Retail Customer Experience

If you want to understand how quickly the customer experience is changing, all you need to do is take a spin through your Spotify or Netflix recommendations. As you scroll through these lists of songs, TV shows, and movies, chances are that you will find at least a few of them that genuinely pique your interest. A computer algorithm using your existing listening and watching habits created this list. Its recommendations are probably more accurate to your interests than those suggested by your own friends and family. This is AI (artificial intelligence) in action, and it’s already reshaping the customer experience for millions of people.

Chances are that you’ve seen this machine learning-driven system in other online settings, such as Amazon’s product recommendations. As customers, we’ve come to expect a certain level of “personalization” in the retail experience, particularly if those AI-generated recommendations are both accurate and helpful. These machine-learning tools are also becoming more readily available to smaller-scale retailers, with some being as simple as plugin to their existing business technology solutions.

To put it another way, we’re at the very early stages of an AI-fueled revolution in the retail customer experience. Over the next few years, machine learning will reshape how customers make their purchasing decisions. The retail game is changing, and AI technology is leading the way.

To understand AI’s application outside of the standard online retail experience, let’s take a look at a few examples where machine learning will have an immediate impact on retail customer experience.

Predictive Retail

One of the most powerful applications of AI in online retail is the ability to predict churn. When a customer is losing interest in buying from a retailer, it generally doesn’t happen all at once. There are warning signs to look for, such as:

By using an AI solution to monitor customer activity, companies can identify these high-churn-potential individuals. This provides the company with the opportunity to take proactive steps to revitalize those customer relationships. These incentives also aren’t limited to obvious options, such as individually targeted coupons and sales. The next generation of AI will have the ability to scour these customers’ shopping histories, potentially identifying less-obvious issues — slow shipping times, a lack of clothes in a particular size, or a poor customer service experience — that may be contributing to their high churn potential. These problems can then be specifically and individually addressed through automated processes.

Deep Personalization

When it comes to the online retail experience, modern customers have come to expect a certain level of personalization. Even with today’s relatively simple machine learning algorithms, AI-driven personalized shopping recommendations can be surprisingly accurate. As this technology continues to evolve, those recommendations will be able to make increasingly specific, individually targeted recommendations that precisely reflect the customer’s tastes, interests, and shopping budgets.

The next generation of these personalization solutions will also have real-world applications for brick-and-mortar retail. It’s not difficult to imagine a situation where a customer enters a physical store, and is guided by an app on their smartphone to the location of products they might be interested in. Personalized discounts and coupons can be automatically generated based on that customer’s shopping habits. They can even purchase these items instantly, without having to wait in a checkout line. This isn’t some crazy sci-fi idea. Amazon has been actively testing variations on this concept in their boutique stores for years.

AI-Powered Support

It can be easy to overlook the fact that most people are already interacting with an AI on a daily basis. As we’ve already discussed, major online retailers like Amazon use machine learning to generate their personalized recommendations. If you’ve ever asked Siri or Alexa a question, you’ve used AI. These AI virtual assistants are becoming a completely normal part of modern life. It’s so normal that many people don’t even recognize that they’re talking to an AI in other everyday situations.

Take customer support, for example. AI-powered chatbots are already extremely sophisticated. They allow customers to get helpful answers to most common questions. This allows the actual humans working in the customer support teams to focus on the more complex support issues that are beyond the scope of the AI’s abilities. As machine learning processes improve, however, AIs will be increasingly able to manage more complex customer interactions. This has huge potential for online retailers and other businesses. It allows them to offer truly comprehensive support to their customers while keeping their labor costs stable.

Conclusion

This overview just scratches the surface of the potential uses for AI in a retail context. These tools allow companies to upgrade their customer retention, personalize their marketing, and deliver exceptional customer service without a significant increase in overhead. In fact, AI-powered tools can often reduce costs by automating a wide variety of activities. Why pay a human to do these tedious tasks when an AI will do it 24/7 for a fraction of the cost?

Interested in learning how AI can upgrade your business? Want to improve your retail customer experience? Faye offers a variety of solutions — including our Flare suite for Zendesk — to help your business stay ahead of the technology curve. Contact us today for a free consultation.