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Brian D. Evans engagement report

@BrianDEvans - 1.3M followers on X

Measured over 3 original posts from a 30-day window, last computed on October 29, 2026.

Engagement

Per follower
0.067%
of 1.3M followers
Per impression
0.098%
889K views on a typical post
Reach
68.4%
of its followers see a post
Typical post
873
interactions (median)
Saved
0.005%
49 bookmarks on a typical post
Posting rate
0.17/day
active 17% of days
Peak time
16:00 UTC
Monday

Early reading. We have captured 3 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 873 interactions against 1.3M followers, an engagement rate of 0.067%. Posts are seen about 889K times each, and 0.098% of those impressions turn into an interaction. That is about 68.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.17 posts a day over the last 30 days, though only 17% of days saw any activity at all. Most posts go out around 16:00 UTC, and Monday is the busiest day of the week. Of the 3 posts sampled, 33% link out. The account's strongest tracked post pulled 70K interactions, about 68x its own typical post. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 3 original posts from a 30-day window, last computed on October 29, 2026.

Where this sits in the catalog

At 0.067%, Brian D. Evans sits above the 25th percentile of the 212,146 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.

p100.004%
p250.025%
p50 (median)0.146%
p750.694%
p902.61%
p9983.1%
Engagement rate as a share of followers, across the 212,146 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,455 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 percentile0.694%
90th percentile2.61%
99th percentile83.1%

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 Monday 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: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
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 video0% of posts+111%+108% to +115%34K
Outbound link33% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 0% 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.
  • 33% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
  • Its average post runs 246 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.

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

  • Jun 5, 202668x their median

    never waste a good crisis https://t.co/yXxqE7xCMC

    66K3.1K1.1K4643.3M viewsView on X
  • Jun 23, 202630x their median

    The world you were born in no longer exists https://t.co/KcRCc2abUD

    30K919159741.2M viewsView on X
  • May 4, 202611x their median

    You are your own worst enemy. You waste precious time dreaming of the future instead of engaging in the present. Since nothing seems urgent to you, you are only half involved in what you do. The only way to change is through action and outside pressure.

    15K2.4K18546306K viewsView on X
  • Jun 13, 202618x their median

    Nobody teaches you that discipline feels like punishment until the results start feeling like freedom

    12K2.1K165105848K viewsView on X
  • Jun 14, 202618x their median

    How to Earn a Billion Dollars: https://t.co/WeWBUkKym6

    12K1.5K5765293.7M viewsView on X
  • Jun 27, 202611x their median

    .@danawhite says one of the keys to longevity is to block out all negativity: “It never even crosses my mind that something's not going to work. I just keep going until it does work.” “There's this Bruce Lee quote where he says, ‘Never say negative things about yourself or what you're working on even if you're joking, because your body doesn't know the difference.’” “I never take in any negativity.”

    9.8K1.1K1341181.7M viewsView on X
  • Oct 22, 202610x their median

    AI isn't making everyone better. It's making a small group of people ridiculously hard to compete with. https://t.co/H8Qzd0OWbx

    8.2K44319022921K viewsView on X
  • Jul 28, 20269.3x their median

    Game theory explains why improving yourself rarely fixes your outcomes. People keep treating their own skills and discipline as a dominant variable because it's the one they can consciously control. They end up running never-ending optimizations but leave the whole structure around them untouched. Suddenly, they are the shiniest object in the room, but it gets them nowhere. That's because a diamond in the mud is still part of the mud. Cleaning it and putting it back to where you found it changes absolutely nothing. Hence, you must change the structure. Swipe the whole room clean; toss out the junk. Ask yourself which environment converts what you already have into a return and what it would cost to move there. Don't spend a decade improving yourself while covered in filth. The structure around you either works for you or against you. There is no middle ground.

    6.9K9837954215K viewsView on X
  • Mar 15, 20266.6x their median

    My conversation with Marc Andreessen (@pmarca), co-founder of @a16z and Netscape. 0:00 Caffeine Heart Scare 0:56 Zero Introspection Mindset 3:24 Psychedelics and Founders 4:54 Motivation Beyond Happiness 7:18 Tech as Progress Engine 10:27 Founders Versus Managers 20:01 HP Intel Founder Legacy 21:32 Why Start the Firm 24:14 Venture Barbell Theory 28:57 JP Morgan Boutique Banking 30:02 Religion Split Wall Street 30:41 Barbell of Banking 31:42 Allen & Company Model 33:16 Planning the VC Firm 33:45 CAA Playbook Lessons 36:49 First Principles vs. Status Quo 39:03 Scaling Venture Capital 40:37 Private Equity and Mad Men 42:52 Valley Shifts to Full Stack 45:59 Meeting Jim Clark 48:53 Founder vs. Manager at SGI 54:20 Recruiting Dinner Story 56:58 Starting the Next Company 57:57 Nintendo Online Gamble 58:33 Building Mosaic Browser 59:45 NSFnet Commercial Ban 1:01:28 Eternal September Shift 1:03:11 Spam and Web Controversy 1:04:49 Mosaic Tech Support Flood 1:07:49 Netscape Business Model 1:09:05 Early Internet Skepticism 1:11:15 Moral Panic Pattern 1:13:08 Bicycle Face Story 1:14:48 Music Panic Examples 1:18:12 Lessons from Jim Clark 1:19:36 Clark Versus Barksdale 1:21:22 Tesla Versus Edison 1:23:00 Edison Digression Setup 1:23:13 AI Forecasting Myths 1:23:43 Edison Phonograph Lesson 1:25:11 Netscape Two Jims 1:29:11 Bottling Innovation 1:31:44 Elon Management Code 1:32:24 IBM Big Gray Cloud 1:37:12 Engineer First Truth 1:38:28 Bottlenecks and Speed 1:42:46 Milli Elon Metric 1:47:20 Starlink Side Project 1:49:10 Closing Includes paid partnerships.

    4.9K6061881116.1M viewsView on X
  • Jul 30, 20266.4x their median

    The scariest part isn't that you haven't started. It's that you've convinced yourself you have.

    5.2K371547912K 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 873 interactions against 1.3M followers, an engagement rate of 0.067%. Posts are seen about 889K times each, and 0.098% of those impressions turn into an interaction. That is about 68.4% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.17 posts a day over the last 30 days, though only 17% of days saw any activity at all. Most posts go out around 16:00 UTC, and Monday is the busiest day of the week. Of the 3 posts sampled, 33% link out. The account's strongest tracked post pulled 70K interactions, about 68x its own typical post. Only 3 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is Brian D. Evans's engagement rate on X?
Brian D. Evans (@BrianDEvans) has an engagement rate of 0.067%, based on the median interactions across 3 original posts from the last 30 days against 1,299,820 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.067%, Brian D. Evans sits above the 25th percentile of the 212,146 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 @BrianDEvans have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @BrianDEvans post?
Most posts go out around 16:00 UTC, and Monday is its busiest day, at roughly 0.17 posts per day across the measured window.

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