What is matched-SKU inflation (same-SKU price change)?

Matched-SKU inflation, also called like-for-like or same-SKU inflation, compares the price of exactly the same products at two points in time. Products that are new or discontinued are excluded from the comparison.

This is the approach official statistics agencies use for price indices, because average price across a changing range mixes real price changes with changes in what is on sale.

Matched-SKU inflation = exp( average over matched SKUs of ln(price now / price a year earlier) ) - 1

Three products are listed in both periods: one went from $50 to $55 (+10%), one from $20 to $20 (0%) and one from $80 to $76 (-5%).

The geometric average of the price ratios (1.10, 1.00, 0.95) is about 1.016, so matched-SKU inflation is about +1.6%. A product launched this year, however expensive, does not change the figure.

Data Purl builds a panel of SKUs observed in both periods and averages their price changes geometrically (the Jevons method used for elementary price indices), so each product counts equally. Where pack sizes vary, prices are normalized to a price per unit (per ounce, per 100g, per liter).

The difference between average-price change and matched-SKU change is reported separately as mix shift and new-product effect.

It answers the question 'did this brand actually raise prices?' rather than 'did it sell more expensive products?'. The two can move in opposite directions.

• It measures listed online prices, not transaction prices across all channels.

• Tracking a company's pricing power with eCommerce data
• Measuring category inflation from online prices
• Monitoring portfolio companies and competitors after the deal
• Measuring tariff price pass-through with online shelf prices
• Tracking private label share and price gaps
• Using eCommerce data in a consumer earnings preview
• How to choose an eCommerce pricing and assortment data provider