Analytics for JC Dollar Essay

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Business Analytics Project

JC Dollar Analytics Strategy

The $10M investment in creating a customer loyalty program has set the foundation for capturing, aggregating, analyzing and making recommendations from customer's preferences and expectations that are not being delivered in experiences today. Continuing to pursue a price reduction strategy in an attempt to increase sales has proven ineffective, which is further validation to JC Dollars store management that their stores operate in an inelastic market. Additional data on price elasticity captured as part of the customer loyalty program will over time will continue to underscore just how inelastic the chain's pricing is based on the commodity-like nature of clothing and accessory retailing. Of the many benefits of analytics, one of the most valuable is being able to gain insights into pricing and purchasing behavior for specific product and service categories, providing decision makers on which value-add strategies are most effective (Gnatovich, 2007).

The business problems that JC Dollar is fixing revolve around incorrect assumptions about customer loyalty. Combining customer loyalty data and predictive analytics will provide a unique glimpse into their customer base not seen before. One of the most significant contributions of predictive analytics is the ability to take massive data sets and succinctly gain insights through the use of advanced predictive analytics and Big Data-oriented analytical tools (Sharma, Dadhich, 2014). In addition, JC Dollar's modifications to their pricing strategy and merchandising mix may be contributing more indirect customer loyalty than the company realizes. With predictive analytics, the individual contributions of each component of a strategy can be isolated provided a suitable methodology has been defined (Davenport, Harris, Emberson, 2007). Competing on price alone, making the incorrect assumption JC Dollar customers are only driven on price, will be proven wrong when this level of granularity is applied to the current and future conditions of their business. What's missing from the scope of business problems the company is the measurement of the customer experience being delivered in the stores. One of the most underrated aspects of predictive analytics is the ability to track attitudinal data in addition to the many more easily quantified metrics of customer behavior (Sharma, Dadhich, 2014).

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It's reasonable to assume that the JC Dollar sales problem may not have anything to do with pricing but instead with the in-store experience and shoppers in their target audiences may just be bored with the experiences of being in their stores. The lack of enthusiasm for their products and the stores is what's potentially driving the sales drop, not their pricing. Using analytics to measure how pricing reductions may have actually hurt their brand is also possible and often done in industries that have commodity-like pricing structures (Schauer, 2004). Another business problem that the company must contend with is the grim reality that their product lifecycles may not be fast enough to keep up with the preferences, perceptions and expectations of their customers. In retailing the speed of new product development and introduction often dictates which store chain will be profitable or not. Predictive analytics also needs to be applied to the challenging issue of planning product lifecycles that are very short, which are common in retailing. Using predictive analytics for product development and the timing of new product introductions can significantly improve the execution of this critical strategy (Schauer, 2004). With nearly all retailers getting at least 70 of their revenues from their new product introductions, this issue of the product strategy, its timing, seasonality and measuring customers "expectations vs. experiences all needs to be taken into account in the context of this study. Finally customer loyalty is not a fixed or predictable investment, it is rather a relationship built with customers over time that must be invested in with new, exciting, interesting products and serves. Analytics will help to show that customer loyalty must be constantly earned over time.

Planned Process

The two hypotheses that senior management have initially chosen for this study include the following:

Whether or not the loyalty data at JC Dollar can be effectively leveraged to increase customer loyalty, and lead to improved business results.

A broader, enterprise-wide analytics….....

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