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Making Sense of Price Intelligence

While many retailers and brands are developing traction in their market through the use of price intelligence, it's important for them to take a few factors into consideration.

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.

About the Author
Jenn is a senior marketing executive with significant startup and small company experience gained in the telecommunications, software, and semiconductor industries. Jenn helps early stage companies build their market presence, customer footprint, and strategic business value. Jenn brings more than two decades of strategic marketing, product management, and business development expertise to 360pi, with an MBA from York University. Prior to 360pi, Jenn held senior technical and management posts with SkyWave Mobile, J2 Global, UBM TechInsights, CrossKeys, Bell Canada International, and IBM. Jenn is also a published author and regular speaker at industry conferences.