Condition-Based Targeting: Find Leads by Real-World Signals

Almost every lead tool filters the same way: pick an industry, a company size, and a location, and get a list. The problem is that a list of “restaurants in Miami” tells you nothing about which ones have a problem you can fix today. You end up scanning hundreds of records by hand looking for the signal that made them worth contacting in the first place.

Conditions are the signal

A condition is a real-world fact about a business that maps directly to your offer. If you build websites, the condition is “has no website” or “has a slow, outdated one.” If you do reputation management, it's “has bad reviews.” If you sell to fast-growing teams, it's “recently raised funding.” Targeting on the condition means every lead on your list already has the reason you're reaching out baked in.

Why category-only targeting underperforms

When you target by category alone, most of your list is doing fine. They have a decent website, solid reviews, no urgent need — so your outreach lands as noise. Reply rates suffer not because the email was bad, but because the timing and relevance were wrong. Condition-based targeting fixes the input: a smaller, sharper list where every prospect has a visible gap.

The classic play: businesses that need a website

It's the cleanest example. If you sell websites, your best prospects are local businesses with no site at all — or one that's broken, slow, or clearly outdated. That's precisely the segment a normal filter discards, because tools usually keep only businesses that already have a working website and email.

Website-less local businesses often have no email, so Flowfiy keeps the phone number and Maps listing it scrapes and marks those leads exportable — instead of silently dropping the exact prospects you want.

How Flowfiy evaluates any condition

You can't hardcode every phrasing a person might type, so Flowfiy decomposes each request and routes every condition to the cheapest evaluator that can check it — narrowing the candidate set before the expensive checks run:

• Search filters — pushed straight into the data source (industry, size, location, category). Free.
• Attributes — computed from results in memory (rating, review count, has-email, founded year). Free.
• Signals — active probes run only on survivors (website audit, tech detection, ads, funding news).
• AI judge — for fuzzy, subjective conditions like “looks high-end” or “B2B not B2C.”

Before you spend a single credit, the plan shows you exactly how each condition will be checked and whether it's a hard filter or a soft ranking boost. Anything Flowfiy can't evaluate, it raises as a question instead of quietly dropping it.

Just describe it

You don't configure any of this. You write what you want in plain English — “coffee shops in Austin with no website,” “dentists in Texas with bad reviews,” “agencies under 20 staff with an outdated site” — and Flowfiy finds the matches, scores each 0–100, and writes outreach that references the actual reason they qualified.