I kept losing deals to timing, so I built a daily signal monitor for my own market
Years of building SaaS with small teams, and my most expensive losses were never the deals I lost in a bake-off. They were the ones I never saw: the perfect-fit company that raised a round, hired the team I sell into, and picked someone else, while I was in a browser with thirty tabs open, researching the wrong accounts.
So I built the thing I wanted: describe the companies you sell to, and it watches that market for the public changes that mean something (funding, hiring for the buying team, leadership moves, relevant news), checking priority accounts daily, then ranks your accounts by how strong that evidence actually is. Every signal links back to the source it came from, and the score decays as news gets old, because I did not want another number I had to trust.
Two things I got wrong on the way, in case they save someone time:
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I started with "more leads" and it was the wrong product. A longer list made the problem worse. The value is a shorter list you can verify.
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Scores need to show their work or nobody believes them. My first version showed a number. Users did not act on it. Now every point of the score opens into the dated evidence behind it, and that changed how people use it.
It is live at leadalise.com. 14-day trial (card and work email required), pricing is on the site, and the whole thing is one person so far. Happy to answer anything about the signal pipeline or the scoring; the parts that were hard were mostly "is this evidence real" rather than "can we fetch it".
What I would ask this crowd: if you sell B2B, what change at a company has actually made you pick up the phone? I want to know which signals matter to people who are not me.
The point about a shorter list being more valuable than a longer one really resonates. In outbound, having 500 random prospects is often less useful than having 50 accounts with a clear reason to reach out right now.
I’d also be interested in how you separate a meaningful buying signal from something that simply looks relevant on the surface. A company hiring for a role, for example, doesn't always mean they're ready to buy.
This is what a working measurement system looks like: "shorter verified list > longer unverified list" and "evidence must show its work." The first one cuts through founder blindness (we think more options help, they actually paralyze). The second one forces transparency (confidence matters more than conviction).
Most sales tools measure "did we get a lead." You measure "is this the right lead right now." That gap is your moat. You can't commoditize the judgment that comes from showing work - the moment a founder sees the evidence, they already know what to do. A confident black box number? They ignore it.
The best part: every signal you weight reveals an assumption about which founder decision matters. "VP re-evals vendors in 90 days" is measuring founder psychology (new leader needs a quick win). "Hiring for a specific role" is measuring purchasing momentum. By weighting them differently, you're not building a lead engine, you're building a founder clarity engine.
The shift from “more leads” to a smaller list of verified, timely opportunities is really interesting. I also like the idea of showing the evidence behind a score instead of asking users to blindly trust another number. In my experience, knowing why something is being flagged is often more valuable than the score itself. Curious to see how you balance signal quality with false positives as the system scales.
That balance is the hardest part, and I'll answer with a real false positive from this week instead of theory. My pipeline read "Mirendil raises $200M led by a16z and Kleiner Perkins" and briefly credited the raise to Kleiner Perkins, the investor, not the company raising. A confidence gate exists exactly for this, and it didn't catch that one.
Two things keep this survivable. First, every signal carries its source link, so a wrong flag costs the user ten seconds to dismiss, not a wasted call, the evidence contradicts the claim right there. That's the practical difference between a false positive in a black box and one in a glass box. Second, I'd rather miss a weak signal than promote a wrong one, there's a confidence threshold below which signals don't ship at all, and the score decays as evidence ages instead of accumulating forever.
Scaling will stress this, no illusions there. My bet is that showing work turns false positives from a trust killer into a correctable annoyance.
How do you handle the why behind flags in your own work?
For me, the strongest B2B signals have been a recent product launch, funding, hiring around growth/marketing, or a visible push into a new market. Those usually create an actual reason to talk now instead of sending the same pitch to a company six months too early.
I also like the move from “more leads” to a smaller ranked list. Better timing on 20 relevant accounts seems much more useful than another database of 10,000.
"An actual reason to talk now instead of the same pitch six months early" is exactly the job I want the product to do.
Product launches and new-market pushes are a sharp addition. Right now my pipeline files those under general news, and your comment makes me think they deserve their own weight. A launch is arguably the most self-published signal there is. The company is actively asking the market to look at them, so reaching out lands as attention, not interruption.
Interesting pattern across the replies here. Everyone names a different strongest signal — hiring for one person, leadership change for another, launches for you. Which supports the ranked-list idea more than any single signal type does. The value isn't picking the one true signal, it's weighing whatever evidence exists for this specific account this specific week.
When you spot a launch or market push, how fast does that window close for you, days or weeks?
For me it depends on the signal. A product launch feels strongest in the first few days while the team is actively pushing attention. Hiring or entering a new market usually gives a wider window, maybe a few weeks.
The main thing is reaching out while the reason is still fresh enough that the message feels contextual, not like generic outbound.
Your two "got wrong" lessons are the whole product. "Shorter list you can verify" beats "more leads" is the exact inversion most intent tools never make, and "scores must show their work or nobody acts" is what makes the first one usable. Those aren't footnotes, they're your moat, most competitors ship a confident number and lose on exactly the trust gap you closed.
To your question, the signal that makes me pick up the phone isn't any single event, it's the one that creates a new buyer or breaks the status quo. A funding round alone is noise, everyone spams those. But "they hired a VP of X" is gold, a new leader arrives needing to prove themselves, actively re-evaluating vendors in their first 90 days. Same with "the champion who blocked you left." The best signals aren't "company is doing well," they're "the person who decides just changed, and the old no is void."
So the sharpest scoring might weight people-change over company-change. Money events are crowded; power-shift events are where a closed door reopens.
Which signal is your evidence strongest on so far, funding, hiring, or leadership?
This is the sharpest framing of signal quality I've seen: "the person who decides just changed, and the old no is void." Stealing it for my thinking, with credit.
Honest answer on evidence strength: hiring is where my data is deepest right now, job postings are abundant, self-published and dated, so verification is nearly free. Funding is the most reliable to detect but you're right that it's crowded, I treat it less as "reach out now" and more as a context multiplier: a raise plus first sales hires within weeks is a different animal than either alone.
Leadership change is exactly where my coverage is thinnest today, and your comment moves it up my roadmap. The "new VP re-evaluating vendors in their first 90 days" window is real, and it decays fast, which fits how my scoring already works (evidence ages out).
Did you act on those power-shift signals manually, or did some tool actually surface them for you?
Honest answer: mostly manually, and badly. The power-shift signals were the ones I caught by accident, someone mentioned a VP move in a newsletter, I happened to see a LinkedIn post. Which is the problem, the highest-value signal was the one I had no system for, so I caught the loud ones and missed the quiet ones that mattered more. No tool surfaced them reliably, which is why your thin leadership-change coverage is your biggest opportunity, not a gap. Whoever solves "reliably detect the decision-maker changed" owns the signal nobody else does well.
Your "context multiplier" instinct on funding is the sharp part, though. A raise alone is noise, a raise plus first sales hires is intent, that's compound signal detection, harder to fake or spam than any single event. That combinatorial layer might be a bigger moat than any individual signal, because reading-them-together can't be commoditized.
This "which signal actually means something, and how to weight the combinations" is what I spend my time on, part of the team building Hivemind, an AI strategy copilot. If you want to pressure-test the signal-weighting model: https://hivemind.myosin.xyz
The funding, hiring, leadership and news signals make for an interesting mix. Curious which one has produced the most useful signal so far.
Hiring so far, mostly because it's the most verifiable. Postings are self-published, dated, and link back to a source. Funding is easier to detect but noisier as a buying trigger. The mix matters more than any single type though, two moderate signals within a month beat one loud one.
That makes sense — the distinction between verifiable signals and noisier triggers is useful. If you’re open to continuing the conversation, feel free to share your email.