Brands across industries are increasingly embedding artificial intelligence (AI) into their marketing and customer experience (CX) strategies. AI’s application in analytics and market research has become a standard for providing actionable insights.
Tools help brands understand consumer behavior and improve decision-making. However, the next frontier for AI lies in content creation, customer service, and website development, where customer-facing interactions introduce greater risks.
Customer interactions are key, and even minor missteps can erode trust or damage the brand’s reputation. Brands must carefully balance the use of AI in direct interactions, ensuring AI-driven experiences are accurate, efficient, and respectful of customer preferences.
Early adopters like Discover, Papa Johns, and L’Occitane are leading the way, but their approach remains cautious and measured, focusing on small, testable use cases rather than sweeping transformations.
What we learned from the CX circle
At the CX Circle New York, AI, personalization, and omnichannel approaches dominated discussions. New technologies are shaping how companies connect with consumers across multiple channels, creating a cohesive brand experience.
John O’Melia, Chief Customer Officer at Contentsquare, pointed out that while AI offers immense value, its significance differs from one company to another.
Some organizations are focusing heavily on omnichannel personalization, creating individualized experiences across online and offline touchpoints. However, companies need to tread carefully, as too much personalization can feel invasive.
Brands are still finding the right balance between leveraging AI’s capabilities and avoiding overstepping in customer interactions.
The risk of using AI in customer-facing functions, particularly for personalization, is that it can easily cross the line from helpful to intrusive. John O’Melia discussed this tension, noting that brands must strike a fine balance between crafting memorable, positive customer experiences and over-personalizing, which could alienate consumers.
While AI helps automate and tailor interactions, an overly “creepy” or invasive message could lead to a loss of trust, especially when customers feel watched or over-targeted. The key challenge for brands is to build a relationship that feels personal without crossing into discomfort.
Taking small steps for big wins
AI’s role in analytics is well-established, giving brands a way to mine data for deeper insights. Market research, consumer sentiment analysis, and segmentation have all benefited from AI’s precision in handling large datasets.
This is the first step in many companies’ AI journey, brands that have already embraced AI-driven analytics now look to extend its use to automating customer experiences and enhancing personalization.
AI’s ability to recognize patterns and predict customer behavior opens new possibilities for automating entire customer journeys and delivering personalized recommendations in real-time.
This means less guesswork and more targeted marketing efforts. While many brands are still testing the waters, those with mature analytics systems are exploring how to bring these insights into live, dynamic interactions with customers.
At Discover, AI began with creative optimization, where it helped to deliver more relevant promotions to customer segments based on first-party data.
Tarun Dadoo, Vice President of Products and Delivery, explained that Discover relies on AI to segment customers and improve web experiences without delving into hyper-personalization, which might lead to privacy concerns.
For financial services, caution is not for customer preferences but a regulatory necessity. Discover operates in a heavily regulated industry, where using data incorrectly could lead to both reputational damage and legal repercussions.
Discover maintains strict controls between first-party and third-party data, making sure its use of AI for personalization adheres to compliance standards. Discover’s AI strategy focuses on segmenting audiences and delivering tailored experiences in real-time, but without crossing into overly specific personalization that could make customers uncomfortable or risk discrimination.
Brands must think beyond AI
Tricia Wang, a social scientist, stresses the need for brands to differentiate between personalization and humanization. Personalization, which AI excels at, focuses on delivering relevant content or offers based on data.
While personalizations can be beneficial, it doesn’t inherently create a deeper emotional connection with the customer.
Humanization, on the other hand, is about creating a sense of community, loyalty, and belonging. Wang points out that AI-driven personalization alone doesn’t make customers feel connected to the brand.
The real challenge for companies lies in using AI to complement, not replace, human touchpoints, making sure that customers feel a genuine connection, rather than simply receiving tailored ads or product recommendations.
How AI is improving customer engagement
During the pandemic, L’Occitane en Provence turned to AI to bridge the gap between its in-store and digital experiences. The beauty brand launched a mobile app that helped customers continue shopping while stores were closed, providing an online shopping experience powered by AI-driven search and product education tools.
Customers use the app to learn more about L’Occitane’s products, and this same information is also available to in-store employees, helping them offer better customer service.
When there’s downtime in stores, employees can use the app’s AI tools to further their product knowledge, ensuring that they are well-equipped to assist more seasoned shoppers.
How L’Occitane engages high-value customers
Beyond customer education, Carole Silverman, Chief Commercial Officer at L’Occitane, revealed that the company is now looking to use AI for more targeted customer outreach. L’Occitane maintains a structured messaging schedule for customers after visits or purchases.
The next step is using AI to identify high-engagement customers and offering video consultations or other personalized follow-ups. Such a strategy helps L’Occitane to stay connected with its most loyal customers, nurturing relationships that drive long-term value.
Sonic automotive is reducing showroom time with AI
At Sonic Automotive, AI is helping to simplify the car-buying experience, which historically involves in-person interaction. When letting customers complete much of the purchase process digitally, Sonic is reducing the time consumers spend in dealerships, an essential factor in increasing customer satisfaction.
Steve Wittman, Chief Digital Retail Officer, states that while AI improves efficiency in certain aspects, challenges remain when it comes to upselling warranties and additional services.
Customers are less likely to agree to an upsell from a chatbot, which requires further innovation to optimize this key revenue stream.
How Papa Johns is testing AI to boost CX
With 5,500 stores worldwide and a staggering 240,000 pizza permutations, Papa Johns is using AI to make sure its CX strategy is data-informed. The company runs comprehensive testing programs to solve operational challenges related to the menu, supply chain, and digital experience.
Grant Gunderson, Director of Digital Product and Customer Experience, notes that testing is not just about tweaking the digital interface but also understanding external factors. For instance, a promotion like “extra cheese” could create a supply chain issue, potentially impacting both customers and employees.
A broad testing approach, supported by AI, makes sure that operational issues are addressed before they become problems at the store level.
AI is also helping Papa Johns understand customer behavior by analyzing first-party data, such as order history, and behavioral data, including how users interact with the app. A small change, such as moving the log-in screen to the front of the ordering process, has already helped reduce friction and improve the user experience.
Looking ahead, Papa Johns plans to start testing AI-driven personalization next year. The goal is to make the ordering process smoother and more personalized for each customer, which could lead to higher satisfaction and repeat purchases.
Tackling the future of CX
Brands adopting AI in customer experience are doing so with caution, focusing on small, testable steps rather than full-scale deployment. The future of AI in CX lies in balancing personalization with humanization, ensuring that customers feel connected to the brand without feeling over-targeted.
Testing and data analytics will continue to be invaluable as brands work to improve customer interactions, safeguard trust, and create sustainable, AI-powered experiences.
