How Leading Retailers are Leveraging AI to Engage Customers Better
Artificial Intelligence (AI) is fundamentally changing the e-commerce landscape, as chatbots fueled by AI are improving in their ability to communicate seamlessly with users. While some early bots suffered from poor customer experience (CX) reviews, today's leading retailers have developed intuitive algorithms that offer exceptional CX across the board.
The typical chatbot is designed to respond based on keywords. The system is built on a document retrieval model that takes a cue from a keyword mentioned and automatically pulls up whatever it deems relevant. Interacting with this kind of chatbot can be quite a task as it requires adapting to the limitations of the chatbot rather than the other way around. Siri is a good example of a document retrieval model chatbot that has been augmented over the years to reflect changes in AI software development.
The big change in chatbot functionality came with the incorporation of natural language processing and machine learning — the two pillars of AI. In the words of WorkFusion CMO Adam Devine, these two features give “virtual customer assistants (VCAs) the ability to determine not just what rules-based action to take based on a word but to understand the meaning of words in different combinations, ask questions to create context and intent, and actually do something for the customer.”
While people may still be on the fence about the role of AI in e-commerce, however, there are two important things to remember. The first is that there are always ways for it to improve. Any piece of software is in a continual process of modification and augmentation to match the changing demands of CX. Web developers and retailers are the first to say that they are in a continual process of research with AI testing (in the form of visual search cues, predictive analytics, and dynamic pricing features). The important point is that AI represents a paradigm shift in the structure and function of e-commerce. Thanks to AI, customers can now access specific information much more efficiently than before. Retailers and shoppers should be ecstatic about this progression.
The second point is that AI is an emerging technology. It is in its infancy, which means a full understanding of its impact is yet to be known. It took years for the first Apple computers to get up to speed with the demands of CX; but once it did, the entire landscape of digital user interfaces emerged. AI has the potential to make a huge impact of this magnitude in the e-commerce industry.
From recent experience in the e-commerce world, it appears there is no limit to the kind of experiences afforded by AI in the pursuit of engaging CX for users. Retailers have been making the most of chatbots for a couple of years now, and they have proven to be a great success. From chatbots to visual searches, retailers are finding ways to make life easier for the customer while also cutting down on their expenses. Looking at from an objective point of view, AI chatbots bring a large number of changes to the e-commerce experience.
- Instant Information. In the first place, a chatbot will not make you wait for any information you might want. They are very responsive and get right to the point with the most accurate information available. There is no chance for human error in mis-reporting numbers or the status of an item.
- Chatbot Never Sleeps. In the second place, chatbots are available at all times of the day or night. This means that if you have some questions about a piece of clothing sold on a Japanese clothing website, you do not need to wait hours to get an answer. The chatbot will always be available to you no matter where in the world you might be. From a retailer’s perspective, that’s an exceptional saving compared to paying for a customer service team around the clock.
- Chatbots Forge Relationships. The consistency of a chatbot means it does very well at forging meaningful relationships with customers. What is a key feature of a meaningful relationship? Reliability is something the AI chatbot has in spades!
- Chatbots Collect Great Data. Human customer service agents benefit greatly from the chatbots’ ability to collect huge amounts of data on every customer interaction. These actionable insights help the customer service team personalize the shopping experience for each customer. They also inform personalized marketing campaigns whether it is for lead generation or for keeping up with regular customers.
Some AI Driven features
So what are some of the features that retailers use to improve CX and drive engagement of their brand? There are three main features worth exploring in detail via case studies and analysis. They are visual search, dynamic pricing, and predictive analytics that could boost your sales. Some retailers have bots that make use of all three features, while others have chosen to focus on either one or two of these features, depending on what their product or service is. From these examples, you will learn how AI chatbots can be modified to fit the needs of the industry and the specific characteristics of a company’s consumer base.
Amazon’s Echo Look
Is it a camera? Is it a search algorithm? Is it a personal assistant? Amazon’s Echo Look is all these things and more. Defined by its automated voice-controlled assistant Alexa, the Echo Look is able to help Amazon users and retailers with all aspects of their experience on the site. It really has set the standard for AI technology in the ecommerce domain because of its ability to provide assistance in so many different capacities.
We should not be surprised by its prowess, however, given that it is an Amazon creation. Amazon is the trailblazing ecommerce giant that has such mammoth reach that it can get away with making something this bold. This is the one limitation of Echo Look — it only works within the (admittedly large) domain of Amazon.com. It does comprehensive searches within Amazon to help people shop or to help retailers curate their profiles on Amazon.
So what are some of the specific features of Echo Look?
Hands-Free, Floor-Length Photograph — Amazon knows that its retailers need to post great pictures of their new clothing products on a regular basis. The Echo Look is their solution to this demand, and it does an excellent job. The camera is connected to a mobile app where the user can store all the pictures of their clothing. Each time a new picture is taken, the camera automatically uploads it to the app and compares it to the rest of the user’s images to see if it is high quality enough. The Echo Look app is designed specifically for the purpose of comparing users’ images and outfits. It allows independent retailers the opportunity to reach potential customers and it allows customers to browse through the potential outfits they may want. Users can select an outfit they like, inquire about more details, and then get directed to the Amazon shopping app to browse similar outfits.
Works with Alexa — Alexa is the voice-controlled operator that works across all Amazon platforms. With Echo Look, she is present at all times to answer any questions the user may ask. It could be to check the weather, the time of day in Abu Dhabi, or to find a suitable album from YouTube to play while making dinner. Alexa is the connecting link to all Amazon chatbot functionality and more, helping shoppers navigate from the Echo Look app to the Amazon app and back in a seamless fashion.
When it comes to finding deals and relying on the analytic strength of a bot, there is arguably none better than Flipkart. While Amazon’s Echo Look is more of a style guide for users and retailers alike, Flipkart places its focus on comparative analytics of price across the ecommerce landscape and lets users decide what choice to make. The real value of Flipkart is finding the best bargains across the web and updating users on when a new sale emerges that they may be interested in. It is a model that clearly works for many people, as Flipkart has reported having over 75 million registered users worldwide.
So how does Flipkart leverage huge amounts of data into meaningful insights for all its 75 million users?
Flipkart has developed an AI bot by the name of Mira. Mira helps buyers get a personalized and optimized shopping experience on this huge site with thousands of retailers. Launched in February 2017, Mira has already done wonders for shoppers who may know what they are looking for but are unable to come to a decision given all the available options.
Mira was designed according to the President of Product, Ram Papatla, in response to the increasing number of mobile shoppers that Flipkart was receiving. Mira solves any confusion or navigational difficulty experienced in mobile shopping because it prompts the user to answer a few questions about what exactly they are looking for, and Mira finds it for them.
So Mira has proven to make the browsing experience easier for mobile users, increase the speed at which users find what they want, and collect relevant information about all user searches to help Flipkart personalize the shopping experience even more going forward. It is the best example of a predictive analytic bot in the market today.
Millions of Netflix users struggle with the question: “what should I watch tonight?” The days of randomly scrolling through all the options waiting for inspiration are over, thanks to the Netflix chatbot. Given the tongue-in-cheek name of “And Chill”, this intelligent algorithm will be able to tell you what you want to watch in seconds. The intuitive nature of the chatbot is due to the fact that it mines all user past experience, considers the question being asked, and scans the entire Netflix library for matches.
The fact that it is compatible with Facebook makes a big difference to consumers. It also highlights an important infrastructural point about chatbots that retailers should be aware of. Chatbots should be available on all digital platforms a company has. Netflix knew they had tons of users on Facebook so they installed it there. Whether or not it appears as a separate app is up to the developers at Netflix to decide. So far, they have done an exceptional job of using big data to provide how personalization can deliver a great customer experience with real value: users go to the bot for advice rather than to look for something in particular. This is a sign that the intuitive capabilities of a chatbot have become extremely effective.
The Future of AI in eCommerce
These three heavyweight examples give a good indication of where AI is going to go in the e-commerce industry. Here are some major trends to look out for in the near future as AI continues to disrupt the e-commerce industry in some major ways:
- No More Search Glitches. All three chatbots mentioned above are great examples of how searching will become easier and more accurate. Searching for items online today means juggling a set of keywords and putting them in the right order to get optimal search results. It is a time-consuming and frustrating procedure, which leaves potential customers disinterested. AI bots will help with this. As chat bots become more integrated with natural language processing, they will be able to interpret the implicit assumptions and meanings inherent in the human language. It should go a long way in dealing with this hole in the e-commerce chain.
- A Personal Shopping Assistant. Personal assistant bots are bound to emerge on the market in the next five years. These bots will be so familiar with their owners’ spending habits and desires that they may even be able to shop for their owners without direct oversight. The owner could say: “find me the best white blouse on the internet, in my size, and under $100”; and that’s all the info a personal assistant bot will need to make the purchase!
The Way Forward
The 22-trillion dollar eCommerce industry is undergoing a paradigm shift. The rise of AI chatbots has dealt with a number of infrastructural hurdles apparent in the current e-commerce marketplace and offered consumers a way to shop easily and effectively. The Amazon Echo Look bot, Mira at Flipkart, and the Netflix chatbot — all convey a personalized service that manages to dissect and interpret huge amounts of data and improve customer experience more effectively than ever before.