Bad Change Detector
Detects whether any page changes correlate with performance drops
- agent ›Front page: clicks on the 'Winter jackets' tile fell 41% after Tuesday's update, when its model photo was swapped for a flat-lay. Estimated cost so far: DKK 18,400.
- you ›Clicks always dip after a change. People need a few days to get used to a new photo.
- agent ›It's been five days and there's no recovery: 6.1% click-through before, 3.6% since, against a steady 5.9–6.3% in the eight weeks before. The other tiles on the page held their numbers.
- you ›So we roll the whole update back?
- agent ›Just the tile. The two other changes in that update — the new USP bar and the reordered menu — show no regression. Put the model photo back on 'Winter jackets'; the next run will show whether click-through returns.
What it does
Watches your highest-revenue pages — the front page and the pages you mark as key — and the key elements on them: hero tiles, banners, navigation, buttons. Every time one of those elements changes, it compares the element's click-through before and after the change, using regression detection rather than a simple average, so a normal day-to-day dip is not reported as a problem. When a change and a drop line up, the insight names the page, the element, the version that changed it and when, how far clicks fell, and an estimate of the revenue the drop is costing. Changes that did no harm are left alone, so one bad edit in a busy release does not get the whole release rolled back.
An example insight.
What a result from Bad Change Detector looks like. The numbers are an illustration, not a customer's.
Revert hero image to recover lost conversions
The hero image deployed Tuesday correlates with a 12% drop in add-to-cart rate on mobile. Reverting to the previous version would recover estimated revenue immediately.
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Every category
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Book a demo and we'll show you what Historian finds on your own store.