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Whether retailers use mobile for line busting, mobile point-of-sale, endless aisle customer ordering, or personalized consultative selling, the need for rich and relevant data is critical to driving the desired customer engagement model. Accurate and timely aggregation of the data needed to drive a differentiated cross-channel mobile customer experience challenges even best data architecture design. Legacy systems and data integration strategies have simply not been built to support a mobile world.
Retailers generally agree that rich and relevant associate-to-shopper engagement is a winning strategy that facilitates a differentiated customer service experience in the store. Retailers have also made significant investments in defining a cross-channel mobile customer engagement strategy, building a supporting IT infrastructure, and designing mobile applications to drive the customer experience. At this point, it becomes clear that strategy execution is bound by the data available. Rich, relevant, and timely data is the medium that makes a mobile strategy real. In most instances, a retailer’s data architecture is not designed to support the needs of mobility.
Take for instance a mobile customer who is just about to walk into a store. A customer may have researched an item on the Web, may have requested an item be reserved online and picked up in the store, or even requested an out-of-stock item be ordered and shipped to their home. Each scenario poses a myriad of data challenges for legacy systems:
• How are pricing disparities across channels rationalized?
• How are differing assortments unified across stores and stores vs. eCommerce?
• How are differing inventory sources, replenishment minimums, and available-to-promise quantities unified?
• How are mismatched and missing item descriptions and digital content managed?
• How are different views of the customer consolidated?
• How are different payment and financing options managed?
• How are transactions segregated and sales credited by channel?
Failure to resolve these issues ahead of time results in, at best, an inconsistent brand experience and, at worse, a disappointing customer engagement that leads to loss of loyalty and confidence. Solving the data problem requires a retailer to understand the data they have and the data they need as an overlay to the customer experience they want to drive, then to deploy the appropriate secure and high performing information platform to meet the customer needs.