Data analytics is disrupting how retailers market their stores, while also changing how business is conducted for the consumer brands that line their shelves. While retailers and brands have been analysing data for years, the reams of consumer information generated in the era of online shopping, coupled with the rise of technology solutions, is upending the way stores and their suppliers evaluate how to sell, what is and isn’t selling, and why.
Drones zooming through the skies to deliver us packages that we haven’t even ordered yet is admittedly a slightly clichéd vision of how technology, Big Data and analytics will impact the retail landscape, but I believe it to be an accurate one. The way we buy and sell is evolving rapidly. Both online and offline, retailers which are embracing a data driven strategy to understand their customers, match them to products and willingly part them from their cash are reaping dividends.
Although we are not quite yet at the stage where drone delivery and mindreading predictive dispatch are mainstream realities of the modern retail environment, things have moved on greatly from early Big Data retail experiments, such as Target’s infamous attempts to work out who was pregnant (and subsequently inform her unwitting Father via a voucher offer for baby care products).
Today, retailers are constantly finding innovative ways to draw insights from the ever-increasing volumes of structured and unstructured information available on their customers’ behaviour.
The Growing Importance of Big Data in Retail
According to Dan Berthiaume, Senior Editor of Chain Store Age, the future can only see retailers turning more attention to data analytics.
Berthiaume asserts, “Granular analysis of individual SKU performance metrics can allow retailers to adjust merchandise assortments and promotions on the fly, improving inventory throughput while avoiding the need for costly end of season markdowns.”
Not only are retailers using data to predict trends and prepare for demand, they will also eventually be able to use real-time analytics to provide more personalised, tailored experiences to their customers across channels––whether it’s instore or online.
These kinds of initiatives are not exclusive to national chains. With a myriad of low cost, accessible technology solutions on the market, small and medium independent retailers are also benefiting from the big data boom.
For example, Swarm (recently acquired by Groupon) is a service that allows independent retail stores to measure foot traffic, predict patterns, and staff their stores accordingly. They can also connect that information to a POS system, calculating a physical instore conversion rate (i.e the percentage of store visitors who actually make a purchase).
Systems like this are not just becoming de rigueur for the future-looking retailer with billions to invest, they’re becoming an essential part of smaller, more niche companies inventory planning, marketing, staffing, and customer service strategies.
What Retail’s Big Data Trend Means for Wholesale
As retailers begin to rely more on data analytics to run their stores, they will require more flexibility, knowledge, and expertise from their wholesale suppliers. The days of simple catalogue and price sheet selling are over. Wholesale brands and their sales reps must be able to work hand-in-hand with retailers to leverage data insights.
For instance, power tool manufacturer Stihl distributes their products only to independent retailers. In order to compete with other gas-powered outdoor tool brands sold at big box stores like Home Depot and Lowe’s, the company works directly with retailers to track sales and optimise marketing efforts.
One revelation that resulted from looking at the data? If retailers had focused on the 30 to 40 year old demographic in certain marketing campaigns, they could have captured a combined $200 million in additional sales. Brands –especially those in the mid-market– have an enormous opportunity to leverage data and work more closely with retailers to maximize sales on both sides of the chain.
How Analytics is Changing Retail
Big Data analytics is now being applied at every stage of the retail process – working out what the popular products will be by predicting trends, forecasting where the demand will be for those products, optimizing pricing for a competitive edge, identifying the customers likely to be interested in them and working out the best way to approach them, taking their money and finally working out what to sell them next. In our next article, we'll be looking at the specific uses for these technologies in the sector.
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