Retail Analytics in Realtime

More operational links to real time analytics are emerging.

Reacting Faster in Retail with Real-Time Big Data
By Raluca Neagu - in Customerthink

Consider the following scenario: You are a supermarket store manager. Popcorn, pretzels, and the like seem to be suddenly disappearing from your shelfs, but you have no idea why. You know you need to leverage this popcorn crisis somehow. You can order more, and have it shipped quickly, but how much stock should you get for popcorn? Why is this happening now? Will it last? To understand the cause of such episodes, one needs to be able to quickly compare the current situation with the same day last year, last months, last weeks and consider events around the shop. Consider festivals, movies, political events and weather. Maybe a new Game of Thrones episode was released.

When top line is no longer the most important growth factor, the bottom line becomes crucial. A relatively untapped source of growth is the time dimension. Data loses part of its value when decisions are not made in the right time window. And these time windows can be very small. Reacting faster, better, offering faster services or well stocked stores all add up.

Optimizing checkout wait times
Kroger uses real-time predictive analytics to estimate when shoppers are likely to reach the checkout lanes. This helps them optimize the number of opened lanes to keep wait times low. Since the technology was implemented, average wait time dropped from 4 minutes to 26 seconds. .... "