Analytics for creators who aren't 'data people'

A lot of creators avoid engaging with their own analytics because the terminology feels built for someone else — reach versus impressions, saves-to-reach ratio, engagement rate calculated three slightly different ways depending on which app you're looking at. None of it is actually complicated once it's translated into a plain question you'd naturally ask anyway.

The jargon-to-plain-question translation

You genuinely don't need to memorize the technical definitions. You need answers to a small handful of plain questions: what's working, what isn't, and what should I try next. Everything else in a typical analytics dashboard is detail you can safely ignore until, specifically, it starts to matter for a decision you're actually trying to make.

Why "just look at the dashboard" doesn't actually work for most people

The problem was never that the numbers are hidden — most platforms show you plenty of data. The problem is that raw numbers require a translation step to become a decision, and that translation step is exactly the part that feels like it requires being "a data person," when really it's just unfamiliarity with the vocabulary, not an actual difficulty with the underlying concepts.

A three-question monthly check

What got the most saves or shares this month, and what did those pieces have in common? This is your "what to make more of" answer.

What got the least engagement relative to your average, and is there a pattern? This is your "what to reconsider" answer — not necessarily "stop entirely," but worth a second look.

Is my reach trending up, flat, or down over the last month compared to the month before? This is your overall temperature check — the single number that tells you if things are broadly working or need real attention.

Three questions, asked consistently once a month, will tell you more than an hour spent staring at a full dashboard without a specific question guiding what you're looking for.

Skipping the translation step entirely

That's the entire premise behind mayy.ai — ask the plain question directly, skip the terminology and the manual chart-reading, and get a direct answer you can act on the same day, without first having to become fluent in a vocabulary that was never actually necessary to understand your own content's performance.

You don't need to become a data person to use your numbers well. You need someone or something to translate the data for you — and then you can go back to actually making things.