Lakeland is using new technology to connect data from across the customer experience and so improve the service it offers shoppers.
The kitchenware retailer is integrating its online and offline marketing, merchandising, operations and returns data from across its business, making sure that data from the shopper’s first contact with Lakeland to fulfillment is brought together.
Lakeland sells through 68 UK stores, as well as nine in the Middle East, as well as online through a website and the mobile web, with catalogues produced specifically for iPad. It shows thousands of products to hundreds of thousands of visitors through tens of millions of page views, while real-time store stock data helps to power click and collect and next-day delivery. Now it has introduced Dynamic Action from OrderDynamics to detect signals from the large amounts of data created by these interactions and convert them into specific action lists, ranked by their potential impact on profit.
“Retail is becoming increasingly complex with interactions across advertising, merchandising, segmentation, personalisation and promotion,” said Tony Preedy, Lakeland marketing director. “It is getting harder and harder for the modern shopkeeper to work out cause and effect and to know which challenge to tackle first. Dynamic Action will allow Lakeland to garner the deep insight needed to optimise our operation, striking a balance between sales and cost to drive greater profitability.
“Being able to see and take action on all of your data holistically is no longer a nice-to-have, it’s necessary to enable customers to be served well and, I think, is critical to the success of omnichannel retail organisations.”
“Lakeland’s global success rests on its philosophy that if you look after the customer, the business will look after itself,” said John Squire, president of OrderDynamics. “We share this view and know that the key is understanding and taking action on data to keep up with expectations on inventory, delivery and returns. It’s impossible for retail teams to manually pore over reams of data, to figure out how to sell more products, and sell them profitably. We eliminate all that complexity and deliver intelligent actions into Lakeland’s hands.”
