Grant Miller engagement report
@AIGuide_ - 510K followers on X
Measured over 14 original posts from a 30-day window, last computed on August 27, 2026.
Engagement
A typical post picks up 6 interactions against 510K followers, an engagement rate of 0.001%. Measured over 14 original posts, its engagement rate beats 10% of 3,810 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 5.7K times each, and 0.114% of those impressions turn into an interaction. That is about 1.11% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.4 post a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 03:00 UTC, and Wednesday is the busiest day of the week. Of the 14 posts sampled, 21% carry an image or video. The account's strongest tracked post pulled 206 interactions, about 34x its own typical post.
Measured over 14 original posts from a 30-day window, last computed on August 27, 2026.
Compared with accounts its own size
Grant Miller's engagement rate beats 10% of the tracked X accounts closest to it in follower count (3,810 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 9% 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%, Grant Miller sits below the 10th percentile of the 36,960 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.012%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.435% |
| 90th percentile | 2.10% |
| 99th percentile | 159.8% |
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 03:00 UTC, and Wednesday 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 51K |
| 01:00 UTC | -2% | 52K |
| 02:00 UTC | -3% | 51K |
| 03:00 UTC | -4% | 54K |
| 04:00 UTC | -6% | 44K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 49K |
| 07:00 UTC | -5% | 53K |
| 08:00 UTC | -4% | 61K |
| 09:00 UTC | -3% | 70K |
| 10:00 UTC | -2% | 73K |
| 11:00 UTC | -3% | 79K |
| 12:00 UTC | -2% | 87K |
| 13:00 UTC | -2% | 96K |
| 14:00 UTC | -4% | 99K |
| 15:00 UTC | -2% | 102K |
| 16:00 UTC | -3% | 99K |
| 17:00 UTC | -2% | 92K |
| 18:00 UTC | -1% | 85K |
| 19:00 UTC | -2% | 80K |
| 20:00 UTC | -1% | 75K |
| 21:00 UTC | -1% | 67K |
| 22:00 UTC | -2% | 58K |
| 23:00 UTC | -1% | 52K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 233K |
| Monday | 0% | 292K |
| Tuesday | -3% | 284K |
| Wednesday | -1% | 253K |
| Thursday | -2% | 246K |
| Friday | -3% | 255K |
| Saturday | +3% | 229K |
Best tweets
- Aug 26, 202634x their median
Introducing Commas Webinars Your buyer never leaves the room to pay. • In-room checkout • Minute-by-minute revenue analytics • Live, evergreen or hybrid • Create polls and drop offers • Watch sales land while you present • Bring your viewers on screen The first webinar platform with checkout and payments built in, designed to help you make more commas.
- Aug 27, 20262.5x their median
Meta, Google and Shopify just opened five marketing businesses you can start with one client and a Claude Code login. none of them are crowded yet: 1. creative testing at volume. Meta's own plan is fully automated ad creation by end of 2026. ad production is going to $0, which makes the person who runs 500 variants a week and reads the results the most valuable seat in paid 2. search after google. AI Overviews and AI Mode are eating the clicks every SEO agency sold. all of those agencies have to be rebuilt for answer engines and almost none have started. first GEO shop in a vertical wins the vertical 3. marketing for the 30 million businesses that never had a marketer. Runable just raised $21M for an agent that runs a small business's ads, calls and emails. the cost of serving a $2M plumbing company just dropped to software 4. the two person marketing department. Shopify's hiring rule is prove AI can't do the job first, Duolingo went AI-first in a memo. the six person in-house team becomes two people running agents 5. the setup business. MaxFusion open sourced a full marketing team as a Claude skill this week. every seed startup is going to install one and none of them know how to feed it, so the person who sets it up with the company's real customer data, twenty startups at a time, is a business on its own i could do ten more everyone's posting that AI is taking marketing jobs. it's taking marketing departments, and the person who can run the agents is the department none of these need a raise or a team pick one, get the client this month, post the result
- Aug 26, 20261.5x their median
A lot of marketing influencers need to be sentenced to a year of in-house marketing at a dental office
- Aug 25, 20261.5x their median
the best thing AI did for GTM is getting founders back on discovery calls
- Aug 26, 2026
GTM research that takes a new hire a quarter, done before lunch. the way i run it w/ new clients: "research this market" is the prompt that gets you a wikipedia page. feed Claude the actual evidence: > the pricing page and changelog of every competitor, 12 months back > the 1 to 3 star G2 reviews of the top 3, all of them > the risk factors section of the biggest incumbent's 10-K > your last 20 lost-deal transcripts > job posts from your 30 best target accounts > whatever reddit or slack community your buyers complain in then ask it: "which complaint shows up in every competitor's bad reviews, and which one of them has quietly stopped fighting it" "list every claim on their homepages, then tell me which ones their own customers contradict" "who is the buyer this whole category ignores because they're annoying to sell to" that gets you the objection you'll hear on every call, the segment no competitor is selling to, and the one claim none of them can make then make it play the other side: "write the memo the incumbent's head of product sends the day they hear about us" what comes out is a hypothesis w/ receipts. book 10 calls w/ the segment it found and see if the objection shows up by call 3
- Aug 27, 2026
Roy Lee's 5 step plan to make $80k a month with AI video ads: 1. find 100 VC-backed software companies 2. make each one a free ad 3. email them every day 4. when one prints, put yourself on a $10k a month retainer for more 5. do it 8 times 8 x $10k is $80k a month, and he says he'd sign that deal himself the free ad is the pitch. a 20 second ad about their own product gets watched by a founder who'd never open the email
- Aug 26, 2026
if you're waiting for the AI market to settle before you sell, watch this. it's from 2015 "AI will probably most likely lead to the end of the world, but in the meantime there'll be great companies" the category was just as unsettled then. he built the company anyway, and the founders waiting for it to settle now are losing deals to the ones who don't wait
- Aug 25, 2026
give one agent one job: telling you what changed one slack message every morning, pulled from the six places your customers are already talking: 1. Gong or Fireflies: what buyers said on calls this week 2. HubSpot or Attio: closed-lost notes and stage changes 3. Stripe: upgrades, downgrades, churn 4. PostHog or Amplitude: which features got used and which got abandoned 5. Intercom or Zendesk: what got complained about 6. competitor changelogs and their G2 reviews: what buyers are asking for that you haven't built the rule that makes it work: it can only write about what's different from last week. if nothing moved it says nothing moved. a recap is what every other agent already does, this one only gets to talk about deltas This will catch things like: 1. "consolidating" came up on 4 calls this week, last month it was 0 2. 3 of the 5 churns never connected the integration 3. losses to one competitor went from 1 a quarter to 3 this month 4. trial signups from fintech doubled and nobody targeted them 5. export tickets tripled the week after the pricing change a number on its own tells you nothing, the same number next to last week's tells you what to do every message has three parts, what moved, who said it or did it, and the one decision this week it should change. like: "4 discovery calls mentioned a competitor we hadn't heard in a quarter, all 4 in fintech, 2 asked about soc 2 in the first ten minutes. that's a positioning gap in one segment, so i'd put the security page in front of fintech traffic before touching outbound volume" if it says nothing changed three mornings in a row, that's information too
- Aug 27, 2026
this is NOT the time to build another tool nobody asked for... you're sitting on more leverage than any marketer in history had with a team of 20... research, copy, outbound, creative, all of it, in a $200/month login the window won't stay this empty so lock in on SELLING, on turning AI into clients that pay, nothing else here are 5 plays that change how much you make this quarter: - deep research on your niche's top offers, their reviews and your own sales calls, into a knowledge base that writes copy in the customer's words - scrape the leads, read the competitors' 1 star reviews, build outbound that gets replies - post the results every day and grow an audience on receipts - take the free distribution, Reddit is one of the most cited sources in AI answers now, answer questions there for 30 days - write the pages that answer what buyers ask ChatGPT, Google's AI Overviews are taking the clicks anyway
- Aug 26, 2026
SaaS founders, the best thing to build in Claude Code this week: an automated review miner that writes your ad hooks in your customers' words Here's the exact system I used: 1. tools (10 min) Firecrawl MCP for anything public: competitor changelogs, pricing pages, reddit, the G2 pages Your own exports: lost-deal transcripts from Gong or Fireflies, Intercom tickets, churn surveys 2. competitors Pull the 1 star and 3 star G2 reviews for the three you lose to most, skip the 5s 1 stars are the switching pitch, paste them into the ad angle doc as written 3 stars are the features they keep promising, that's the gap you sell into 3. your own Claude clusters the tickets, churn surveys and lost-deal calls by theme, sorted by count Most repeated praise becomes the homepage h1, in their words Most repeated complaint goes to the top of the sprint before the next renewal 4. off your own turf Point Firecrawl at the subreddits and slack groups your buyers complain in Reddit is the day they chose someone else over you, and that reason is the cold email opener 5. how it compounds Everything lands in positioning.md and objections.md in the repo, and Claude Code reads both before it drafts an ad, a sequence or a homepage change Every ad after that starts from something a customer said
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 510K followers, an engagement rate of 0.001%. Measured over 14 original posts, its engagement rate beats 10% of 3,810 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 5.7K times each, and 0.114% of those impressions turn into an interaction. That is about 1.11% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 1.4 post a day over the last 30 days, though only 10% of days saw any activity at all. Most posts go out around 03:00 UTC, and Wednesday is the busiest day of the week. Of the 14 posts sampled, 21% carry an image or video. The account's strongest tracked post pulled 206 interactions, about 34x its own typical post.
- What is Grant Miller's engagement rate on X?
- Grant Miller (@AIGuide_) has an engagement rate of 0.001%, based on the median interactions across 14 original posts from the last 30 days against 510,394 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.001%, Grant Miller sits below the 10th percentile of the 36,960 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 @AIGuide_ have real engagement?
- Its engagement rate beats 10% of the tracked X accounts closest to it in follower count (3,810 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 @AIGuide_ post?
- Most posts go out around 03:00 UTC, and Wednesday is its busiest day, at roughly 1.37 posts per day across the measured window.