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Analytics

What each widget earned, how the numbers are gathered, and why they are not instant.


The Analytics page reports what each widget did: how often it was seen, how often it was used, and what it earned. Every number is per widget, so you can tell which placements are working rather than reading one total for the whole app.

What is measured

MetricWhat it counts
ShownWidget impressions — a widget scrolled into view.
ClickedA shopper opened a recommended product.
Added to cartAn add-to-cart from the widget itself.
OrdersOrders containing an item added from a widget.
RevenueThe value attributed to those items.
Click rate, add-to-cart rate, conversion rateThe three ratios between the counts above.

Why numbers are not instant

Counts are gathered in the shopper’s browser and sent as a single batch when they leave the page — one request per visit, not one per event. Those batches are totalled on the hour.

So a number you have just generated by testing typically appears within the hour rather than immediately. This is a deliberate trade: it is what stops the analytics costing your shoppers a request every time they scroll.

How revenue is attributed

When a shopper adds an item from a widget, Somix writes a marker onto that cart line. When the order is placed, Shopify tells us about it and we read the marker back. No order is matched by timing, by product, or by anything about the shopper — it is a direct lookup, which is why the number is trustworthy.

What is stored from each order is five values: the order id, the widget, the amount, the currency and the date. See Data and privacy.

Reading it usefully

  • Compare a widget against itself over time, not against another widget in a different position on a different page.
  • A high click rate with a low add-to-cart rate usually means the recommendations are interesting but wrong — try a more curated source.
  • A low click rate is more often placement than content. Try moving the block before you change the products.

Something here wrong or missing? Tell us — we would rather fix the page than answer the same question twice.