Analytics in the digital retail world

by Mark Thomson. The amount of data available today is greater than ever before and shows no sign of abating as more and more devices are connected to our digital environment either directly or via sensors. Everything from printers and consumer mobile devices to food service equipment and coolers are now capable of sending back data – but how can convenience store (C-store) operators harness that data properly?

It wasn’t long ago that merchants ran their businesses based on scanned data and gut feel from their years of experience. The challenge now is seasoned veterans are retiring or being lured away by a stronger job market. Meanwhile, the data keeps coming faster – requiring companies to reconsider the skill sets they look for in their managers and other employees. It’s not uncommon to see titles such as ‘Chief Innovation Officer’ or ‘Customer Analytics’, as C-store retailers look for new ways to generate insights from data they’ve collected.

While C-store operators need to understand their owned data (such as point of store and loyalty) and existing data such as weather or census information, it is becoming increasingly important to leverage technology to their advantage. Artificial intelligence (AI) and machine learning (ML) aren’t simply terms to drop at industry events. ML analyses data looking for exceptions and anomalies in just a fraction of the time that it used to take. By gleaning simple insights in near real time, like determining when a store location is struggling to meet KPI’s, C-store operators can get to the root cause before it becomes a systemic problem that drives shoppers elsewhere.

Identifying out-of-stocks using shelf edge technology is yet another way C-stores can leverage technology to their advantage. These new, innovative solutions provide a remote view to store shelves stocked with fast-moving consumer goods. They can transmit alerts via the cloud to direct store delivery (DSD) drivers’ rugged mobile devices enabling them to alter delivery patterns in real time to address and remedy out of stock inventory before it negatively impacts the shopper experience. The days of data being held close to the vest are slipping away as it becomes a commodity.

Retailers also need to consider their shoppers’ privacy when collecting data. While consumers have become more open to sharing data, businesses must ensure they’re using that data the right way or risk losing consumers’ trust. It’s a fine line between using data to help them and using it in a way that it feels invasive. While some consumers may feel uncomfortable with facial recognition being used to greet them as they enter a store, other instances of using data to improve their experience could be appreciated. C-stores could use loyalty data from their most frequent shoppers to analyse previous purchases to predict future behaviour. Having an order ready for them as they walk through the door could be seen as excellent customer service and keep them coming back in the future.

All of the necessary Internet of Things (IoT) sensors, integration technology and data are available today. Retailers need to ask themselves if they’re using their data to empower their performance and workflows or if they’re simply collecting it. If the answer is the latter, identifying the right way to harness this data will be crucial to staying competitive and providing shoppers with the experience they want.

Mark Thomson is Director of Retail and Hospitality Solutions EMEA, Zebra Technologies (formerly Motorola Solutions). Thomson’s exploration of the global retail landscape helps retailers gain a focus on what’s real and what works when building a retail strategy in a digital world. He works closely with retailers and hospitality businesses on developing a vision for their retail business that aims to improve customer experience and drive business efficiencies.

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