Paste a Link
One video URL, a list of them, or an account's recent uploads — the analysis runs the same way whichever you hand it.
One hundred thousand views is a flop on one account and a breakout on another. Read the numbers beside the account that posted them.
A view count on its own only tells you the video was shown to people. AllyHub reads the six figures TikTok prints under every public video, turns them into rates, and puts each video next to what that account normally does — none of which needs the TikTok API.
One video URL, a list of them, or an account's recent uploads — the analysis runs the same way whichever you hand it.
Views, likes, comments, saves, shares, and the post date, taken from the video as TikTok displays it rather than from an analytics account you would need access to.
Engagement rate, save rate, share rate, and average views per day since posting — arithmetic on the figures above, labelled as computed so nobody mistakes it for a platform metric.
Each video lands next to the account's recent uploads on the same measures, so you can see whether it beat that account's normal run or just matched it.
Hand over fifty links and get fifty rows. Nothing about the analysis changes with volume, so a month of uploads costs the same attention as one video.
A spreadsheet or a document with every video on its own line, each carrying the original link so any figure can be checked against the post it came from.
Three moves take a bare link and give the numbers on it something to be measured against.
Give AllyHub one video URL or a batch of them, and say how many of that account's recent uploads should form the comparison.
It collects views, likes, comments, saves, shares, date, caption, and handle for each video plus the account's recent uploads, then computes engagement, save, share, and daily-view rates.
Read each video against the account's normal run, keep the ones worth studying further, and send the batch to a sheet or run the next set.
Every analyser can tell you a video got views. Almost none tell you whether that was good.
A number with nothing beside it can be read whichever way suits the person reading it, which is why screenshots of view counts settle so many arguments and prove so little. Put the video next to the last twenty the same account posted and the number stops being negotiable.
.jpeg&w=1920&q=75)
Read alone, views make everything look like a ranking. Read together, the six pull apart: high views with thin comments and modest views with heavy saves are not the same result, though both get filed under "did okay" when one figure is quoted.
.jpeg&w=1920&q=75)
Everything here comes off the public page: there is no impression count, no audience breakdown, and no traffic source, because those live in an analytics account this never touches. The rates are AllyHub's division, and what made a video work is a judgement the figures cannot make for you.
.jpeg&w=1920&q=75)
The link format, the size of the comparison window, the columns you wanted — your AllyHub never starts from scratch again, so next month's batch is one line of instruction, and it compounds with every task you send it.
.jpeg&w=1920&q=75)
For anyone who has to state whether a video worked and then defend the number they used to say it.
You remember the video that took off and the one that died, and nothing in between — which is most of them. Run the last three months as one batch and the pattern you have been guessing at turns up in a column.
You took over a channel with two years of uploads and a handover doc that lists passwords. Analysing what is already there tells you which posts landed before you decide what the next quarter looks like.
Organic posts are the cheapest test you will ever run, but choosing which one to put budget behind off a view count means backing whatever got shown most. The save and share rates separate the ones people passed on to someone else from the ones that simply got seen.
The target gets set at a round view number because that is the figure everyone recognises. Pull what the account has actually done across a year and the goal can be argued from its own history instead of a guess.
Explore more AI-powered tools across research, content, and data.

Amazon Bestsellers Scraper — pull any ranking list with rank position, ASIN, price, and rating. No code, no Amazon API, all marketplaces. Try AllyHub free.

Amazon Product Scraper — pull structured product data from any Amazon domain without code or the Amazon API. Export JSON or CSV. Try AllyHub free.

Amazon Niche Finder — start from your interests, a category, or a rival, and get underserved niches scored on demand vs competition. Try AllyHub free.
Reading the figures under a post without inventing reasons for them.

Struggling to scrape Amazon product data without getting blocked? Learn safe, effective Amazon scraper methods using APIs, no-code tools, and Python.

Discover the 10 best Amazon competitor analysis tools used to track competitors, uncover keyword gaps, and understand why top listings outperform yours.

Discover the best Amazon SEO tools to boost your rankings, find high-converting keywords, and outpace competitors. Reviewed and ranked for e-commerce marketers.
What comes back, what is deliberately absent, and where the reasons have to come from.
It takes a published TikTok video and reports the figures attached to it — views, likes, comments, saves, shares, and date — with ratios worked out from them. AllyHub adds the account's recent uploads as the reference, so each figure arrives with something to be compared against.
A single video costs nothing. Paid plans are where long batches, wide comparison windows, and file exports live.
No. It reports what happened and how that sits against the account's usual range; the reason sits in the hook, the sound, the timing, and what the algorithm did that week, none of which is visible in a public count. For the content side, the TikTok Video Summarizer is the tool that reads what was actually said.
No. Reach, traffic source, and audience breakdown sit behind an account's own login and are never published. Everything here is taken from what the public page displays, which is exactly why it works on accounts you do not control.
Spreadsheet or document. The first suits sorting and charting; the second suits a write-up someone will read. Either way each row keeps its video link, so you can open the post behind any figure.
Most hand back the same figures the page already shows, arranged more neatly. AllyHub does the division, sets each video against the account that posted it, is explicit about which numbers are TikTok's and which are its own, and keeps the setup — so it gets faster every time you come back with another batch.