Methodology

CraftRank exists to surface numbers Etsy keeps fuzzy. Etsy does not publish exact sales or revenue for a listing, so we estimate them from data that is public. This page explains how, and just as importantly, how to use the estimates well.

Where the data comes from

CraftRank's research data is derived from publicly available Etsy data, the same information anyone can see on the site: listings, prices, views, favourites, shop sold counts, reviews, and tags. If you optionally connect My Shop, you authorise CraftRank through Etsy OAuth to verify ownership. We never receive your Etsy password and do not retain private seller, transaction, or private listing data.

Most metrics are refreshed daily. Shop and keyword results are cached briefly (typically within a day) so repeat lookups are fast, which is why two analyses close together can show identical numbers.

How estimated sales work

Etsy shows views but not how many of those views became orders. We estimate sales by applying a typical view-to-sale conversion rate to a listing's view count. The result is an estimate, not a counted figure, so treat it as directional.

When we analyse a whole shop, we can do better than a generic rate: we use the shop's own observed conversion, derived from its real sold count against the views of its active listings. That makes per-shop sales estimates more grounded than a single listing's estimate.

How estimated revenue works

Revenue is estimated sales multiplied by the listing's price, converted to USD where needed. Because it builds on the sales estimate, it carries the same caveat: good for comparison and scale, not an exact dollar figure. Actual revenue varies with sales, promotions, and other things Etsy does not expose.

Listings with variations

Etsy publishes one price per listing. On a listing that offers variations, such as several sizes or finishes at different prices, that published price is the cheapest option. The exact per-variation prices are only available to the shop owner, so no external tool can read them for a competitor.

We do not guess at the difference. Instead we mark it. Wherever a price comes from a listing with variations, the app shows it as a starting price ("from"), and every figure built on that price is a lower bound rather than a best guess:

The listing's estimated revenue, on its own page and in the results tables.
A shop's average listing price and gross lifetime sales, where the effect grows with the share of the catalogue that uses variations. Shop Analyzer tells you that share.
The price bands in Shop Analyzer, which count those listings at their cheapest option.

In practice this means a shop selling mostly variation listings will estimate lower than it really earns. Read those numbers as a floor, and compare like with like: two shops that both lean on variations are still directly comparable.

The one measured number: shop conversion rate

The conversion rate in Shop Analyzer is the exception to all of the above. It is measured from the shop's own public sold count and views, not estimated from an average. That makes it the most reliable signal in the app, and a good one to benchmark against.

How the opportunity score works

The Opportunity score in Keyword Explorer is a single 0-100 read of whether a search term is worth competing for. It balances two things:

Demand how much buyers want the term, based on how many listings target it and how well the leaders sell.
Competition how hard it is to break in, based on how crowded the term is and how entrenched the ranking listings are.

A term with strong demand and weak competition scores high; a crowded term with little demand scores low. The app labels the bands for you: 66 and above is high, 33 to 65 is moderate, below 33 is low, and the demand and competition meters use the same bands so you can see what is driving the score.

How to use directional numbers well

Estimates are most useful when you lean on their strengths:

Compare, do not quote. The estimates are reliable for ranking shops or listings against each other, less so as a precise figure to put in a spreadsheet.
Watch the trend. Because data refreshes over time, the direction a number moves is often more telling than its absolute value.
Trust the measured signals more. Shop conversion rate, review counts, and prices are observed, not estimated, so weight them accordingly. The one caveat is a price marked "from", which is the cheapest of several variations rather than the whole picture.

FAQ for data, privacy, and plan questions.
Keyword Explorer for the opportunity score in action.