Buyer intent data vs public buying signals: what a small team can actually use

Buyer intent data is information that suggests a company is researching a problem or a type of product. You'll see it sold as "surging accounts", "in-market companies" or "intent scores". It promises to tell you who is looking before they contact anyone. That's a real need, but the data has limits that matter a lot more for a small team than for a large one.

The three kinds of intent data

First-party intent is the most accurate, because it's about you, but it only covers people who already found you. Third-party intent covers everyone, but it's indirect: it tells you a company's readers spent more time on a topic, usually without saying who or why. Review-site intent sits in between.

Where intent data falls short

• It's usually company-level. You learn that "someone at Acme" is researching, not who. You still have to guess the person.
• It's hard to quote. You can't write "I see your team has been reading about lead scoring". It's unsettling to the reader and you can't show where it came from.
• It's noisy for small companies. A 30-person company produces very little reading activity, so the accounts that "surge" tend to be large ones.
• It's priced for larger teams. Most providers sell annual contracts sized for sales teams with many reps.
• It decays fast and shows no date. A score tells you something changed recently, but not exactly what or when.

Public buying signals: the alternative you can check

A public buying signal is an event anyone can see and you can link to: a job posting, a new leader announced on LinkedIn, a funding round, a launch, someone asking for help in a community. They aren't a secret dataset, which is exactly why they're useful in a message: you can say what you saw.

The catch with public signals is checking them. In our own runs, only 8 of 58 job postings found through web search were still open and under 45 days old. A public signal is only as good as the check behind it.

When intent data is worth paying for

• You sell to large companies, where reading activity is big enough to be meaningful.
• You have a long list of named target accounts and need to decide which to work this quarter.
• You have a team of reps who need routing, and marketing that can run ads to surging accounts.

If you're a founder or a small team selling to small and mid-sized companies, it's usually better to start with first-party signals (who visits your site and replies) plus public signals you can check yourself.

A simple setup for a small team

• Your own signals: pricing-page visits, trial sign-ups and replies. Follow up on these the same day.
• Three public signals: pick the three from these 20 buying signals that fit your product best, and check them weekly.
• One process: find, check, contact within days, follow up, and count replies by signal. That's signal-based selling.

Audyense is built for the public-signal half. It looks for job postings that match your product and people asking for help in public, checks each one is real and recent, and attaches the date and source to every prospect so you can quote it.