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Knowledge at Wharton engagement report

@whartonknows - 111K followers on X

Measured over 10 original posts from a 30-day window, last computed on October 10, 2026.

Engagement

Bottom quarter for its size
Per follower
0.005%
of 111K followers
Per impression
0.601%
915 views on a typical post
Reach
0.83%
of its followers see a post
Typical post
6
interactions (median)
Saved
0.055%
0 bookmarks on a typical post
Posting rate
0.33/day
active 33% of days
Peak time
15:00 UTC
Tuesday

A typical post picks up 6 interactions against 111K followers, an engagement rate of 0.005%. Measured over 10 original posts, its engagement rate beats 13% of 21,185 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 915 times each, and 0.601% of those impressions turn into an interaction. That is about 0.827% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.33 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 15:00 UTC, and Tuesday is the busiest day of the week. Of the 10 posts sampled, 90% carry an image or video and 100% link out. The account's strongest tracked post pulled 42 interactions, about 7.0x its own typical post.

Measured over 10 original posts from a 30-day window, last computed on October 10, 2026.

Compared with accounts its own size

Knowledge at Wharton's engagement rate beats 13% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 8 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 29% 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 0.005%, Knowledge at Wharton sits above the 10th percentile of the 212,656 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.025%.

p100.004%
p250.025%
p50 (median)0.146%
p750.697%
p902.61%
p9982.9%
Engagement rate as a share of followers, across the 212,656 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,418 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 percentile0.025%
50th percentile0.146%
75th percentile0.697%
90th percentile2.61%
99th percentile82.9%

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 15:00 UTC, and Tuesday 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: 15:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 15:00 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: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Tuesday
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 video90% of posts+111%+108% to +115%34K
Outbound link100% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 90% 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 292 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 22, 20257.0x their median

    🎙️ Get to know our five podcasts, where @Wharton professors bring you insights every week on the biggest issues shaping business: https://t.co/grAn9eVTtY Featuring these hosts and many more experts: @EBradlow @BCMassey @AdiWyner @BarbaraKahn @AmReed2 @KHosanagar @SNetesin https://t.co/35GMyIqvKy

    2793310K viewsView on X
  • Jul 24, 20265.8x their median

    Many assume the fastest path to expertise is to narrow your focus as early as possible. @DavidEpstein, author of the new book, "Inside the Box: How Constraints Make Us Better," argues on the latest @WMoneyball podcast that the opposite may often be true when it comes to sports. https://t.co/872c1NsCXY

    2015002.0K viewsView on X
  • Jan 13, 20264.7x their median

    AI is accelerating the shift from a role-based labor market toward a skills-based economy. Findings from the new Wharton-Accenture Skills Index from @WhartonAIAI reveal a mismatch between what workers emphasize and what employers actually reward. https://t.co/TAZgQYV5AM https://t.co/jszebZvitI

    1115111.6K viewsView on X
  • Jan 24, 20263.8x their median

    In a competitive bidding war, should you really play to win? @ChicagoBooth's @R_Thaler & @AlexolegImas explained the “winner’s curse,” the tendency for winning bidders to overpay, at a @BehaviorChange event w/ @Wharton's @AngelaDuckw & @Katy_Milkman. 📝: https://t.co/b06jSQXGuQ https://t.co/dh9JQdcmyr

    166103.2K viewsView on X
  • May 6, 20263.5x their median

    Even with more data, more scouting, and better tools, NFL teams still struggle to predict which college players will perform best as pros. #NFLDraft On @WMoneyball, @R_Thaler explains the striking "better than the next guy" stat uncovered in research with @Wharton's @BCMassey. https://t.co/7pmfHLMEbS

    173102.0K viewsView on X
  • Aug 27, 20262.8x their median

    As valuations for sports franchises like the Lakers soar, @Wharton professor Kenneth Shropshire explains to dean @ErikaHJames why teams have evolved into an increasingly attractive asset class, and how sophisticated management and technology are creating opportunities for growth. https://t.co/iUp6nPhJbk

    95211.5K viewsView on X
  • Dec 28, 20252.8x their median

    What's in store for AI in 2026? Our annual @Wharton faculty predictions series opens with @EMollick looking back at developments from the past year and ahead at what he'll be monitoring in the year to come. Watch the This Week in Business podcast: https://t.co/TDC5LJINLw https://t.co/Osn0pjFyrZ

    97102.0K viewsView on X
  • Sep 4, 20262.7x their median

    Financial literacy shapes how we prepare for retirement — but it’s only part of the equation. New research coauthored by @Wharton's @OS_Mitchell examines how financial literacy and trust influence retirement saving and investment decisions. https://t.co/sMAxSWatcM

    106001.3K viewsView on X
  • Feb 10, 20262.7x their median

    Which #SBLX commercial stood out to the @Wharton Marketing Matters hosts? We asked @AmReed2 & @BarbaraKahn for their takes and the answer was clear: @DunkinDonuts'​ "Good Will Dunkin'" ad featuring stars of the past tapped into nostalgia and pop culture aligned with its brand. https://t.co/PkwFJ9BPjW

    105011.9K viewsView on X
  • Jan 6, 20262.7x their median

    What can a calendar reset do for your goals? @Wharton's @Katy_Milkman, co-director of @BehaviorChange, has found that time markers signal new beginnings and help us forgive our former setbacks. Tune in to our first Ripple Effect podcast of 2026: https://t.co/0MXk88YCdv https://t.co/1ipKkqnFjv

    105101.9K 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 6 interactions against 111K followers, an engagement rate of 0.005%. Measured over 10 original posts, its engagement rate beats 13% of 21,185 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 915 times each, and 0.601% of those impressions turn into an interaction. That is about 0.827% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.33 posts a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 15:00 UTC, and Tuesday is the busiest day of the week. Of the 10 posts sampled, 90% carry an image or video and 100% link out. The account's strongest tracked post pulled 42 interactions, about 7.0x its own typical post.

What is Knowledge at Wharton's engagement rate on X?
Knowledge at Wharton (@whartonknows) has an engagement rate of 0.005%, based on the median interactions across 10 original posts from the last 30 days against 110,603 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.005%, Knowledge at Wharton sits above the 10th percentile of the 212,656 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 @whartonknows have real engagement?
Its engagement rate beats 13% of the tracked X accounts closest to it in follower count (21,185 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 @whartonknows post?
Most posts go out around 15:00 UTC, and Tuesday is its busiest day, at roughly 0.33 posts per day across the measured window.

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