Competitor store research, from public facts

Shopify competitor analysis usually starts with an afternoon of clicking through someone else's catalog. This analyzer does the reading for you, on a small and clearly stated sample, and keeps two things apart: what it observed, and what that might mean.

  • Overview. The store's name, its platform and the evidence for it, the positioning it states in its title, description and main heading, its navigation, its currency and market, and whether shipping and returns policies are linked.
  • Catalog sample. On Shopify, the first page of the store's public product feed: names, prices, compare-at prices, product types, variants, images and description length. On other platforms, a few product pages linked from the home page, read through their structured data.
  • Observed pricing. The lowest, highest, median and average price of the sample and how prices are distributed, always with the sample size, the scope, the currency and the time of collection.
  • Merchandising. Imagery per product, naming patterns, how discounts are presented, bundles and packs, review technology, trust messages and promotional messages on the home page, and how complete the product details are.
  • Interpretation. Visible strengths and the opportunities they leave open, each one linked to the observation it rests on.

Compare with your own store

Add your own store's address and the same public characteristics are collected for it and shown side by side. Prices are compared only when both stores price in the same currency.

How prices are handled

Prices are the list prices shown to an anonymous visitor when the analysis ran. They do not include taxes, shipping or checkout discounts, and a store selling in several markets may show other prices elsewhere. When a sample contains more than one currency, each currency is summarized on its own. Currencies are never mixed and never converted, because a converted figure would be an estimate presented as a fact.

What an ecommerce competitor analyzer cannot know

No public page reveals a store's revenue, sales, profit, advertising budget, conversion rate, customer acquisition cost or customers, and this tool never claims to know them. The sample is the order the store's own feed returns, not a random sample, so treat the statistics as a description of what was sampled. The analyzer reads only public pages, respects robots.txt and crawl limits, and stops if a site blocks automated requests.

Questions

How many products are sampled?

Up to a few dozen on Shopify stores, and a handful of product pages elsewhere. The exact number and where it came from are shown with every result.

Why are some prices missing?

A product page may not publish a machine-readable price, or the store may hide prices behind a login. Missing prices are counted and reported, never filled in.

Is this allowed?

The analyzer reads only what the store publishes to every visitor, follows the store's robots.txt and keeps requests few and slow. It does not log in, bypass protections or collect personal information.

Worked examples

Illustrative figures, not benchmarks.

Finding the price gap

Illustrative: a sample of 60 products shows most prices in the lower half of the range. Your store sells above it, so your page has to explain why.

Reading discount habits

Illustrative: 40% of the sample has a compare-at price. A competitor that is always on sale gives you room to compete on something else.

Comparing product pages

Illustrative: your competitor averages 5 images and 120 words per product, and you average 2 and 40. That gap is yours to close.

Common mistakes

  • Treating a sample as the whole catalog.
  • Comparing prices across currencies.
  • Assuming a compare-at price means a real discount.
  • Copying prices without knowing the competitor's costs.

Questions

Does this track prices over time?

No. It is a one-time view, labelled with its date.

Can it see their sales?

No. Sales, revenue and traffic are not public, and the tool does not estimate them.