We measured which companies actually give off buying signals. Under 50 employees, it's mostly silence
Building a signal monitoring product forces you to confront an uncomfortable question. Do small companies emit enough public signals to be worth watching at all?
We ran the measurement on our own production data in August. Companies under 50 people were silent about 96 percent of the time over a 90 day window. Then we probed the silent cohort externally, checking careers pages directly, and found the silence was mostly real, not a gap in our detection. Small companies hire through their network and skip public postings.
So the honest answer shaped the product and the content. Hiring signals work best from roughly 50 employees up. Below that, a posting that does appear is rare and therefore strong.
The flip side is that when companies do post, the posting is remarkably honest. It names the tools they've committed to, the team that's growing, and the problem in their own words. There's a Management Science study showing posting changes predict future revenue growth, which was fun to find because it matches what we see daily.
Full breakdown of how to read postings here https://leadalise.com/blog/hiring-signals-job-postings
Curious how others handle this. If you sell to small companies, what do you actually watch, given that public signals mostly aren't there?
This matches what we see at SocialPost.ai selling to sub-50-person companies: they don't run a posting cadence, they don't publish a hiring page, nothing shows up in a signal tool. The earliest honest tell for that segment is usually the founder's own LinkedIn behavior, a CEO who suddenly posts more often, or a new hire's "started a new position" update, tells you more than any job board scrape will.
Founder posting behaviour as the earliest honest sign matches what I see too.
The uncomfortable part is that it sits on a person rather than on a company,
and I do not want to build monitoring around someone's personal profile. So I
stay with what a company publishes about itself and accept that the small end
is out of reach. Narrower product, easier one to defend.
The silence under 50 employees isn't failure, it's honest measurement. Most measurement systems treat absence of signal as zero value, but you're measuring what actually happened - and being willing to report null results is exactly what separates this from typical sales measurement theater. The real signal here: small companies don't broadcast buying intent because they can't afford the noise. Your 50-person cutoff is the inflection point where operations departments formalize procurement, not where intent suddenly exists. That's a constraint-driven insight. The founders who succeed with your data won't be the ones hunting for non-existent signals in the under-50 set - they'll be the ones understanding that measuring what didn't happen is sometimes more valuable than celebrating what did. Null results are actionable when the measurement system is honest enough to report them.
I was one of those companies for a few years (small team doing client work). Never posted a job publicly, almost every hire came through someone we knew.
Now I'm on the other side of it, about to start outreach to companies that size, and I don't have a good answer either. Where I'm landing is static stuff rather than events -- directory profiles where someone filled in a minimum project size, a services page that says how they price. No timing information at all but at least it exists.
Is the sub 50 segment just structurally not reachable this way, or have you seen something that works?
Honestly I have not found anything that works there, and I stopped looking
for now. What you describe is the wall. Static profiles and a services page
with prices, no timing anywhere. My conclusion was that this segment is
reachable through relationships and communities, not through public signals,
so I moved my own list up to 51 to 200 people and left the smaller end alone.
If you find a timing proxy that holds up on the way in, I would like to hear
it, because I have nothing.
The 96% silence is where your measurement system shines. Most teams would read that as "weak signal quality" and optimize away. You read it as "the signal is in the absence." That distinction — recognizing when your measurement system is honest about what it can't see — is what turns a tool into something actually useful. The fact that you verified the silence externally rather than assumed a detection gap is even rarer. Most measurement problems hide at that step.
I ran a signal-based outbound engine across 500+ bespoke motions. The useful split was not “signal/no signal.” It was “enough evidence to justify contact/not yet.”
Below 50 employees, a rare event can open the account, but I’d still require a second step tying it to a current problem before sending anything. Otherwise a job post just becomes an excuse for generic outreach.
The 96% silent cohort is operationally useful: exclude it from automated outreach rather than score it as low intent. No evidence is not no need. It is just no license to interrupt them.
Enough evidence to earn a contact versus not yet is a better line than signal
versus no signal, and I am stealing it. The second step you describe is what
killed my first wave. Thirty two emails, zero replies, and about a third had an
event with no bridge to the person reading it. Absence of evidence not being
absence of need is the correct caveat too. I deprioritise, I do not conclude.
The step most people skip is the one you did: externally probing your own silent cohort to make sure the silence was real, rather than just a detection gap. Verifying the null result before building on it is much rarer than it should be.
In my corner (hardware measurement tools) the equivalent was publishing what our measurements can’t show. Counterintuitively, that ended up becoming one of the strongest trust and distribution drivers.
I’m curious whether narrowing the claim to ≥50 employees cost you any deals in the pipeline, or whether prospects actually respected the honesty.
This matches what I’ve been seeing too. Smaller teams often don’t leave clear public signals even when they have the problem. Curious what you ended up using as a proxy when the usual buying signals were missing.
I did not find a proxy, which is the boring answer. I tried treating a
services page update and a new pricing page as weak timing, and neither
predicted anything I could act on. So I excluded the segment rather than
dressing up a guess as a signal. When a company is silent I now record it as
unknown, not as not buying.
That’s a clean way to handle it.
Most people would rather invent a weak proxy than admit the signal just isn’t there. Treating silence as “unknown” instead of forcing a conclusion feels more honest, even if it’s less satisfying in the short term.
The interesting part for me is that you didn't treat “no public signal” as “no activity” — you actually checked the silent cohort externally.
It makes me wonder if the signal model should distinguish between absence of evidence and evidence of absence.
For smaller companies, public hiring may simply be a poor observable signal rather than a reliable negative signal. So instead of lowering their priority entirely, the system could potentially treat a rare positive signal as high-confidence while keeping prolonged silence as “unknown” rather than “not buying.”
I'd be curious whether your data shows a similar pattern with other public signals beyond hiring.
Absence of evidence versus evidence of absence is the right distinction, and I
now record silence as unknown rather than as a negative. On other signals, yes,
the same pattern. Funding decays fastest, three weeks after a round the inbox
is already crowded. Hiring stays live for months. Leadership change is the
strongest of the three and the least covered anywhere, because someone new is
rebuilding a stack and has budget to do it. A rare signal from a quiet company
is worth more, exactly as you describe.
The 96% silence finding is more interesting than the obvious “signals are better at 50+ employees” conclusion. It suggests the absence of a signal may itself be meaningful, rather than simply a weakness in the dataset.
The 96% silence finding matches what I've seen selling to small teams — the signal isn't in postings, it's in behavior. Small companies move fast and publicly skip the paperwork: a team member's LinkedIn updates, new job titles appearing, tools they start mentioning in conversations, even reply times dropping. Postings are a trailing indicator; the network is the leading one. And you're right that a rare posting is worth more — when a small company goes to the trouble of writing one, it usually means real growth, not a compliance checklist. The uncomfortable trade-off is that watching behavior at scale is manual and noisy, which is exactly why most signal tools avoid it.