Data quality is important in every corner of the business world, but in retail, it's a particularly salient issue because consumers today demand speed. They want their merchandise and they want it now - and by using large volumes of data to analyze supply chains, vendors can improve their decision-making and advance toward their ultimate goal of giving customers the products they need quickly.
Gagan Mehra, an expert on e-commerce and big data, recently wrote for Practical E-Commerce that improving the supply chain is the most relevant area where merchants can apply data analysis. If stores can obtain goods in a timely fashion, they can then turn them around and deliver them to end users. In a competitive business climate, this separates successful companies from failed ones. The store that wins the supply chain race will eventually win the customers as well.
With that in mind, let's look at a few areas where data analysis can improve supply-chain procedures.
Sourcing is of utmost importance to retailers. If a product is ever out of stock for any reason, companies are in trouble. Not only are they unable to make certain sales that could help improve their bottom lines, but it's also bad PR to admit that supplies have run low. Using data analysis to improve automated sourcing processes can help businesses improve their profit potential and their images.
When a customer logs onto an e-commerce portal and makes a purchase, he or she expects to receive goods quickly. Retail companies need to examine the way they deliver products to their customers and make sure there are no inefficiencies. By using data analysis to evaluate different methods of shipping and handling, merchants can find the best ways to deliver their products.
Personalizing the supply chain
People don't want to be treated like they're "just another customer" when they order from stores, whether in person or online. They want a personalized experience that includes respect and good customer service. Companies in the retail sector should therefore use data analysis to evaluate the way they interact with customers, recommend products and lend a helping hand when things go wrong. Each customer has different tastes, and while data can't isolate every single individual, it can certainly find some general rules of thumb that work.
Customers have lofty demands for their retailers today. Thanks to data analysis, companies now have the power to meet and exceed those expectations.
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