Price intelligence is one of the most dynamic and rapidly evolving categories in retail technology today. While price intelligence software was relatively unknown several years ago, today it’s a “must-have” for every retailer, and increasingly for brands.
Having implemented a large number of retail and brand price intelligence solutions, here are some of the factors 360pi recommends that you consider when evaluating the quality of data and interpreting competitive insights.
- The inclusion or exclusion of out-of-stock products can greatly affect your analysis. For example, during the 2014 holiday season, 360pi reported that including out-of-stock products in a major retailer’s average online daily price resulted in price variation of four to eight percent and spiked to double digits during a 75-day period. 360pi also observed retailers changing prices on out-of-stock items.
- Sample selection. Quite simply, a different sample will yield different results.
- Sample size. The number of product matches included will impact the statistical validity of the results.
- Timing and frequency of price extraction. Pricing data is extracted at a point in time. It may change before or after the data is collected and some large retailers including Amazon, are known to change some prices intraday.
- Marketplace consideration. The decision whether or not to include pricing for marketplace or third-party vendors will impact a retailer’s relative price position.
- Consideration for shipping and taxes. Either of these options may or may not be included in a price intelligence exercise, impacting the resulting data set.
- Match equivalence. Pricing data may include exact matched products only or also include pricing for other similar products and private brands.
- SKU aging. The number and type of product matches change over time (i.e. a shopper does not buy the same television model this year, as last) requiring different assumptions in terms of how to report relative retailer competitiveness over time.
- Price index weighting. All matched products may be weighted equally in a competitive price index calculation or different weightings may be applied to reflect the specific roles that different products play in a retailer’s assortment.
As these examples illustrate, determining relative retailer competitiveness using price intelligence is not a simple “black or white” assessment, but rather a strategic exercise that directly affects the top and bottom lines.