Should Outbound Run on Intent Data or Hiring Signals?

Should your outbound run on intent data or hiring signals?

For most small B2B teams, hiring signals are the better first trigger, and intent data is the better second one. A job post is public, specific, and easy to verify. Intent data is broader and noisier, but it catches research activity that never shows up as a job listing. The right choice depends on what your product fixes.

I get this question from founders who have just set up a tool like Clay or Apollo and are staring at a menu of signals. Every vendor promises that its signal is the one that predicts a deal. The honest answer is that no signal predicts a deal on its own. A signal only tells you when to look closer.

So the real decision is not which signal is best. It is which signal is closest to the moment your buyer starts feeling the problem you solve.

What is the difference between intent data and a hiring signal?

Intent data is an inference that a company is researching a topic, usually built from content consumption, review site activity, or visits to your own site. A hiring signal is a public fact: a company posted a job for a role connected to your product. One is a probability. The other is an event you can read yourself.

Third-party intent providers such as Bombora build topic-level signals from activity across many publisher sites. Review platforms like G2 can show which companies are looking at your category. Platforms like 6sense combine several sources into account-level scores. How each provider collects and models its data differs, so read each vendor's own documentation before you trust a score.

Hiring signals are simpler. A company posts a role for a RevOps manager, a first SDR, or a head of demand generation. You can see the listing on their careers page, on a board powered by Greenhouse or Lever, or on LinkedIn. Nobody had to model anything. The company told the world what it plans to spend money on.

Why do hiring signals work so well for small teams?

Hiring signals work because they are cheap to verify and easy to write about. A rep can open the job post, read the responsibilities, and reference a real detail in the first line of an email. That specificity earns replies. Intent scores rarely give a rep anything concrete to say without sounding like they are watching.

There is also a timing logic. When a company hires for a role, it has already decided the problem matters enough to pay a salary for it. If your product makes that new hire faster or more effective, you are arriving at the moment budget and attention are both pointed at your category.

The weakness is coverage. Plenty of companies feel your problem and never post a job about it. If you only listen to hiring signals, you miss the buyers who are trying to solve the problem with software instead of headcount. That is exactly where intent data earns its place.

When does intent data beat a job post?

Intent data wins when your product replaces a hire rather than supporting one, and when the buying research happens long before anyone posts a role. If a buyer is comparing tools in your category on review sites, that activity can show up as intent weeks before a sales conversation, with no job post ever appearing.

It also wins for products bought by a function that rarely hires. A three-person finance team evaluating spend software may never post a role. Their research, though, can leave a trail on review platforms and in your own site analytics.

The cost is noise. Topic-level intent can fire because a student wrote a paper, a competitor did research, or one curious employee read three articles. I wrote about how I score intent signals from G2 and website visits because raw intent, unscored, will flood a small team with accounts that were never going to buy.

How do you decide which signal fits your product?

Ask one question: when your best customers started looking for a solution, what did they do first? If they hired someone, lead with hiring signals. If they researched tools, lead with intent. Your closed-won deals hold the answer, so read the last ten before buying any data.

I do this exercise with every client before I touch a sequence. I pull recent closed-won accounts from HubSpot or Salesforce and ask what was true about each company in the ninety days before the first meeting. Did they post a related role? Did they raise money? Did they show up on a review site? Patterns appear fast, even with a small sample.

If the pattern is mixed, that is still useful. It tells you to run both signals, but to treat them as separate plays with separate messaging rather than blending them into one score.

Should you combine intent data and hiring signals into one score?

Not at first. A blended score hides which signal actually produced the meeting, so you cannot learn from it. Run each signal as its own play, with its own list, its own message, and its own reporting. Once you know what each one converts at, combining them becomes a decision based on evidence instead of hope.

The temptation to combine comes from tools. Many platforms make it easy to stack signals into one number, and a single number feels clean. But if an account scores high because of three weak signals, you have built a confident-looking guess. A rep cannot write a good email from a number.

When you do combine later, keep the reasons visible. The account record should say which signals fired and when, so the rep knows whether to reference a job post, a funding round, or category research. The score decides priority. The reasons decide the message.

How do you write outbound that references each signal without sounding creepy?

Reference public facts directly and private inferences never. A job post is public, so mentioning it is normal. An intent score is an inference about someone's browsing, so mentioning it feels like surveillance. With intent, write about the problem the research suggests, not the research itself, and let the buyer connect the dots.

For a hiring signal, the first line can be plain: you saw they are hiring a first SDR, and teams at that stage usually hit a specific problem in the first quarter. That is relevant and respectful. It shows you did your homework without pretending to know their internal plans.

For intent, I write to the category pain instead. Something like noting that teams evaluating their reporting stack often run into a particular gap, and offering a short way to check for it. No mention of tracking. The signal earns the timing. The message earns the reply.

What does a simple signal stack look like for a two-person sales team?

Keep it to two plays. One hiring-signal play built on roles connected to your product, refreshed weekly. One intent play built on your own site visits and one review platform, scored before anyone reaches out. Route both into your CRM with the reason attached. Anything more is overhead a small team cannot maintain.

For the hiring play, I would set up a weekly pull of job posts that match a short list of titles, filter by your firmographic fit, and push qualified accounts into HubSpot with the job post link on the record. Tools like Clay and Apollo are where teams usually assemble this, though what each covers changes, so check their current docs.

For the intent play, start with first-party data you already own. Website visits to your pricing or comparison pages are higher quality than third-party topic intent because the buyer was on your site. Add a review platform signal if your category is active there. Skip the expensive third-party feed until the first two plays are working.

And remember that some signals look strong and mean little. I keep a running list of buying signals that turn out to be noise, and it grows every quarter.

How do you measure which signal is actually working?

Measure meetings and pipeline by signal source, not opens or replies. Tag every outbound account with the signal that triggered it, then report meetings booked and opportunities created for each tag. After a quarter, you will know which signal deserves more budget. Without the tag, every signal looks equally good in a vendor demo.

The tag needs to live on the contact or company record in your CRM, set at the moment the account enters a sequence. If it is set later, people guess, and guesses drift toward whatever signal the team likes. A required property set by the automation that enrolls the account removes the guessing.

Then give each signal a fair window. Hiring signals often convert faster because the need is immediate. Intent signals can take longer because the buyer is earlier in research. If you judge both on the same thirty-day window, you will undervalue the slower one.

What should you do next?

Read your last ten closed-won deals and write down what happened at each company before the first meeting. That list tells you which signal to lead with. Then build one play around it, tag every account with its trigger, and only add the second signal once the first one is producing meetings.

If funding news is one of the patterns you find, my notes on timing outbound after a funding announcement cover that play in detail. It pairs well with hiring signals, since new money and new roles usually arrive together.

If you want help choosing signals for your market or wiring them into your CRM so the reasons travel with every account, reach out. I build these systems for B2B teams, and I am happy to talk through what your closed-won data is telling you.