A Best Sellers report has one job: show you the products that are actually selling in a category right now, ranked by real demand, with every number explained. We publish reports for 141 categories. This is the long version of how one is built and what every column means, because a report you cannot interrogate is not worth trusting.
Coverage is bounded by the Etsy API, on purpose
We do not claim to read every listing on Etsy. We sweep continuously against Etsy’s official API, as much as our daily quota and rate limits allow, which in practice is millions of requests a day. A rate limiter sits in front of every worker and can only ever slow us down, never speed us up, and it backs off the moment Etsy pushes back. We spend that budget where it matters first: the shops and listings showing the strongest signals. The picture rolls forward all day rather than trying to capture the whole marketplace in one pass.
A new review is a confirmed sale
On Etsy a buyer can only leave a review after an order has been delivered. So a new review is proof that a sale happened. This is the signal at the center of every report, because it is the one number a seller cannot inflate. We capture reviews, dedupe them by transaction so the same purchase is never counted twice, and roll them up per listing per day. When we say a listing gained reviews, we mean confirmed, delivered sales.
The columns in the report, and what each one is
When you open a category you see a ranked table. Here is what every column actually is:
- Rank. The listing’s position by reviews gained in the window you picked, not by all time totals.
- Product. The listing title and thumbnail, linking straight to Etsy.
- Price. The listing’s full price on Etsy, meaning the regular, non discounted price, before any shop sale or coupon. We show the list price on purpose so two listings are comparable.
- Rev change. Reviews gained inside the window. This is the core demand signal, the confirmed sales count for the period.
- Fav change. The change in favorites over the window, not the lifetime total, so a product heating up now stands out.
- View change. The change in views over the window, measured the same way.
Two badges add context. A New entry badge means the listing got its first ever review in the last 30 days, so you can tell a fresh breakout from a long running seller. A Top shop badge marks listings from shops with two or more rising products in this category and window, which is a signal of sellers with repeat best sellers rather than a one off hit. The header count itself is honest about scope: it shows listings reviewed in the last 30 days, and the 15, 7 and 1 day windows show fewer.
Windows
Every report can be read over four windows: the last day, the last week, the last fifteen days, and the last month. We rank by what gained the most inside the window, because an old bestseller is not a trend. Fast categories like apparel reward the daily and weekly views. Slower ones like home and living read better over fifteen or thirty days.
Open a product to see the full picture
Click any row and the detail view explains the listing end to end, with the same plain tooltips you see in the app:
- Reviews, the Etsy review count plus the gain today. Favorites, the number of shoppers who favorited the listing. Views, lifetime listing views. Fav per View, favorites divided by views, a rough proxy for shopper interest, not a conversion rate.
- A chart of the selected metric over time, so you see the shape of the trend, not just a single number.
- A shop card: Rating, the shop average review score from 0 to 5. Sales, the shop’s lifetime completed sales. Listings, active listings currently in the shop. Selling, years since the shop opened. In stock, quantity available for this listing. Pace, an approximate sales per day, computed as shop sales divided by the days the shop has been open.
- A full attributes panel pulled from the listing itself: type (physical item or digital download), who made it and when, processing time before it ships, whether it accepts personalization, variations and SKU count, where it ships from, and the published, modified and renewal dates.
The pipeline behind it
None of this is computed when you load the page. A daily pipeline does the heavy lifting in bounded chunks, never one giant query: sweep listings and reviews within our rate budget, prune dead and ended listings so the set only holds products you can still buy, enrich missing details once and cache them, snapshot favorites and views daily, aggregate reviews per day, compute the change over each window, rank the movers, and publish a finished report. The app then serves that precomputed result in milliseconds.
What we are honest about
Review based sales are a floor, not an exact total, because not every buyer leaves a review, so the real number is usually higher. Prices are the listed price before discounts. Favorites per view is a proxy for interest, not a true conversion rate. We state these limits in the product and here, because the point of a data tool is to tell you exactly what each number is and where it stops.