AI in Customer Service: 11 Ways to Use it + Examples

Chatbots and virtual assistants are great examples of conversational AI in practice. Conversational AI can be implemented in various ways to enhance customer engagement across all channels and touchpoints throughout the customer journey. It might sound odd, but conversational AI can, in some ways, make people feel more at ease than speaking to a human. Because they’re so adept at automating tasks, one chatbot can take on work normally done by several humans.

If you’re a mid-market or enterprise business and want deeper insights into your customer feedback, SentiSum is worth considering. Almost 80% of customer service leaders acknowledge AI’s pivotal role in shaping their strategies. Automation also plays a significant role in social media management, automating tasks like scheduling posts, monitoring engagement, and analyzing performance metrics. This allows businesses to efficiently manage their social media presence and drive engagement without the constant need for manual intervention. Hootsuite’s Content Calendar simplifies social media management by streamlining the planning and publishing process, saving valuable time, and enhancing overall marketing efficiency. U.S. Bank initially adopted AI for fraud prevention, but then recognized AI’s potential for strengthening the customer experience (CX).

How contact center AI overcomes common customer challenges.

So, this third element in making an IVR web-aware is to determine the most logical channel pairs for your company. What are the high- volume channels that people use and tend to escalate from one to the next? There are three key elements to ascertaining a complete picture of customer intent. Shaping an experience based on intent makes it more personalized, thus lowering customer effort. The next task in using data is to focus on the right journeys in addressing intents. Assessing those journeys (their volumes, value, and how best to treat them) will help companies understand how best to solve the right problem.

This paper provides several avenues for future research focusing on the design of anthropomorphic information agents and may help in improving the interaction of AI-based CAs through user compliance and feedback. For example, we demonstrate the importance of anthropomorphism and the perception of social presence to trigger social bias as well as the need to stay consistent to increase user compliance. We conducted an online experiment with 153 participants and show that both verbal anthropomorphic design cues and the foot-in-the-door technique increase user compliance with a chatbot’s request for service feedback.

Anticipate trends

AI or Artificial Intelligence has seen a wide range of applications throughout the years, including healthcare, robotics, eCommerce, and even finance. AI is used by Twitter for fraud detection, for removing propaganda, and hateful content. Twitter also uses AI to recommend tweets that users might enjoy, based on what type of tweets they engage with. It can be used to translate posts languages automatically.

Success no longer depends solely on product or pricing — a satisfying experience for your customers is a must. And if customer experience (CX) is the new competitive battle zone then artificial intelligence (AI) is your most powerful weapon. More and more companies are discovering how AI can improve customer experience and meet the demands of modern consumers. As ChatGPT continues to learn and improve from its interactions with customers, its accuracy and effectiveness in addressing inquiries also increase over time.

This proactive approach positions companies to proactively shape their sales and marketing strategies, reinforcing their position in the market. AI has revolutionized the way companies can process customer feedback across various channels in real-time. Today’s race to get first to market demands for even greater speed and agility in every industry. However, as businesses amass vast volumes of customer data, the challenge lies not only in collecting this information, but in distilling it into actionable insights that propel informed decision-making in real-time. Predictive analytics can help companies guess what their customers want today—and what they’ll expect tomorrow. Gradient Insight uses this technology to “forecast customer needs and tailor our service offerings accordingly,” said Iu Ayala, the consultancy’s founder and CEO.

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