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5 Best Practices for Using AI in Your CX Strategy

5 minute read
Phil Britt avatar
Want to enhance your brand's customer experience strategies? Learn how with these five AI in CX best practices.

Talkdesk’s Future of AI in the Contact Center report found that 84% of CX professionals expect their company’s total spending on AI and automation to increase in 2025 compared to 2021, with 89% of CX professionals — including customer service leaders, managers and operational staff — believing in the importance of using AI in contact centers. However, only 14% of businesses consider themselves transformational with AI.

Just having the technology isn’t enough to produce positive results. AI users also need to follow these five best CX industry practices.

Leverage Timely, Relevant Data

To be useful in CX, it’s important that AI can leverage the right data at the right time, said Karl Phenix, Avtex director of sales engineering. “It’s easy to conceptualize AI as conjuring answers out of nowhere, creating something that wouldn’t exist otherwise."

He added, "AI helps employees gain useful insights and context about customers and proactively answer questions to serve them better. Does this customer prefer to be contacted by phone or email? Are they on the East or West coast? What times do they prefer to be contacted? AI can harness data and make intelligent recommendations, learning and improving from each interaction.”

Customers want to be seen, understood and valued, Phenix said. Many companies haven’t unlocked the potential of AI due to underlying fears or reservations that it will remove the personal relationship with the customer. Enhancing data with AI helps deliver a seamless, personalized experience every time a customer engages with your brand — and that’s more important now than ever.

Protect Customer Privacy

With brands having a digital-first mindset, digital data privacy is paramount, according to Jonathan Moran, SAS head of martech solutions. “AI based systems that use techniques like reinforcement learning can constantly learn and evolve customer preferences."

"For example," he explained, "if a customer feels progressively less confident sharing certain levels of PII data (SSN/income/race, for example), AI can pick up on this and adapt/evolve consent forms, password policies and requests to account for this change. Automation allows for adaptation of how individuals customers are engaged with from a data privacy perspective.”

Companies commonly use AI systems for automated data compliance monitoring, making sure they're using, storing and moving customer data properly and ensuring that brands are engaging with customers correctly, Moran added. AI based enforcement of consumer regulations for privacy helps to protect a brand from encountering customer data privacy issues and build digital trust between your brand and end consumer.

“... It’s a fine line you are walking to use all the data you can to make the best decisions while erring on the side of caution not to go too deep to infringe on users’ privacy," said Jaime Meritt, Verint chief product officer. “Responsible and ethical AI must be used for good, without bias and in a privacy-first manner.”

Related Article: Is It Possible to Have Both Privacy and Personalization?

Incorporate Conversational AI

Brands need to be operationalizing conversational AI technology to analyze customer conversations in real time — including intent and sentiment — while automation can help take care of manual tasks (such as auto-filling forms) to free up agents’ time, said Sabrina Atienza Pegasystems director of product.

“These solutions should work together and serve as co-pilots for agents — enhancing their jobs, not replacing them — by making recommendations for next steps and automating work whenever possible so agents are equipped to handle any inquiry," Atienza added. "With AI and automation guiding them throughout their customer interactions, agents can operate more efficiently and be more present with each customer. This helps reduce agent frustration and drives the point home for customers that the brand truly cares about them.”

Learning Opportunities

Find the Optimal Customer Path

“AI provides the means to qualify and characterize customer preferences and behaviors into broader buckets or segments, which are then specialized so the segment becomes a segment of one,” Meritt said.

“AI finds the patterns in data that humans are incapable of finding, enabling the ability to ask and answer key questions related to CX — i.e., Is this fraud? Will this customer churn?”

AI providers also make the technology simpler, making it practical for companies of all sizes, not simply those on the “bleeding edge,” Meritt added.

Focus on Customer Journeys

Build a solid data foundation around customer journeys, recommended John Koo, co-founder and CEO of Airkit. “One of the most exciting opportunities in automating CX is using AI to anticipate the customer's needs and preferences to orchestrate a personalized customer experience that maximizes success metrics and customer satisfaction."

To truly unlock this opportunity, more customer experiences need to be digitized and tracked with telemetry, sentiment and outcomes data, Koo added.

While digital-first companies like Uber or Instacart have a wealth of data, most companies we talk to are still in the early stages of digitizing customer experiences and, therefore, lack adequate data. These companies should digitize more, faster and via a standard data architecture that you can use for data analytics and AI. 

Related Article: Getting the Most From Your Customer Journey Maps

Final Thoughts

AI in CX is an essential way marketers can ensure their brand stays customer-centric. By following the five best practices above for AI in CX, you can ensure you're taking the right steps towards developing a transformational AI strategy. 

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