Price Change Impact Detector
Detects products where performance shifted sharply and correlates changes with pricing movements to identify pricing wins and mistakes.
- agent ›A pricing win: three weeks ago you raised the 'Espresso Grinder Pro' from DKK 1,895 to DKK 2,195. Orders fell 9%, revenue rose 6%. I've posted it to your Slack channel.
- you ›Revenue was up across the whole site those weeks, though. Black Friday warm-up.
- agent ›Site revenue rose 4%, and I take that out: net of the site, the grinder is up 2%, not 6%. Still a win — smaller than it looks.
- you ›Should we raise the price on the other grinders too, then?
- agent ›One at a time. The 'Grinder Mini' sells in very different baskets: its average order is DKK 640, against DKK 2,300 for the Pro. A price rise there is a separate test, not the same result.
What it does
Not every price change is a mistake; some are the best decision of the quarter. This agent starts from the products whose revenue, conversion or order volume shifted sharply and checks whether a price change sits behind the shift. It filters out the movement of the site as a whole, so a product carried by a good week is not credited to its new price, and it looks at average order value too, because a cheaper product can sell more and still earn less. Each outcome is classed as a pricing win or a pricing mistake, with the numbers before and after and a recommendation. Insights can be posted to your connected Slack channel, where the people who set prices will see them.
An example insight.
What a result from Price Change Impact Detector looks like. The numbers are an illustration, not a customer's.
Price cut on 'Trail Pack 30L' sold more but earned less
Cut from DKK 899 to DKK 699 on 3 October: orders up 38%, revenue down 7% once the site-wide trend is taken out. Average order value with the pack fell from DKK 1,120 to DKK 860 — buyers no longer add an accessory to reach free delivery.
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