Big and Small: A Refresher on Big Data in Retail

Technology is the consumers’ conduit – we start with a mobile app for product research, jump to  a price-comparison website, and then ask Alexa to reorder some toiletries – it’s necessarily also retailers’ window into our behaviour, if they take advantage.

Big data is another tech touchstone that passes some of us by because it’s a little hard to hold on to. Let us remind ourselves how it is applied to retail.

Identifying customers

Crunching the numbers are recommendation engines that collect purchase history and loyalty-scheme activity. Combine that with smart demographics and it’s hard to find a better automated way to know which customers are likely to want which products.

Forecasting demand

Computers take their cue from clever algorithms to sift through social media posts and web browsing habits to pinpoint which items will create marketable buzz. Retailers who get this right can accurately predict what the top-selling products in a category are likely to be.

By incorporating demographic data here too and accounting for economic indicators, tech-savvy retailers can generalise about spending habits across a targeted market. Take the demand for books, for example, which increases energetically as the weather turns colder. Responsive booksellers increase the volume of book recommendations that customers are exposed to online as the mercury drops in their local areas.

Small retailers can capitalise

Certainindustry watchers make the case that big data will kill all but the biggest retailers. Gary Hawkins, in the Harvard Business Review, asserts that ‘large retailers, with their larger IT budgets and resources, can capitalize on the big data opportunity and increase market dominance’.

Though smaller businesses are indeed without the resources to implement expensive hardware solutions or hire expensive data scientists, that’s not the end of the story. A growing number of innovators are taking data-driven approaches to sales and marketing, akin to what the big retailers use, and can sell their services without breaking the bank. In fact, some such services come in the form of open-source software from the likes of Hadoop and Spark.

It is hard to think of smaller retailers as properly squeezed out then, especially as most of the potential in big data has yet to be realised. A recent KPMG survey described an undeniable 96 per cent of respondents as feeling that they were not making the most of the opportunities that their data presented. Big retail will always outspend its smaller rivals, but there is no fundamental reason that the nimble and innovative won’t find smart ways to make big data mean something.