Sears Auto Center and AI: Leveraging IBM Watson® to Put a Human Touch on Tire Buying Using the Power of Conversation
At Laughlin Constable, we like to consider how users interact with brands across different devices, platforms and locations in order to help them learn, achieve their goals and interact with brands in a positive way. We refer to it as the interaction surface, and it’s our job as technologists, to figure out how to get the most out of it to best allow interactions to happen, keeping in mind the end user’s desires and goals.
I’d like to relate how we used Natural Language Processing (NLP) and IBM Watson® to help one of our clients reimagine the way its customers searched and bought products on their site.
Sears Auto Center approached LC with an interesting situation. They wanted to see if we could help reimagine the way customers found tires for their cars. One of our first observations was this: There was a lot of technical information that could be found, but fundamentally navigating the site relied on the user drilling down through the information to find something pertinent. It also didn’t try to discover a person’s specific needs. For instance, a soccer mom might have safety as her top priority as opposed to an off-roading single woman, who might want rugged off-road tires. In other words, the context of a person’s daily routine or desires was completely lost in the traditional product category-based search approach.
What was missing was the conversation between a floor associate and the customer. Given the fact that a lot of people research/browse before entering the store, would it be possible to have some of the in-store dialogue digitally?
Let's Get Digital
This is where NLP allowed us to help Sears’ customers. It allowed us to ask them a fundamental question, “When it comes to tires, what’s most important to you?” It changed the interaction from users trying to find information, to users telling us what they most wanted (in the context of tires), allowing us to bring forth more relevant results. It allowed us to present results that more closely related to their customers’ routines and needs, laying the foundation for deeper, more nuanced conversation.
So when a user responded with, “I love going on bumpy terrain” or responded with “off-roading capabilities are super important to me,” we could show them all-terrain tires (high performer). These are two very different responses, but both look to meet the same need.
This is the power of conversation. When people can tell your brand what they are looking for, and you can respond in real-time with relevant information, you transform that relationship, making interactions more meaningful and actionable.
In order to do this, we leveraged the NLP capabilities of the IBM Watson® platform using training data that we collected from internal surveys.
It’s a fundamental shift for Sears Auto. It shows the value they place on their customers and those relationships, which they want rooted in their customers’ needs and desires.
It’s a first step that will lead to more meaningful conversation, allowing Sears Auto customers to find the tires and services they need, as opposed to relying on them to drill down through massive amounts of information.
Converse With Your Customer
Most brand interactions today, at least in the digital realm, are centered around responsive websites and mobile apps. These follow a traditional content and functionality balance in order to provide meaningful user experiences that improve engagement and, hopefully, enough value to keep users coming back to a trusted partner.
With the advent of Alexa®, Chatbots and other NLP systems, the mechanics of user brand interaction has undergone a fundamental shift. Technology that once was blamed for removing the humanistic aspects of consumer brand interactions is now enabling them to reconnect – albeit with Artificial Intelligence (AI) playing the role of the brand’s agent. These systems, although not exhaustive, fall under the umbrella of a conversational User Interface (UI).
A conversational UI is basically an interface that allows users to interact with a system using natural language, whereby an agent (potentially using Artificial Intelligence), to some degree, plays the role of a human. It allows for the interaction to be rooted in one of the most fundamental means of communication – speech, which leads to tantalizing prospects of intelligent conversation users can have with the agent in order to meet their needs.
Let’s be clear, this article is not about AI replacing a human, but rather about facilitating interactions that are more closely aligned with the way people interact with their surroundings and entities (living, non-living, zombies). One of the fundamental means of interaction, from the time cavemen could grunt at each other, has been speech. Speech is transformative, allowing for the rapid transfer of ideas, needs, desires, likes and dislikes; essentially the whole plethora of emotions and thoughts that make us human.
Harnessing speech to enable users to achieve their goals should be an obvious goal.
Adding speech/NLP used to be the domain of highly specialized companies. It took very dedicated teams and lots of development to add such capabilities as a core part of the user experience. However, with the advent of various cloud-based NLP providers (IBM Watson®, Google and Amazon, among others), such technology has been democratized and now is available at affordable prices with graceful scaling (handle increased loads).
Side note: NLP is just one of the applications of Machine Learning/Artificial Intelligence. There are a host of other applications, such as image recognition, classification and search, which are being profoundly impacted by these systems. For solutions providers, this is insanely empowering, as it allows them to focus on the actual problem that’s trying to be solved. Now, if we want to build a smart refrigerator that can tell us about the lack of fruit in it, we can leverage image recognition and focus on the refrigerator problem as opposed to spending months trying to solve the immensely complex problem of figuring out how to recognize fruit in the picture.
These are still early days and natural language-based systems continue to evolve to provide richer, more contextual experiences for users that build brand trust and goodwill. NLP, bots and other conversational aspects of Machine Learning will continue to add to the ways in which users will be able to interact with your brand. LC is tremendously excited to partner with our clients to take them to the very leading edge of this technological revolution...taking them from now to next!
Need tires? Check out the Watson® integrated NLP interface from Sears Auto.
IBM Watson® is a registered trademark of International Business Machines Corporation (IBM Corp.). Alexa® is a registered trademark of Amazon Technologies, Inc.
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