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Big Data, Analytics, and KPIs in E-commerce and Retail Industry



As of 2018, retail industry represents 31% of the world’s GDP and employs millions of people throughout the globe. As the number of retailers, companies, and competition for a product has increased there is a rising pressure to lower the pricing in the retail environment.


Innovations in technologies dealing with scanning, analytics has strived to improve customer experience through the ease in the availability of product information. Through ‘Red laser’ technology, customers can directly scan barcodes of products and get relevant information that is required to choose a product. Bar-codes also help in obtaining transactional data that could be leveraged by the retailers to improve their customer experience.


Analytics has been widely used in various sectors across the world. The retail industry is one of them. Companies like Bestbuy strive to improve customer experience through analytics. Analytics helps companies to optimize their merchandising decisions to drive topline and bottom-line improvements, provide more timely responses to customer requests, reduce cost in prior, and also enhance the productivity of employees.


Following are the types of Big data analytics used in Retail industry:


  • Customer analytics and Key performance indicators (KPIs): Customers are the most integral part of the retail environment and solely decide the future of the company’s profit and place in the market. Through customer analytics and KPIs, retailers can discover the interests of their customers, track their expectations and sentiments, track their behavior, track impacts of promotions on basket, use transactional data to gain insights on the relations between the different components in retail i.e., customers, stores, products and promotions, create targeted micro-segments etc. As a whole, retailers can find their most valuable customers and target them to maximize their profits and improve loyalty through analytics.


  • Merchandising KPIs: Through KPIs in merchandising, retailers can evaluate top-selling products and accelerate shipments, cancel shipments for bottom-selling products, make mark-down decisions based on seasonal sell-through, and communicate more effectively with vendors based on the insights. As a whole, through merchandising KPIs retailers can significantly reduce costs, eliminate the expense of stock-outs and overstocks, and make powerful and rapid decisions.


  • Store operation analytics and KPIs: Though online retail has increased its pace, stores still occupy an integral position in the retail environment. Analytics and KPIs in store operations help in improving the effectiveness of sales assistance by placing them at the right floor at the right time, reducing queues, improving merchandising and promotions by providing store operations the right information at the right time to make right decisions. These, in turn, reduce out-of-stock situations. As a whole customer experience is enhanced, staffing is optimized, efficiency is improved and profitability is increased.


  • Vendor and SKU Management scorecard and KPIs: Stock Keeping Unit management systems enable a connection between retailers and suppliers to achieve a combined goal of accurate and efficient management of item information to improve future performance. Such as system allows for electronic SKU submissions from suppliers, online SKU set-up, and an automatic SKU management workflow. Through employing analytics in SKU and vendor management, retailers can increase their sales due to faster product reach, improved data accuracy for inventory management and replenishment to cut down out-of-stocks and reduced costs through minimization of manual processes and elimination of data entry.


  • Marketing analytics and KPIs: In this age of social marketing, the retail environment is susceptible to any influence in customer interests. Analytics helps in finding the traffic and prospects through social media conversations, find the reach of the product through subscribers, followers etc., gain insights on competing companies etc.


  • Returns, Fraud, and Loss prevention analytics: With the rise in cyber-crimes like hacking, the illegal gaining of information on public etc., it is a very important task for retailers to provide confidence to their customers for the privacy and security of their data and money. Through analytics, retailers can predict return trends and suggest the number of necessary reserves, gain insights intro thefts related to credit cards and checks etc.


Through the use of IT and digital data, the retail industry is boosting profitability. Top retailers like Amazon, Neiman Markus have been leveraging analytics to their advantage. But, tight margin retailers have been facing challenges. These challenges could be solved by improving selling, general and administrative costs and inventories which would directly improve margins. In the end, for retailers to stay top in the market they need to manage costs in short-term and have a sustainable competitive advantage in the industry.


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