In the first part of this blog, we looked at how Artificial Intelligence (AI) has changed the supplier side of the retail eco-system, especially on two fronts – Price and Product Offering. In this post, we shall analyze how it has affected the buyer’s journey at almost every step of the way.
As most of you will know, a buyer’s journey starts from the awareness stage, where he comes to learn of a product or a brand, and then goes on to the following stages: research, consideration, purchase and retention; the latter is where a company tries to hold on to its customers. After all, history shows that people who have bought from your company before are most likely to be repeat customers if they are happy with the overall journey.
AI retains the power to analyze vast tracts of data, and that includes human behavior. If you were to look at it from the customer’s view point, the ushering in of the digital era, and now AI, has leveled the field for the buyer vis-a-vis Price and Product Offering. All that a customer has to do to get the best price or the best product in a price range is to use his portable computing device and search the entire marketplace for what they want.
The introduction of AI and its applied fields such as Machine Learning, now affects almost every stage of a customer journey. What is the facilitator today is that consumers live in an omni-channel, multi-channel world, and AI provides a means to enable informed and intelligent responses across all these platforms.
It is also a known fact that good customer service means good business. And good customer service never ends at a sale; it continues way beyond that.
Take for example how retailer Neiman Marcus’ Innovation Lab or iLab used digital tech to help customers in the department stores. Some years ago it introduced the ‘Memory Mirror’ technology. This is a digital mirror that a customer stands in front, and keeps twirling. A hidden camera takes eight-second videos of you spinning. On playback, a buyer can see himself from all angles. You don’t have to ask anyone how you look in different poses, you can see it for yourself. This was an advancement on the average dressing room we’ve all seen so far. Today, Neiman has 38 fashion Memory Mirrors in 20 stores.
With newer technologies such as AI in the picture now, retailers such as Neiman can use them to create even “more meaningful” customer experiences. In fact, Neiman is believed to be already contemplating AI, and augmented reality to be build into the buying experience of a costumer.
The use of AI in a buyer’s journey for now may be in an early stage, with some brands testing the water by introducing chatbots. But experts believe the day is not far off when AI will affect every stage of the customer journey – from marketing messages, ads, product design and shipping.
Virtual shopping assistants or recommendation engines that help consumers find a product from catalogs is another area where AI is helping. Even real-time recommendation even as a shopper is in the store looking up what’s on display, turning the entire experience into a one-on-one level.
Here are the many ways in which AI is helping customers:
It is a fact known to every marketer – customers are drawn to experiences, which in turn, makes them loyal to a brand. In the offline world, thanks to the assembly line method of producing goods for the masses, not much personalization was possible. With the advent of digitization though, that changed. Data surrounding individual customers was used to create an engaging experience to attract them back to the e-store.
Now, with AI in the picture, and its ability to analyze vast chunks of data at very high speeds, personalization of goods has taken on a whole new meaning. AI techniques help recognize patterns, learn from them and churn out hyper-personalization recommendations for customers.
What’s more, AI can analyze customer sentiments across various social media channels, and also match customer profiles to their social experiences regarding a particular product. It can perceive what a shopper’s style is and adapt product recommendations in real time, even as the customer shops. Such AI-generated output is then being used by some retailers to offer products that will appeal to an individual customer’s taste.
AI, at every stage of a customer journey, will offer gains to a retailer as well as its customers.
The next disruption in long-term keyword search is visual search, and it’s almost around the corner. After all, much of shopping is a visual experience. No amount of words can ever accurately describe a product or service. Visual search is expected to take customer experience to the next level.
Here’s how: Brands will upload images of goods in their inventory, each with their own unique codes. When customers upload a picture of a product they like, in their online search, an AI-based software will evaluate it and also factor in aspects such as brand, color, and so on. This may be done by analyzing the pixels in the image. It will then surface suggestions on alternative brands or products, all in real time. Alternately, AI-based software will also be able to throw up suggestions of products based on a shopper’s history, likes and dislikes. Experts predict that once visual search is in full swing, cases of abandonment of shopping carts will reduce significantly. Using AI, brands can scan through petabytes of data to predict customer behavior, and throw up visual recommendations to individual consumers. Going ahead, companies will be able to combine AI and visual capabilities to develop analytics models to identify even micro trends and consumer behavior patterns, and then make smart recommendations.
Department store Macy’s tried to do this in late 2016. Using IBM’s Watson, it created a personal mobile AI shopping assistant called ‘Macy’s On Call’. Using Watson’s Natural Language API, the cognitive mobile tool helps potential shoppers with information related to some of Macy’s retail stores.
Not everybody can duplicate what Macy’s did for now, because of the high costs involved. Yet, AI-driven virtual assistants can prove to be highly effective recommendation systems. There’s little doubt that they retain the potential to transform the retail industry, and eventually help drive sales. Where time is money, consumers will find using a personal shopping assistant, so to speak, very effective.