Postey Analytics
Reading numbers is easy. Saying what they support, and refusing to say more, is the job.
Check the data is real before interpreting it
Do this first, every time. Platform analytics arrive partial, delayed, or absent, and a confident reading of a broken feed is worse than saying nothing.
| Symptom | What it means | What to say |
|---|---|---|
every metric is 0 across all posts on a platform |
the feed is not returning, or the platform never provided it | say the platform reports nothing; do not rank by it |
impressions present, engagement all 0 |
partial fetch | use impressions only, and name the limitation |
| one post has numbers, its siblings do not | the others have not been fetched yet | compare only the ones that have data |
fetch_count is 0 |
never collected | not "zero performance" — no data at all |
Zero is not a result. On a real account checked during development, every LinkedIn post reported zero impressions while the same content on X reported between 481 and 2,935. Ranking that account's LinkedIn posts would have produced a confident ordering of nothing.
What the numbers can and cannot support
They can support: this post got more reach than that one; this format appears more often near the top; this account's median engagement moved after a change.
They cannot support: why. Attribution needs a controlled comparison that social platforms do not give you. Say "these three of your top five were lists" — not "lists perform better for you", which is a causal claim from five data points.
Three traps worth naming out loud when they apply:
- Survivorship. Top posts are top by definition. Look at the bottom too, or every conclusion is "do more of what already worked".
- Sample size. Under ~10 posts with real data, report observations, not patterns.
- Time confounds. A post published during a spike in following did not earn that reach on content alone.
Turning it into a decision
The output is a recommendation the user can act on this week, with its evidence attached:
Observation 4 of your 5 highest-reach posts on X opened with a question.
Evidence posts 6016, 6028, 6017, 5994 (481–2,935 impressions)
Caveat 5 posts, one platform, one month
Recommendation Try a question opener on the next three X posts and compare.
Never emit a recommendation without its caveat. The caveat is what makes it honest, and it is what stops the next session treating a hunch as an established fact.
Hand recurring findings to postey-voice if it is installed: a consistent structural habit among
top posts is exactly the kind of observation its rules ledger can accumulate evidence for. Do not
write to its ledger from here — say what you found and let the user decide.
Scope
Per-post numbers: postey://posts/{post_id}/analytics. Account roll-up:
postey://accounts/{account_id}/analytics. Ranked posts:
postey://accounts/{account_id}/analytics/posts.
Whether a post published at all is not this skill's question — that is postey-ops and
post.publish_status. A post that never went out has no performance to explain, and confusing the
two produces a very confident analysis of a post that does not exist.