Authored by Brian Chung (edited by Nicki)
For years, retailers have chosen their differentiation strategy to gain competitive advantage in the market. These determined core retail capabilities include scientific merchandising to identify market-relevant products, dynamic pricing to secure the profit, campaign/promotion analytics to optimize marketing spendings, store profile/location analytics to maximize the real-estate investments, etc. Today, these strategic approaches are still relevant to retailers, but they have also become vastly more complex. Take pricing, for example. Historically, this was mainly focused on setting the optimal product price point, finding the best time for mark-downs, and negotiating a good deal with vendors. But now, these same relevant pricing factors have become more complex. Retailers need to automate pricing changes across channels, and predict the profit impacts nearly in real-time. This is all required to capture the highly-informed consumers, with likely multiple alternate retailer options at their disposal. And, such valuable save-the-sale pricing across these channels is only relevant if you can keep customers on the desired platform long enough with relevant, desirable offers.
In describing these increased complexities to core retail competitive strategies, with pricing as one example, I also mentioned necessary functions such as