Competitor Price Monitoring: Price Index, Changes & Promotion Detection

What you'll build

What you will be able to do

Each lab ends with a concrete result that you build yourself and the checker confirms, cell by cell.

• Build normalised match keys from brand and model for Copperleaf Outdoor's catalogue and for scraped competitor listings, link each listing to our SKU with XLOOKUP and measure the match rate.
• Calculate Copperleaf Outdoor's price index per product against the average of three competitors, roll it up into a unit-weighted overall index and count the products priced above the market.
• Rank Copperleaf Outdoor's price among all shops for each product, label the position as Cheapest, Middle or Most expensive and measure the gap to the cheapest competitor.
• Turn two weeks of scraped competitor prices into day-over-day changes, flag every change, count how often each competitor reprices and chart the price history.
• Separate competitor C's temporary promotions from a permanent price cut: flag drops beyond a threshold, test whether the price returns to its old level within N days using OFFSET, then count the promos and measure their depth.
• Estimate the price elasticity of Copperleaf Outdoor's trekking poles from ten weeks of own price changes with a log-log regression slope, then predict the unit change for a planned price rise.
• Build Copperleaf Outdoor's automatic repricing rule: find the lowest competitor price, compute a margin floor from unit cost, set the new price with MAX and count the products where the floor stops the price war.
• Build Copperleaf Outdoor's weekly price dashboard: the price index per product, the share of products above an alert threshold, a sorted bar chart and red highlighting for the products that need attention.