May 28, 2024

AI-Driven Customer Engagement: Strategies from Amazon, Nike, and Hilton

Companies using AI for customer insights and personalization have seen a 20% increase in customer satisfaction. Let's discover how these AI strategies reshape customer engagement and lead to business growth.

6 min read

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Paul Estes

For 20 years, Paul struggled to balance his home life with fast-moving leadership roles at Dell, Amazon, and Microsoft, where he led a team of progressive HR, procurement, and legal trailblazers to launch Microsoft’s Gig Economy freelance program

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  • Customer engagement is vital, with 92% of executives deeming it critical to their success.

  • By 2025, 80% of businesses will compete based on customer experience, but only 22% have effective strategies. AI can bridge this gap by enhancing real-time personalization and predictions.

  • Amazon, Nike, and Hilton use AI technologies such as predictive analytics and chatbots to boost customer engagement, leading to higher satisfaction and retention rates.

Staff writer

From AI to FinOps, our team's collective brainpower fuels this blog.

"As AI drives down the cost of intelligence, it is increasingly possible for companies to deliver a deeply personalized experience for every customer." - Brad Lightcap, COO of OpenAI.

Customer engagement fuels a company's success and helps drive loyalty and repeat business. A survey in April 2022 found that 92% of executives view customer engagement as "extremely critical" or "very critical" to their success. That is why Ken Blanchard, an American author and business consultant, says,  "Just having satisfied customers isn’t good enough anymore. If you want a booming business, you must create raving fans.”

Despite the importance of customer engagement strategies, there are often pitfalls when making customers happy. Studies show that 50% of customers who did not encounter a problem when purchasing a product or receiving a service are fully engaged. However, when customers do encounter a problem, only 15% are fully engaged. It is concerning because unengaged customers can be directly correlated with losses in sales, frustrated consumers, and, ultimately, a decline in market shares. 

Effective customer engagement is built over time. It's more than just the initial sale; it involves ongoing interactions that build loyalty. Traditional engagement strategies are often static and impersonal. Mass marketing emails, generic loyalty programs, and one-size-fits-all customer service don't cut it anymore. There is a significant gap between strategies needed to engage customers and engaging customers. According to a Gartner report, 80% of businesses expect to compete mainly based on customer experience by 2025, yet only 22% have a customer experience strategy that they consider highly effective.

The answer to this is personalization. Customers crave personalized experiences, real-time interactions, and a genuine connection with the brands they interact with. According to McKinsey & Company, companies that excel at demonstrating customer intimacy generate faster revenue growth rates than their peers. And the closer organizations get to the consumer, the bigger the gains. A study by Forbes in 2022 found that 58% of customers are willing to pay more for a better customer service experience.

Artificial Intelligence (AI) technologies like data analytics, machine learning, and natural language processing can create tailored experiences. AI can analyze customer data to understand preferences, predict behavior, and deliver real-time, personalized interactions. With 56% of business owners focusing on customer-centric AI, this article explores how AI helps businesses build stronger customer connections, foster loyalty, and drive revenue growth.

AI's Role in Personalizing Business-Customer Interactions

The COVID-19 crisis significantly boosted e-commerce, with many consumers exploring new products and brands. Up to 75% of consumers tried new categories, and 40% switched brands. This shift highlighted the need for improved customer experiences across digital channels. Today, 71% of consumers expect personalized interactions, and 76% will switch brands if dissatisfied. Charles Golvin, the senior director analyst in the Gartner for Marketers practice, said, “Personal data has long been the fuel that fires marketing at every stage of the customer journey, and the drive to find new forms of fuel and devise new ways to leverage them seems to be boundless”. 

So, to succeed, businesses must collect and use this data to promote their values and create personalized customer journeys. Retailers increasingly focus on tailoring the entire customer experience to meet these expectations. Customers have long been told that the future of shopping is the connected retail experience. 

Recent advances in AI and real-time data analysis are finally making it a reality. AI technologies can change how businesses engage with customers by making interactions more personal, automating routine tasks, and providing deep insights into customer behavior. By analyzing customer data, AI helps create tailored experiences that enhance the customer journey and build loyalty. About 59% of marketers believe AI will transform the industry. Consumers have high expectations: 70% want chatbot responses within 5 minutes, 74% demand instant answers, and 67% prefer messaging apps to communicate with businesses. Advances in AI are pushing brands to improve customer experiences. 

John Riccio, chief executive for Asia-Pacific at Merkle, says, “The proliferation of AI, real-time data, and intelligent automation in recent years has resulted in cost barriers dropping significantly. Finally, the true connected retail experience is within reach.” He adds, “We now have an opportunity with advances in AI, such as ChatGPT and real-time data processing, to drive data-driven marketing, to truly unlock the value that we’ve been promised over the past 10 years”. 

Next, we'll review various case studies showing how businesses are using AI to improve customer engagement. By understanding these practical implementations and successes, we can see how to take AI trends and effectively use them as real tools in customer engagements.

How Amazon Uses Predictive Analytics and Generative AI to Boost Customer Engagement

Predictive analytics is studying historical and current data to make predictions. It uses advanced mathematical, statistical, and machine-learning techniques to analyze data to determine and extrapolate hidden trends. Many businesses and organizations use predictive analytics to guide future decisions. According to a survey by Forrester, 53% of marketing leaders use or plan to use AI for predictive analytics and customer insights.

A great example of this is Amazon’s predictive analytics solutions on AWS. They use it for many applications, including proactive customer engagement. Amazon uses this tool to obtain insights about customer behavior and predict future actions and decisions, such as the likelihood to subscribe and customer intent. According to McKinsey's report, such level or personalized services can increase customer satisfaction by up to 10% and boost sales by up to 15%. Personalized services create a sense of anticipation and keep customers returning for more. Amazon’s predictive analytics anticipate customer needs and suggest relevant products before users know what they want. 

Beyond predictive analytics, Amazon also uses other AI techniques to engage with customers actively. Maria Boschetti, an Amazon spokesperson, said during a CNBC interview, “We’re constantly inventing to help make customers’ lives better and easier, and are currently testing a new feature powered by generative AI to improve shopping on Amazon by helping customers get answers to commonly asked product questions.” 

Amazon is testing an AI tool that answers shoppers’ questions about products in the mobile app, summarizing information from reviews and listings. It aims to simplify the shopping experience by reducing the need to read numerous reviews. Such AI innovations can completely change the way customers interact with online retailers.

The image above illustrates how Amazon is using generative AI to engage with customers. (source)

AI and Innovation: Key Drivers of Nike’s Market Strategy

Nike is focused on increasing its sales by elevating its customer service. Nike’s CEO, John Donahoe, said his priorities are to refocus on sports, develop new products faster, boost sales with its wholesale partners, and advertise more aggressively. Nike has pumped money into advertising to spur demand, spending $1 billion on marketing in the quarter, up 10% from the prior period. He also expressed the need to create more meaningful connections with everyday runners and effectively scale those innovations across the marketplace.

Using AI and computer vision technology, customers can use the Nike Fit feature in the Nike App to snap a picture of their feet using their phone and get the perfect shoe size for every style of Nike shoe. According to Nike, the app uses computer vision, data science, machine learning, AI, and recommendation algorithms to measure your feet. This sizing data is stored on your Nike Plus profile, so you know the correct size wherever you shop. The stored data can be later used by Nike for predictive analysis.

The image above illustrates the Nike Fit scan feature on the Nike app. (Source)

Also, Nike uses AI to collect user data through its apps, such as Nike Sneakers, Nike Training Club, and the Nike app. This data can also later be used to gain valuable insights and assist Nike in deciding which designs to make and which products to stock in which stores. Such features are a massive advantage as they replace traditional sizing and designing methods, which can be stressful. While discussing this during an interview with Forbes, Michael Martin, Nike’s global head of digital products, said, “We want to free our in-store associates to have more meaningful conversations and interactions with customers. This would boost purchase confidence. It’ll reduce returns online and in stores.” 

Nike saw great results from its AI implementation. Thanks to AI-driven predictive analysis of five years' worth of customer data, they increased customer retention by 40%, leading to a 10% increase in direct-to-consumer sales in 2020.

How Hilton Uses AI to Improve Guest Experience and Reduce Costs

Hilton is an American multinational hospitality company founded in 1919. Currently, its portfolio includes 5,500 hotels across 110 countries. Hilton’s primary focus is on its customers. With so many locations worldwide, the organization has a wealth of data about customers, including reservation details, profiles, and details on how they use hotel amenities. Gaining these insights allows Hilton to know its customers better and, in turn, deliver more value to them. This results in more repeated visits and happier guests. 

But then came the pandemic, and it changed everything. According to Wendy Huang, senior vice president and commercial director of Hilton Greater China and Mongolia, “In the post-pandemic era, guests increasingly rely on online services and resources to choose travel destinations and products so that they can have better offline experiences. Consumers tend to trust authoritative information from enterprise-owned digital platforms,”. So, they have started innovating with AI technologies, such as Xiao Xi. 

Born on February 19, 2020, Xiao Xi, Hilton’s AI customer service chatbot, provides Hilton Honors members and all guests with a quick and convenient one-stop source for travel advisory services. Xiao Xi is available 24/7 via Hilton China mobile apps, including iOS, Android, and the WeChat Mini Program. Honors members and guests can ask Xiao Xi various travel-related questions such as hotel information, local weather, Hilton Honors check-in, and promotion details. Xiao Xi can provide additional travel advice and entertain guests throughout their journeys by offering smart suggestions and tips through intensive training.

And the results are astonishing. According to Hilton, Xiao Xi has replied to more than 50,000 customer inquiries, with a 94% customer satisfaction rating, surpassing the average performance for a general AI chatbot. Such chatbots have provided Hilton Hotels with several key advantages, including

  • Enhanced customer satisfaction: People using the bot are more likely to describe their experience as "excellent" all around. 
  • Cost savings: The bot has contributed to a $1 million yearly reduction in customer service expenses. 
  • Increasing the number of direct bookings: Visitors who interact with the bot are likelier to make a reservation directly on the Hilton website. 
  • Personalized Recommendations: The bot provides recommendations based on each visitor's preferences and past travel history, improving the guest experience.

Staying Competitive with AI in Customer Engagement

AI is changing how businesses interact with customers. For example, Amazon uses predictive analytics to anticipate customer needs and generative AI to answer product queries. Nike uses AI for perfect shoe sizing, and Hilton uses AI chatbots for travel advice. 

In the future, AI will get even better at understanding what each customer likes and needs, creating deeply personalized experiences. It will also recognize customer emotions, providing more caring and timely communication. Plus, AI will predict what customers need before they ask, offering solutions immediately and building trust.

These tools help create loyal customers and increase sales. To stay competitive, businesses must adopt AI to meet customer expectations and enhance their overall experience. Embracing AI is critical to future success.

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