What the category publishes, what its buyers ask for, and where the two do not meet.
82 companies, 826 posts. Every engagement number fetched and counted.
The short version. Everything after this section is the evidence behind it.
Three kinds of post get the most response across the whole industry — roughly 2 to 3 times the response of an average post:
The single cheapest thing that works is how a post opens. starting the post with the word “Introducing” gets about 2.1 times the response of an average opening. Magic Hour measured that across 42 posts.
Magic Hour is writing for the wrong person. Every post was scored out of 5 on one question: would somebody who actually pays for this product care? The average is 1 out of 5. The posts are aimed at people who follow AI news — they like it and move on. They are not aimed at the person who signs off a budget.
Everyone is shouting about the same thing. “What does one video actually cost me?” is what 13% of the industry's posts are about — but only 5% of what real customers talk about. It is the most crowded message out there, and saying it louder will not win it.
Make posts about the things customers keep asking that nobody answers. Magic Hour read thousands of real conversations in public forums where these buyers talk to each other, and compared what they worry about against what companies actually post.
Three easy changes to test first. Open posts with “Introducing”, write very long (150+ words) rather than short ones, and post on Wednesday and avoid Sunday. None of these change what Magic Hour sell — only how the post is put together — so they are quick to try and easy to undo.
Check a post before it goes out. There is a tool at the bottom of this page: paste in a draft and it will tell you whether it looks like the posts that do well, and whether it is written for a buyer or for a fan.
Each company against other accounts its own size. 1.00 is exactly typical for that size; 2.00 is twice that. Top 12 of 80, then the bottom 5.
| # | Company | Followers | Posts | Index | What they post most |
|---|---|---|---|---|---|
| 1 | Bflai | 63,307 | 8 | 31.70 | Adding somebody else's AI model, Telling developers they can build on it |
| 2 | Dreamina Ai | 8,192 | 10 | 10.28 | Adding somebody else's AI model, Competitions and reposting customers' work |
| 3 | Freepik | 97,312 | 7 | 7.79 | Adding somebody else's AI model, Launching a brand-new product |
| 4 | Tavus Io | 24,188 | 11 | 6.50 | Webinars and conferences, A step-by-step how-to |
| 5 | Minimax Ai | 33,793 | 9 | 5.39 | Adding somebody else's AI model, Hinting at something before it launches |
| 6 | Akool | 71,230 | 17 | 4.89 | Webinars and conferences, Written for one industry only |
| 7 | ElevenLabs | 389,548 | 11 | 4.88 | Telling developers they can build on it, Showing how many people use it |
| 8 | Syntx Ai | 2,686 | 10 | 4.62 | Job adverts, Showing how many people use it |
| 9 | Magnific Ai | 18,932 | 9 | 3.65 | A new feature on an existing product, Launching a brand-new product |
| 10 | Suno Ai | 56,768 | 9 | 3.14 | A step-by-step how-to, Job adverts |
| 11 | Lovable Dev | 540,511 | 6 | 3.12 | A point of view about how the work is done, One named customer's story |
| 12 | Floraai | 33,865 | 10 | 3.08 | Webinars and conferences, Adding somebody else's AI model |
| · · · | |||||
| 58 | Magic Hour | 1,404 | 6 | 0.75 | Adding somebody else's AI model, A step-by-step how-to |
| · · · | |||||
| 76 | Picsart | 70,627 | 9 | 0.25 | Competitions and reposting customers' work, Webinars and conferences |
| 77 | Aragonai | 5,142 | 10 | 0.22 | Competitions and reposting customers' work, Opening with the customer's problem |
| 78 | Animaker | 110,816 | 10 | 0.22 | Competitions and reposting customers' work, A step-by-step how-to |
| 79 | Midjourney | 168,701 | 10 | 0.20 | Job adverts |
| 80 | Renderforest | 12,784 | 10 | 0.03 | A step-by-step how-to, A new feature on an existing product |
Magic Hour sits 58 of 80, at exactly 1.00 — precisely what a page its size normally gets. Not failing, not winning: average. The gap between 1.00 and the top of this table is what the rest of the report is about.
Ranking by reactions-per-follower instead would put every small page on top: pages under 2,000 followers average 7.18 reactions per thousand against 0.24 for pages over 150,000, a thirty-fold gap created by size alone. Each post is compared against posts from accounts of similar size instead.
Every kind of post, placed by how often the category writes it and how well it does. 1.00 is a typical post.
the openings
table stakes
leave these alone
where effort is being wasted
Whole corpus. Correlations, not experiments — priors for what to test.
| How the post opens | Posts | Index |
|---|---|---|
| Opens with “Introducing…” The first word announces that something is new. | 42 | 2.12 |
| Opens with “You can now…” Leads with the new thing the reader is able to do. | 5 | 1.40 |
| Opens with a number “3 million creators…” or “$0.009 per image…” | 19 | 1.11 |
| Opens by withholding “Coming Thursday” — deliberately says almost nothing. | 17 | 1.06 |
| Opens by plainly describing the thing No hook at all: the first line just states what the post is about. This is what most of the category does. | 689 | 1.00 |
| Opens with a bold or contrarian claim “Nobody needs a film crew any more” — a statement written to be argued with. | 54 | 0.94 |
| What it asks for | Posts | Index |
|---|---|---|
| Asks people to DM “DM me and I'll send it over.” | 3 | 1.62 |
| Sends people to the product “Try it free — link below.” | 89 | 1.22 |
| Asks for nothing The post ends without telling the reader to do anything. | 593 | 1.00 |
| Points at more reading “Full story on the blog.” | 65 | 1.00 |
| Asks for a comment “Comment BLENDER for the link.” | 27 | 1.00 |
| Asks for a like or repost in exchange “Repost this and I'll DM you the guide.” | 3 | 0.75 |
| Asks for a sign-up “Save your seat.” | 46 | 0.59 |
| How long it is | Posts | Index |
|---|---|---|
| Very long 150 words or more — a proper piece of writing. | 94 | 1.38 |
| Long 100 to 150 words. | 162 | 1.22 |
| Medium 60 to 100 words — about a paragraph. | 222 | 1.03 |
| Short 30 to 60 words. | 202 | 0.95 |
| Very short Under 30 words — a line or two. | 146 | 0.71 |
| Day posted | Posts | Index |
|---|---|---|
| Wed | 158 | 1.15 |
| Mon | 132 | 1.12 |
| Tue | 147 | 1.12 |
| Thu | 193 | 1.00 |
| Fri | 148 | 0.76 |
| Sat | 23 | 0.67 |
| Sun | 21 | 0.40 |
What buyers raise in public forums, against what the category actually posts about. Above 1.00 means they ask about it more often than anyone answers it.
| Theme | Buyer quotes | Demand share | Category posts | Supply share | Rate /1k | Opportunity |
|---|---|---|---|---|---|---|
| hiring vs doing it in-house | 47 | 12% | 13 | 2% | 0.60 | 7.25 |
| manual / tedious workflow | 117 | 29% | 49 | 6% | 0.94 | 4.92 |
| volume / scale | 53 | 13% | 44 | 5% | 0.49 | 2.47 |
| reshoots / revisions | 21 | 5% | 19 | 2% | 0.75 | 2.26 |
| speed / turnaround | 35 | 9% | 64 | 8% | 0.97 | 1.13 |
| output quality / realism | 24 | 6% | 66 | 8% | 0.97 | 0.74 |
| cost per asset | 19 | 5% | 111 | 13% | 0.86 | 0.35 |
How much of this survived the corpus growing? Between the first measurement (120 buyer quotes, 540 posts) and this one (404, 826), the average theme moved 19%. The top 2 positions are unchanged; the order shifts below that. Every theme also kept its side of the 1.00 line. The largest single move was cost per asset. Read the head of this table as the durable finding and the exact multiples as indicative — they rest on a few hundred quotes and will keep moving as the corpus grows.
The openings, in order: hiring vs doing it in-house, manual / tedious workflow, volume / scale. These are themes the buyer raises unprompted and the category has not built content around.
“Particularly working in agency (although can be in house for a brand) How do you scale output?”
“I do it by hand monthly and it is the highest-leverage hour I spend, but it should not be manual.”
“Lighting & Atmosphere: Set up the volumetric fog using native Maya and Arnold tools (aiAtmosphereVolume and Fluids).”
51 accounts, 1,671 posts, including Magic Hour's own. Collected differently — the section explains why that changes what can be claimed.
1671 posts from 51 accounts, including Magic Hour's own. Compared on what gets posted, not on engagement rate — the reason is at the foot of this section.
| Kind of post | X posts | X share | LI posts | LI share | Leans |
|---|---|---|---|---|---|
| Launching a brand-new product “Introducing Studio” — a whole new thing, not an update. | 125 | 7% | 44 | 5% | both |
| A new feature on an existing product “You can now change the outfit without reshooting.” | 92 | 6% | 51 | 6% | both |
| A step-by-step how-to “Here's how to turn one photo into a week of content.” | 66 | 4% | 65 | 8% | |
| Giving something away free “Free for everyone this week, no card needed.” | 60 | 4% | 39 | 5% | both |
| Adding somebody else's AI model “Veo 3 is now available on our platform.” | 48 | 3% | 69 | 8% | |
| Competitions and reposting customers' work A contest with a prize, or showing off what a user made. | 40 | 2% | 65 | 8% | |
| Telling developers they can build on it “Add video generation to your own app in five minutes” — aimed at engineers, not marketers. | 34 | 2% | 18 | 2% | both |
| Hinting at something before it launches “Something big is coming Thursday” — no detail, just the date. | 28 | 2% | 19 | 2% | both |
| Webinars and conferences “Register for Thursday's session” or “come find us at the booth”. | 24 | 1% | 74 | 9% | |
| Showing how many people use it “3 million creators”, funding raised, or a big-name customer. | 23 | 1% | 31 | 4% | |
| Publishing original research A survey or industry report, not a product announcement. | 18 | 1% | 15 | 2% | |
| Tied to a date or holiday Christmas, Black Friday, back-to-school. | 16 | 1% | 10 | 1% | both |
| Announcing a deal with another company “We've teamed up with Adobe” — two logos, one announcement. | 16 | 1% | 9 | 1% | both |
| Money off, for a limited time “70% off this week only.” | 14 | 1% | 10 | 1% | both |
| A best-of list “The 10 best free tools for X” — SEO content on social. | 12 | 1% | 0 | 0% | X |
| One named customer's story “How Nike cut their shoot budget” — a specific company, a specific result. | 10 | 1% | 26 | 3% | |
| A point of view about how the work is done “Most AI video looks fake because people prompt for a mood, not a camera angle.” | 9 | 1% | 14 | 2% | |
| Written for one industry only “For estate agents” or “for Shopify stores” — not for everyone at once. | 7 | 0% | 19 | 2% | |
| Job adverts “We're hiring a content lead.” | 7 | 0% | 37 | 4% | |
| Life at the company Team photos, hackathons, someone's work anniversary. | 5 | 0% | 7 | 1% | |
| The founder or CEO giving a personal opinion A named person arguing something, posted from the company page. | 5 | 0% | 9 | 1% | |
| A recurring show or episode “Episode 3 of our weekly series”. | 4 | 0% | 5 | 1% | |
| engagement prompt | 3 | 0% | 4 | 0% | |
| Commenting on industry news Reacting to something a competitor or a big lab just did. | 0 | 0% | 6 | 1% | |
| Changing the company's own name or logo A rebrand or new visual identity. Rare, so it stands out when it happens. | 0 | 0% | 5 | 1% | |
| Opening with the customer's problem Naming what is going wrong before mentioning the product at all. | 0 | 0% | 13 | 2% |
The split is consistent: X is where this category announces things, LinkedIn is where it explains them. Launches and new features take 13% of X posts against 12% on LinkedIn; tutorials and community posts run the other way.
| Opener | X posts | X share | LI posts | LI share |
|---|---|---|---|---|
| Opens by plainly describing the thing | 1385 | 83% | 689 | 83% |
| Opens with “Introducing…” | 117 | 7% | 42 | 5% |
| Opens with a bold or contrarian claim | 73 | 4% | 54 | 7% |
| Opens with a number | 68 | 4% | 19 | 2% |
| Opens by withholding | 19 | 1% | 17 | 2% |
| Opens with “You can now…” | 9 | 1% | 5 | 1% |
Median length is 31 words on X against 69 on LinkedIn — a different format, not just a different audience.
| Account | Posts | Median likes | Best post | Posts mostly |
|---|---|---|---|---|
| @pika_labs | 5 | 2069 | 24,138 | Not classified |
| @ElevenLabs | 8 | 1684 | 2,906 | Launching a brand-new product |
| @runwayml | 8 | 1515 | 4,050 | Launching a brand-new product |
| @higgsfield_ai | 67 | 1306 | 4,384 | Giving something away free |
| @midjourney | 20 | 1170 | 39,619 | Not classified |
| @ltx_io | 6 | 750 | 1,303 | Not classified |
| @joshua_xu_ | 7 | 625 | 5,247 | Not classified |
| @StabilityAI | 99 | 554 | 7,702 | Not classified |
| @krea_ai | 20 | 363 | 5,151 | Not classified |
| @magnific | 10 | 344 | 1,692 | Not classified |
| @LeonardoAi | 9 | 289 | 2,446 | Not classified |
| @HeyGen | 6 | 184 | 2,400 | Launching a brand-new product |
| @fal | 18 | 114 | 2,869 | Not classified |
| @loom | 100 | 66 | 744 | Not classified |
| @magichourai | 108 | 3 | 18 | Not classified |
Magic Hour's own X account gets a median of 3 likes a post, against 20 across the category sample. The account posts mostly not classified — the same shape as the LinkedIn page, and the same problem: it announces capability rather than answering a buyer's question. X rewards announcements more than LinkedIn does, so the angle is less wrong here; the aim still is.
“Announcing a new division of Midjourney called "Midjourney Medical" https://t.co/c14YcO6yaU”
“A technical dive inside our new "Midjourney Scanner" https://t.co/wJBHz2O7ro”
“Introducing Pika 1.0, the idea-to-video platform that brings your creativity to life. Create and edit your videos with AI. Rolling out to new users on web and discord, starting today. Sign up at https”
“Adobe for creativity + Claude 🤝 Now, Claude users can power their content with more than 50 Creative Cloud tools. Simply describe the outcome you want and let the assistant orchestrate workflows behin”
“Introducing Ideogram 4.0: the best open image model in the world. Think it. Make it. Own it. Download the weights, fine-tune on your own data, and run it on your hardware. Live on every Ideogram plan ”
“We are excited to announce the release of Stable Diffusion Version 2! Stable Diffusion V1 changed the nature of open source AI & spawned hundreds of other innovations all over the world. We hope V”
Why there is no engagement rate here. X's timeline endpoint throttles to roughly one account per ten minutes, so 164 of these 1671 posts were found through search rather than by reading whole timelines. Search surfaces what got picked up, so the sample leans toward the posts that did well. A median calculated on it would flatter X and would not be comparable to LinkedIn's clean window.
What survives that bias. Which angle a company reaches for, how it opens, and how long it writes are properties of the posts themselves, not of how they were sampled. Those are what the tables above show. The median likes column is there to show the sample is real, not to be compared against LinkedIn.
The posts worth stealing from, split by platform and by company versus founder — 603 founder posts from 96 profiles, collected by permalink because the profile activity page is rate-limited shut.
The posts that actually travelled, ranked by the engagement they got, split by platform and by whether a company or a person published them. Ranked on raw numbers rather than the size-adjusted index used elsewhere — a swipe file should show what worked, with the account size beside it so you can judge for yourself.
What the best posts have in common. Among the forty most-engaged LinkedIn posts the commonest kinds are Adding somebody else's AI model (6), Telling developers they can build on it (5), Webinars and conferences (4). On X they are Launching a brand-new product (10), Giving something away free (5), Adding somebody else's AI model (3). The platforms reward different things, which is why the quadrants below are worth reading separately rather than as one list.
The highest-engagement company posts in the category. Drawn from 795 posts across 82 accounts.
Introducing FLUX 3. One multi-modal model for Image, Video, Audio and Action-Prediction. Creations are truer to life in every kind of style. FLUX 3 is a checkpoint on our mission to develop real-world visual intelligence: models that perceive, predict, and act across digital and physical environments. Jointly trained in one unif
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Founders posting from their own profile. Drawn from 581 posts across 94 accounts.
Today, ElevenLabs is announcing a $500M Series D at an $11B valuation, led by Sequoia, with a16z quadrupling down and ICONIQ tripling down. It reflects the trust of customers and partners building at the frontier alongside us - and gives us momentum to ship even faster. With this funding, we’re going even deeper with ElevenAgent
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Today, as shared by The New York Times, we’re announcing two things: >Our Series B at a $2.1B valuation led by Sarah Wang at Andreessen Horowitz. >Reaching $100M ARR, profitably, with a team of just 50 people. That's $2M ARR per employee. PowerPoint was invented before the first website, before the Game Boy, before the Berlin Wa
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The category's biggest posts on X. Drawn from 1654 posts across 45 accounts.
Announcing a new division of Midjourney called "Midjourney Medical" https://t.co/c14YcO6yaU
A technical dive inside our new "Midjourney Scanner" https://t.co/wJBHz2O7ro
Introducing Pika 1.0, the idea-to-video platform that brings your creativity to life. Create and edit your videos with AI. Rolling out to new users on web and discord, starting today. Sign up at https://t.co/JHRrinsIwx https://t.co/Rve3I2FzmK
Adobe for creativity + Claude 🤝 Now, Claude users can power their content with more than 50 Creative Cloud tools. Simply describe the outcome you want and let the assistant orchestrate workflows behind the scenes: https://t.co/G70cSsca8P https://t.co/OHFktWNKYE
Introducing Ideogram 4.0: the best open image model in the world. Think it. Make it. Own it. Download the weights, fine-tune on your own data, and run it on your hardware. Live on every Ideogram plan and the API today. https://t.co/AdH9hfSEdb
We are excited to announce the release of Stable Diffusion Version 2! Stable Diffusion V1 changed the nature of open source AI & spawned hundreds of other innovations all over the world. We hope V2 also provides many new possibilities! Link → https://t.co/QOSSmSRKpG https://t.co/z0yu3FDWB5
Founders and CEOs posting as themselves. Drawn from 17 posts across 6 accounts.
Excited to share that I recently left Stanford AI PhD to start Pika. Words can't express how grateful I am to have all the support from our investors, advisors, friends, and community members along this journey! And there's nothing more exciting than working on this ambitious &
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Founder coverage is thinner than company coverage. Company pages are enumerable — there is a list of them and each has a public feed. Founders are not: finding the right profile means knowing the person, and several guesses landed on the wrong human entirely (one search for Pika's founder returned an accountant with the same name). The founder quadrants here are verified accounts only, which makes them small but correct. Adding more is a matter of naming the people you want tracked.
X is ranked on a search-found sample, so it leans toward posts that already travelled. For a swipe file that bias is mostly harmless — it is a list of posts that worked, which is what was asked for — but it means the X quadrants are not a complete ranking of the platform.
Thirty drafts for LinkedIn, written against the gaps measured above. Every factual claim traces to a page on magichour.ai.
Thirty drafts, grouped by what each one is for. 7 are aimed squarely at someone who buys; the median score is 3 out of 5, against 1 out of 5 for what Magic Hour publishes today.
Every brand that starts making video hits the same fork: hire a videographer, brief a freelancer every time, or try to do it in-house.
The honest answer is that it depends on how often you need to change something. A shoot is the right call when the thing you are making will not change for six months. It is the wrong call when you need the same product in nine formats by Friday.
That second job is the one Magic Hour built for. Upload the product photo, get the clip, change it as many times as the brief changes.
Magic Hour is not going to tell you to stop hiring people who are good at this.
A camera operator who understands your brand is worth the money for the handful of shots a year that carry it. What they are not worth is the twentieth variation of a product clip that has to go out this afternoon.
Use the crew for the hero. Use Magic Hour for the twenty.
If you are about to write a brief for a freelance editor, it is worth checking which half of the job you actually need them for.
The creative decisions - what the ad says, which moment sells it - are worth paying a person for. The mechanical half is not: resizing, subtitling, swapping the outfit, producing the vertical cut.
Split the brief in two and the freelancer bill usually halves with it.
Bringing video in-house normally means a headcount conversation, and that is where it dies.
It does not have to. The tools now cover the parts that used to need a specialist: face swap, lip sync, dubbing, subtitles, upscaling, clothes changing. What is left is the judgement, which your marketing lead already has.
Start with the free tools before anyone writes a job description.
Nobody complains about the creative part. They complain about the rest:
Export. Resize for four placements. Re-cut for the vertical. Burn in subtitles. Upload to three tools that each do one thing. Realise the client wanted a different opening line. Start again.
That is the part worth automating, and it is the part almost nobody sells against.
Count them honestly. Most teams Magic Hour talks to are running four or five: one for generation, one for subtitles, one for upscaling, one for the resize, something else for voice.
Every handoff is a file export, a re-upload and a chance to lose the latest version.
Magic Hour is one place. That is not a feature so much as the removal of four of them.
Product demos always show the generation. They never show what happens twenty minutes later, when the brief changes.
So: change the outfit without reshooting. Swap the face. Redo the voiceover in another language. Extend the clip. Add the subtitles. Push it to 4K.
Same file, no round trip, nothing re-exported.
The request that eats an afternoon is never "make a video". It is "make this video again, but square, and thirty seconds, and with the logo bigger".
Upload once. Take the formats you need. If the brief moves, move with it.
There is a point in every agency's growth where video stops being a creative problem and becomes a throughput problem. Usually around the fourth or fifth retained client.
Strategy scales. Media buying scales. Production does not, because it is tied to people and calendars.
The fix is not working faster. It is removing the steps that require anyone to be available.
Paid social rewards volume of concepts, not polish. Most teams know this and still test three variants, because a fourth means another shoot.
With 90+ preset avatars and a written script you can put ten openings in front of the algorithm and let it pick. The ones that lose cost you nothing but the credits.
One product photo. Nine placements. Three scripts each.
As a shoot, that is a day and a schedule. As a generation queue, it is an afternoon, and Most videos finish in 3-10 minutes.
Nothing here replaces a good idea. It replaces waiting for a slot.
Most brands are still running a creative that tested well in spring, because replacing it means commissioning something.
Creative fatigue is not a creative problem. It is a supply problem. If making the next one is cheap, you stop defending the old one.
If your app needs video or images, you have two options: integrate several model providers and maintain several billing relationships, or integrate one.
The Magic Hour API is the second one. Python, Node, Go and Rust SDKs. First API call in ~5 min, and From $0.009 / image.
Unlimited parallel API requests, so a queue that spikes does not need a conversation with Magic Hour first.
Before you build on someone's infrastructure, the only things that matter are whether it stays up and what it costs.
50M+ API calls. 99.9% uptime. From $0.009 / image.
The rest of the evaluation is whether the output is good enough, and you can answer that on the free tier before you talk to anyone.
Two things that should not be remarkable and somehow are.
Credits carry forward with no expiration date. If a job fails or you cancel it, credits refunded for failed or cancelled jobs.
You should not have to plan your release schedule around a billing cycle.
First API call in ~5 min. Python, Node, Go and Rust SDKs.
No sales call required to find out whether it works. If it does not fit, you have lost an afternoon rather than a quarter.
The awkward thing about building on generative video is that the best model changes every few months, and swapping providers means rewriting the integration.
One integration, and the model choice becomes a parameter rather than a project.
3.7M+ creators and 2K+ teams have now made something on Magic Hour, with 500K+ of those creators arriving in the last 30 days.
Between them: 20M+ AI videos and 30M+ AI images.
There has never been a sales team.
An NBA franchise has the budget for any production company it wants.
Dallas Mavericks are on Magic Hour anyway, which tells you something about where the constraint actually is in sports content. It is not budget. It is that the moment worth posting about happened ninety minutes ago.
Magic Hour is 4.9/5 on Product Hunt, which is lovely and proves very little.
The number that matters more: 20M+ AI videos generated, and 500K+ creators in last 30 days in the last month. People come back to tools that work and quietly stop opening the ones that do not.
2K+ teams use Magic Hour, and they are not all doing the same thing. Some are agencies clearing client work. Some are ecommerce teams making product clips. Some are engineering teams who never open the web app at all and only touch the API.
The common thread is not the industry. It is that all of them need the next version of something faster than a shoot allows.
5 free photo face swaps a day, no watermark.
3 free UGC ads a day.
Free daily credits, no credit card required.
There is no signup wall in front of finding out whether the output is good enough for your brand. If you outgrow it, you will know before Magic Hour tells you.
No sign-up required for supported tools. Open it, use it, close the tab.
Better that you find out the output is good before anyone asks you for an email address.
A fair question that most AI tools answer badly.
Free-tier uploads deleted after 1 day; content is not used to train models.
If you are putting a client's unreleased product through a tool, that is the sentence you need in writing.
Free daily credits, no credit card required and 3 free UGC ads a day. Enough to run a real brief through it and see whether the output survives contact with your brand guidelines.
Then have the internal conversation, with something to show.
You already paid for the product photography. Most brands then let it sit in a folder and commission video separately.
One image becomes a clip. The clip becomes nine placements. When the SKU changes colour, you do not rebook anything - you change the outfit and re-export.
Most videos finish in 3-10 minutes, so the version that goes live this afternoon can be the version someone asked for this morning.
The expensive week in an agency month is not the shoot. It is the round of changes afterwards - a different opening, a colour the client reconsidered, a nine-by-sixteen nobody mentioned until Friday.
Video-to-video, clothes changer and lip sync handle that round without going back to camera. The shoot stays. The reshoot goes.
App install creative burns out faster than anything else in paid social, and each replacement traditionally means a creator, a brief and a wait.
90+ preset avatars and a written script gets you a batch to test this week. The winners get a real production budget. The losers cost credits.
Localisation usually means re-recording, which usually means the localised version is a quarter behind the original.
Dubbing and lip sync mean the same clip speaks another language without going back to the talent. The mouth matches. That is the part that used to give it away.
The objection to generated video is almost never that it is generated. It is that it does not look like the brand.
10,000+ templates and character consistency exist for exactly that: the output has to survive a brand guidelines review, not just look impressive in a demo.
The previous set of thirty was written before anyone read the product pages, and about half of it carried numbers that were simply made up. This set may only use facts from this list.
| Claim | Source |
|---|---|
| 3.7M+ creators | magichour.ai homepage |
| 2K+ teams | magichour.ai homepage |
| 500K+ creators in last 30 days | face-swap / ugc-ad pages |
| 20M+ AI videos generated | ugc-ad-generator page |
| 30M+ AI images generated | face-swap page |
| 50M+ API calls | face-swap page |
| 99.9% uptime | face-swap page |
| first API call in ~5 min | face-swap page |
| from $0.009 / image | face-swap page |
| 4.9/5 on Product Hunt | face-swap page |
| most videos finish in 3-10 minutes | ugc-ad-generator page |
| 90+ preset avatars | ugc-ad-generator page |
| 10,000+ templates | homepage |
| Python, Node, Go and Rust SDKs | api page |
| unlimited parallel API requests | api page |
| credits carry forward with no expiration date | api page |
| credits refunded for failed or cancelled jobs | api page |
| 5 free photo face swaps a day, no watermark | face-swap page |
| 3 free UGC ads a day | ugc-ad-generator page |
| no sign-up required for supported tools | homepage |
| free daily credits, no credit card required | homepage / api |
| free-tier uploads deleted after 1 day; content is not used to train models | face-swap page |
| Dallas Mavericks | homepage |
| Creator $144/yr, Pro $300/yr, Business $792/yr | api page |
| 4K exports and unlimited concurrent generations on Business | pricing page |
Nothing here needs fact-checking before it goes out, because every figure was taken from a live page rather than invented to fit the sentence. Where the product does not publish a number, the post is written without one.
Same scoring as everything above.
| Post | Actual /1k | Angle | Hook | CTA | Reach | ICP |
|---|---|---|---|---|---|---|
| From stop-motion to ASMR videos, you can create it all wit… | 4.27 | model integration | descriptive | comment/tag | 1.06x | 1 |
| Fun AI idea to try this week! There’s a cute weather-forec… | 4.27 | community/UGC | descriptive | comment/tag | 1.04x | 0 |
| The possibilities are limitless! You can now create studio… | 2.14 | tutorial | descriptive | comment/tag | 0.95x | 0 |
| Say hello to Veo 3.1 on Magic Hour Available in 9:16 verti… | 2.14 | model integration | introducing | engagement gate | 1.14x | 1 |
| Say hello to Kling 2.5 on Magic Hour Available in Text-to-… | 2.14 | model integration | introducing | engagement gate | 1.14x | 1 |
| From UGC-styled videos to cinematic sequences, you can cre… | 0.71 | model integration | descriptive | none | 1.06x | 1 |
The diagnosis is not what it looks like. 4 of 6 posts are model-integration announcements — the most crowded angle in the category, and one of the better-performing ones, so not the problem. The 5 engagement gates are not the problem either: engagement gates run 0.8x baseline here, on only 3 posts, which is too small a sample to lean on either way; comment asks run 1.0x baseline across 27 posts. The mechanics here are broadly fine. What is wrong is the aim. Median ICP score across all six posts is 1 out of 5 — the words are written for people who follow model releases, not for people who sign contracts. And none of the six touches any of the three themes where buyer demand most outruns category supply: whether to hire or do it in-house, manual workflow, and the round of changes after the shoot. This is well-made content pointed at the wrong reader.
No statistics in these drafts on purpose — every claim is a product surface Magic Hour already describes, so there is nothing to verify before publishing.
Your product photo already has a video in it.
Upload one image. Pick an aspect ratio. Get a clip you can put straight into a paid placement.
No shoot, no crew, no second booking when the SKU changes.
The most crowded angle in the category. Announcing someone else's model tells a buyer nothing about their own problem, and the audience it reaches is other people who follow model releases.
The free tier, with no asterisks:
Face swap. Talking photo. Image to video. AI headshots.
No signup wall to find out whether the output is good enough for your brand. If you outgrow it you will know before Magic Hour tells you.
Not rewritten because the gate underperforms -- on this corpus it does not. Rewritten because "retweet" is not a LinkedIn verb, so the post reads as cross-published from X rather than written, and because trading a guide for a repost buys reach from people who wanted the guide, not from people evaluating the product.
An agency shipping client video has one expensive week every month, and it is not the shoot.
It is the round of changes after the shoot: a different opening, a colour the client changed their mind about, a nine-by-sixteen nobody asked for until Friday.
Video-to-video and clothes changer handle that round without going back to camera.
Reads as capability rather than consequence. A content lead is buying throughput and a predictable turnaround, not an animation generator.
What this is built on. Company pages expose their recent posts to logged-out visitors; every post here was fetched, parsed and counted directly. No engagement number is estimated. Follower counts are read off the same pages.
The window is recent, not historical. LinkedIn shows roughly the last ten posts per company anonymously, so this is a current-form snapshot, not a six-month history. A logged-in scrape would extend it.
The demand side is a sample, not a census. Forum feeds expose only the newest threads per community, so the corpus grows by re-polling over time rather than by searching. Quote counts are therefore a floor.
About a fifth of posts are unclassified. The angle taxonomy was built for AI-video companies and the corpus now also spans design, audio, stock and general SaaS, so 19% of posts fall into other and contribute nothing to the angle tables. The mechanics tables (hook, CTA, length, day) are unaffected — they do not depend on the angle. Sampling other and adding rules is the standing maintenance job.
Correlation. Every rate here is observational. The scorer encodes what historically co-occurred with engagement in this category — it is a prior for what to test, not a prediction about any single post.