What gets checked
Whether the products that earn the most are published where buyers search. Which pages are indexed and which are quietly excluded. Whether every email flow is actually sending, measured against list size. How many visitors the store can identify. And what each channel really produced, from your own Shopify sales by referrer report rather than each platform's report on itself.
Why tracking is part of the audit
A store cannot decide where to spend until its channel report tells the truth. Untagged email and social inflate the direct bucket. GA4 installed through Shopify's web pixel does not appear in the page source, so people conclude it is missing when it is not. Deposit and variable weight products understate revenue unless the basis is fixed first. So Search Console and GA4 are read here, not sold as a separate project.
What it found on one store
On the beef brand in the case study, the checks turned up its highest-value products never published to Google, a weekly email that reached 13 people in six weeks, Facebook visits where 1 in 1,793 completed checkout, and a store that could identify about 0.8 percent of its visitors. Sales went from $5,110 in the slowest 30 days before the work (March 20 to April 18, 2026) to $35,812 in the best 30 days after (August 17 to September 15, 2026), by Shopify's own reports.
What you get
A plain list of what is wrong, in the order that pays fastest, with the reason each item sits where it does. If your store is not the bottleneck, the audit says so.
The proof, from one store
Straight from the case study, with the source and what it does not prove. See all five results.
Result 1 · SalesTotal sales: $5,110 to $35,812 in 30 days
Mar 20 to Apr 18, 2026$5,110
→Aug 17 to Sep 15, 2026$35,812
7x- Baseline: the worst case before the work
- $5,110 in sales from 27 orders, March 20 to April 18, 2026: the slowest 30 days the store had before the work began on June 4, 2026. Google and email brought in 24% of it.
- What we changed
- Rewrote product names, titles, descriptions and search snippets around what buyers search, with real weights (August 7 to 30). Built six city landing pages (August 1 and 2). Published the highest-value products to Google (August 24). Put welcome, abandoned cart and browse abandonment emails live (July 28) and replaced a weekly email that was not sending (September 4). Moved the Facebook budget to warm audiences (August 26).
- Result: the best case after
- $35,812 in sales from 75 orders, August 17 to September 15, 2026, 7 times the baseline. Google and email brought in 59% of it.
- Evidence source
- Shopify Analytics, Total sales over time and Total sales by referrer, pulled September 16, 2026. Beef shares count at full price on the day the deposit is paid, and the balance invoice that follows is left out, so no sale counts twice.
- What this does not prove
- This is the slowest 30 days before against the best 30 days after, not an average, which is why every month is in the table below. Beef shares are seasonal, and one September order for two whole shares was $9,480 of the result. The Facebook ads ran in both periods.
- Test it on your store
- In Shopify, go to Analytics, then Reports, and open Total sales over time. Find your slowest 30 days of the past year and compare them with your last 30. If you take deposits, count the full price on the day of the deposit.
Where this fits
This is the Stack Check stage of The Traffic to Sales Method. See it applied to one store, with the numbers,
in the case study.