The retail industry is rapidly evolving, gone are the days when there were very few players who dominated the market. Today, the competition retailers are facing are not only from the brick and mortar stores but also from online retailers and marketplaces. To stay ahead of the game, retailers have no other choice but to embrace changes and make better business decisions.
But wait, it’s not all doom and gloom. Technology has opened multiple avenues for businesses to grow and one of the advantages that retailers this age have is the large amount of data they are generating on a daily basis. These big data in retail, if properly capitalized, can help businesses improve in many dimensions.
Essentially, retail data analytics allow businesses to glean important information from the huge amount of data they generate, process these big data in retail and turn them to actionable strategies.
Big Data and the Walmart Story
Big data is historically defined by the three V’s – volume, velocity, and variety.
- Volume refers to the insanely huge amount of data generated every second; from gigabytes to terabytes, now companies are talking about petabytes, exabytes, and petabytes.
- Variety is the different types of data generated – numbers, tweets, videos, CCTV recordings, emails, and audio files among others.
- Velocity refers to the speed of new data being generated, processed and stored.
In the retail industry, Walmart has led the way in coming up with a brilliant retail data solution to improve its business processes and enhance customer experience – it is in fact in the process of building the biggest private retail data analytics cloud in the world.
These big data in retail are channeled and processed in an analytics hub, which they fondly named the ‘Data Café’. The hub, located in Walmart’s headquarters in Arkansas, USA, has the capacity to model, manipulate and visualize over 200 streams of internal and external data – this involves 40 petabytes of transaction data!
Internal data includes store inventory, customer loyalty data, and price comparisons while external data ranges from meteorological data, economic data, social media data, and data sourced from research houses such as Nielsen.
Teams from any part of Walmart can go to the nerve center of the hub with their problems and a solution will immediately appear in front of them on a “smart board”. What used to take a few weeks to process, can now be solved within minutes by this powerful tool. Walmart not only saved a lot of time using this retail data solution, but they were also able to produce more sales thanks to the insights gained from their Data Café.
Retailers of different scales are embracing retail data analytics, although not on such a big scale as Walmart, they are starting to get their feet wet with this growing technology. In Malaysia, companies such as Innergia Labs have created retail data solutions that have helped many retailers solve their day-to-day issues and develop plans for the growth of their businesses.
By adopting retail data analytics, businesses can match supply with demand more efficiently, deliver promotions that fit customers’ real-time needs, adjust pricing to compete or increase margin, detect fraud and understand the patterns of different stores for those who have more than one branch.