What a Shopify store audit returns

Pricing position

Every product is matched against comparable items sold elsewhere and placed in one of three bands. The split matters more than any average: an average sits in the middle while the products at either end are the ones costing you margin or sales.

Below the range

[SAMPLE DATA: count and % below]

Inside the range

[SAMPLE DATA: count and % inside]

Above the range

[SAMPLE DATA: count and % above]

The full report also names the products furthest above their range, with how many competing listings undercut each one, so you can see whether the position is deliberate positioning or drift.

Collection merchandising findings

What fills the top of each collection, and whether the ordering puts sellable products in front of shoppers.

• Sold-out products in the first row of [SAMPLE DATA: collection name]

  [SAMPLE DATA: n] of the first [SAMPLE DATA: n] products in this collection are out of stock. The first row is the most-viewed part of a collection page, so shoppers meet dead ends before they reach anything they can buy.

• [SAMPLE DATA: collection name] is a thin collection ([SAMPLE DATA: product count] products)

  Collections this small read as unfinished and give shoppers little to compare. Either merge it into [SAMPLE DATA: parent collection name] or expand it before giving it a slot in the navigation.

• [SAMPLE DATA: collection name] holds [SAMPLE DATA: product count] products in creation-date order

  Nothing is actively ordering this collection, so newest-added wins regardless of whether it sells. Proven sellers sit below products that have never converted, and shoppers rarely scroll far enough to find them.

Product listing issues

Listings a shopper, an on-site search index or an AI assistant cannot fully use.

• [SAMPLE DATA: count] products with no primary image

  These render as blank tiles in collections and in on-site search results. A shopper cannot evaluate them and will usually skip past them entirely.

• [SAMPLE DATA: count] products with descriptions under [NUMBER NEEDED: thin-copy word-count threshold] words

  Short descriptions leave buyer questions unanswered on the page where the decision happens, and give search engines and AI assistants little to work with when matching your products to a query.

• [SAMPLE DATA: count] sold-out products still published

  These stay linked inside collections and remain crawlable, so they absorb attention and crawl budget while sending shoppers to pages they cannot buy from.

Discounting and freshness observations

How much of the catalogue is marked down, how deep those markdowns run, and how recently anything new appeared.

• [SAMPLE DATA: %] of the catalogue is currently on sale

  Discounting at this share stops reading as a promotion and starts reading as the standing price, which trains repeat shoppers to wait for the next markdown.

• Average discount depth is [SAMPLE DATA: %], deepest is [SAMPLE DATA: %]

  The deepest markdowns are concentrated in [SAMPLE DATA: collection name], where the products discounted hardest are not the ones with the most stock to clear.

• Last product published [SAMPLE DATA: time since last publish] ago

  Returning shoppers see the same catalogue they saw last visit, which gives them no reason to browse rather than search for a specific item.