Brands are integrating AI into their marketing functions, and some are ready to test these tools in customer experience. Currently, analytics and market research are top AI use cases, with content, customer service and website development further down the list. Adopting AI for CX functions like building content and designing websites comes with an added risk because these experiences are customer-facing. But some are taking the plunge.
This week, marketers and CX experts gathered at CX Circle New York hosted by Contentsquare with roughly 600 of the CX platform’s customers. Much of the buzz in New York was about CX innovation, and these innovations included AI adoption.
“The key themes were really around AI, personalization, omnichannel and the sort of correlation between those three,” John O’Melia, Contentsquare’s chief customer officer told MarTech. “And I think one thing that really stuck out to me, depending on your business and brand, your level of importance on using those technologies can be very different.”
He added: “I think what everybody is wrestling with is the art of what’s possible, and it’s moving so quickly. What’s possible isn’t necessarily what’s right … I think a lot of [marketers] are really wrestling with the line in terms of creating a great customer experience with personalization and letting AI play a role in that. You want it to play a role, but you don’t want to overstep — and does that turn off your customers?”
Small steps toward big AI transformations in CX
AI is widely used by marketers for analytics, providing them with customer and market insights. Using AI to automate and drive experiences with this personalization is an important next step. However, the experience involves a customer and how they perceive this next level of personalization. Do they find these messages relevant and helpful? Does the level of knowledge come across as creepy?
“We can use AI at every touchpoint in the customer journey today,” said Tarun Dadoo, vice president of products and delivery at Discover. “We started with smaller use cases and we looked at creative optimization.”
Creative optimization helps serve the right messages or promotions to the right segment of customers, but it’s not yet a fully personalized message speaking to a specific customer. Discover uses AI applications on first-party data to create customer segments that help inform marketers when planning campaigns. Those insights can also drive new, personalized web experiences.
“How do we make the experience personalized based on what information customers provide to us?” Dadoo asked. “AI brings a lot of productivity to that data by building segments and a personal experience in real-time, there’s some success in that space. We’re not introducing customized offers, just creating experiences that are positive moments to that user.”
Financial services are a heavily regulated industry, so Discover keeps heavy guardrails up between first-party and third-party data, Dadoo said. Not only could a personalized offer risk creeping out a customer, but it could also fuel discrimination, which comes with regulatory penalties and the risk of alienating customers.
“Personalization is an opportunity, but it’s not the same as humanization,” said Tricia Wang, a social scientist and consultant. “Brands need to hold the two side-by-side. Be intentional about how you use AI…and don’t conflate personalization with humanizing a product with community, belonging and loyalty.”
Dig deeper: What is customer experience and why does it matter?
AI-driven experiences to better serve customers and employees
Luxury beauty and home retailer L’Occitane en Provence uses digital experiences to connect and maintain customer contact. But, the company also wants to leverage its in-store experience.
The company launched a mobile app a few years ago, allowing customers to shop and explore during the pandemic shutdowns. Whether customers are using the app in-store or remotely, they are educating themselves about products, and so are the agents who work for L’Occitane. The app also supports remote customer service and sales. AI drives search and education experiences on the app.
“We want to bring learnings from the in-store experience to the online experience by leveraging our client app,” said Carole Silverman, L’Occitane’s Chief Commercial Officer. “The AI makes it quicker to have access to soundbites and education. If there’s downtime in the store, then go to the AI tool and reinforce [the employee’s] knowledge, deepen the knowledge on one product or ingredient … Especially when customers are more seasoned, we need our people to be very educated.”
The retailer has a fixed cadence for messaging customers after they visit a store or make a purchase. In addition to that, L’Occitane plans to use AI “to identify high engagement and provide video advisors with strategy guidance on who to contact and why to contact that customer,” Silverman said.
Auto dealership Sonic Automotive has a different CX approach due to its specific industry needs. Its customers don’t want to spend more time in a car dealership, they want to test drive, sign papers and leave with the car.
Sonic Automotive’s digital experience is focused on supporting the car-buying experience remotely to cut down the in-store time. This frees up sales associates to close more deals, said Steve Wittman, chief digital retail officer, Sonic Automotive.
Dealerships also look to upsell services and warranties after a car purchase, and it’s difficult for chatbots and apps to close these purchases.
“Warrantee penetration [is] an ecommerce challenge,” said Wittman. “It’s easier to say ‘no’ to a bot, so we’re still figuring that out.”
Papa Johns tests promos and toppings…and AI?
With 5,500 stores worldwide (about half of them in the U.S.), Papa Johns serves a lot of pizzas to a lot of customers. The pies can be made in approximately 240,000 permutations when combining different options for toppings, crusts and sauces. This means there’s lots of data and variables to test, and Papa John’s has a robust testing program to make sure CX and sales improvements are validated.
“Testing fundamentally comes down to solving a customer problem, and that can impact digital experience, the menu team, operations and supply chain,” said Grant Gunderson, director, digital product and customer experience at Papa Johns.
For instance, if Papa Johns launched an “extra cheese” promotion and it took off, that could spark a supply shortage at stores, affecting customers, employees and suppliers, said Gunderson. Also, solving customer problems isn’t just about watching key measurements like conversion rates and tweaking the order app. External events like a major storm or power outage require human attention and insight to provide a solution.
Dig deeper: How Beef ‘O’ Brady’s streamlines customer experience
Gunderson pointed to two main segments of data the Papa Johns analytics team focuses on. One is customer first-party data, which includes order history. The second is customer behavior analytics. When testing and validating changes to user experience, the team looks to tie the behavioral data to the sales data. The team has to take a broader view and look at other events during the test. For instance, if a new type of crust is offered, are those sales cannibalizing the sales of other crust types or toppings?
Customer experience can also lead to better data. Papa Johns tested and made a simple change in its ordering that put the log-in on the first screen. Some customers were ordering without the log-in because of this friction point, not necessarily because they didn’t want to share information.
Gunderson’s team is thinking about AI, especially how it can improve the ordering experience. They are also focusing on personalization.
“We’re keeping an eye on AI and plan to be testing it for next year,” he said.
The post How brands are taking the AI plunge and testing customer experiences appeared first on MarTech.
# How Brands Are Leveraging AI to Enhance Customer Experiences
In today’s fast-paced digital world, customer experience (CX) has become a key differentiator for brands. As consumers demand more personalized, efficient, and seamless interactions, companies are increasingly turning to artificial intelligence (AI) to meet these expectations. From chatbots and recommendation engines to predictive analytics and sentiment analysis, AI is transforming the way brands engage with customers, offering new opportunities to enhance satisfaction, loyalty, and overall experience.
In this article, we explore how brands are leveraging AI to improve customer experiences and why this technology is becoming an essential tool for businesses across industries.
## 1. **Personalization at Scale**
One of the most significant ways AI is improving customer experience is through personalization. Consumers today expect brands to understand their preferences, behaviors, and needs. AI-powered algorithms can analyze vast amounts of data, including browsing history, purchase patterns, and social media interactions, to deliver highly personalized recommendations and offers.
### Example:
– **Amazon**: The e-commerce giant uses AI to power its recommendation engine, which suggests products based on a customer’s past purchases, browsing history, and items in their cart. This personalized approach not only enhances the shopping experience but also drives higher conversion rates and customer loyalty.
– **Spotify**: The music streaming platform uses AI to curate personalized playlists, such as “Discover Weekly” and “Daily Mix,” based on users’ listening habits. By delivering tailored content, Spotify keeps users engaged and encourages them to spend more time on the platform.
## 2. **AI-Powered Chatbots and Virtual Assistants**
AI-driven chatbots and virtual assistants have become a cornerstone of customer service for many brands. These tools can handle a wide range of tasks, from answering frequently asked questions to guiding customers through complex processes. By providing instant, 24/7 support, AI-powered chatbots help brands improve response times, reduce operational costs, and enhance customer satisfaction.
### Example:
– **H&M**: The fashion retailer uses AI-powered chatbots on its website and mobile app to assist customers with product searches, sizing recommendations, and order tracking. The chatbot can also provide personalized styling advice based on a customer’s preferences and past purchases.
– **Bank of America**: The bank’s virtual assistant, Erica, uses AI to help customers manage their accounts, track spending, and even provide financial advice. Erica can answer questions, send alerts, and offer personalized insights, making banking more convenient and accessible for customers.
## 3. **Predictive Analytics for Proactive Engagement**
AI’s ability to analyze historical data and predict future behavior is helping brands engage with customers in a more proactive and meaningful way. Predictive analytics can identify patterns in customer behavior, allowing brands to anticipate needs, prevent churn, and offer timely solutions.
### Example:
– **Netflix**: The streaming service uses predictive analytics to recommend shows and movies based on a user’s viewing history. Netflix’s AI algorithms analyze data such as viewing time, genre preferences, and user ratings to predict what content a customer is likely to enjoy, keeping them engaged and reducing the likelihood of churn.
– **Sephora**: The beauty retailer uses predictive analytics to anticipate when customers may run out of products and sends personalized replenishment reminders. This proactive approach not only enhances the customer experience but also drives repeat purchases.
## 4. **Sentiment Analysis for Real-Time Feedback**
Understanding customer sentiment is crucial for brands looking to improve their products and services. AI-powered sentiment analysis tools can analyze customer feedback from various sources, such as social media, reviews, and surveys, to gauge how customers feel about a brand in real-time. This allows companies to address issues quickly, improve customer satisfaction, and build stronger relationships.
### Example:
– **Coca-Cola**: The beverage giant uses AI-driven sentiment analysis to monitor social media conversations about its products. By analyzing customer sentiment in real-time, Coca-Cola can identify potential issues, respond to customer complaints, and adjust its marketing strategies accordingly.
– **Zappos**: The online shoe and clothing retailer uses AI to analyze customer feedback and reviews. By understanding customer sentiment, Zappos can make data-driven decisions to improve its product offerings and customer service.
## 5. **Voice and Visual Search for Enhanced Convenience**
AI is also transforming the way customers search for products and services. Voice and visual search technologies powered by AI are making it easier for customers to find what they’re looking for, even if they don’t know the exact name or description of the product.
### Example:
– **Google Lens**: This AI-powered visual search tool allows users to take a photo of an object and search for similar products online. Retailers can integrate this technology into their apps, making it easier for customers to find and purchase items they see in the real world.
– **Siri and Alexa**: Voice assistants like Apple’s Siri and Amazon’s Alexa are becoming increasingly popular for shopping and customer service. Brands are integrating these voice assistants into
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