The AI Developer’s Role in Creating Great Customer Experiences

AI is the key to putting data into action. See how you can amp up the value you provide your clients.

customer experience and AI

If you develop software for retailers, restaurants, and other merchants, you know customer experience is everything. PwC research reveals that consumers are willing to pay more for good customer service, ranging from an additional 7 percent for excellent service from a car insurance company to 16 percent for great experiences at a coffee shop. However, analyzing the terabytes of data that these businesses collect so that they can optimize service takes more time and resources than most merchants have.

Andrea Polonioli, AI Product Marketing Manager at Coveo, shares his insights on how artificial intelligence (AI) can help your clients deliver the types of service consumers want – and pay a premium – to experience.

Shopper experiences have emerged as one of the most important competitive differentiators. How can AI help improve experiences?

Polonioli: There’s one thing that sits at the center of every good customer experience: Relevance– finding exactly what you’re looking for quickly and easily. Shoppers today demand that level of personalization, having grown accustomed to the experiences delivered by the likes of Amazon. Digital leaders that have mastered relevance and personalization are running on massive amounts of data from regular, recurring users and using it to their business benefit with their own technology.

But the number of retailers and brands that have access to data like this, and have the resources to act on it, is actually fairly small. The user data that most businesses can collect is fragmented and incomplete, and most of the website visitors don’t log in as they do on sites like Amazon. In fact, they may not make purchases with the same brand all that often. And yet, retailers can still deliver relevant experiences by leveraging signals about in-session behavior. The missing link is a layer of intelligence that puts that data into action. This is where AI comes into play. AI gives retailers a deeper understanding of their customers, enabling them to deliver personalized experiences that keep customers coming back.

What are some of the insights an AI-powered solution can provide about customers?

Polonioli: AI can and should positively impact the customer experience at every single interaction during the buyer journey. Even for a first-time customer with limited data or a “cold start shopper,” AI can learn in just a few clicks, much like a sales assistant would look for visual cues from an in-store shopper. With session-based capabilities, you can have “personalization-as-you-go.” Retailers can deliver personalization –  search ranking, search suggestions, recommendations –  to help determine shopper intent, even if they are shopping anonymously. This helps retailers who don’t have user identification or huge volumes of data.

For repeat customers, AI can begin to develop behavioral patterns about how they prefer to shop, what they like vs. dislike, and what will surprise and delight them. AI can also bring to light problems and product gaps, enabling retailers to address issues and explore new opportunities faster.

Can AI also help retailers make better decisions about purchasing, merchandising, and forecasting?

Polonioli: Absolutely. AI can improve nearly any key metric a retailer has, from cart conversion rate to average order value to gross merchandising value. Ultimately, AI democratizes relevance. If implemented well, retailers of any size can deliver Amazon-level customer experiences without the massive amounts of resources or hordes of data scientists.

Is AI an online-only tool, or can brick-and-mortar stores also leverage it for better experiences?

Polonioli: AI helps brick-and-mortar retailers offer shoppers the personalized experiences and competitive prices to which they’ve grown accustomed. For example, AI can offer shoppers services that once required a personal stylist or shopper. By using AI, the retailer can make personalized recommendations and offers. Stores can provide in-store dynamic pricing and use AI to deliver personalized training to sales associates.

Are there opportunities for ISVs to innovate in this area?

Polonioli: AI implementation can minimize the need for manually ranking search results, which eats into time and resources, and can lead to better outcomes, saving time and improving ROI. But despite the optimism about AI, few enterprises have deployed it to improve their search services.

A recent study from my company, Coveo, shows that while 91 percent of enterprises have AI as part of their search stack, only 15 percent have implemented it or turned it on. Other priorities have forced 57 percent of businesses to hold off on implementing AI, while a lack of resources impacts 61 percent and worry about AI tuning impacts 39 percent. Rather than establishing a unified enterprise search strategy or embracing new technologies such as AI, organizations are often scrambling to find fixes and make their search results better.

Bernadette Wilson

Bernadette Wilson, a DevPro Journal contributor, has 19 years of experience as a journalist, writer, editor, and B2B marketer.

Zebra MC9400
Bernadette Wilson

Bernadette Wilson, a DevPro Journal contributor, has 19 years of experience as a journalist, writer, editor, and B2B marketer.