Data-Driven Transformation Affair in Retail
Retail is one of the strongest and fastest-growing industries worldwide. 2019 onwards it will further pick up the pace and witness a glorious data-driven transformation. If you take a look at the statistics, the global retail industry is expected to register a CAGR of 5.3% between 2018 to 2023. However, such tremendous growth will also be fraught with competition. As of date, there are over 3.8 million retail organizations in the U.S. This ever-growing competition between retailers has made the scuffle for bagging bigger pie shares extremely taxing. Additionally, it has led to consumers demanding much more out of their retail customer experiences. Staying ahead of the competition today calls for much more than delivering exceptional products. It commands delivering exceptional retail customer experiences. As a joint report by IBM and SAP on data-driven transformation in retail quotes, “The proliferation of geographies, channels, and changing customer expectations has led to highly complex organizational structures that often operate independently. The result is inefficiency, high operational costs and inventory, increased markdowns, and suboptimal margins.”
Exceptional Customer Experiences are Etched in the Data-Driven Transformation
The best of brands are reaching to the roots of what their customers really want out of interactions. Of course, it’s quite a lot more than the product itself. Right from the status quo till the purchase and thereafter, today’s shoppers are looking for meaningful interactions that bring them a sense of joy, happiness, and emotional-fulfillment. Be it with online purchases or offline ones, what most shoppers appreciate is how well a brand is able to understand their needs, and provide personalized solutions, easily and speedily. To add to this, an omnichannel world also demands consistency and seamlessness across difference touchpoints that a buyer might come across during his purchase journey.
People don’t tend to purchase in their first interaction with a brand. Equipped with and enabled by the technology they are likely to do their own research before making the final purchase decision. What consumers demand is that their research is facilitated across all these touchpoints to help them make a better purchase. Needless to say, seamlessness and consistency should be ensured across all channels - online and offline.
Creating such consistent experiences that deliver exactly what the consumer is looking for is only possible through data-driven transformation. Walmart, the world’s biggest retailer, has over the past few years been brilliantly shining in providing convenient and connected experiences for in-store and online buyers. After all, that’s what users hunt for today - a super smooth and easy buying experience wherever they wish to shop from. For example, Walmart has positioned associates in those areas inside their stores that are likely to receive a huge rush of customers on all days. This helps these buyers bypass the regular checkout lines, and instead pay for their purchases right inside the department that they are shopping in. This is just one of the many ways in which Walmart has worked towards data-driven transformation.
To further ease up shopping in a retail store that’s full of inventory, Walmart has come up with Store maps. Just open the app when you are shopping in the store trying to look for your items. The map will show you the exact location of the items you are searching for inside the store. Without making use of customer data, Walmart wouldn’t possibly have figured out what makes people abandon their in-store purchases. They could have kept losing out a high volume of instore traffic because of the overflowing checkout line. Or even because of an overflowing inventory making it difficult for people to look up for products that they need.
Apart from the ease and convenience of shopping, winning an upper-edge over the laggard competition with data-driven transformation also demands to build personalized experiences. Whenever a shopper interacts with your brand, regardless of the channel they use, they leave considerable information and insights that brands can use to their advantage. Retailers can use this data for adequately fulfilling what consumers require and deliver personalized experiences. Consider this hypothetical example. A Walmart customer might look up a product on the Store map but end up not buying it because it wasn’t in stock. Store owners can use the shoppers ‘Store map’ data to alert him about when the product gets back in stock or to send him real-time notifications of the product being available for online purchase.
Where this is just a hypothetical situation of data-driven transformation, brands like Dansk Supermarked Group have in reality leveraged this trend to facilitate personalization through data. Right before the store opens every day, the store manager review morning before DSG’s retail locations open, store managers review each customer’s purchase history and prepare personalized reports that they can make use of to make wise inventory-stocking decisions, reduce spoilage, and, to improve their company’s profit margin. Moreover, gaining a complete picture of every customer helps the retailer understand their target market better and how consumers tend to interact with brands. This doesn’t just help them predict market patterns but also get a competitive edge in the industry. All with the help of technologies such as the cloud, predictive analytics (real-time), the Internet of Things and artificial intelligence. One can go on and on about how data-driven transformation has powered up retailers to deliver exceptional retail customer experiences. Enough evidence about the importance of data exists in the forms of examples and stories. However, it’s best proved by statistics. A McKinsey research establishes that data-driven enterprises are 23 times more likely to acquire customers, 6 times as likely to retain customers, and 19 times as likely to be profitable as a result. No one can ignore these numbers.
Even Capgemini suggests, “From finance and procurement to product lifecycle and supply chain, you can automate, accelerate, analyze, and predict across all your core processes. You gain a foundation for digitization and real-time business across your geographies and lines of business. Plus an intelligent platform for AI-enabled applications and digital assistants.”
Wrapping it up. Collecting relevant customer data and driving meaningful insights out of them lies at the heart of creating and implementing data-driven transformation for better customer experience. However, in an omnichannel environment where in-store and onsite experiences converge, data can be overwhelming. The ever-changing customer shopping patterns and trends are getting extremely complex and incomprehensible. To be able to map how they interact with a brand online versus offline has a direct impact on how sustainable the bottom line is for a retailer. This is where retail analytics solutions for data-driven transformation comes into the picture. From uncovering product and inventory data to unveiling customer purchase patterns to making sense out of store analytics, BluePi powers the data-driven transformation for your retail business. With a complete picture of what your customers need, how you can facilitate their requirements better, and where you need to improve, you can create experiences that resonate positively with your customers.
Leveraging accurate forecasts to maximize profits, BluePi reduces the operational costs for a retail business. It takes care of everything from demand planning, replenishment, markdown optimization, inventory rebalancing, product availability insights to POS analytics for a holistic data driven transformation.
In the retail industry, the accuracy of inventory is only about 63%. How accurate is yours?