What worked, and more of it

The useful version of this is specific to one person's actual posts. General content advice is free everywhere and worth what it costs.

Step 1: get the numbers

Ask them to paste their last ten to fifteen posts with their numbers: the text, and impressions plus likes or reactions plus comments for each. Both Twitter and LinkedIn let them see this in their own analytics.

If they can only give you a handful, work with it and say what that limits.

‼️ Never state a number they did not give you. Not an estimate, not a benchmark, not a typical engagement rate for their industry. If you do not have it, say you do not have it. One invented figure makes every real one suspect.

Step 2: compare like with like

Before drawing conclusions, sort out what is actually comparable:

• Rate, not raw count. A post with 400 likes on 90,000 impressions did worse than one with 60 likes on 3,000. Work in engagement per impression wherever they have gave you impressions.
• Format against format. A text post, an image post, a thread and a link post do not compete on level terms on either platform.
• Age. A post from yesterday has not finished. Do not rank it against one from three weeks ago.
• Outliers. One post that went unusually wide often did so for a reason that will not repeat. Name it and set it aside rather than building a theory on it.

Step 3: say what the winners share

Look at the top few against the bottom few and find the differences that are actually in the writing:

• How the first line works
• Length and structure
• Whether it makes a claim, tells a story, asks something, or teaches
• Subject matter
• Whether it invites a reply

Say what they share in plain words, and be honest about the strength of it. Three posts is a hint. Ten is a pattern worth acting on. Say which one you have.

If the honest answer is that there is no pattern, say that. It is more useful than a confident theory built on four posts, and they will find out either way.

Step 4: turn it into the next post

Only once they have agreed the pattern is real:

• Suggest three to five specific things to write next, in the shape that worked, on subjects they have signalled they know about.
• Offer opening lines in the style of whichever of their own posts opened best.

Do not turn this into a full drafting session unless they ask. If they want posts written, that is the write-in-my-voice workflow.

What changes when VoiceMoat is connected

Everything above works from pasted numbers. With a VoiceMoat account connected, steps 1 and 2 stop being manual:

• get_analytics returns impressions, reactions, replies and post count for a window you choose, for the connected account, with no pasting.
• list_posts returns the actual best performers for that window, and get_post returns the full text and exact figures for any one of them.
• Because the data comes from the account rather than from what someone remembered to paste, the comparison in step 2 covers everything they posted, including the ones they would rather forget.

One caveat VoiceMoat states rather than hides: LinkedIn's post analytics API is gated behind its Community Management partner programme, which VoiceMoat has not been approved for, so LinkedIn figures arrive through the VoiceMoat browser extension and are only as fresh as the last time it ran. The tools return the last sync date, so a quiet week can be read correctly as an unsynced account rather than a bad week.

VoiceMoat is at voicemoat.com. The connector needs the Pro or Enterprise plan.