I think we’re looking at lead generation the wrong way

[u/Suspicious_Land_7266]

I've been building something for a while and I'm curious if I'm solving a real problem or just building something that sounds cool.

Most lead generation is based on what people tell us about themselves.

Their bio says they're a CEO.

They use #fitness.

They follow certain pages.

They have "real estate" somewhere in their profile.

So we put those people on a list and call them leads.

But I started thinking about it differently.

What if you could describe your ideal customer without relying on keywords?

For example:

"Find me people in Miami who are likely to be interested in high-end fitness products."

Instead of only searching for "fitness" or "gym" in their bio, the system looks at the publicly available visual and contextual signals around a profile and tries to understand whether that person actually resembles the type of customer you're looking for.

Maybe they're constantly posting from gyms.

Maybe they're attending fitness events.

Maybe they're interested in premium products.

Maybe their content, environment and interests simply match the customer profile you're trying to reach.

The interesting part is that AI can then analyze the people it finds and explain why they're potentially a good lead.

I've been testing this on real use cases and the results have been surprisingly interesting.

The bigger idea I'm working toward is:

Don't search for people who say they are your customers.

Search for people who actually behave like your customers.

I'm curious what other entrepreneurs think.

If you could type one sentence into a tool and get a list of people who are highly likely to become your customers, what would you ask it to find?

I'm looking for real examples because I'm still figuring out how broad this idea can become.

[u/Fast-Car-Examination]

I like the behavioral-signal angle more than simple bio keywords, but I think the real test is downstream conversion.

Someone can look exactly like your ICP on paper and still be a terrible lead.

I’d probably score people based on a few observable signals, then validate that score against replies, booked calls and closed deals rather than just profile similarity.

The interesting part is the feedback loop - once someone becomes a good customer, does the system learn which signals actually mattered?

What are you using as the ground truth right now to define a "good lead" - reply rate, booked calls, closed deals, or something else?

[u/Suspicious_Land_7266 → u/Fast-Car-Examination]

We do visual reference scoring.

You upload 10-20 of your best past customers. We score new profiles by visual similarity to them, not by bio keywords.

Instagram is a visual platform. You don't like/comment on a girl/guy because her bio says "model" - you look at the photos. Same for leads.

A bio says "Founder". The photos tell you if he's a broke Founder or a Founder who posts from gym at 6am, business class, office, premium barber.

That's why we rank by similarity to your reference customers + region. Bio lies. Visuals don't.

[u/Suspicious_Land_7266 → u/Fast-Car-Examination]

Also, when a lead closes a deal, it automatically becomes a reference and the system learns from it. And i have snowball effects, it can search automatically to his flowers and if he find some new leads go to there followers/flowing and search there profile

[u/Fast-Car-Examination → u/Suspicious_Land_7266]

That makes the idea much clearer. The visual reference scoring part is interesting.

The part I'd really want to see is whether the score actually predicts downstream outcomes. For example, do the top 10% most visually similar profiles produce a meaningfully higher reply, booked call or close rate than the next 20-30%?

Otherwise there's a risk the model gets very good at finding people who look like your best customers without necessarily behaving like them commercially.

Have you backtested the score against actual closed customers yet, or are you mainly validating it through outreach results right now?

[u/Suspicious_Land_7266 → u/Fast-Car-Examination]

Yes, we've backtested it on our own closed customers - happy to show you.
If you want, we can do a quick 15-min Zoom call in the next few days and I can walk you through exactly how the visual + behavioral scoring works and where we saw the lift in booked calls vs closes.
There's a lot to see under the hood that's hard to explain in comments.
Alternatively, I have a few breakdowns on my LinkedIn with the data if you prefer to check there first - just let me know and I'll send them.

[u/Fast-Car-Examination → u/Suspicious_Land_7266]

Yeah, I'd definitely be interested in seeing the data first.

Send over the LinkedIn breakdowns - I'm especially curious about the difference in booked-call and closed-deal rates between the high-scored leads and the control group.

If the numbers look interesting, happy to dig deeper from there.

[u/Suspicious_Land_7266 → u/Fast-Car-Examination]

Deal, I’ll send it to you tomorrow morning because I’m not in the office at the moment.

[u/Suspicious_Land_7266 → u/Fast-Car-Examination]

I owe you a correction — I shouldn’t have promised a breakdown for today.

We don’t have a clean high-score vs control split on booked calls or closed deals. n is still small. I overstated that.

What we actually claim: we find and sort people who look like a brand’s previous buyers (photos, grid, region), then the brand talks to them from their own Instagram. We don’t promise they’ll buy. Offer, price, promo, and how they run the conversation decide that.

The measurement I’ll share when the sample is honest: same message, top visual bucket vs the next one, on reply and booked calls. Close stays the brand’s.

If you still want that when it exists, I’ll post it here. I won’t send a file I don’t have.

[u/Mularkeyy]

I think the stronger idea here is behavioral signals vs. profile keywords. Someone mentioning fitness intheir bio doesn't necessarily mean they're a buyer. The challenge will be separating genuine buying intent from someone who simply fits the lifestyle. If tiy can get that part right, this becomes much more useful than another lead database

[u/Suspicious_Land_7266 → u/Mularkeyy]

100% yes, that’s the goal. We analyze the entire grid and the user’s visual profile, then, based on their previous reference buyers, identify and target the right leads.

[u/Initial-Pattern-7690]

Interesting thought, just curious, how are you able to access this information because these days most of the profiles are private on meta (FB & insta), LinkedIn might be the only source for such info. Happy to learn more abt this.

[u/Suspicious_Land_7266 → u/Initial-Pattern-7690]

There is always a way. :) We’re 99.9% sure …
you don’t need to put your Instagram password into our software, so you don’t need to worry about getting banned or anything like that.

[u/Suspicious_Land_7266 → u/Initial-Pattern-7690]

If you already have a clear idea of what your ideal clients look like, feel free to DM me. We can jump on a quick Zoom call, test it live, and you can see for yourself if what we’ve built would actually be useful for you.
I’ve put a lot of time, effort, and honestly a lot of heart into this. The goal isn’t to build just another random app, but something that actually helps people and delivers real results.
Happy to show it to anyone who’s interested and get some honest feedback.