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SitePoint engagement report

@sitepointdotcom - 106K followers on X

Measured over 13 original posts from a 30-day window, last computed on October 13, 2026.

Engagement

Bottom 10% for its size
Per follower
0.001%
of 106K followers
Per impression
0.15%
665 views on a typical post
Reach
0.63%
of its followers see a post
Typical post
1
interactions (median)
Saved
0%
0 bookmarks on a typical post
Posting rate
0.5/day
active 40% of days
Peak time
08:00 UTC
Monday

A typical post picks up 1 interaction against 106K followers, an engagement rate of 0.001%. Measured over 13 original posts, its engagement rate beats 3% 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 665 times each, and 0.15% of those impressions turn into an interaction. That is about 0.63% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.5 post a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 08:00 UTC, and Monday is the busiest day of the week. Of the 13 posts sampled, 100% carry an image or video, 15% are part of a thread and 85% link out. The account's strongest tracked post pulled 10 interactions, about 10x its own typical post. Recurring topics include #sitepoint, #nodejs, #seo.

Measured over 13 original posts from a 30-day window, last computed on October 13, 2026. Recurring tags: #sitepoint, #nodejs, #seo.

Compared with accounts its own size

SitePoint's engagement rate beats 3% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 7 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 8% 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 0.001%, SitePoint sits below the 10th percentile of the 212,270 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%
p750.695%
p902.61%
p9983.1%
Engagement rate as a share of followers, across the 212,270 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 percentile0.695%
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 08:00 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: 08:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 08:00 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 video100% of posts+111%+108% to +115%34K
Outbound link85% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 100% 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.
  • 85% 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 285 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

  • Jul 22, 202610x their median

    Running a local LLM is easy. Running it in production is a different story. Ollama is a great starting point, but production deployments need more than just inference. Load balancing, caching, monitoring, and health checks are what make self-hosted AI reliable at scale. https://t.co/hlj6rhaTJ3

    7210702 viewsView on X
  • Sep 2, 20266.0x their median

    Responsive images can lose sharpness, crop badly, or load files that are too large. Test them across real breakpoints to catch quality and performance issues before launch. Read more: https://t.co/pzLNUw3jss #WebDevelopment #Frontend #SitePoint https://t.co/cfTCyp9jNC

    6000845 viewsView on X
  • Jul 17, 20266.0x their median

    The best AI systems don't replace people. They work alongside them. Human-in-the-Loop keeps critical decisions in human hands while AI handles speed and routine tasks. That's how more reliable systems are built. https://t.co/iImrj0NmP3

    4110429 viewsView on X
  • Aug 7, 20265.0x their median

    Not every writing tool is built the same. From distraction-free writing to Markdown support and real-time collaboration, this comparison explores six online editors and what each one does best. Read more: 🔗https://t.co/AI2dsvL0iD https://t.co/CKYh7iIO1n

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  • Jul 20, 20265.0x their median

    Generative AI video is quickly becoming a standard feature in modern web apps. But integrating a video API takes more than a single request. From async workflows to job tracking and a smooth user experience, there are a few key pieces every developer should get right. ⬇️⬇️⬇️ https://t.co/TcXZqtnYYz

    3110522 viewsView on X
  • Aug 31, 20264.0x their median

    Wrong crop, low resolution, or oversized file? Instead of fixing images blindly, first identify the real problem, then choose the right frontend solution. A practical framework for better image decisions: 🔗https://t.co/jf6KZH0q3q #Frontend #WebDevelopment #SitePoint https://t.co/iZxPHHmsdJ

    40001.1K viewsView on X
  • Aug 26, 20264.0x their median

    Which one should you use? 🔑 API keys for low-risk public APIs 🔐 OAuth for delegated access ⚙️ Service accounts for app identities The right choice depends on your architecture and who needs access. Read more: 🔗https://t.co/YXoGLukHf5 #APIs #Security #SitePoint https://t.co/a6U17rvKaW

    4000770 viewsView on X
  • Aug 24, 20264.0x their median

    WebSockets are fast, but real-time systems need more than speed. Learn how validation, rate limits, timeouts, and backpressure can make Node.js matching systems safer and more reliable. Read more: 🔗https://t.co/wuyZ0WNfTo #NodeJS #WebSockets #SitePoint https://t.co/BT0IGVwWbQ

    4000889 viewsView on X
  • Aug 21, 20264.0x their median

    Qwen3.8-27B can run on a single 24 GB GPU with Q4_K_M quantization, keeping your data local and cutting API costs. The guide covers setup with Ollama, LM Studio, and vLLM. Read more: https://t.co/rgcCN584rQ #AI #Qwen #LocalAI #SitePoint https://t.co/qupP6HvmhL

    4000950 viewsView on X
  • Aug 19, 20264.0x their median

    Knowing the tools isn’t enough. You need to show how you think about scale, trade-offs, failures, and architecture decisions. Here’s what’s actually worth practicing: 🔗https://t.co/Ep891wtNdj #SystemDesign #DataEngineering #SitePoint https://t.co/u2GRn9Kawu

    3100760 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.

Recurring topics

#sitepoint#nodejs#seo#automation#javascript

The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.

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Reading these numbers

A typical post picks up 1 interaction against 106K followers, an engagement rate of 0.001%. Measured over 13 original posts, its engagement rate beats 3% 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 665 times each, and 0.15% of those impressions turn into an interaction. That is about 0.63% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.5 post a day over the last 30 days, though only 40% of days saw any activity at all. Most posts go out around 08:00 UTC, and Monday is the busiest day of the week. Of the 13 posts sampled, 100% carry an image or video, 15% are part of a thread and 85% link out. The account's strongest tracked post pulled 10 interactions, about 10x its own typical post. Recurring topics include #sitepoint, #nodejs, #seo.

What is SitePoint's engagement rate on X?
SitePoint (@sitepointdotcom) has an engagement rate of 0.001%, based on the median interactions across 13 original posts from the last 30 days against 105,552 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.001%, SitePoint sits below the 10th percentile of the 212,270 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 @sitepointdotcom have real engagement?
Its engagement rate beats 3% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the bottom 10% 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 @sitepointdotcom post?
Most posts go out around 08:00 UTC, and Monday is its busiest day, at roughly 0.5 posts per day across the measured window.

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