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Retailers Find Success Using Self-Service and Advanced Analytics

By Robert Hetu | April 27, 2015 | 1 Comment

Retail AnalyticsData and Analytics StrategiesCustomer Analytics

Gartner defines advanced analytics as the analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover. These advanced analytics tools enable deeper insights and discovery that will challenge business assumptions. Retailers express interest in increasing their use because these tools put information in the hands of business analysts and business users and offer significant potential to create business value and competitive advantage (see Figure 1).

Gartner describes four stages of advanced analytic evolution:

Descriptive — reporting and dashboarding focused on what did happen
Diagnostic — reporting and query focused on why it happened
Predictive — modeling focused on what may happen
Prescriptive — decision making based on what will happen

With the rise of digital media came explosive growth in data volumes, and inexpensive storage encouraged retention of data with no present value because of the hope that it would be fruitful in the future. Today, retail BI analysts are so busy gathering information, often in reaction to an opportunity or challenge perceived by the business, that there is no time to analyze the data and glean useful information. Analytics teams have turned into reporting teams. The impetus of discovery, instead of being driven by information, continues to be driven by gut instinct, suspicion and assumptions. Since much of what the business is requesting has little chance of producing results from the first try, projects are often abandoned due to other priorities.

The connectivity between discovery and execution continues to be lacking. Poor execution capability has stolen the benefits of traditional BI. In cases where the retailer’s analytics teams have identified unique business opportunities, the business user’s ability to act can be hampered by inefficiencies in the existing execution systems.

My latest research Retailers Find Success Using Self-Service and Advanced Analytics describes the current state of analytics and what is required to ensure future success for retailers.  Several examples are included as well as a partial list of analytics providers for retail.

 

 

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1 Comment

  • Melody Burgess says:

    Nice thought. Having access to advanced analytics does help a great deal in taking constructive business decisions that would directly affect the growth of the company. Any eCommerce oriented business would require a RMS software like MultiFlex to be in place so as to streamline the business process and enable tracking of progress/regress.