Buying signals and intent data: a practical guide to signal-based selling

A buying signal is any evidence that a person or company is more likely to buy now than they were last month. This guide explains the main types of buying signals and buyer intent data, gives concrete examples, and shows how to turn them into outbound that feels timely instead of random.

What is a buying signal?

A buying signal is an observable action or event that raises the probability someone will buy. In a live sales conversation, signals are things like a prospect asking about pricing, implementation timelines or contract terms. In outbound, signals happen before any conversation: a VP engages with a competitor's post, a company starts hiring for the function you serve, or a champion from a past customer joins a new company.

Signals do not prove intent. They change the odds and, just as importantly, they give you a genuine reason to reach out. "I noticed you just took over the RevOps team" is a far better opening than "I hope this finds you well".

What is buyer intent data?

Buyer intent data is the collected record of these signals, usually scored and attached to accounts or people. It comes in three broad kinds.

Type	Where it comes from	Examples
First-party	Your own properties	Website and pricing-page visits, product sign-ups, email clicks, people engaging with your own LinkedIn posts
Platform	A platform you use surfaces it	LinkedIn Sales Navigator Buyer Intent and company-page visitor filters, review-site category activity
Third-party	Aggregated from across the web	Topic research across publisher networks, technology changes, hiring and funding data

There is also a difference in grain. Account-level intent says "someone at Acme is researching this topic". Person-level signals say "Priya, Head of RevOps at Acme, commented on a post about this problem yesterday". Person-level signals are far more useful for outbound, because you know who to talk to and what to talk about.

Buying signal examples

Engagement signals

• Following a competitor's LinkedIn company page.
• Liking or commenting on posts about the problem you solve, or on your competitors' posts.
• Engaging with your own company's or your founder's content.
• Registering for a webinar or attending an event in your category.

Change signals (trigger events)

• A new leader joins in the function you sell to. New leaders often review tools and processes in their first months.
• A past champion or power user moves to a new company.
• The company raises funding or announces expansion into a new market.
• Job postings mention the problem you solve or the tools you replace.
• A merger, acquisition or reorganisation reshapes the team you sell to.

Research signals

• Repeat visits to your pricing or comparison pages.
• Visits to review sites or comparison content in your category.
• Searches for alternatives to a competitor. This is why honest alternatives pages are worth writing.

Activity signals

• The most active people in your ICP on LinkedIn, who post and comment often, are easier to start a conversation with than people who never log in.
• Lookalikes of your best customers: people in similar roles at similar companies to the accounts that already love you.

Which signals matter most?

Rank every signal on three questions:

1. Is it person-level? You need to know who to talk to.
2. Is it recent? Days, not months.
3. Is it about my problem specifically? Engaging with a post about your exact problem beats a broad topic surge.

A comment on a competitor's product post yesterday scores high on all three. A company-level topic surge from last month scores low on two.

Stacking matters too. One signal is a hint. Two or three on the same person or account is a priority: an ICP-fit VP who follows two of your competitors and just started a new role should be at the top of your list.

Signal-based selling, step by step

Signal-based selling is an outbound approach that starts from evidence of interest or change and only then decides who to contact. Here is how to run it.

1. Pick three to five signals that predict buying for you. Look at your last twenty closed deals. What was happening at those companies, and to those people, just before they bought?
2. Set up capture. Use a signal tool for LinkedIn and change signals, and your own analytics for first-party signals.
3. Filter to your ICP. A signal from someone outside your ICP is noise, no matter how strong it looks.
4. Reach out within days. Signals decay quickly.
5. Lead with the signal, lightly. Reference what they engaged with or what changed, then offer something useful. Do not recite their activity back to them.
6. Measure by signal type. Track acceptance, reply and positive-reply rates per signal and stop using the ones that do not convert.

Writing messages from signals

Signal	Weak opener	Better opener
Commented on a post about SDR ramp time	"I see you're interested in sales!"	"Your point about ramp time on [author]'s post matched what we hear from most RevOps leads. Curious how you're handling it."
New VP of Sales	"Congrats on the new role!"	"First 90 days in a new sales org usually means a stack review. Happy to share what others in your seat changed first."
Follows two competitors	"I noticed you follow [competitor]"	"Looks like you're evaluating tools in [category]. Here's a short, honest comparison of the trade-offs."

The better openers are specific, useful and do not make the prospect feel watched.

How GTM Plays uses buying signals

GTM Plays is an AI outbound agent built around signals. It finds people showing intent, scores each one for fit against your ICP, writes a LinkedIn message for each prospect that references the signal that surfaced them, and sends it from your own LinkedIn account. Replies come back into one inbox, and the conversation is yours from there. Pro is $149 a month after a 7-day free trial.

Buyer intent in LinkedIn Sales Navigator

According to LinkedIn's Sales Navigator page, Sales Navigator includes 50+ search filters and lead and account alerts. Its Advanced and Advanced Plus plans add Buyer Intent signals and a "Who viewed my company page" filter. These are useful for research and prioritisation. They live inside Sales Navigator, however, and LinkedIn restricts exporting data from it, so many teams pair Sales Navigator with a separate signal and outreach tool, or look at Sales Navigator alternatives.

Intent data providers and tools

The market splits into four groups. Vendor descriptions are from each vendor's site, checked in October 2026.

• Website visitor identification: RB2B (person-level identification for US traffic) and Leadfeeder by Dealfront (EU-built, with 40+ buying signals).
• Signal aggregation platforms: Common Room ("buyer intelligence" across many sources) and UserGems (30+ contact-level signals, including job changes).
• Contact databases with signals: Apollo and Lusha, which both advertise buying signals alongside their contact data.
• LinkedIn-native signal and outreach tools: AI agents such as GTM Plays, which turn LinkedIn signals into outreach.

Teams that relied on Trigify should note that its standalone platform has been retired after the team joined HubSpot; our Trigify alternatives page covers the options.

Privacy and ethics

Use public, professional signals. Respect opt-outs immediately. Comply with the data-protection law that applies to you and to the people you contact, such as the GDPR for people in the EU and UK. Never pretend a signal is a coincidence, and never reference something a prospect would reasonably expect to be private. Done well, signal-based outreach feels like good timing. Done badly, it feels like being watched.