While the perks of running a business in an innovation-aggressive era commercialized cutting-edge tools for anyone to elevate their game, the downsides have shown them that, from a customer’s point of view, trends are highly volatile. The profile of a Gen Y consumer, irrespective of the age, can be best described as someone who is extremely articulate about their opinions and are always on the lookout for better options and flexible solutions. This evolution has pushed retailers to invest, more than ever before, on sentiment analyses derived from feedback data from the customers.
The biggest caveat here is that the data that gathers sentiment to understand the pulse are not served ready with analytics for the retailers. In fact, a 2016 e-commerce estimate suggests that companies lose over $10 billion worth of revenue because of their inability to accurately parse customer data (from social media posts, reviews in forums, ratings data etc.) and adequately push for changes from within. By investing in technologies like Natural Language Processing (NLP), text mining and other sentiment analysis techniques retailers can ensure that they process the outcomes better and retain their target audience much longer.
Another niche area where analytics becomes the foundation of customer engagement is crafting personalized experience based on historic data. People who are active on social media couldn’t have missed pop-up notifications of advertisements about the products they were browsing just a few minutes ago. Top brands have already started becoming more observant in understanding and predicting what the customer might want in the near future.
At the 2016 edition of Consumer Electronics Show (CES), British tech firm Smarter showcased their latest innovation called “Smarter Mats”. These mats can be placed in the fridge or work station and gauges how much is left of the products that are kept over it. If the mat’s weight sensor detects a shortage, a notification is triggered to the owner’s smartphone through a wireless or 3G connection. The mat will also offer recipes based on the real-time availability of the goods.
But arriving at data-oriented business decisions comes as a double edged sword with outcomes transforming to troublesome branding (remember, the infamous Target’s story?). In a social-media driven environment where people are equal parts willing and sceptical to share their personal data to the world around them, brands have to be careful about how they extract and utilize their customer data. Retailers must manage walking on the tight rope between gathering more ways to understand intricacies in customers’ patterns and losing their trust when they feel that data has been exploited and not used.