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McKinsey Global Institute engagement report

@McKinsey_MGI - 207K followers on X

Measured over 80 original posts from a 30-day window, last computed on October 7, 2026.

Engagement

Bottom quarter for its size
Per follower
0.009%
of 207K followers
Per impression
0.779%
2.2K views on a typical post
Reach
1.09%
of its followers see a post
Typical post
18
interactions (median)
Saved
0.312%
7 bookmarks on a typical post
Posting rate
2.67/day
active 50% of days
Peak time
16:00 UTC
Sunday

A typical post picks up 18 interactions against 207K followers, an engagement rate of 0.009%. Measured over 80 original posts, its engagement rate beats 22% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 2.2K times each, and 0.779% of those impressions turn into an interaction. That is about 1.09% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.7 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 16:00 UTC, and Sunday is the busiest day of the week. Of the 80 posts sampled, 85% carry an image or video and 100% link out. The account's strongest tracked post pulled 538 interactions, about 30x its own typical post.

Measured over 80 original posts from a 30-day window, last computed on October 7, 2026.

Compared with accounts its own size

McKinsey Global Institute's engagement rate beats 22% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 36% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.009%, McKinsey Global Institute sits above the 10th percentile of the 205,676 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.

p100.004%
p250.024%
p50 (median)0.143%
p750.679%
p902.56%
p9982.4%
Engagement rate as a share of followers, across the 205,676 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,897 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.024%
50th percentile0.143%
75th percentile0.679%
90th percentile2.56%
99th percentile82.4%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 16:00 UTC, and Sunday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 16:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 16:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Sunday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Sunday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video85% of posts+111%+108% to +115%34K
Outbound link100% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 85% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 100% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 293 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Sep 11, 202630x their median

    AI capabilities are advancing exponentially by some measures. Infrastructure builds more linearly. Organizations can take years to change. The result: bottlenecks, risks, and opportunities. New MGI research maps the AI economy as an interconnected system: https://t.co/MQbYD8Lyxa

    39812111824K viewsView on X
  • Sep 13, 202622x their median

    AI capabilities are advancing exponentially by some measures. Infrastructure builds more linearly. Organizations can take years to change. The result: bottlenecks, risks, and opportunities. New MGI research maps the AI economy as an interconnected system: https://t.co/MQbYD8Lyxa

    288857921K viewsView on X
  • Sep 13, 202617x their median

    AI won’t make most human skills obsolete, but it will change how they’re used. Negotiation, problem solving, and leadership will matter more than ever as people work alongside agents and robots. Our new Skill Change Index shows which skills will be most, and least, exposed to automation in the next five years: https://t.co/fRXfHF1k56

    224728511K viewsView on X
  • Oct 5, 202616x their median

    AI capabilities are advancing exponentially by some measures. Infrastructure builds more linearly. Organizations can take years to change. The result: bottlenecks, risks, and opportunities. New MGI research maps the AI economy as an interconnected system: https://t.co/MQbYD8Lyxa

    21963239.5K viewsView on X
  • Sep 12, 20269.7x their median

    Faster chips. More capital. Better models. None guarantees better outcomes if the constraint lies elsewhere. Our new framework looks at AI as an interconnected system – from capabilities and resources to adoption and outcomes. https://t.co/STm49x5Tw1 https://t.co/oPJm02dW10

    13637107.0K viewsView on X
  • Oct 3, 20269.4x their median

    The latest Economic Conditions Outlook from @McKinsey out. In this edition: Executives’ economic pessimism has eased since June, but they remain cautious. Negative views continue to be more common than positive ones, and expectations for the next six months are mixed. Take a deeper dive: https://t.co/FlxG6e8DXX

    12639407.3K viewsView on X
  • Oct 4, 20268.3x their median

    The chips get the headlines. The electricity bill decides the economics. Same data center: $200/MWh in China, $380 in London. Explore the investment case: https://t.co/KNq13bSKU0 https://t.co/8acbPNMjL6

    10835526.8K viewsView on X
  • Sep 12, 20266.3x their median

    US data center investment is up ~200% since late 2022. Outside AI, productive investment has stayed flat. China adds $4.4T in net productive assets a year, 4x the US. Our new report on where investment happens and why: https://t.co/rpxAZsC2uD https://t.co/CRuYHk7Uyn

    8227315.9K viewsView on X
  • Sep 13, 20266.2x their median

    AI is moving fast. But not everything around it is. Capabilities can advance exponentially, while infrastructure takes years to build and organizations can take even longer to adapt. Leaders will need to manage at multiple speeds: https://t.co/STm49x5Tw1 https://t.co/OqLXk9gmtY

    9219004.8K viewsView on X
  • Sep 10, 20264.4x their median

    By 2030, automation could unlock $450 billion in annual economic value across Latin America. Capturing it will depend less on new tech breakthroughs – and more on how we redesign workflows and how quickly human skills adapt. Learn more: https://t.co/qMHmWgVF1q https://t.co/RJB3qEAyPB

    5914424.8K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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Reading these numbers

A typical post picks up 18 interactions against 207K followers, an engagement rate of 0.009%. Measured over 80 original posts, its engagement rate beats 22% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 2.2K times each, and 0.779% of those impressions turn into an interaction. That is about 1.09% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.7 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 16:00 UTC, and Sunday is the busiest day of the week. Of the 80 posts sampled, 85% carry an image or video and 100% link out. The account's strongest tracked post pulled 538 interactions, about 30x its own typical post.

What is McKinsey Global Institute's engagement rate on X?
McKinsey Global Institute (@McKinsey_MGI) has an engagement rate of 0.009%, based on the median interactions across 80 original posts from the last 30 days against 206,986 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.009%, McKinsey Global Institute sits above the 10th percentile of the 205,676 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @McKinsey_MGI have real engagement?
Its engagement rate beats 22% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the bottom quarter for its size group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @McKinsey_MGI post?
Most posts go out around 16:00 UTC, and Sunday is its busiest day, at roughly 2.67 posts per day across the measured window.

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