The adoption of self-retail solutions has not only allowed for up-to-date data on consumer habits but also for a faster response time for cross analysis of retail sales data.
Big Box Vendors generally use this data for predictive analysis, useful to allocate resources in critical moments and provide better customer service.
For example, thanks to these predictive analysis, Macy can predict what to stock in which stores, when it's a good idea to give a buyer a loan and which items to feature on the website's home page.
2. Mobile analytics
Retailers are increasingly taking advantage of the opportunities that in-store WiFi can give them in order to strengthen the network with the data on hand.
Sales reports are no longer stored on computers and in folders, but have become mobile and interactive through the use of tablets and smartphones, allowing decisions to be made on the fly.
3. The Internet of Things
It seems like almost everything nowadays, from products, to pedestrian traffic, to merchandising displays, is equipped with sensors for collecting and returning data for analysis.
Adapting offers to customers' needs and providing them with a better shopping experience through the use of sensors and big data analytics, results in a better understanding of the customer.
4. Omni-Channel and Data Integration
Obtaining real time analysis nowadays is a big challenge because data is located in many different places. To achieve this, retailers must integrate sales data with channels and customers.
5. The new retail marketing mix
The massive use of mobile devices has a great influence in marketing decisions. Smartphones and tablets used before and while shopping influence 28% of in-store sales ($970 billion EUR) in the US alone.
6. Real-time inventory
Omnichannel shopping has increased the number of customers, as they have more information regarding a product's availability in the store and when to pick it up at the nearest store. Inventory data is stored in different places within an omnichannel network and for retailers it is very important to be able to trace this data minute-by-minute.