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“Being a girl I should be more shopaholic, but I am not. One day, me and my friend went to central mall and saw that the accessories section which was there on first floor has been shifted next to ethnic wear section, which made us buy earrings matching my kurti right away, otherwise I would have delayed it. I was wondering, why they have reallocated the sections”… there is nothing called coincidence in this, here is where analytics plays a critical role in retail sector. With customers becoming more techno savvy, retail sector is experiencing growth both at online and offline fronts, opening up new stream for forward-thinking retailers. With the wealth of data, analytics holds the potential to drive real front line differentiation for the particular retailer. Retail Analytics can be applied on various business functions be it customer management, pricing, strategies, Fraud detection, supply chain management, workforce analysis, cross selling and up selling analysis etc.
Here are some of the business functions on which analytics can be applied:
Customer management: With informed and challenging customers in this highly competitive environment, traditional methods of customer engagement have become redundant. Customers’ preferences and behavior keep on varying over time. Therefore, meeting customer expectations has become priority for retailers. Analytics deliver insights on customer engagement assessment, churn rate, share of wallet (identifying customers with the propensity to increase spending and opportunities for the same). Using predictive analytics, retailers can increase their sales and reduce potential losses by proper targeting.
Pricing strategies: Pricing is a key to survive competition as well as the growth for any entity. Analytics provides valuable insights on the demand for a particular good, competition in market, customer segments and their shopping behavior, with which price can be set up accordingly without eroding the customer base.
Fraud detection: Analytics plays a role for evaluating processes within the organization by analyzing the unusual patterns encountered; this reduces the risk for the organization. More complex the operations, higher the chances of fraud. With periodic analyses, analytics captures where things are going wrong.
Workforce analytics: Quality matters more than quantity, the same holds for workforce employed. By increasing their efficiency, one can better handle the customer base. Analyzing store traffic, required tasks etc. increases workforce efficiency and productivity. Analytics also captures productivity of the employees which influences their hiring and retention decisions.
Supply chain Management: With increasing customer base, maintaining inventory, reducing transportation cost, increasing collaboration with suppliers becomes crucial for the retailer. With the help of data, predictive analytics can be applied to draw insights related to amount of inventory that will be required and at what time.
Cross-selling and up selling : This is one of the strategies used by retail outlets to increase their revenue. By analyzing the shopping pattern of customers, retailers can suggest the complementary products to the customers. With appropriate product mix it can make offers that can be mutually beneficial for both customers and outlet. Likewise, up selling to the target customer requires analytics to identify them. These are some of the focused areas where analytics has proved to be invigorating with respect to overall growth of a retail store and there are many more areas to explore in retail analytics.
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