Each Reel, as Data
Each Reel comes back as its own row — everything a Reel carries publicly, from the play count to the sound it rides — instead of a thumbnail you have to open.
Pull a public account’s Reels into a table with view counts, their audio, and the engagement — or every Reel on a given sound.
What a Reel did comes down to views and the sound it used — and the vertical feed lets you compare neither. AllyHub pulls the Reels into rows: the play counts, the audio, the engagement, whether you name an account or a single sound.
Each Reel comes back as its own row — everything a Reel carries publicly, from the play count to the sound it rides — instead of a thumbnail you have to open.
AllyHub takes the play count and computes a view rate — likes and comments against views — so a Reel that got seen but held no one is easy to tell from one that landed.
Name a song or original audio and AllyHub pulls the Reels using it — top and recent — so you can see who’s on a sound and how their Reels did.
Across the Reels you pull, AllyHub surfaces the sounds, formats, and hashtags that show up most on the highest-view ones — the patterns in the data, not a claim about why they worked.
Point AllyHub at several accounts or a hashtag and it pulls them in one run — every Reel in matching columns — so the category reads as one table, not a dozen feeds.
Set a minimum view count, a date window, or a media length and AllyHub keeps only the Reels that match — then hand it back as CSV, JSON, or Excel.
Name an account, a hashtag, or a sound, set the scope, and get a structured Reels table back.
Give AllyHub an account, a hashtag, or a sound — plus a scope like recent Reels, top performers, or a minimum view count. No login for public Reels.
It reads each matching Reel — caption, play count, likes, comments, the audio, duration, date, and creator — into a row, plus a view rate from the counts.
Take the export, run it through analysis for the sound and format patterns, or keep it as a Playbook that re-runs monthly to show what’s shifting.
A high view count can just mean a Reel got pushed — AllyHub gives you the rate behind it too.
A view count on its own is passive exposure — the algorithm pushed it into feeds. The view rate, likes and comments measured against those views, is the part that shows whether anyone actually stopped. AllyHub computes it for every Reel.
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On Reels the audio is half the strategy, and you can’t see it by scrolling — which sounds a niche is riding, who jumped on early, how their Reels did. AllyHub reads the sound off every Reel, so the layer half the strategy runs on is finally in the data.
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AllyHub shows which Reels and sounds got the views, and what recurs on the top ones — it won’t tell you why a Reel blew up or hand you a formula for the next one. Views, timing, and the algorithm decide that; the data shows what happened, honestly.
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Sounds and formats burn through a niche fast — what’s everywhere this month is tired the next. Keep the scrape as a Playbook and AllyHub re-runs it on your cadence, so you see the turnover as it happens and it builds on what it already knows.
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Creators, brand teams, short-form agencies, and talent scouts who need the numbers and sounds behind Reels, not a feed to swipe.
You’re guessing which sound to use and which hook to open on while the creators ahead of you clearly aren’t. Pull the top Reels in your niche, see the sounds and openings on the ones that got the views, and plan your next batch from what’s landing — not a hunch.
Your Reels calendar gets signed off on taste, and taste keeps losing to whatever the category is actually doing. Watch competitors’ Reels by view count and the formats getting traction, and bring the sign-off meeting data instead of opinions.
Every client wants proof the brief will work, and “trust us” stopped closing deals. Pull the high-view Reels in the client’s niche and build the brief on what got the views there — the sounds, the lengths, the hooks — so the pitch stands on data.
A creator’s follower count says nothing about whether their Reels actually get watched. Pull a prospect’s Reels and read the public view counts and engagement against their following, so a partnership call rests on what their content does, not how big they look.
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Answers on pulling Reels, scraping by sound, and what Reel data is public.
An Instagram Reels scraper turns a set of Reels into rows of data — everything public on each one, from the play count to the audio — pulled from an account, a hashtag, or a sound. AllyHub computes a view rate from the counts and can re-run on a schedule.
Yes — a single account or a single sound is free to pull, with the everyday Reel fields. Multi-account sets, deep histories, sound sweeps, and scheduled monitoring sit on the paid plans.
Yes — give AllyHub a song or an original audio and it pulls the Reels using it, with each one’s views and engagement. It shows you which sounds recur across the Reels you scrape, so you see what a niche is on now — it doesn’t predict which sound peaks next.
What a Reel shows publicly is the caption, the counts under it, the sound, and its length. Private to the owner — shares, saves, reach, impressions — so no scraper reaches them. AllyHub works from the public numbers and computes the rates from those.
AllyHub computes them — Instagram doesn’t publish a rate, so it works out view-to-like and view-to-comment ratios from the public play, like, and comment counts. The raw counts come with it, so you can build whatever ratio you prefer.
Swiping the feed, you can’t compare two Reels, let alone a category, and nothing exports. AllyHub structures every Reel across the set, computes the rates, and pulls a sound’s Reels on demand — then keeps it as a Playbook, so the next month’s pull picks up warm and compounds with every task.