An Overview of AI Influence on Customer Experience and Engagement

The ongoing development of artificial intelligence (AI) and related technologies has impacted virtually every aspect of business, including customer experience and customer support. There are several ways in which AI has influenced customer engagement in recent years.

First of all, AI, particularly when partnered with machine learning, has allowed for a more nuanced, insightful understanding of customer needs and behaviors. Machine learning is a subset of AI that focuses on the analysis of data and development of algorithms as a means of replicating the way that humans learn. By designing machine learning systems to evaluate social, historical, and behavioral customer data, brands can gain a much clearer picture of the ways in which customers engage with their products.

However, while standard data analytics software can provide useful overviews of existing customers, AI can actually anticipate customer needs and behaviors. By staying ahead of these trends, brands can promote more relevant content and better target sales efforts. This not only benefits the brand, but also streamlines and personalizes the customer experience.

AI allows for predictive behavior analysis in other areas, expanding a brand’s ability to successfully execute real-time decision-making processes. Real-time decision-making has always been an important part of business, with leaders needing to make snap decisions to take advantage of emerging trends. With AI, “real-time” becomes much more literal, with software providing insight into ongoing customer interactions with near-zero delay. Decision-AI, for example, is a precognitive system that uses AI and machine learning to respond to real-time customer events in less than 200 milliseconds.

Decision-AI is just one example of predictive analytics software, a combination of AI and machine learning powered by various statistics, modeling, and data mining reports. When it comes to the customer experience, predictive analytics can be used to produce actionable insights in live customer scenarios, a process known as predictive engagement.

Chatbots are one of the most notable forward-facing examples of how AI has transformed customer experience and engagement. In fact, a recent study conducted by MIT Technology Review found that customer service chatbots rank as the top AI application for brands today. Nearly three quarters of respondents said that AI chatbots would continue to be the main AI-driven technology utilized at their companies through 2022. AI sales and marketing applications ranked second, at 59 percent.

A separate study conducted by Capgemini found that 54 percent of customers interact with chatbots, digital assistants, and similar technologies on a daily basis. Nearly half of these customers said they believed these AI-driven interactions to be trustworthy, up from 30 percent in 2018.

Finally, AI is being used to greatly enhance personalization applications and capabilities on behalf of customers, a trend known as hyper-personalization. As mentioned, AI has allowed brands to engage in targeted, customized interactions with customers. Hyper-personalization furthers these trends through tactics such as conversational chatbots. Some business leaders may not see the value in such details, but consumers are more likely to maintain a positive brand outlook following a conversational chatbot interaction compared to spending an extended period of time holding on a customer service line.

These are only a few of the ways AI, along with related movements such as machine learning, have significantly altered the business landscape in regards to customer experience and engagement.

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