Big data plus IoT makes for a store that knows your needs better than you do.

If you want to glimpse the retail store of the future, consider the following scenario.

A shopper enters a store to buy shampoo. Instead of searching through several aisles, she opens an app on her smartphone that guides her to the aisle containing hair care products. Once there, the phone app offers promotions based on her shopping history, such as a 20 percent discount on a brand she buys regularly. To purchase the product, there’s no need to wait in line for a cashier. The shopper simply takes the item from the shelf and leaves the store. Sensors detect when products are removed and track those movements in a virtual cart. On exiting the store, the shopper is billed automatically, her identity having already been verified by in-store facial recognition technology.

In the age of digital disruption, this vision of a retail store is fast becoming a reality, and the new paradigm requires a variety of skills and technologies. For example, a large retailer recently needed help upgrading its wireless capabilities, but the company’s stores needed more than a simple upgrade. They required an ultra-fast Wi-Fi network on which the retailer could build a state-of-the-art in-store shopping experience for the customer, with "mobile anywhere” communications and Internet of Things capability.

These capabilities are now vital to a retailer’s arsenal. Digital disruption of retail is continuing at a blistering pace, and traditional retailers that have spent massively on their legacy systems are now seeing the barriers to entry in retail fall away: An online retail store can be up and running in just a few hours and immediately competing with the likes of Nike or Amazon. The retailers that will thrive in this environment are the ones that bring frictionless experiences to their customers—that is, they use technology to create holistic, intuitive, and convenient shopping experiences across all platforms, both online and offline, an approach known as omni-channel retailing.

While online retail is the hot new thing, Gartner notes that 91 percent of retail goods are still purchased in physical stores. Big retailers with a long-established offline presence can drive higher levels of customer retention and satisfaction by digitizing their offline retailing experiences using a combination of sensors, data analytics, and computing power. Gartner says retailers should think about the “seven Cs” of customer interaction: connected, continuous, convenient, contiguous, consistent, collaborative, and customized. Doing so means understanding how consumers use technology in their everyday lives and deploying technology accordingly.

To achieve this, some forward-thinking retailers are turning to technology such as facial recognition, a non-contact biometric identification method where a retailer uses sophisticated cameras to scan your face for identification. Once you’re identified, the retailer can track your purchases and movements in a store, and use that data to present you with special offers that are likely to appeal to you. The technology can also be used to verify purchases, as in the example above.

It works by measuring the unique qualities of the human face, such as the position of a person's nose or the space between their eyes. The proliferation of higher-resolution cameras and low-cost computing power means these measurements can be collected and analyzed quickly and at scale, creating a mathematical formula for the unique dimensions of an individual's face.

In addition, in-store cameras can be used to create heat maps of customer movements inside stores in order to analyze traffic flows. So, for example, if a retailer is selling sweaters in one corner of the store and sales are low, it can analyze traffic flow to see if placing them in another location could increase sales.

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Similarly, a retailer can use location-services venue navigation to guide shoppers toward products that may be of interest to them. Geofencing and location-services messaging, using GPS and Bluetooth beacon technology, allow a retailer to create a virtual geographic boundary and trigger a message or promotion when a mobile device enters or leaves a particular area. By controlling the path a shopper takes in a store, and using highly targeted, context-aware advertising and marketing, there is the potential to increase basket size and therefore revenue.

Facial recognition can also be used to identify repeat visitors to a store, allowing alerts to be created if the same individual is seen multiple times in a given area over a defined period of time. Face-based analysis of store traffic can also help retailers understand the types of customers visiting different stores or identify the times of day when they tend to visit. This analysis can provide unique insights into the efficacy of retail campaigns that try to target a particular segment, such as age group, gender, or ethnicity.

Another benefit of smart data analysis is more effective inventory management. Research by global research and advisory firm IHL Group found that overstocks, due primarily to poor data collection and forecasting, cost businesses around the world approximately $1.1 trillion each year. Real-time data from customer points of sale, as well as sensors and tracking technology at the warehouse level, can help retailers better manage the risks and performance of inventory supply.

The explosion of Internet-connected consumer smartphones and tablets is enabling these improved in-store customer experiences. Such devices—and the retailer’s own IoT devices, sensors, and cameras—are putting out tons of data that must be collected, stored, and analyzed in the most cost-efficient manner possible, and all in real time.

With data flowing from an ever-increasing number of devices, retailers will need to process and analyze that information quickly where it is captured: at the network’s edge. This is best achieved by using Hybrid IT and Intelligent Edge together. A public cloud is not necessarily the best option here. An on-premises, hybrid solution can provide the control and security benefits needed for real-time data analytics. Deep machine learning mines data for customer trends, behavior, and preferences to upsell services. But it must be done instantly.

This new approach not only requires retailers to rethink their technology, but it also requires retail CIOs to orchestrate culture changes at their companies, preparing them for a digital transformation—not always an easy task. To achieve this, CIOs should consider reaching out to other C-level executives, or leaders within other business units, to build consensus for change. They should also think about hiring the right talent, and acquiring the right customers. Delivering outstanding experiences that earn customer loyalty and advocacy is important here. This is what is meant by customer-led digital business transformation.

It’s also important to remember that today's organizations are building the foundations for future retail opportunities. Millennials (those born between 1995 and 2010, accounting for a quarter of the world’s population) are entering the workforce with increasing spending power. The cohort is changing consumer behavior and placing new demands on retailers, and how companies respond to their growing economic influence will characterize the online consumer experience for years to come. Retailers need to establish a meaningful relationship with them now.

Millennial consumers move with ease between the parallel media worlds of mass communication, generated by advertisers, and user-created social media. They are less inclined to trust companies and brands, and are quick to switch preferences. As research firm Forrester noted three years ago, power is shifting away from companies and toward digitally savvy, technology-empowered consumers who decide winners and losers and are seeking out engaging digital experiences.

A brand depends on its ability to retain and add customers, so every interaction with this emerging consumer group must be meaningful. The shopping journey may start at a physical store, but it could end online, or vice versa, so retailers must provide the technology to sustain that experience, including IoT, virtual personal assistants, artificial intelligence, and data analytics. All these technologies will soon become integral parts of our day-to-day customer experiences.

Such technologies will also help retailers see sales and performance data from all channels (online and offline). Doing so leads to more accurate sales forecasts, but it also requires extensive data collection, sharing, and analysis.

The pace at which the retail sector is evolving is astonishing, and these days, a store is essentially wherever the customer wants it to be—on a smartphone in the street, on a laptop at home, or in physical stores at the mall. It’s impossible to predict what retailing will look like in the years ahead, but the customer continues to be the focus as the industry enters a new phase of mass personalization led by digital connections. Success in that world is about understanding who the customer is, what they would like to buy, and how they want to buy it. It’s about making each consumer’s shopping experience completely unique.

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