Retail success has always been about delivering on the “4 Rs”: getting the Right products to the Right place at the Right time and for the Right price. While that success formula remains valid, technology-enabled advancements promise to disrupt how — and how well — retailers will be able to deliver on each element.
“Omnichannel” is a theme that has dominated retailers’ mindshare the last several years as digital influence and mobile connectivity become bigger and bigger elements in the shopping journey. Now emerging are the Internet of Everything (IoE) and Big Data analytics. While pervasive IoE connectivity generates a deluge of data, new analytics tools are helping to turn this raw data into actionable insights. The mashup of omnichannel, Big Data, and IoE is positioned to drive new operational benchmarks through a focus on the retail industry’s new “4 Ps of Performance”: Precision, Personalization, Prediction, and Platforms.
At Cisco, we estimate that by 2020, 50 billion things will be connected to the Internet. For retailers, this means more than just RFID on products and cookies on websites. It also means sensors on trucks, shopping carts, and fixtures, in the aisle, and in the parking lot. All this data provides an opportunity to use advanced analytics — including machine learning — to better understand what is happening and why it happens. This will allow retailers to deploy assets more efficiently and effectively than ever before, creating improvements in important performance measures, including return on inventory, employee productivity, and customer satisfaction.
Personalization continues to be a hotly debated topic in the retail industry, especially as it intersects with privacy and security. Recent events in the retail industry and beyond have made consumers leery. A recent Cisco consumer study found that consumers trust retailers with personal information significantly less than they trust hospitals, financial institutions, and even the government. Yet, as consumer data increases in both volume and variety in an IoE world, the quality of the insights derived from that data will also increase dramatically. For customers who are willing to share their data, retailers will create increasingly personalized interactions. This will unlock a much richer view of the relationship, and further enhance retailers’ ability to attract and retain their most profitable customers. Even without specific personal data, anonymous sensing will be a rich source of data, enabling a next generation of both segmentation and consumer insights. One day soon, retailers may have enough data based on anonymous behaviors to offer loyalty benefits to customers without ever knowing their names or registering them in a loyalty program.
Perhaps the most advanced capability at the intersection of omnichannel, IoE, and Big Data is the ability to create new algorithms that can more accurately predict the next 15 minutes, the next hour, the next day, week, month, and season. Analytics across numerous data sources — and in some cases, in real time — will be the fuel for new predictive algorithms that will be used to drive efficiency and effectiveness in retail operations — from product conception all the way through POS. This level of foresight will contribute to improvements in time to market, revenue, return on inventory investment, supply-chain costs, and labor efficiency.
One of the key challenges in building the capabilities for precision, personalization, and prediction is the myriad of emerging hardware and software choices available for retailers. Sensors are getting smarter, with capabilities such as video behavioral analytics and precision Wi-Fi location detection. Similarly, analytics tools are adding advanced real-time and visualization capabilities, along with new database structures and query capabilities. A well-thought-out platform architecture that integrates sensors and analytics in a way that provides flexibility to adjust to the optimal set of capabilities is key to success. Simply focusing on advanced capabilities with one sensor (for example, video) can create costly IT redundancies, and limit the integration of multiple sensors — which is how Big Data maximizes its value.
Opportunities To Create Value
McKinsey & Company estimates a 60 percent margin improvement opportunity from Big Data analytics for retailers. Cisco estimates $1.58 trillion in IoE Value at Stake for retailers over the next 10 years. Consumers who shop in more than one channel are consistently more profitable for retailers than their single-channel counterparts. These are all leading indicators of the large opportunities that are in front of retailers as they build the IT platforms and new business tools at the intersection of omnichannel, Big Data analytics, and IoE.
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