Calibration — measured against the profile's own history

A post earns a winner badge when it outperforms the profile's own recent history — not when it beats some other account, and not against an industry benchmark. Huntit reads each profile's posts from the last 12 months and works out what strong looks like for that one profile. A badge means "this post did better than most of what this profile normally puts out."

There are no industry benchmarks anywhere in Huntit. There is no shared leaderboard of "good numbers" that every account is measured against. Every threshold a post has to beat is built from that one profile's own output, on its two axes: Reach and Engagement.

Why own-history, not benchmarks

A creator with 5,000 followers and a creator with 5 million live in completely different worlds. A view count that would be a runaway hit for the small account is a quiet day for the large one.

Grade both against one fixed number and the big account badges everything while the small one badges nothing. Neither reading tells you a thing.

Measuring each profile against itself fixes that. Whatever the size of the account, a badge means one thing:

This post beat this profile's own threshold.

One consequence follows: a smaller profile can absolutely out-badge a bigger one. Winning is about beating your own normal, not about raw numbers.

What "the profile's own history" means

Calibration looks at the profile's posts from the last 12 months and builds its threshold from that pool. As the profile keeps posting, the pool refreshes — so the threshold reflects how it's performing lately, not how it did two years ago.

All of that happens on its own. There's nothing to configure and no sensitivity slider to tune.

Because the threshold is per-profile, a competitor you track and your client's own brand are each judged against their own history — never against each other. That is exactly what makes the badges comparable across a whole client: every winner, big profile or small, cleared its own threshold.

A small example

You track a competitor that averages modest view counts, and a much larger inspiration profile that routinely pulls big numbers.

One post from the small competitor earns a ⭐ Top 10% Reach badge. A post from the large profile, with far more raw views, earns nothing.

That's correct: the small post was exceptional for its profile, the big one ordinary for its own. The badge tells you where the real outperformance is.

Before badges start

Calibration needs enough of a profile's own posts before it can draw a reliable threshold. Until then the profile shows a Calibrating · N of 30 meter instead of badges.

Reach and Engagement each need 30 posts they can measure, so one axis can be badging while the other is still building.