Shopify’s built-in analytics are better than most operators give them credit for. The order and revenue data is the ground truth every other tool tries to match, and the reports cover most of what a weekly review needs. The problem is that there are dozens of reports and no guidance on which ones matter. Here are the seven I check every Monday, in order, and what I am looking for in each.
1. Net sales over time, against last year
Net of discounts and returns, by day, with the same period last year alongside it. Gross sales flatter you. I care about the trend line and whether this week broke from it. A single bad day is noise. Three in a row is a question.
2. Sessions and conversion rate
When sales move, this tells me whether it was traffic or conversion. Traffic down with steady conversion points to marketing. Conversion down with steady traffic points to the site, the offer, or stock. I also glance at add-to-cart and checkout rates, because a drop late in the funnel usually means something broke. Benchmarks are in what is a good conversion rate for a Shopify store.
3. First-time versus returning customers
The number of new customers and their share of revenue. If total sales are up but new customers are flat, growth is coming from your existing base, often through email or discounts, and acquisition is stalling. This is the report I would show a founder if I could only show one.
4. Sales by product
Top products by net sales, and anything that moved sharply up or down. I filter to first-time customers once a month to see which products are bringing people in. A sudden drop on a top product usually means stock, price, or a broken ad, in that order of likelihood.
5. Sales by discount code
How much revenue came through discount codes, and which ones. Influencer and affiliate codes show up here, as do codes that leaked to coupon sites. If discounted revenue is creeping up week over week, margin is quietly eroding. I wrote about the pattern in the discount frequency problem.
6. Sessions and sales by traffic source
Shopify’s referrer and UTM-based views give a rough last-click picture by channel. I use it as a sanity check, not as attribution. If Meta reports a great week and Shopify shows Meta-referred sessions down, I want to know why. Shopify’s attribution has real limits, which I covered in does Shopify have built-in attribution, and is it enough.
7. Returns
Return volume and value, by product if your setup records it. Returns lag sales, so a spike this week usually traces to orders from two or three weeks ago. Watching it weekly catches sizing or quality problems before they compound.
Where Shopify analytics stop
Shopify does not see ad spend across platforms, so it cannot give you ROAS, CAC, or MER by channel without another tool or a spreadsheet. Its channel view is last click, so it under-credits anything that works earlier in the journey. And it does not model customer value over time in depth.
So the weekly review needs one more input for the marketing side. Mine is an attribution tool. ThoughtMetric pulls spend from the ad platforms, credits each Shopify order once across channels, and splits new and returning customers by channel and product, which extends reports 3 and 4 above into ad decisions. (Disclosure: ThoughtMetric sponsors this site.) It starts at $99 a month for 50,000 pageviews. For broader options, see Shopify analytics tools that go beyond built-in reports.
The Monday routine
- Net sales against last year, then traffic versus conversion to explain any change.
- New customers and their share of revenue.
- Top products, discount code revenue, and returns for early warnings.
- Shopify’s traffic sources as a sanity check on ad platform claims.
- An attribution tool, such as ThoughtMetric (our sponsor), for spend, CAC, and channel decisions.
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