Tony Restell engagement report
@tonyrestell - 48K followers on X
Measured over 21 original posts from a 30-day window, last computed on October 22, 2026.
Engagement
A typical post picks up 6 interactions against 48K followers, an engagement rate of 0.012%. Measured over 21 original posts, its engagement rate beats 12% of 20,445 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 347 times each, and 1.73% of those impressions turn into an interaction. That is about 0.716% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.87 post a day over the last 30 days, with activity on roughly 67% of days. Most posts go out around 07:00 UTC, and Thursday is the busiest day of the week. Of the 21 posts sampled, 10% carry an image or video and 24% link out. The account's strongest tracked post pulled 13 interactions, about 2.2x its own typical post.
Measured over 21 original posts from a 30-day window, last computed on October 22, 2026.
Compared with accounts its own size
Tony Restell's engagement rate beats 12% of the tracked X accounts closest to it in follower count (20,445 accounts, accounts of similar size (decile 4 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 47% 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 0.012%, Tony Restell sits above the 10th percentile of the 204,956 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 07:00 UTC, and Thursday 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% | 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 10% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 24% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 10% 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.
- 24% 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 512 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
- Oct 15, 20262.2x their median
A business owner told me yesterday he was thrilled to be getting consistent inbound leads through ChatGPT. Then we pulled up his site analysis together. His expression completely changed when he realised his business had done absolutely nothing to be optimised for AI search. They hadn't taken a single step to actually be recommended by AI. Those leads were arriving entirely by accident. Which led to a very exciting conversation: If that is the volume of leads coming in from zero optimisation through just one AI engine, imagine how many come through once you are properly optimised to get recommended by ChatGPT, Claude, Perplexity, and Google AI!! His eyes lit up at the potential upside! So many founders are stumbling into AI enquiries by pure luck, without realising how much bigger the opportunity actually is. Are you?
- Apr 18, 20262.0x their median
A question for Founders. Are your team active on social media just for a bit of brand visibility... or because you actually want it to generate new business wins? If the latter, take 90 seconds to watch this: https://t.co/Y0MVgQGF88
- Oct 12, 20261.8x their median
Two of our clients became the top recommendation in Google AI answers in less than a month. With traditional SEO, seeing meaningful results usually took 6 to 12 months. With AI search optimisation (AEO), the turnaround can be startlingly fast. Before checking your own results, make sure you test in an incognito window or use an independent AI tracking tool. Otherwise your own search history will skew what you see. Here is the 3-step blueprint we used to get those results: 1. Homepage Schema and Technical Signposting Your website needs bespoke Schema code on every page. AI crawlers use this markup to understand what your business specialises in and whether you are a credible authority. The critical piece on the homepage is the "sameAs" schema markup. You want to explicitly link your business entity to your LinkedIn company page and your personal founder profile. When external publications or LinkedIn articles quote you as an industry expert, that schema allows AI engines to map that credibility straight back to your company website. Behind the scenes, we also turn existing pages into FAQ resources answering 3 to 5 high-intent buyer questions in the code. You do not need to publish endless new blog posts to give AI crawlers the structured answers they need. 2. External Validation on LinkedIn AI engines do not just take your website's word for it. They prioritise third-party consensus. LinkedIn articles, newsletters, Reddit, and review sites are among the heaviest crawled sources for AI answers. Personal founder profiles carry significantly more weight with AI crawlers than faceless corporate company pages. Thoughtful, balanced commentary on your personal profile builds the external proof AI engines look for when deciding who to recommend. 3. Answering Early Buyer-Intent Questions You need to dominate queries like "who is the best [provider]". You also need to answer the early research questions buyers ask before seeking vendors. When you answer both types of buyer-intent queries early, your business becomes the clear answer for AI search engines to recommend. (and I say that as an agency founder who does this daily)
- Sep 17, 20261.7x their median
Cultivating a modest number of warm relationships outperforms massive cold outreach sequences for B2B firms every time. At least, that's been my experience. Pumping generic email or DM sequences into people's inboxes burns the market before conversations even have a chance to start. Suggested action for this coming week: focus on 20 to 30 high-value relationships and focus on adding value and being conversational first. Are you still relying on high-volume cold outreach, or have you already shifted to relationship-led selling?
- Sep 15, 20261.7x their median
Let's quickly take a look at what can be achieved on Google, ChatGPT and the like if you invest just a few weeks getting your firm recommended. Who else has been having success with this? https://t.co/ffYWuOul9g
- Sep 8, 20261.7x their median
Most B2B websites are completely invisible to AI search engines. When a prospective client asks an AI tool to recommend firms in your industry, the tool does not evaluate your site on keyword density. It looks for consensus, structured context, and third-party proof. Here is the 3-step playbook we used at Social Hire to get recommended across major AI engines: 1. Schema markup AI crawlers need explicit structured context. We added detailed schema that tells machines who we are, sectors we serve, our areas of expertise, and the specific challenges we help address. 2. External evidence and citations AI models cross-reference what you say about yourself against third-party platforms. Client reviews, directory listings, media and podcast appearances, Reddit and Quora brand mentions, and consistent LinkedIn presence all feed each model's confidence in your business. 3. Answering high-intent client questions directly Instead of writing generic SEO keyword fluff, we structured our content around the actual sales call objections and triggers our ideal clients voice. Clear, direct answers upfront give AI systems the factual responses they want to cite. When you give AI search models clean structure and external verification, getting recommended becomes predictable. And from those recommendations then flows a stream of warm leads. It's going to be a busy Q4 ahead!! P.S. our new service offering just this can be found at: https://t.co/mRgh0Adpvo
- Sep 7, 20261.7x their median
In under 90 days, Social Hire went from barely ranking on traditional Google search to being recommended by all 6 major AI engines. When prospective clients ask ChatGPT, Claude, Perplexity, Copilot, Gemini, or Grok to recommend the best B2B social media agency for their sector, our name appears in the shortlist. This shift was important for us to adapt to, because B2B buyers have changed how they research suppliers. Instead of browsing through Google search links and sponsored ads, senior decision-makers are typing detailed prompts into AI search tools. They ask who has proven case studies in their niche, who has strong client reviews, and who they should engage. If an AI engine cannot find clear, structured evidence of what you do, you'll find you aren't recommended in those answers. We rebuilt how our agency is indexed across the web. The result has been inbound enquiries from buyers who were already sold on working with us before they booked the call. P.S. If you want to see how we now set this up for our B2B clients, the details are here: https://t.co/mRgh0Adpvo
- Oct 16, 20261.5x their median
Hearing B2B founders panic when post reach drops always surprises me. If you sell a £20k service, chasing 50,000 views makes zero sense. You only need 20 ideal prospects seeing your perspective and starting conversations. (and I say that having run Social Hire for 13 years)
- Oct 14, 20261.5x their median
Join me for this! How To Be The No.1 Firm Recommended in AI Answers You'll leave with a much better idea of how to get your firm being recommended by Google, ChatGPT, etc. Details & registration via LinkedIn: https://t.co/tZjpaAtJIQ https://t.co/pY4nCwO0Uz
- Oct 2, 20261.5x their median
Answer Engine Optimisation doesn't care about key phrases. I was discussing this with Lynnaire Johnston on a podcast recently, and the shift for B2B founders is massive. Traditional SEO forced everyone into an endless race to rank for isolated search queries. AEO works completely differently. You win by owning the big-picture answer in your niche. At Social Hire, our focus is making sure Google AI Overviews, ChatGPT, and Claude know without doubt that we are the go-to social media agency for professional services like recruitment agencies and consultancies. Once you establish that foundational positioning, prompt phrasing stops mattering. Whether a prospective buyer asks "Who do you recommend for...?", "Name the top...", or "Which agency should I hire for...?", the AI serves your firm up in its answer. You've become the definitive recommendation. So - are you building your presence to be the obvious answer AI engines suggest, or are you still spending hours chasing fragmented keywords?
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 48K followers, an engagement rate of 0.012%. Measured over 21 original posts, its engagement rate beats 12% of 20,445 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 347 times each, and 1.73% of those impressions turn into an interaction. That is about 0.716% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.87 post a day over the last 30 days, with activity on roughly 67% of days. Most posts go out around 07:00 UTC, and Thursday is the busiest day of the week. Of the 21 posts sampled, 10% carry an image or video and 24% link out. The account's strongest tracked post pulled 13 interactions, about 2.2x its own typical post.
- What is Tony Restell's engagement rate on X?
- Tony Restell (@tonyrestell) has an engagement rate of 0.012%, based on the median interactions across 21 original posts from the last 30 days against 48,477 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.012%, Tony Restell sits above the 10th percentile of the 204,956 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 @tonyrestell have real engagement?
- Its engagement rate beats 12% of the tracked X accounts closest to it in follower count (20,445 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 @tonyrestell post?
- Most posts go out around 07:00 UTC, and Thursday is its busiest day, at roughly 0.87 posts per day across the measured window.