I spent months chasing clients who already had a webmaster. So I built something that only finds the ones who don't.

Smart pivot. The Reddit API lockdown killed a lot of monitoring-based tools last year — glad you caught it early instead of doubling down.

The "visit each website and check for problems" angle is interesting. I've been doing something similar but from the other side — monitoring my own sites for outdated pages, broken links, expired certificates. Same concept, different use case.

One question: how do you handle false positives? Like a copyright year showing 2023 doesn't always mean the site is neglected — some businesses just don't update the footer. Do you weigh multiple signals together or is one red flag enough to surface a lead?

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I relate to the pain you described. I've spent hours researching agencies only to realize they already had everything covered. The biggest challenge isn't sending outreach—it's knowing who's actually worth reaching out to. Curious to see how accurate your website analysis is in practice. If it delivers on that, it could save a ton of wasted time.

The pivot after watching a competitor die from a rented API is the sharpest decision in this post: never build your core on data someone else can turn off. On the outreach itself, the outdated-footer detail is the product, because proof you did homework earns the reply, not the pitch. My first company grew by doing free IT migrations for businesses that were visibly struggling, and "I can see the problem from here" beat every cold script we ever wrote.

The "checks the actual website, not just the listing data" step is the part I'd lean into hardest. I built something with a similar shape recently — a Shopify app that scans a store's live theme for leftover code from apps that were installed and later uninstalled — and the whole value is in verifying ground truth instead of trusting a directory/API. A listing can say a business "has a webmaster," an app store can say an app is "installed," but neither tells you what's actually still running. Once you're willing to go fetch the real page and check it yourself, you catch the stale entries everyone else's leads-lists are full of.

Curious how you're handling false positives — sites that look outdated (old copyright year, no booking widget) but are intentionally simple by choice rather than neglect. That distinction seems like it'd matter a lot for how warm the lead actually is.

the underrated lesson in your own story isn't the targeting — it's that you moved off a rented API onto signals you crawl yourself. that 140k competitor didn't die from a bad idea, they died because their whole business sat on Reddit's terms, and Reddit changed them overnight. that's the real thing you built here: the day someone can flip a switch and kill your data source, you don't have a company, you have a feature on their platform. owning the pipeline end to end beats any single signal running through it.

This tool is very, very interesting. I'm wondering if it only works for B2B or if it also works for B2C, even if not now, in the near future. Could you clarify this for me? Thank you and good luck on your journey ahead.

the "qualify before you pitch" shift is the whole game, nice work. one thing i'd watch: "no website" on its own is a weak signal. a plumber with a full book from word of mouth doesn't want a site, and pitching them is the same dead end as pitching someone who already has one.

the strong signal is "no website AND visibly trying to get customers": running ads, a barely-updated facebook page they clearly care about, a gmb listing they're actively managing, posts like "we're taking new clients." absence of a site plus evidence of demand-chasing is the actual buyer. if SignalsHunt can layer even one intent signal on top of the filter, your reply rate probably jumps, because you stop pitching people who are deliberately offline.

This resonates — the "just another person in their
inbox" feeling is exactly why generic outreach
fails. Love that you rebuilt around "who needs help
right now" instead of "who's complaining." The
detail about checking outdated copyright years and
missing booking options is smart — that's the kind
of specific signal that makes a first message
actually land.

The pivot story hits home too. I'm building in a
different space (checkout/fintech) and had the same
experience — my first version was something I ended
up scrapping almost entirely once real users told me
what was actually broken. Watching that competitor
get killed by the Reddit API change is a brutal
lesson in platform risk.

Curious — when the AI writes the personalized first
message, how often do you find people still tweak it
before sending vs. sending as-is? Wondering how close
to "ready to send" it actually gets.

This resonates hard. I'm a solo dev who built a macOS app (Emdee) and now
trying to find my first paying client projects.

My ideal clients: indie SaaS founders who need a desktop layer, export
system, or AI workflow — not local businesses who need websites.

The "filter out people who already have help" insight is underrated.
I wasted time on communities before realizing I should look for founders
who posted "need a dev" in the last 48 hours, not everyone building something.

Would love to try it — trying to land clients in the dev/services space,
not web design. Curious if that works with your tool.

I really like the idea. However, when I pasted my website and recieved 20 leads, most of them were pin pointing on technical issues and not so much issues that I would try to solve with my app.

The insight of "only pitch the ones who don't already have it" is one of those things that sounds obvious in retrospect but almost nobody executes on. Most cold outreach tools optimize for volume; yours optimizes for relevance. Curious — what's the false-positive rate looking like? i.e., how often does the AI flag a site as "needs help" when actually the business already has someone in-house who just hasn't updated the footer?

i think the "who not to contact" filter is one of the biggest levers in outbound. Most campaigns fail because they're optimized for volume instead of relevance. The better your exclusion criteria, the higher the quality of every conversation.

Smart — most outreach dies on targeting, not the pitch. Filtering out the ones who already have the solution is exactly the trigger-signal that turns a cold list warm; the "who NOT to contact" filter is underrated. Curious how you detect the absence at scale — tech-stack detection, or manual checks?

How are you handling false positives on the "needs help" detection?
An outdated footer year or slow load doesnt always mean they're unhappy with their current setup, plenty of businesses know their site is old and just dont care. Curious if you found a signal that actually correlates with them being ready to switch vs just having a rough site

Good

The pivot after watching that 140k user competitor get wiped by an API change is such a good instinct honestly, most people would've kept building on the same shaky ground.

The "outdated copyright year, no booking option" detail in the personalized message is a smart way to actually earn that first reply.

Painful pattern — hunting people who are actually in-market vs everyone who could theoretically buy. Curious which channel surfaced the "already have a webmaster" vs open prospects — cold outbound, communities, or something else?

The shift from “pain signals” to “clear underserved intent” is the real unlock here. That’s also where most tools either get too noisy or too confident.

Curious how you’re validating that a site is actually worth pitching vs just looking outdated.

Strong idea — this solves a real pain: wasted cold outreach. Curious to see how accurate the “needs detection” is in real client scenarios. 👍

Love this idea

smart pivot — building your whole funnel on someone else's API (Reddit) is exactly the trap, good instinct killing it fast. one signal worth adding: businesses actively running Google/Meta ads to a weak site. "no website" can mean they don't want one, but "spending money to send traffic to a slow/broken site" means they already believe in growth AND have an obvious gap — much higher intent than an outdated footer year. that's the buyer who actually replies.

The strongest part here isn't the prospecting logic—it’s the shift from “finding people who have a problem” to “finding people who are demonstrably underserved right now.” That second framing is closer to intent than interest, and I think that's what actually makes outreach feel relevant instead of intrusive.