Retail Analytics

Customer-centric analytics is the backbone of retail insights, and by understanding your customers better - e.g. what are the common characteristics of your most loyal customers, what's driving customer churn, what product mix is typical of new customers, what are my customers saying about their experience - you are well placed to service them more effectively and grow revenue. 

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Retail analytics, however, can be wider; it covers all areas of operation for a retail firm, which may also include questions such as: what are the common features of my best sales people, can product demand be forecast more accurately and inventory management improved, are my products optimally priced? Finding answers to these questions may also grow revenue or alternatively help to reduce costs. 

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Analytics solutions will broadly fall under one of three categories:

• Descriptive - Passive reporting of historical and current data, "what happened?"

• Predictive - By modelling historical data, which helps to uncover "why did it happen", we can estimate "what will happen"

• Prescriptive - combining descriptive and predictive analytics, specific recommendations can be made to influence outcomes and achieve a desired result. 

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These solutions then need to be operationalized, and analytics embedded into the rhythm and culture of the business.​

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