How big data is helping brick-and-mortar stores fight back

Facebooktwittergoogle_plusredditpinterestlinkedinmailFacebooktwittergoogle_plusredditpinterestlinkedinmail

One of the advantages that online retailers have traditionally had over brick-and-mortar stores is their ability to gather large amount of actionable data — a valuable commodity in the digital era. The rise of online retail has hit high street sales and footfall hard, but shops are fighting back. While they may not have access to the same level of browsing and conversion data that their online counterparts have, physical stores are increasingly making use of big data and in-store analytics to find out exactly how shoppers are engaging with their shops. This information then enables retailers to streamline their store layout and operations in order to boost profits.

A recent report from Cisco suggests that in-store analytics could add a staggering $61 billion (£45 billion) of value to retailers worldwide throughout 2018. The report states that retailers can significantly improve their workforce efficiency using real-time information, operational analytics, workforce management tools and shopping analytics.

With this kind of added value at stake, it is essential that retail businesses understand what they can do to ensure that they are getting the most out of big data and analytics. Gathering and analysing as much useful data as possible allows retailers to gain a competitive advantage, giving them the tools to completely rethink the physical environment of their stores as well as offering more personalised, convenient and flexible experiences for their consumers. This enables them to differentiate themselves against the competition and live up to the increasingly demanding expectations of contemporary shoppers.

Big data is completely transforming the retail sector in a number of ways, fuelling a shift in the way that retailers engage with their customers and run their stores. The increasing availability of data enables retailers to streamline inventory, optimise pricing, and improve targeted marketing. Data gathered from in-store sensors can also help them to rethink the customer journey and layout of the store, while information gathered from self-checkouts can also be incredibly useful.

For example, NCR’s new Horizon service is a data-driven consultancy and analytics system that helps retailers to see the bigger picture. Horizon analyses the data from self-checkout lanes in order to provide retailers with actionable insights along with recommendations on how they can tweak their installations. Not only does this reduce downtime, but it also helps businesses to optimise their store operations while also improving the customer experience.

For a holistic view of the entire self-checkout system, Horizon focuses on five key performance indicators (KPIs) — productivity, availability, interventions, tendering and cash, plus system health. As an example, these metrics help retailers to determine how often staff need to intervene when people are using self-checkouts, whether that’s because of an unexpected item in the bagging area, or a mismatch between an item that has been scanned and its weight. Not only does this help retailers to optimise staffing levels, but it also enables them to determine which specific products are causing weight mismatches, and then address the problem for all stores and lanes.

Horizon’s digital dashboard displays these key metrics in an easily readable way, giving head offices a comprehensive view of all their sites in one place. This enables them to compare regions or individual stores so that they can identify potential problems. Retailers can also use the dashboard to determine best practices, which they can then replicate across all stores. What’s more, Horizon users benefit from a monthly insight report compiled by NCR’s team of data analysts. This includes KPI data along with additional observations and tailored recommendations as well as a performance prediction for the following month. The Horizon platform is part of a wider drive from NCR to make more data available to supermarkets, with more initiatives set to launch soon.

In future, retailers will need retail platforms that offer valuable partnerships, such as collaborating with proximity marketing providers to push notifications onto shoppers’ devices when they are near to a store. Extending data analysis from self-checkouts to include other POS devices could help to paint a broader picture of the business for retailers.

Big data is completely transforming the retail industry. And retailers that realise its full potential will be able to stay ahead of the pack by making smarter decisions that help them to boost their profits. The ever-increasing amount of data gathered by retailers also opens up the possibility of utilising new technologies such as Artificial Intelligence (AI) and machine learning to further enhance the insights gained. In order to compete against their online rivals, brick-and-mortar retailers simply cannot afford to ignore the world of big data.