Amazon Go has created the most advanced shopping technology. To spare people from time-consuming check-out lanes, shoppers simply download the Amazon Go app, then log in via their Amazon accounts. Once at the Seattle-based store, they need only scan their phone at the entrance, then shop like normal.

The brand’s proprietary Just Walk Out technology then uses computer vision, sensor fusion, and deep learning to detect who pulls what items from store shelves. Based on this data, once people exit the store with products in hand, the smart store tallies their total and charges their Amazon account via the app.

Merging in-store and online experiences allows Amazon Go to literally know who customers are, track their behaviors and, in turn, offer personalized convenience the world has not yet seen.

Not all brands can create proprietary technology for omnichannel personalization but there are plenty of technologies already on the market to help them form the bridge. Let’s explore 4 technologies helping brands to create personalized, truly omnichannel brand experiences.

Artificial Intelligence (AI) makes consumers happy to spend more both online and off.

Amazon knows how to convert customer data into revenue flow. A Bain and Co. study of 522 shoppers revealed that a customer’s fifth purchase is 40 percent larger than her first. For Amazon, this is perpetuated by greater 360-degree customer understanding via data accumulation. For example, a customer who started out purchasing one item a month converts to one who purchases several related items a month via AI-powered relevant recommendations.

Once a brand has gone through all the added expense of gathering data and extracting preference insights from it, then building the customer’s interest in additional products, it would be a shame to start all over getting to know her during an in-store experience, as if starting all over with customer acquisition. This means lost revenue: A Boston Consulting Group study found that acquiring a new customer via marketing is 500 percent more expensive than retaining an existing one.

This is why smart brands like Amazon know to leverage online data to inform in-store purchases and vice versa. Every shopping event — whether online or in-store — means more data brands can use to better understand their customers via a 360-degree view. Without in-store combined with online customer data, a truly 360-degree view hasn’t been realized.

For example, by keeping running tabs on purchases made by a customer in an Amazon Go store, Amazon allows for the potential to lean on AI to make relevant online recommendations based on those in-store purchases and behaviors. In the end, with relevant omnichannel recommendations, the customer spends more and is grateful the brand gave them the opportunity to do so.

Beacons partner with digital technologies to enhance the offline sports-fan experience.

93 percent of Major League Baseball (MLB) parks, 53 percent of National Basketball Association (NBA) arenas, and 47 percent of National Football League (NFL) stadiums are sporting beacon technology, driving personalized experiences for attendants and revenue boosts for both teams and their sponsors.

People who download the Golden State Warriors team app, for example, are identified as fans. The app then offers breaking team news, live stats, player bios, and game calendars. In person, when fans enter an event, they might receive 3D maps of seating and concession stands, live traffic updates, and the ability to upload game photos and videos to Facebook.

In turn, beacon technology allows the Oracle Arena to receive perks like the ability to offer push notifications for seat upgrades when fans enter less-desirable areas, track fans’ footpaths for greater customer-behavior understanding, offer proximity marketing of team merchandise, and even help team sponsors connect with fans.

Other teams install beacon technology to benefit their sponsors as well. For example, when McDonald’s sponsored the Milwaukee Buck’s app, they also reached fans via beacons installed near stores in town. In turn, McDonald’s could market to fans via push notifications sent to the team app.

In the end, beacon technology creates brand wins via increased revenue and fans enjoy a personalized omnichannel experience. Revenue from app marketing covered the Warrior’s indoor-marketing-infrastructure and beacon costs in half of the first season following installation. And, despite — or perhaps because of — all the personalized upselling and push notifications, the app enjoys a 4.7-star rating in the Google Play Store.

Augmented Reality helps consumers merge their physical and online homes.

Home Depot is bridging the online and offline brand experience with their augmented reality (AR) app. If a customer would like to replace a door in their home, they can peruse door options online and even see which are available at their local Home Depot. Once they’ve found a door they like, they can click the “see this in your home” tab, then hold the phone up to the physical door for an AR view of how the door would look installed.

From the app, the customer can then purchase the door and pick it up in-store. Or, once in-store, they can locate the item via mobile-based in-store navigation, then purchase it.

Via AR, Home Depot customers become interior designers, mixing and matching brand products for the perfect look. Then they can order online and pick them up in-store. In addition, product recommendations are based on trends popular within the customers’ region. The result is a seamless and personalized bridging of online and offline brand experiences.


Photo by Brian Metzler on Unsplash

The Internet of Things (IoT) boosts one brand’s revenue via personal performance tracking.

Under Armour has bridged their online and offline brand experience via IoT smart shoes. Their SpeedForm Gemini 2 Record Equipped tracks runners time, cadence, duration, distance and more via an IoT sensor device embedded in the shoe’s foam sole and their companion UA MapMyRun app. Performance data is sent to the app via Bluetooth technology, allowing the runner to go up to 5 runs between syncing their performance data with the app.

Sound like a runner’s dream? It’s a brand’s dream as well. Performance data like heart rate, run maps, and personalized audio coaching tells Under Armour if the runner is a casual, when-I-feel-like-it performer or is a more-committed marathon trainer. By tracking runners’ performance and shoe condition, Under Armour earns the perfect opportunity to offer replacement products, performance-enhancing accessories and more via timely, relevant and, therefore, welcomed MapMyRun push notifications.

The bridging of the online and offline brand experience pays off for both the consumer and the brand. On all channels, the experience is personalized, a privacy trade consumers are willing to make. Lack of personalization cost brands $756B in 2016 alone, according to Accenture.

Brands not preparing for 360-degree omnichannel personalization are losing out.

For 60 percent of today’s executives and marketers, personalization is limited to one channel and is integrated throughout just portions of their tech stack. Only 22 percent of brands globally admitted to having cross-functional teams to execute personalization across channels.

While brands may not be taking omnichannel personalization seriously, consumers are. Harvard Business Review found omnichannel retail customers spend 4 percent more in-store and 10 percent more online than those who only interact with one brand channel.

To compete on personalized customer experiences (CXs) of the future, brands must work for a truly 360-degree omnichannel view and ability to interact with their customers. This means developing cross-functional teams and the end-to-end technology infrastructure to not just create a 360-degree view of today’s online and offline customer behaviors, but to be prepared to integrate emerging technologies and channels into the mix for a continued and predictive 360-degree understanding of and outreach to customers.

This post originally published on Towards Data Science.