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Harsh Makadia engagement report

@MakadiaHarsh - 228K followers on X

Measured over 63 original posts from a 30-day window, last computed on October 1, 2026.

Engagement

Bottom quarter for its size
Per follower
0.009%
of 228K followers
Per impression
0.311%
6.4K views on a typical post
Reach
2.81%
of its followers see a post
Typical post
20
interactions (median)
Saved
0.047%
3 bookmarks on a typical post
Posting rate
2.97/day
active 100% of days
Peak time
04:00 UTC
Tuesday

A typical post picks up 20 interactions against 228K followers, an engagement rate of 0.009%. Measured over 63 original posts, its engagement rate beats 24% of 15,519 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 6.4K times each, and 0.311% of those impressions turn into an interaction. That is about 2.81% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 04:00 UTC, and Tuesday is the busiest day of the week. Of the 63 posts sampled, 14% carry an image or video and 21% are part of a thread. The account's strongest tracked post pulled 800 interactions, about 40x its own typical post.

Measured over 63 original posts from a 30-day window, last computed on October 1, 2026.

Compared with accounts its own size

Harsh Makadia's engagement rate beats 24% of the tracked X accounts closest to it in follower count (15,519 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 19% 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%, Harsh Makadia sits above the 10th percentile of the 156,596 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.022%.

p100.003%
p250.022%
p50 (median)0.127%
p750.604%
p902.32%
p9983.4%
Engagement rate as a share of followers, across the 156,596 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 26,062 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 percentile0.003%
25th percentile0.022%
50th percentile0.127%
75th percentile0.604%
90th percentile2.32%
99th percentile83.4%

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 04:00 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: 04:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 04:00 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 video14% of posts+111%+108% to +115%34K
Outbound link3% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 14% 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.
  • 3% 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 406 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 4, 202640x their median

    AI writes great code. It designs terrible landing pages. So I fixed it. Free skill + full video so you can run it yourself 👇 https://t.co/idy9ygSJlO

    70430579108K viewsView on X
  • Aug 27, 20265.5x their median

    Start with one job and one agent. Clear the newsletter pile. Unsubscribe the ones I have not opened in 30 days. Leave anything that looks personal. When that comes back finished, you already have a win, and you still have a Bot to talk to for the rest of the day.

    94211210K viewsView on X
  • Sep 13, 20263.7x their median

    your AI agent doesn't care which provider fulfills the token. your margin does. if API spend is a real line on your P&L, the way you BUY the models matters as much as which ones you pick. you're paying retail for AI tokens. https://t.co/60zfAszyrh is the wholesale door. more ↓

    54164033K viewsView on X
  • Aug 27, 20262.6x their median

    My current agency preferred stack: VA: Victor AI Chat: Slack Video: Loom Forms: Tally LLM: LiteLLM Repo: GitHub Leads: Arc AI Coding: Codex Editor: Cursor Projects: Jira Agents: Grok Bot Research: Claude Booking: Cal .com Inbox: Superhuman Database: Supabase Hosting: Cloudflare Scraping: Firecrawl Voice / SMS: Twilio Notetaker: Circleback Outreach: Smartlead Automations: Activepieces Tool connectivity: Composio Voice agents: ElevenLabs/ Retell AI

    4111107.5K viewsView on X
  • Sep 14, 20262.3x their median

    The future will not belong to businesses using the most AI. It will belong to businesses that apply AI to the most expensive problems.

    2921407.2K viewsView on X
  • Sep 16, 20262.1x their median

    The best AI system is not the one that sounds the most intelligent. It is the one that makes the fewest expensive mistakes.

    2621507.3K viewsView on X
  • Sep 11, 20262.1x their median

    A process is ready for automation when: The trigger is clear. The inputs are known. The output is defined. The rules are repeatable. The exceptions are visible. The result can be measured. If the process fails these tests, fix the thinking first.

    296707.0K viewsView on X
  • Sep 10, 20262.1x their median

    A system that only works when the founder is available is not a system. It is founder dependency with better branding.

    2531407.3K viewsView on X
  • Sep 28, 20262.0x their median

    sent a cold email to a transportation company last week. no pitch deck. just a link to their website, already rebuilt. their current site was from 2014. i showed them what it could look like. it took me 20 minutes. they replied in an hour. people ignore offers. they don't ignore their own business, improved.

    2801216.8K viewsView on X
  • Sep 27, 20262.0x their median

    closed a $5,000 client last week with one small trick. went on discovery call with a telecom business. i listened to every problem they had and what they wanted. most agencies send a scope doc and a price after that call. i sent the scope, the price, and a working POC that solved their biggest problem. it took me 4 hours to build. they signed the next day. it's hard to say no to something already working in front of you.

    2411607.1K 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 20 interactions against 228K followers, an engagement rate of 0.009%. Measured over 63 original posts, its engagement rate beats 24% of 15,519 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 6.4K times each, and 0.311% of those impressions turn into an interaction. That is about 2.81% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 3 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 04:00 UTC, and Tuesday is the busiest day of the week. Of the 63 posts sampled, 14% carry an image or video and 21% are part of a thread. The account's strongest tracked post pulled 800 interactions, about 40x its own typical post.

What is Harsh Makadia's engagement rate on X?
Harsh Makadia (@MakadiaHarsh) has an engagement rate of 0.009%, based on the median interactions across 63 original posts from the last 30 days against 228,264 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.009%, Harsh Makadia sits above the 10th percentile of the 156,596 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 @MakadiaHarsh have real engagement?
Its engagement rate beats 24% of the tracked X accounts closest to it in follower count (15,519 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 @MakadiaHarsh post?
Most posts go out around 04:00 UTC, and Tuesday is its busiest day, at roughly 2.97 posts per day across the measured window.

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