How we source and score buyer-intent signals

Hailports watches public conversations across 14 markets and surfaces the people who said, out loud and in public, that they are shopping, switching, or fed up with what they have. This page explains exactly where those signals come from, how we score them, and the lines we will not cross. We keep it concrete on purpose: if a method matters to whether you can trust a lead, it belongs here, not behind a curtain.

Last updated: June 10, 2026.

Public sources only

Every signal we surface comes from a post the author published in the open — a Reddit thread, a public forum question, a "what should I switch to?" comment, a public review, or a similar place where someone chose to ask in front of an audience. We do not buy scraped contact databases, we do not pull from private groups or DMs, and we do not infer intent from anything that wasn't said publicly. If a person didn't post it where anyone could read it, it isn't a signal to us.

Concretely, that means:

• Open web and public communities — posts and comments that are visible to any logged-out reader at the source.
• The author's own words — we quote the relevant line and link straight to the original post so you can read the full context yourself.
• Recency-weighted — we prioritize posts from roughly the last 90 days, because intent goes stale fast and a year-old "I'm looking for X" is no longer a buying signal.

How we score a signal

Not every public mention is a buyer. We rank each candidate so you spend your time on the warm ones, using signals you could check by hand if you wanted to:

• Intent strength — is the person actively asking for a recommendation or describing a switch ("we're dropping X, what do people use?") versus just talking about a category in passing? Active, decision-shaped language scores higher.
• Recency — newer posts score higher; we drop threads that have gone cold so you aren't reaching out to a months-old decision that's already made.
• Fit to the market — how closely the post matches the specific market and problem language a buyer in that niche uses, so a generic mention doesn't outrank a precise one.
• Specificity — a post that names a budget, a timeline, a current tool, or a concrete pain point is a stronger signal than a vague one.

The output is a ranked list: the post, its source link, the author's own words, and a score that reflects those factors. We don't hide the inputs behind a single mystery number — the source is always one click away so you can judge it yourself.

What we will not do

This is the part that keeps the work honest:

• We link every claim to its original public post. If we can't point you to the source, we don't surface the signal.
• We never publish private data. No private profiles, no harvested email lists, no personal details that weren't part of the public post itself.
• We don't fabricate. No invented quotes, no made-up scores, no synthetic "leads." Every entry traces back to a real, readable post.
• We respect the source. Our checks read public endpoints the way any visitor's browser would; we don't break logins or access anything gated.

Why this holds up

The highest-converting lead isn't the one with the best job title in a stale database — it's the person who described their problem in public in the last few weeks. Recency, plus matching your outreach to their exact words, is what moves reply rates. We automated that listening across 14 markets, but the underlying method is something you could do a slice of by hand tonight: go read where buyers ask, find the recent ones, and reply with their own language. We just do it at scale, and we show our work.

Signals are aggregated from public posts; we link the source on every one and never publish private data. See our Privacy Policy and Terms of Service.

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