Shopify Competitor Analysis: A Step-by-Step Guide
A practical Shopify competitor analysis process: find rivals, profile their theme, apps and catalog, estimate traffic honestly, read their ads, and act.
Roasan Team13 min readTürkçe
A useful Shopify competitor analysis takes about an hour per store and needs no paid tools. You find five to ten stores that sell to your customer, profile each one from what their storefront exposes publicly (theme, apps, catalog, prices, policies), place their traffic in a rough size band, read the ads they are running, and then keep watching what changes. The output is not a report. It is a short list of decisions about your own store.
Below is the process we use, in eight steps, with the free source for each check and a checklist table you can copy.
Most people start with the brands they already know. Those are often the wrong comparison: a large brand with a retail presence and a big ad budget plays a different game from a two-person store. You want stores that sell a similar product, at a similar price, to a similar buyer.
Four ways to build the list:
Keep the list to five to ten stores. Ten profiles done properly beat thirty done halfway. Split them into two groups: direct competitors (same product and price) and reference stores (bigger stores in your niche whose choices are worth studying even if you are not fighting them for the same customer).
First confirm each store is on Shopify. Some stores in your niche will be on other platforms, and the endpoints in step 3 only work on Shopify. The Shopify checker answers that in a few seconds.
The theme tells you how much the store invested in its front end and what it is built to do. For context, Dawn, Shopify's free default theme, is the live theme on roughly 446,600 stores in our crawl, and Horizon on about 218,200. Dawn is the most common theme in almost every niche we track; in Home & Garden, for example, about 22.7% of stores run it.
So a competitor on Dawn is normal, not a sign of a weak store. A competitor on a paid theme built for large catalogs or heavy merchandising tells you they expect to need it. Use the theme detector to check. One caveat: stores often rename their copy of a theme, so a name you do not recognize may be a familiar theme underneath.
Apps show what a store cares about operationally: reviews, email, upsells, shipping tracking, loyalty. Here is how common some of them are across about 1.6 million active Shopify stores we crawl:
| App | Stores running it (approx.) | What it suggests |
|---|---|---|
| Facebook & Instagram (Meta) | 827,000 | Sells or advertises on Meta |
| Google & YouTube | 738,000 | Google Shopping or ads |
| Judge.me Reviews | 402,500 | Collects product reviews |
| TikTok | 243,600 | Sells or advertises on TikTok |
| Klaviyo | 174,100 | Serious about email and SMS |
| Parcel Panel |
Read the table as a baseline. About half the stores we see have the Meta app, so finding it on a competitor tells you little. Roughly one store in four runs Judge.me, so a competitor with no review app at all stands out. Roughly one store in nine runs Klaviyo, so seeing it usually means someone on the team works on retention.
Post-purchase apps (tracking, returns, order status) are the most telling. A store that takes no orders has no reason to install them.
An important limit: any outside tool, ours included, only sees apps that leave a trace on the storefront, such as a script, an app embed or a pixel. Inventory, accounting and other back-office apps are invisible from outside. "No app detected" means "nothing visible", not "nothing installed". The app detector lists what is visible for any store.
Profile a competitor's store in one go
Try it freeCatalog size and shape say a lot about a competitor's strategy: a tight range of 20 hero products is a different business from 3,000 SKUs pulled from a supplier feed.
Two public sources on most Shopify stores:
/products.json. Add it to the store's domain (for example yourcompetitor.com/products.json). It returns products as JSON: titles, prices, variants, vendor, product type, tags, and created and updated dates. It is paginated; add ?limit=250&page=2 and so on to walk through larger catalogs. Some stores block or limit it, so treat a missing result as "not available", not "empty store"./sitemap.xml. Shopify generates this automatically on every store. It links to separate sitemaps for products, collections, pages and blog posts, and is updated when products are added. Counting the URLs in the product sitemap gives you a product count even when /products.json is blocked.What to pull out:
This is where you can compete most directly, and it is all on public pages.
/policies/shipping-policy. Note the free-shipping threshold, delivery times and which countries they ship to./policies/refund-policy. Note the window (14, 30, 60 days), who pays return shipping and any restocking fee.Write the threshold and return window in your table. These two numbers decide a surprising number of purchases in categories where products are hard to tell apart.
No outside tool knows a store's exact traffic. Only the store, its analytics and Shopify do. What you can get is a defensible size band.
The best public source is the Chrome UX Report (CrUX), a dataset Google publishes from opted-in Chrome users. Beyond its speed metrics it places each origin in a popularity rank bucket: top 1,000, 5,000, 10,000, 50,000, 100,000, 500,000, 1 million, 5 million, 10 million or 50 million. A store needs enough real Chrome traffic to appear at all; Google does not publish the exact threshold. Being absent from CrUX usually means low traffic.
Those buckets are wide on purpose. Two stores in the "top 1 million" bucket can differ several times over in visits. Treat the bucket as a size class (tiny, small, medium, large) and compare competitors against each other, not against a precise number. Roasan converts the bucket into a monthly visit estimate and shows a confidence level next to it, because the honest answer is a range.
Plenty of tools show a monthly revenue figure for any store. From outside, that number is built by multiplying three estimates: visits, a conversion rate, and an average order value. Each one has a wide error margin on its own, and multiplying them compounds the errors. The result is a precise-looking number picked from the middle of a wide range.
Roasan puts selling signals next to every store: review counts, post-purchase apps, and products added in the last 30 days, each with its source. Use signals to compare competitors with each other. Do not plan inventory or budgets on someone else's guessed revenue.
The Meta Ad Library is free and public. You can search it without logging in, and Meta states it covers all active ads running across its apps (Facebook, Instagram, Messenger, Audience Network). Ads that delivered in the EU stay visible for a year after their last impression; political and social-issue ads are kept for seven years. For ordinary commercial ads outside the EU, you mostly see what is running now.
How to use it:
What the library does not show for commercial ads: targeting details, spend, clicks or conversions. Anyone selling you exact competitor ad spend is estimating it.
Ad pixels on the storefront also hint at where a store spends. Across our crawl:
A pixel can be installed and forgotten, so treat it as "set up for", not "actively spending on". The ad library is where you confirm it.
A single snapshot tells you where a competitor is. Changes tell you what they are trying. The useful ones:
Doing this by hand means repeating steps 2 to 6 every month and comparing notes. It works for three stores; it gets tedious at ten. Brand tracker follows competitor stores and records app, theme and product changes as they happen. If you check competitors while browsing, the Chrome extension shows theme, apps and product data on any store you open.
An analysis that ends in a spreadsheet changes nothing. For each finding, write one decision: do it, test it, or ignore it on purpose.
| Finding | Possible decision |
|---|---|
| Every direct competitor has visible reviews; you have none | Install a review app and run a post-purchase review request this month |
| Competitors offer free shipping from a lower threshold | Test a lower threshold on one product line for four weeks |
| A competitor's ad has run for months with one angle | Test that angle in your own words, with your product |
| Competitors' catalogs are 10x larger | Do not chase size; go deeper on your best 20 products |
| A competitor added a bundle app and new bundles | Check your average order value and test one bundle |
| Competitor return window is 60 days, yours 14 | Decide whether a longer window is affordable for your margins |
Three to five decisions per quarter is plenty. Revisit them when you repeat the analysis.
| What to check | Where | Free tool |
|---|---|---|
| Is it on Shopify? | Storefront source | Shopify checker |
| Theme | Storefront source | Theme detector |
| Visible apps | Scripts, app embeds, pixels | App detector |
| Product count, prices, new products | /products.json, /sitemap.xml | Browser, or the store analyzer |
Search your product the way a buyer would, note the stores in organic and shopping results, then search the same keywords in the Meta Ad Library to find stores paying for that audience. Narrow the list by niche, price band and country, and keep five to ten.
Yes, for apps that leave a trace on the storefront, such as scripts, app embeds and pixels. An app detector reads those. Back-office apps like inventory or accounting tools leave no public trace, so no outside tool can see them.
Looking at what a store publishes to every visitor (its pages, prices, policies, public product data and ads in a public library) is ordinary market research. Copying their text, photos or brand assets is a different matter and can infringe their rights. Learn from their choices; do not copy their content.
Guide11 min read
Guide13 min read
Guide11 min read
| Order tracking after purchase |
| Smile.io | 13,800 | Loyalty program |
| Shipping terms | /policies/shipping-policy | Browser |
| Returns terms | /policies/refund-policy | Browser |
| Traffic size band | Chrome UX Report rank bucket | Store analyzer |
| Active ads | Meta Ad Library | Meta Ad Library |
| Changes over time | Repeat monthly | Brand tracker |
You cannot see it from outside. Revenue figures shown by "checker" tools multiply estimated traffic by assumed conversion rates and order values, so the error is large. Compare selling signals instead: reviews, post-purchase apps and how often new products are added.
They are size bands, not counts. The most transparent public source, the Chrome UX Report, places sites in popularity buckets such as top 100,000 or top 1 million. Good tools show the band and a confidence level; be careful with any tool that gives an exact visitor number.
A full pass once a quarter is enough for most stores. Track changes (new apps, theme switches, product launches, new ads) continuously or at least monthly, since that is where competitors reveal what they are testing.