To compare social metrics across brands, divide each post's number by the median for the same account, platform and format over the last 90 to 180 days. The result is an index where 1.00 means a typical post for that brand. A small brand and a huge brand can then sit in one table without one of them always looking like the winner.
TLDR: Raw engagement rates punish big accounts and flatter small ones. Index every post to its own account's median, keep platforms and formats separate, and report the share of posts above 1.00 per brand. Mydrop uses this method across the 55,000+ posts it manages.
Why the raw numbers lie
Engagement rate moves with audience size and posting rhythm, not just quality. In Mydrop's September 2026 data, accounts posting under once a week had a median engagement rate of 7.03%, those posting 1 to 3 times a week 3.08%, and those posting 7 or more 0.68%. That is a correlation, not a cause, but it means a quiet small brand will beat a busy large one on raw rate every month.
Platforms differ too. The median post gets about 3.1% on Instagram and 1.1% on Facebook, so averaging them gives a number that describes neither.
The five rules of the index
- Same platform only. Never divide an Instagram post by a Facebook median.
- Same format. In our data carousels indexed at 1.10, text posts 1.04, photos 1.00 and videos 0.99, so formats pull the median around.
- Use the median, not the mean. One viral post drags a mean up for months.
- Rolling window of 90 to 180 days. Short enough to follow the brand, long enough to smooth a bad week.
- At least 20 posts in the baseline. With fewer, flag the index as low confidence.
Two brands, one scoreboard
Take two invented brands to see the effect. Brand A has 200,000 followers and a median engagement rate of 0.9%. Brand B has 3,000 followers and a median of 6.0%. This month, A's best post hit 1.3% and B's best hit 7.2%.
| Median rate | Best post | Raw rank | Index | |
|---|---|---|---|---|
| Brand A | 0.9% | 1.3% | 2nd | 1.44 |
| Brand B | 6.0% | 7.2% | 1st | 1.20 |
On raw numbers B wins by a mile. On the index, A's best post beat its own normal by 44% and B's by 20%. The index answers the question you actually care about: which team is improving?
What to put in the cross-brand report
Keep it to three columns per brand:
- Median index of the last 30 days (should hover near 1.00, and above after a good month).
- Share of posts above 1.00. Half is normal. 65% means the team found something.
- Posts published vs planned. A brand can look great because it posted twice.
Leave raw rates in each brand's own report, where the audience size makes sense. The cross-brand view is for who needs help this month, not for who is bigger.
Build it in a sheet first, automate past 15 brands
You can build this in a sheet with one tab per account, and many teams do. It breaks when you reach 15 or 20 brands because the baselines need refreshing monthly. Mydrop's multi-profile benchmark and performance view compute each post against its own account's median automatically, and white-label reports put the result in a client-facing PDF.
Treat launches, crises and new accounts as exceptions
A baseline assumes a normal stretch. When a brand has a product launch, a viral post or a paused month, mark those weeks and exclude them from the median, or the index will look wrong for the next three months. For a new account with under 20 posts, report raw numbers with a "building baseline" label and do not rank it against the others.
Do not use the index to compare people. Brand context (a launch month, a crisis, a holiday) moves the median, so add a note column and read the number with the story next to it.
Next step: pick your three busiest brands, pull 90 days of posts into a sheet, compute each brand's median, and index last month's posts. Ten minutes in, you will know whether your current ranking was real.
Google review
Trustpilot review
Product Hunt comment
