You build a quick scraper to watch competitor prices. It works for a week. Then a retailer changes its HTML, another starts showing member-only discounts, and your dashboard confidently says a $49 product is now $0. Bad pricing data is worse than missing pricing data because people trust the chart.
Competitive pricing analysis sounds like a business topic, but the hard part is usually engineering: collecting comparable observations from messy websites, detecting when extraction breaks, and avoiding comparisons that look precise but are wrong.
Store observations, not just current prices
A common mistake is keeping one row per competitor SKU and overwriting the price every time a scraper runs. That throws away the context you need when something looks wrong.
Use an append-only model instead:
