Profiles at a Glance
For each public account, AllyHub pulls the handle and name, the bio and category, the external link, the post, follower, and following counts — plus the contact a business profile chooses to show.
Pull public Instagram data — profiles, posts, and hashtag feeds — into one structured dataset, from a handful of usernames or a whole competitive set.
Instagram is built to be scrolled, not exported — every profile, post, and hashtag is a wall you'd have to copy by hand. AllyHub pulls the public data across all three into one structured, exportable table.
For each public account, AllyHub pulls the handle and name, the bio and category, the external link, the post, follower, and following counts — plus the contact a business profile chooses to show.
Per post, AllyHub captures the caption, media type, like and comment counts, timestamp, and the hashtags, mentions, and tagged accounts inside it — the full record, not just the image.
Give AllyHub a hashtag and it gathers what's posted under it — the top and recent grid, the post count, the related tags — so you can map a topic's conversation, not one account's take.
Start from a list of usernames, profile or post URLs, or hashtags — AllyHub takes any of them and returns the matching data in the same structured shape.
Hand AllyHub a list of accounts or hashtags and it works through every one in a single run, returning a combined dataset you can compare across — not one profile scraped at a time.
Because it reads all three, AllyHub can link them: a hashtag to the posts using it, those posts to the accounts behind them — the kind of thread a single-purpose scraper can't follow.
From a list of accounts, hashtags, or URLs to a structured Instagram dataset — in three steps.
Give AllyHub the accounts, hashtags, or URLs you want, and set the scope — recent posts, a date range, an engagement floor. No login for public content.
It reads each profile's stats, every post's caption, media, likes, comments, timestamp, and tags, and any hashtag's top and recent feed, all paged and stacked into one clean table.
Export the dataset to CSV or JSON, run your comparisons and engagement math, or save the run as a Playbook that re-scrapes on the schedule you set.
Most Instagram tools do one thing and hand you a file. AllyHub reads the whole picture, hands you a workflow.
Pick a typical Instagram scraper and it does one job — profiles, or hashtags, or posts. AllyHub covers all three in one pass and connects them, so you can trace a trending hashtag to the posts and the accounts driving it, not toggle between three tools.
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A big follower count can hide a dead audience. AllyHub computes engagement rate from the public likes and comments on recent posts, so you judge a profile — or a potential partner — on how much its audience actually reacts, not on the follower number alone.
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Scraping one profile is a data point; a category is a benchmark. AllyHub runs your whole tracked set — every competitor, every hashtag — in one job and lines the results up side by side, so patterns across the niche show up instead of a single account's numbers in isolation.
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Save your accounts, hashtags, and filters as a Playbook, and the setup's done once. AllyHub builds on what it already knows about your tracked set, so monitoring gets faster every time and each pass flags what moved since the last.
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For the teams treating Instagram as a data source — content and social, influencer, brand and PR, and research.
You're planning a quarter and can't tell which formats and hashtags are actually working across your space — just what your own feed happened to show you. AllyHub pulls every tracked account's posts and their engagement into one table, so the topics, formats, and posting cadence that travel across the niche are visible at a glance, not a guess.
A creator's follower count looks great, but you've been burned by bought audiences that don't convert. AllyHub pulls a potential partner's recent posts and computes the real engagement, so you can spot the ones with a live audience — and the telltale sponsored-post drop-off — before you spend a cent.
Your brand is getting tagged and talked about on Instagram, and you find out days late, by accident. AllyHub watches the accounts and hashtags where your name shows up and pulls the relevant posts on a schedule, so brand chatter reaches you as a feed you can act on, not a surprise.
Your study spans profiles, posts, and hashtag ecosystems, and stitching three separate tools into one dataset eats the week before analysis even starts. AllyHub pulls all three types into a single structured set, so you can analyze how a whole category behaves instead of wrestling with three exports.
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Answers on what Instagram data you can pull, what stays public, and running it across a set.
It's the general-purpose tool for pulling public data off Instagram — profiles, posts, and hashtag feeds — handed back as a structured file you can sort and export, not something you scroll. AllyHub reads all three types in one workflow and runs across a whole set of accounts at once.
Yes. A single-account or single-hashtag scrape is free. Beyond that, bulk runs across many accounts and tags, engagement analysis, scheduled monitoring, and pushing data into your own stack come with the paid plans.
AllyHub reads what's public — profiles, posts, and hashtag pages anyone can open without an account — so no login is needed. Private accounts and anything behind a login are out of scope; it only takes what's already public.
Yes. Point AllyHub at a hashtag and it collects the posts riding it — top and recent — with their captions, counts, and accounts. Pass several related tags and it does them together, so you can compare which tags a topic actually lives under.
Yes. From a profile's recent public posts, AllyHub works out an engagement rate — likes and comments against followers — so a creator's real pull is visible next to the follower count. It's the check that separates a live audience from a bought one before you reach out.
Most scrapers do one data type and drop a raw file on you. AllyHub reads profiles, posts, and hashtags together, computes the metrics that matter, and saves the run as a Playbook — so a recurring study is one click, and each run picks up where the last left off instead of starting over.