About and methodology

How the list is built

A scheduled collection runs against TikTok Shop search in the US across six category queries: meme, mug, retro, shirt, tumbler, vintage. Results land in a sheet that gets reviewed before anything publishes, and the site rebuilds from that sheet every Monday morning. A listing that appears under several queries is merged into one row that remembers each query it surfaced under.

The latest collection held 1,533 unique products. The homepage shows the top 300 by units sold. The tail is cut for page weight, not because it disagrees with the top.

What the numbers are

Price, rating, sold count, and shop name are the values TikTok Shop displayed at collection time, carried through unchanged. Nothing is modelled. We publish no revenue or GMV figure at all, because a modelled sales number attached to a named seller is a claim we cannot source, and publishing it would be guessing about somebody's business in public.

TikTok rounds large sold counts and does not document its method, so treat the figures as a ranking signal rather than an audited sales report. Rating coverage is partial by design on TikTok's side: a rating appears only once a listing has enough reviews, so a blank rating usually means new rather than bad.

What the list supports, and what it does not

It supports questions about direction. Which categories are moving, at what price points, with what review depth. Clusters are the signal worth acting on, because one viral product is luck and five in a category is a pattern.

It does not support conclusions about any single seller's revenue, margin, or business health, and it is not a recommendation to sell anything. A high sold count says a listing got attention and converted at some point before collection. It says nothing about whether that is still true today, or whether it was profitable.

Where this is weakest

The collection is a snapshot, so a product that spiked and died between runs is invisible, and one that spiked the day after a run looks absent. Coverage is limited to the six queries above and to the US, so an entire category can be missing simply because nobody searched for it. Sold counts accumulate over a listing's life rather than resetting weekly, which flatters older products against genuinely new ones.

Corrections

If a row is wrong, tell us and it gets fixed in the sheet before the next build. Corrections about a specific listing get priority, and a correction that shows the collection method is flawed gets more priority than that.