How artificial intelligence will find its way into brick-and-mortar retail

retail store

It’s fair to say that artificial intelligence has helped online shopping take huge leaps and leave brick-and-mortar retail behind in terms of innovation and efficiency. There are no in-store equivalents for the personalized features that you find in e-commerce platforms.

The main hurdle to putting AI to use in retail is data, the new gold, and the reason companies such as Google and Facebook are offering you their services for free. Online shopping platforms provide a direct interface to the customer. This is useful to gather tons of information about every user, including the products they view, their search queries, items they add to or remove from their shopping carts, points where they abandon a purchase, and even the items they pause or hovered on.

All that information is fed into machine learning algorithms and analytics platforms that crunch the data and glean patterns that help e-retailers better understand the needs of customers and come up with personalized product suggestions, loyalty programs, notifications and other things that churn out more sales. Moreover, customer service chatbots powered by natural language processing and generation (NLG/NLP) will be at the disposal of users at all time, responding to their needs based on their historical data, recent activities, and the questions they pose.

Brick-and-mortar retailers have little means to collect a fraction of that information about customers and be able to meet their needs in a timely manner, which translates into confused users, lost opportunities, and less sales.

However, there are a handful of technologies that can help remedy the situation and empower brick-and-mortar retailers to collect valuable and actionable information, employ artificial intelligence in their business, and better serve the needs of their customers.

Mobile apps

The ubiquity of smartphones is a great opportunity of retailers to create omnichannel shopping experiences and be able to identify and gather data about individual customers. Many large retailers are now creating online platforms and mobile apps to complement their physical stores and give their users online access to their wares and services.

Some of these mobile apps have in-store functionality, such as finding specific items or services, choose between different types of items based on their preferences and needs, or even make purchases. Others provide out-of-store functionality such as fitness and health guidance, or tips about how to better use their products.

All of them help retailers collect more information about customers’ interactions with their stores, or data that is related to the specific products or services that they offer. In most cases, the data can be tied to a specific customer’s profile, which provides the opportunity to use AI algorithms to create a more personalized experience. In cases where data is not tied to a specific user, it still provides retailers the opportunity to glean patterns from large datasets, find customer pain points, where they need to up their game, where they’re performing well, etc.

Internet of things

The internet of things is a big deal for every industry that has more to do with the physical world and less with the virtual world, and brick-and-mortar retail is no exception. There are many use cases where IoT technology can help retailers gather valuable information about customers and turn them into actionable insights.

One of the most promising technologies is bluetooth beacons, devices that retailers can install in their stores to interact with the smartphones and other mobile devices of customers. Beacons require the target device to have a specialized app or technology installed in order to perform their functionality. They can be used to detect the location of customers, send them promotions and notifications, and provide payment options, among others.

While beacons didn’t quite live up to their promise, it wasn’t so much due to the failure of the technology as it was to the bad use of it. Retailers mostly used them to spam customers with non-personalized ads and notifications, ultimately disenchanting customers. If combined with AI-powered mobile apps such as the ones mentioned above, beacons can provide opportunities to create a much more personalized experience for customers.

Smart sensors are also crucial to collecting information across the store and helping store management react in time. Motion sensors can help measure the flow of customers across the store without the need to access mobile devices. The data can then be used to glean patterns from in-store traffic. For instance, it can be used to find areas that are being more frequented and are more suitable for promotions. Smart shelf technology can help inventory management keep track of in-store stock and issue refills before wares run out. RFIDs can help find displaced items and return them to their correct places. These are only some of the ways that IoT can help collect the data needed to fuel AI systems that can provide better customer experience. The uses for backstore operations are numerous as well.

Computer vision algorithms

Computer vision is the technology that analyzes photos and videos to identify different elements and the relations between them. This is the technology that can help computers understand the content and context of imagery like human beings.

Computer vision’s potential is immense. Retailers can use them to perform a number of things that were previously impossible.

For instance smart advertisement displays can use computer vision to gather information about customers who watch displayed ads, such as age, gender, etc. and whether they paid attention to the ad or not. The data can be combined with AI algorithms to create segments and correlate each displayed ad to the demographics that it caters to. When new customers stand in front of the display, the algorithm will help display ads that are more likely to draw the attention of the customer. This would actually analogous to the way online ads work in platforms such as Facebook and Google.

Computer vision algorithms behind in-store cameras can help identify customers that are confused, wandering, or need help, and notify store management to dispatch someone to help them, optimizing the use of human resources.

Computer vision is also crucial to augmented reality, the technology that overlays information and elements on real-world images. AR is the technology behind smart mirrors, which let you try on clothes, makeup, glasses, and much more without the need to physically try them on.

Mobile apps powered by computer vision and AR can help retailers see the world through the camera lens of their customers’ smartphones or smart glasses. This provides the opportunity to collect information such as which items customers show interest in, while at the same time providing value to customers such as displaying additional information in AR format, and based on customers’ historical data provide them with upsell suggestions.

Will brick-and-mortar catch up to e-retail?

What’s for sure is a lot of valuable information is going to waste in brick-and-mortar retail, information that does not exist in the online shopping world. Once the data is properly collected and put to use, AI will really start to show its potential, and we’ll be able to answer that question. It’s no wonder Amazon, the biggest online retailer, spent $13.6 billion to acquire a brick-and-mortar grocery chain.


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