AI Applied

By Team ZineOne November 27, 2019
Selecting the Right Application of AI

Selecting the Right AI Application for Your Unique Demands

It’s no secret that Artificial Intelligence (AI) is transforming the way enterprises engage with their customers. Through its ability to deliver human-like interactions at scale, AI empowers enterprises to engage more personally and effectively at every interaction. This translates to more satisfactory experiences for customers, as well as higher total spending for the enterprise.

While AI introduces a myriad of benefits to the enterprise, not all AI platforms are alike; rather, many are optimized to fulfill specific applications. For the enterprise looking to incorporate AI into their customer engagement strategy, selecting a best-fit AI platform, in turn, requires understanding the different applications of AI in a personalization effort.

Application 1: Deploying Intelligent Chatbots

In today’s demanding consumer landscape, AI-enabled chatbots have emerged as a way to optimize the customer experience—resolving common queries in a timely and efficient manner—all while maximizing the enterprise’s resources by freeing up skilled human agents to handle more challenging requests. However, the rise of the chatbot has been met with mixed reviews. While 87 percent of customers are satisfied or very satisfied with their ability to solve problems on their own through the website, nearly 20 percent of internet users don’t think chatbots have enough data on them, and over 28 percent dislike chatbots for making bad suggestions.

Best-in-class AI leverages data collected throughout the customer journey, addressing current queries through a holistic understanding of the customer in order to both prevent frustration over repeating questions on numerous channels and rapidly address customer concerns. To accomplish this requires the AI look across all touchpoints of consumer engagement, understanding customer activity across channels to inform responses.

For example, say Jessica places an order for a kitchen mixer from her phone via a retailer’s mobile app on Monday. After she checks out, she receives a notice that the package will be delivered on Thursday. On Wednesday evening, Jessica logs onto the retailer’s ecommerce site via her laptop, and clicks into live chat. Aware of her previous order, the chatbot immediately pops up:

“Welcome back Jessica! Want to track your order?”

Pleased, Jessica clicks the link to view the latest shipping information.

By leveraging historical, cross-channel data to anticipate her in-the-moment desires, the AI-powered chatbot was able to bring greater value and satisfaction to the customer.

Application 2: Elevating Campaign Relevance

AI is also expanding the capacity of more traditional marketing methods by introducing more technologically innovative functionality beyond the capacity of standard digital marketing campaigns. For instance, facial and voice recognition technologies have made waves in the market, recently cited as areas in which McDonald’s is investing to elevate guest experiences, and are expected to reach $7 billion and $3.5 billion in market size respectively by 2024. 

However, facial and voice recognition are not the only ways in which AI can transform campaigns. By intelligently gathering data on the consumer, AI empowers enterprises to deploy campaigns personalized to a customer segment of one, utilizing past purchasing patterns, in-the-moment context, and real-time insight to drive customer interactions.

For example, Some weekday mornings, Jake stops by his local quick service restaurant to order a medium coffee. Occasionally, he adds a donut or a bagel to his meal. Monday morning, Jake receives a notification from the QSR’s app:

“Jake, are you hungry for more? Stop by for a coffee today, and get one on us tomorrow.”

Excited, he decides to stop by and redeem the offer. Aware that he decided to take advantage of the offer, his customer loyalty app sends him a reminder the next morning:

“Jake, head on over to collect your coffee!”

Happy about his free coffee, Jake decides to add a bagel to his order as well.

Application 3: Understanding When to Intervene

There is power in knowledge—particularly as it pertains to the marketer. And yet, with millions of customers, utilizing data efficiently on the individual level requires advanced functionality that goes far beyond standard approaches like market segmentation. Fortunately, AI is allowing the enterprise to become more data-driven, eliminating a lot of the guesswork that traditionally went into outreach efforts. This allows enterprises to best evaluate when to intervene in the customer journey, and when to let customers continue unassisted. Take the following two scenarios: 

Scenario 1

Jared logs onto an e-retailers website. After browsing the website, he places four jackets in his virtual cart. In the past, Jared has placed numerous items in his cart, and even when given a coupon, only purchased a single item using the reward. As such, the e-retailer allows Jared to continue shopping unassisted. Ultimately, Jared deletes all but one jacket from his cart, then proceeds to checkout.

Scenario 2

Michael scrolls an e-retailer’s website on his phone for a new sweater, placing a few items in his cart. Analyzing his past purchasing patterns, the e-retailer recognizes that Michael only makes purchases in-store, and so sends him an in-app notification:

“Michael, save big with 10% off your next in-store purchase.”

Happy with the offer, Michael decides to stop by the next day, where he purchases a sweater and a pair of jeans he finds while browsing.

By understanding customer’s purchasing patterns, an intelligent AI platform is able to recognize when customers are on the fence, only intervening when necessary to add value and encourage action. 

Augmenting Your Marketing Strategies with AI

While there are many applications of AI, it all starts with selecting the right platform to bring personalized value to your customers. Regardless of your application, ZineOne empowers you to unleash the full value of AI across every industry. By harnessing each customer’s historical, real-time, and contextual data, our AI-driven Intelligent Customer Engagement (ICE) platform can detect in-session purchases by the 5th click with up to 90% accuracy for more intelligent customer interactions. Contact ZineOne today to discover how our solution is the right tool to meet your enterprise’s unique demands.

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