How to Find Patterns in Your Social Media Data

A ranked list of your best posts is easy to produce and almost useless on its own. The useful question is not which posts did well, it is what the good ones have in common, because that is the only part you can repeat deliberately.

The problem is that human beings are extremely good at finding patterns in noise. So here is a method that makes it harder to fool yourself.

One variable at a time

Pick a single thing to group by. The five that usually contain something:

Format. Text, image, carousel, video, link.

Topic or pillar. Which of your recurring subjects.

Opening style. Question, claim, story, number, observation.

Length. Short, medium, long, banded roughly.

Time. Day of week, time of day.

Only one at a time. If you group by format and topic together you get eight groups of three posts each, and three posts is nothing.

Compare against your own median

Each group gets one number: how it did against your own median.

Median rather than mean, because one unusually good post drags a mean up and makes every subsequent post look like a decline. And your own median rather than an industry benchmark, because published averages are drawn from accounts nothing like yours.

So the finding looks like "photo posts run 1.6 times my median" rather than "photo posts get 4.2% engagement". The first is actionable. The second needs a comparison you do not have.

Count the posts before you believe anything

The step that separates analysis from astrology.

• Under 10 posts in a group: no conclusion. None.
• 10 to 25: a direction worth testing on purpose.
• 25 to 100: a pattern, if the gap is large.
• Over 100: something you can plan around.

Most patterns people act on are in the first band. "Posts with questions do better" from six posts is a story, and the reason it feels convincing is that you can remember all six.

Any tool that reports a pattern should tell you the sample size alongside it. If it does not, work it out yourself before you reorganise your quarter.

Hold the other variables still

The classic mistake: you find that video outperforms text, and reorganise around video.

But you only made videos for your best three ideas, because video is expensive. So what you actually measured was idea quality, wearing a format's clothes.

Before believing a pattern, ask what else is different about that group. Common confounders:

• The expensive format is reserved for the best material.
• The topic that performs is also the one you post about when something newsworthy happens.
• The best time of day is also when you post your most considered content.
• The group is concentrated in one month when something else changed.

You cannot eliminate these without a real experiment. You can notice them, and downgrade your confidence accordingly.

Test it before you plan around it

A pattern from your history is a hypothesis, not a finding. The test is to do it deliberately for a month.

If photo posts appear to run 1.6 times your median, make photo posts for a month for material you would otherwise have posted as text. Then look. If the effect survives being applied to ordinary ideas rather than your best ones, it is real.

Most do not survive, and finding that out costs you a month rather than a quarter.

Where AI helps and where it does not

Asking an assistant that can see your posts to find the pattern is a genuine saving: it will group and compare far faster than you will by hand.

What matters is whether it tells you the sample size and hedges appropriately. An assistant that answers "your photo posts do best" with the same confidence whether it saw eight posts or eight hundred is not helping you, it is laundering noise into a recommendation.

The good version says something closer to: based on 24 posts, photo posts run about 1.6 times your median, which is worth testing rather than treating as a rule.

FAQs

How many posts do I need before analysis is worth doing?

Roughly twenty in total before anything, and ten in a group before that group means anything.

What if I do not have enough data?

Then post more and analyse later. Analysing thin data is worse than not analysing, because it produces confident wrong conclusions.

Should I compare against competitors?

You cannot see their denominators, so you cannot compute anything comparable. Compare against your own history.

How often should I look for patterns?

Monthly is plenty. Patterns do not change week to week, and looking more often mostly finds noise.

What is the most common false pattern?

Best time to post. It is drawn from when you happen to have posted, and if you have always posted at nine, the data cannot tell you anything about four.