | Any observable change that makes a purchase more likely | A specific dated event that opens a selling window |
| Example | "Acme is reading more than usual about sales engagement software" | A new Head of Sales, hiring SDRs, a post about a broken process | Funding closed on March 3, a CRO started on Monday |
| Level | Usually the company | Company and person | Company and person |
| Do you know who? | Usually not the individual | Often yes | Often yes |
| Do you know why? | A topic, not a reason | Yes, the change itself | Yes, the event itself |
| Typical source | Data co-ops, publishers, review sites, your website | LinkedIn, job posts, news, your CRM | News, LinkedIn, filings, press releases |
| Typical cost | Paid, often bundled into larger platforms | Free by hand, or a signal tool | Free by hand, or a signal tool |
In practice, trigger events are a subset of buying signals: the ones with a clear date. "Started as VP Sales on October 6" is a trigger. "Has been posting about pipeline problems" is a buying signal without a single date. For a long list of triggers, see our guide to sales trigger events.
Intent data is the odd one out. It measures research, not change, and it typically stops at the account.
First-party vs third-party intent signals
The other way to split intent signals is by who collects them.
| First-party intent | Third-party intent | |
|---|---|---|
| Collected by | You | A data provider |
| Examples | Pricing page visits, demo requests, trial usage, email replies, webinar attendance | Topic research across a network of B2B sites |
| Who it covers | People and companies already in contact with you | Companies that may not know you exist |
| Accuracy | High: it happened on your own channels | Varies: modeled from activity elsewhere |
| Cost | Mostly what you already pay for (analytics, CRM, product data) | A paid data contract or a platform that bundles it |
There's also second-party intent: a partner's first-party data, shared or sold. Review sites and publishers sometimes offer data on which companies researched a category on their site.
How third-party intent data works
The best-known example is Bombora. It describes its Company Surge data as a way to find "in-market accounts", based on research activity across B2B websites that share data through its data co-op. The output is a list of companies showing more interest than usual in topics you choose.
That's useful for prioritizing a large account list, and it's why intent data shows up inside bigger platforms: Common Room's plans, for example, include a number of Bombora Company Surge topics (checked on November 1, 2026).
The limits are worth knowing before you buy:
- It's account-level. You learn that a company is researching, not which person.
- It's a topic, not a reason. "Researching CRM software" could be a buyer, a student, an analyst or a vendor writing a blog post.
- It's invisible to the prospect. You can't open with it. "Our data shows your company is researching CRMs" is not a message anyone wants to receive.
B2B intent signals worth tracking
Here are the buyer intent signals most B2B teams can act on, grouped by source.
First-party (yours):
- Demo or pricing requests, and pricing page visits from known contacts
- Trial or freemium usage that crosses a meaningful threshold
- Replies to outreach, even "not now"
- Several people from the same company engaging with your content
Public (on LinkedIn and the web):
- A new leader in the role you sell to, especially in the first 90 days
- A past champion or customer joining a new company
- Hiring for a team you sell to, or for the job your product does
- A post asking for recommendations or describing the problem you solve
- Expansion into a new market, a new office or a new site
- A funding round or a public growth plan
Third-party (bought):
- Topic surges at target accounts
- Category research on review sites
For a ranked version of the LinkedIn ones, see LinkedIn buying signals ranked by intent.
When each kind is worth paying for
This is where most teams go wrong: they buy the most expensive kind of intent first.
| Kind | Worth paying for when | Not worth it when |
|---|---|---|
| First-party intent | Always. Make sure your CRM records demo requests, replies and key product events | Never skip it; it's mostly setup, not spend |
| Public buying signals | You sell outbound, need a named person and a reason to write, and have a small team | Your market is tiny and you already know every account personally |
| Third-party intent data | You work a large, defined account list, run account-based ads, and have marketing and sales to act on account-level scores | You're a small team without the capacity to research every surging account for the right person |
A rough way to decide:
- Start with first-party. If you can't see who replied, booked or used the product last week, fix that first. It's the cheapest and most accurate intent you'll ever have.
- Add public buying signals if outbound matters to you. They give you a person, a reason and a first line. That's what a small team needs.
- Consider third-party intent when you have more target accounts than you can work, and a team that can turn "this account is surging on a topic" into the right contact and a credible reason.
How to combine intent signals
The strongest accounts show more than one kind of signal at once. A practical way to stack them:
- Public signal + fit: a new Head of Sales at a 50 to 200 person SaaS company in your market. Write this week.
- Public signal + first-party: that same company's new leader also opened your last email. Call or send a short follow-up.
- Third-party + public: an account surging on your topic also just posted three SDR openings. Now you have a reason and a likely buyer: the sales leader building that team.
Each layer narrows the list and makes the message easier to write. One strong signal on a good-fit account beats five weak ones on a poor fit.
Mistakes teams make with intent
- Buying intent data before fixing first-party data. The demo requests nobody followed up on are worth more than any topic score.
- Opening with the data. Never tell a prospect what your tool says about their research. Lead with the public reason or the problem.
- Treating a topic surge as a lead. It's a prompt to look closer, not a contact to sequence.
- Ignoring freshness. A buying signal from four months ago is background. Most are worth acting on in days or weeks.
- Not measuring by signal. Track meetings by signal type, then put money behind what converts. For the full picture of the approach, see our guide to buying signals.
Frequently asked questions
What are intent signals?
Intent signals are evidence that a company or person is moving toward a purchase. They include first-party signals from your own channels (demo requests, replies, product usage), public buying signals (job changes, hiring, posts) and third-party intent data (topic research across other websites).
What's the difference between intent data and buying signals?
Intent data usually means anonymous research activity, measured at the company level across a network of websites. Buying signals are observable changes, like a new leader or a hiring push, that are often public and tied to a specific person. Intent data tells you a company may be researching; a buying signal tells you why someone might buy now.
What are first-party intent signals?
They're signals you collect on your own channels: website and pricing page visits from known contacts, demo requests, trial usage, email replies and webinar attendance. They're usually the most accurate intent you have because they happened with you.
Is third-party intent data worth it for a small team?
Often not at first. It's account-level, so someone still has to find the right person and a reason to write. Small teams usually get more from first-party signals and public buying signals, then add third-party intent once they have more target accounts than they can work.
Does Rodok provide intent data?
No. Rodok doesn't sell third-party intent data from data co-ops or publisher networks. It tracks public LinkedIn signals you describe, such as new leaders, hiring, expansion and posts about a problem, and helps you find the person to contact and write the first message.
