Terms and Tags Go In
Give one keyword, a hashtag, or a handful of both, and AllyHub pulls the videos TikTok returns for each of them into one pool.
Search returns what it thinks is relevant. Give AllyHub a date range, an engagement floor, and a follower ceiling — the list follows those instead.
Scrolling a results page is fine until you need every video that meets a rule, not the twenty the app decided to show first. AllyHub runs the search, brings back each match with its public numbers and its author, and keeps only the rows your conditions allow — none of it requiring an app install or an API key.
Give one keyword, a hashtag, or a handful of both, and AllyHub pulls the videos TikTok returns for each of them into one pool.
Each video arrives with its view, like, comment, save, and share totals, the post date, the author's handle, and that author's follower count — enough to judge it without opening it.
A date window, a minimum on any of the counts, and a ceiling on follower size. Rows that miss the rule never reach your list.
Order the survivors by save rate, by comment count, by recency — whatever the question is. Relevance ranking is what you were trying to get away from.
Run five keywords together and get one pooled list with a column saying which term each video came from, instead of five tabs you have to reconcile.
Spreadsheet or document, with the author handle, the counts, the matched term, and the link on every row so anything interesting is one click from the original.
A search term, a set of rules, and a list that already had the noise taken out of it.
Name the keywords or hashtags to search, and the rules a video has to meet — how recent, how much engagement, how big an account.
It searches each term, collects each video's caption, date, author handle, and follower count along with its view, like, comment, save, and share totals, then filters and sorts what survives.
Open the ones worth watching, send the list to a sheet, or change one threshold and run it again to see how the shortlist shifts.
The app ranks by relevance. Almost every real question is a filter.
A search box answers "what is related to this" and stops there. The questions people bring to it — what has been posted this month, what cleared an engagement level, what came from an account this size — are all rules, and a ranked page cannot be asked a rule.
.jpeg&w=1920&q=75)
A million views from a channel with ten million followers tells you the channel is large. The same million from an account with twenty thousand tells you something about the video. Filter on follower ceiling and view floor together and only the second kind is left.
.jpeg&w=1920&q=75)
It works from what TikTok's public search will return, so it is a wide sample rather than every video ever posted, and results shift as the platform re-ranks. Filters run on the counts the page shows; there is no way to filter on reach or audience, because neither is published.
.jpeg&w=1920&q=75)
The terms, the thresholds, the sort order — none of it has to be described twice. Your AllyHub builds on what it already knows, so tightening one filter and running again costs a sentence, and it gets faster every time.
.jpeg&w=1920&q=75)
For people who need every video matching a rule, not a page of things the app found interesting.
You need to know how a subject is being talked about on TikTok, and scrolling gives you the loudest examples rather than a sample. A list built from stated conditions can be described in a methods section.
You want people already making the kind of video you would commission, not whoever a directory ranks first. Search the subject, cap the follower count, floor the engagement, and the shortlist is people you could actually afford.
A deck, an article, or a training session needs five real posts that prove the point, and finding them by memory takes an afternoon. Set the rule the examples have to meet and pick from what comes back.
A format takes off and everyone wants to know whether it is still working. Search it, restrict the window to the last two weeks, then compare that against the same search run over an older window.
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.
Building a shortlist from conditions instead of from whatever surfaced.

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.
How the search works, what it cannot reach, and where the conditions live.
It searches TikTok for a keyword or hashtag and returns the matching videos as a list rather than a feed. AllyHub attaches each video's public counts and author details, then keeps only the ones that clear the conditions you set.
One search, free. Pooling several terms in a run, pulling deeper into the results, and exporting a file are paid features.
No. It works from what TikTok's public search will return, which is broad but not the whole platform. If a video is not reachable by the terms you gave, no filter will surface it.
No. Every filter runs on something published on the page — counts, dates, follower numbers. Reach, audience location, and traffic source are not published, so nothing here can be built on them.
Both. Take the spreadsheet if the shortlist is going to be cut down further, the document if it is being read as it stands. The matched term and the link travel with every row.
Because search sorts and this filters. TikTok decides an order and shows it to you; here you state the conditions and everything failing them is gone before you look. The conditions are kept as well, so the next brief starts from the last one rather than from an empty box.