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You Can’t Wait to Invest in AI for CX

Brad Anderson, President, Products, UX, and Engineering at Qualtrics, recently sat down with AiThority to discuss how AI is used - and what the potential is - to improve customer experiences. At Farlinium, since 2016, we have worked with businesses to implement XM Discover, Qualtric’s AI tool, into their CX and EX programs. So, the interview was particularly timely and interesting. 

AI is the topic du jour, and for a good reason - it is improving at paradigm-changing rates. As Brad notes, “Investing in AI is no longer optional.” AI is more than using ChatGPT instead of Google. It is about using machine learning to scale your operations - to stay ahead of the sheer volume of information and tasks. Qualtrics “analyzed 2 billion conversations and 1.6 billion interactions on the XM platform in 2022, and 10 billion experience ID profiles were updated with real-time customer and employee insights.” That is mind-boggling - and beyond manual human tasking. 

What about the personal touch of human interaction?

Of course, we want to capture the personal touch only humans can provide. AI empowers employees by providing the information they need so they can focus more on caring for customers and fellow employees and doing their core work. For example, Brad highlights Qualtric’s new Real-Time Agent Assist, which leverages AI and machine learning to “analyze customer needs and emotions, then deliver real-time coaching so contact center agents can take the best next steps for customers.” 

Is AI accurate enough?

Critics quickly raise accuracy concerns with large language models (LLMs), often citing an incorrect fact they got from ChatGPT. However, LLMs, like ChatGPT, when tailored to specific industry needs, have the potential to enhance customer experiences and assist front-line customer service employees. By automating tasks such as call summaries and follow-up actions, LLMs reduce wait times and cut operational costs. And Brad said Qualtrics observed that Automated Call Summaries are more precise than manual entries, which can vary significantly among agents. By providing instant and accurate call recaps, LLMs streamline the process and ensure consistency across agents.

How to address implementation challenges

Fully implementing AI and data analytics into your whole team is challenging as any significant transformation is. As Brad notes in the interview, the main challenge of digital transformation is the presence of silos between teams in an organization. This often results in a limited understanding of customer behavior and feedback, which is not shared across departments like product, marketing, UX, DevOps, and customer care. To address these challenges, companies need to implement a digital tool that allows observation and replay of important customer behavior while also contextualizing the experiences with operational data, customer sentiment, and personalized feedback. 

Implementing these changes is easier said than done, but having an outside expert who knows the tools and how the strategy to transform organizations can be critical. Farlinium has helped companies do this with XM Discover since 2016. Please reach out if you would like to talk more about how we can help you. 

For more insights, read our posts, How can AI Impact Customer Experience?,  and, Why Does CX Continue to Fail?

You can read Brad's full interview at AiThority