Feature
The Gist
- AI is transforming CX. AI provides deep insights into customer behavior, enabling businesses to deliver highly personalized interactions that significantly enhance customer satisfaction.
- Major brands leverage AI to automate routine tasks and streamline operations. This allows for faster service delivery and more efficient customer support.
- Predictive AI machine. AI-driven sentiment analysis and predictive analytics help companies anticipate customer needs and tailor strategies. Building deeper connections and improved customer loyalty.
The integration of artificial intelligence (AI) into customer experience (CX) strategies is transforming how businesses interact with consumers. From leveraging predictive analytics to offering highly personalized service options, AI's role is far from just enhancing customer satisfaction — it's completely reshaping it.
This article examines some of the largest brand’s major investments in AI that are breaking new ground in customer engagement and service innovation, revealing the significant effects these technologies have across diverse industries, and illustrating how companies use AI to build deeper connections with their customers.
The Role of AI in Modern CX
AI is heavily impacting CX by providing deep insights into customer behaviors and preferences, enabling businesses to deliver personalized interactions. AI algorithms analyze data from various sources, predicting future behaviors and tailoring marketing efforts. AI-driven personalization enhances customer experiences, while automation of routine tasks improves service delivery and ensures consistent, accurate information.
AI contributes to improved service delivery by automating routine tasks and enabling faster response times. AI-powered chatbots and virtual assistants can handle a wide range of customer queries efficiently, freeing up human agents to focus on more complex issues. This not only speeds up service delivery but also ensures that customers receive consistent and accurate information. Additionally, AI can monitor and analyze customer interactions in real-time, providing insights that help businesses continuously refine their service strategies.
Steve McCurry, VP of product at LearnUpon, a learning management system (LMS) provider, told CMSWire that the most meaningful impact and change with AI has been the ability to streamline task completion, which ultimately can increase time-to-value.
"AI effectively writes code, crafts emails, drafts content, and more, which allows us to do more in less time," McCurry said. "With data and analysis from AI more accessible than ever, business leaders can make informed decisions and use predictive analysis when making complex decisions."
Understanding customer behavior is crucial for any business looking to enhance its CX. AI algorithms can sift through mountains of data from various sources, including purchase histories, browsing patterns, social media interactions and more. By identifying patterns and trends, AI helps businesses predict future behaviors, enabling more proactive and targeted engagement. For instance, machine learning (ML) models can segment customers based on their behavior and preferences, allowing businesses to more effectively tailor their marketing efforts to specific audience segments.
“In customer experience, the unknowns about our customers pose the greatest challenge,” said McCurry. “AI makes scraping and analyzing available data much easier, providing deeper insights for customer success managers about customer interests or preferences and allowing customer-focused teams to adapt, complete, and target their communications more effectively to the areas customers value most.”
Related Article: AI in CX: The Shortcut to Customer Satisfaction
Tailored Interactions and Predictive Insights Drive Deeper Connections
AI's role in personalizing customer interactions cannot be overstated. Through advanced data analytics, AI can create detailed customer profiles that inform every interaction. This means that whether a customer interacts with a chatbot, receives an email or speaks with a customer service representative, the experience can be tailored to their specific needs and preferences. Personalized recommendations, for example, have become a staple in ecommerce, where AI suggests products based on a customer's past behavior and preferences, significantly enhancing the shopping experience.
“Critically, for the customer experience, this mix of streamlining tasks and data insights can not only increase the time and speed at which customer onboarding and product training can be deployed, but it can also make it highly personalized, too,” said McCurry. “Based on their interests and needs, there's the possibility to create target educational experiences that enable your customers to truly see the value of your solution faster and, in turn, deepen the relationship between your customer and your business."
Damien Smith, senior communications manager at PolyAI, a conversational AI platform provider, told CMSWire that the most impactful AI investments enable seamless, personalized customer experiences.
"For example, virtual agents powered by natural language AI can handle routine inquiries, freeing agents to provide higher-value support," said Smith. "Predictive analytics also unlock value, allowing companies to anticipate needs, recommend products, and guide customers to tailored solutions. Beyond service, AI-powered sentiment analysis and intent detection provide deep customer insights to inform product, marketing and sales strategies." Smith reiterated that the key is a holistic, customer-centric approach to deploying AI across the organization and journey.
Smith said that AI is transforming the customer experience by enabling more personalized, proactive and empathetic interactions.
“In contact centers, AI-powered virtual agents can handle routine inquiries efficiently, freeing human agents to focus on complex issues requiring stronger emotional intelligence,” explained Smith. “By analyzing customer data and conversations, AI can also surface valuable insights to inform product development, marketing strategies and sales approaches.”
Sentiment analysis is another critical component of AI in modern CX. By using natural language processing (NLP) to gauge customer sentiments from feedback, reviews and social media, businesses can gain a deeper understanding of customer emotions and perceptions. This enables companies to promptly address negative sentiments, enhance positive experiences and tailor their strategies to meet customer needs more effectively.
“Sentiment analysis can identify pain points and frustrations, allowing companies to pre-emptively address them,” said Smith. “AI-driven predictive analytics, meanwhile, can help anticipate customer needs and guide them towards tailored solutions. Ultimately, these AI capabilities help companies build deeper, more meaningful relationships with customers, improving satisfaction, loyalty, and revenue.”
Related Article: Customer Contact Week: CX Leaders Dish on AI Breakthroughs and Blunders
Industry Leading Brands and Their Use of AI for CX
AI is no longer a futuristic concept but rather is a critical driver of CX innovation across industries. Major companies are leading the charge with significant AI investments, implementing strategies that have yielded impressive outcomes and setting ambitious plans for the future.
Google: AI Innovation with Duplex and Gemini
Google, for instance, has made substantial investments in AI, notably through the development of Google Duplex and Gemini. Google Duplex, one of its first AI investments, was introduced in 2018 and is an AI-powered virtual assistant that uses natural conversations to carry out “real world” tasks over the phone. It significantly improves customer satisfaction by reducing the time and effort required for these tasks.
More recently, in 2023, Google introduced Gemini, an advanced AI large language model designed to enhance natural language understanding (NLU) and content generation. Gemini's capabilities extend beyond traditional AI applications, allowing it to perform complex tasks and interact more naturally with users, further solidifying Google's position as a leader in AI innovation.
Starbucks: Deep Brew AI Enhances Personalization and Operations
Starbucks leverages AI through its Deep Brew initiative, which began in 2019. Deep Brew uses ML to analyze data from millions of transactions, enabling Starbucks to offer personalized recommendations and deals via its mobile app. This initiative enhances customer satisfaction and loyalty by delivering personalized experiences. Deep Brew's AI capabilities also extend to inventory management and supply chain optimization, ensuring that popular items are always in stock and reducing waste. This comprehensive use of AI not only personalizes customer interactions but also drives operational excellence, positioning Starbucks as a leader in AI-driven retail innovation.
Amazon: AI-Driven Innovation in Customer Experience
Since the early 2000s, Amazon has been at the forefront of AI innovation, leveraging it to enhance every aspect of the customer experience. From personalized product recommendations powered by ML algorithms to AI-driven warehouse automation with robots and drones, Amazon's AI strategy is comprehensive and multifaceted. The company’s Alexa voice assistant has also set a new standard for smart home technology, further embedding AI into everyday life.
Salesforce: Einstein AI Boosts CRM Efficiency
In September 2023, Salesforce integrated AI into its CRM platform through Einstein, an AI-powered assistant that helps businesses analyze data, predict outcomes and automate tasks. Einstein AI provides insights and recommendations that enable sales teams to engage with customers more effectively and close deals faster.
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Adobe: Generative AI Powers B2B Customer Journeys
Adobe recently launched the Adobe Journey Optimizer (AJO) B2B Edition, a tool designed to enhance B2B customer engagement using generative AI. Built on the Adobe Experience Platform, AJO B2B Edition helps businesses identify and personalize experiences for buying groups, consisting of individuals involved in major purchasing decisions.
Microsoft Bing: AI-Enhanced Search for Better Results
In February 2023, Microsoft announced AI-enhanced Bing, an advanced AI-powered search engine integrated into the Bing platform. The enhanced Bing leverages large language models similar to those in OpenAI’s ChatGPT, enhancing search capabilities by providing more accurate and context-aware results.
Alongside Bing AI, in September 2023, Microsoft introduced Copilot, an AI companion integrated into products such as Microsoft 365 and Windows 11. Copilot assists with tasks such as drafting documents, managing emails, and generating creative content, all while using the robust AI capabilities provided by Bing.
In March 2024, in collaboration with NVIDIA, Microsoft announced that it is combining the power of Azure AI and NVIDIA's advanced computing technologies to accelerate innovations in healthcare, life sciences, and industrial digitalization. This partnership brings cloud computing and AI together to improve data interoperability and visualization.
AI-Driven Analytics Tools
AI-driven analytics tools are among the top ways AI is enhancing and improving CX. These tools are essential for extracting actionable insights from vast amounts of customer data, enabling businesses to make informed decisions that enhance customer satisfaction and loyalty. By leveraging ML, NLP, and predictive analytics, these tools help businesses understand customer behaviors, preferences, and trends:
- Google Analytics 4: The latest version of Google's popular web analytics platform, using ML to provide predictive insights, deeper audience segmentation, and more granular data control. For instance, GA4 can automatically alert businesses to significant trends, such as rising demand for specific products.
- Salesforce Einstein Analytics: We discussed earlier, integrates with Salesforce CRM to offer AI-powered insights and analytics, including predictive analytics, data visualization and automated discovery of patterns within customer data.
- Adobe Analytics, powered by Adobe Sensei. Offers advanced AI capabilities for real-time data analysis, customer journey mapping, and predictive analytics. It helps businesses understand customer behavior across multiple channels and devices.
- IBM watsonx BI Assistant. A cloud-based service that automates data preparation, visualization and predictive analytics. It supports natural language queries, making it accessible to users without advanced technical skills.
- Microsoft Power BI. Integrates with Azure AI to enhance data analytics capabilities, offering features such as natural language queries, automated insights, and predictive analytics.
Customer Feedback and AI
AI tools have revolutionized the way businesses gather, analyze and act on customer feedback, enabling a deeper understanding of customer sentiments and improving overall satisfaction. Sentiment analysis, powered by NLP and NLU, allows companies to sift through large volumes of customer feedback from various sources, including social media, reviews and surveys, to extract meaningful insights.
Similarly, AI tools automate the collection of customer feedback across multiple channels. Chatbots and virtual assistants can conduct real-time surveys during customer interactions, while AI-driven platforms aggregate feedback from social media, emails and review sites. This comprehensive approach ensures that businesses capture a holistic view of customer sentiments.
Sentiment analysis involves using NLP to determine the emotional tone behind customer comments. AI algorithms can classify feedback as positive, negative, or neutral and identify specific aspects of the customer experience that are driving these sentiments. This granular analysis helps businesses pinpoint areas of improvement and understand the factors contributing to customer satisfaction or dissatisfaction.
Tricia Allen, VP of business development for Hotspex Media, a Toronto-based digital media agency, told CMSWire that AI is enabling brands to use emotion to drive sales.
"We’ve seen the marketing industry trending towards emotionally-aligned ad targeting that uses AI. New tools can analyze millions of web pages and online videos for emotional intent, and then place ads that have the same tone,” said Allen.
“For customers, this means when they’re viewing content, they won’t be shown an ad that feels out of place, which helps them stay engaged with the content,” Allen added. “If a viewer is watching a recap of a sports final, for example, AI now lets marketers place ads that invoke the excitement and energy of the content the viewer is consuming."
Here are some examples of how leading brands are using AI to enhance their understanding of customer sentiments and feedback:
- Airbnb uses AI to analyze customer reviews and feedback, employing sentiment analysis to understand guests' experiences better. By identifying common themes and sentiments in the feedback, Airbnb can make informed decisions about improving their services. This proactive approach has helped Airbnb maintain high customer satisfaction and loyalty.
- Hootsuite, a social media management platform, uses AI to analyze social media mentions and customer feedback in real time. By using sentiment analysis, Hootsuite can quickly identify emerging issues and respond promptly to customer concerns. This real-time feedback loop has allowed Hootsuite to enhance its customer support and improve the overall customer experience, resulting in higher customer retention rates.
- Netflix employs AI to analyze viewer feedback and viewing patterns. Sentiment analysis helps them understand how viewers feel about specific content, allowing the platform to tailor recommendations and improve its user experience. This personalized approach has been crucial in keeping viewers engaged and satisfied, contributing to Netflix's success in the highly competitive streaming industry.
“As an industry, we tend to reward ‘efficiency’ over actual brand building and the measurement of outcomes,” said Allen. “Advertisers often optimize towards metrics like CPM, CPC, CTR, etc., which incentivizes platforms to optimize towards low-quality placements. Improving the quality of placement not only improves overall efficiency because you are eliminating wastage but allows brands to capture attention and engagement in order to truly stand out from the sea of sameness.”
Final Thoughts on AI Use Cases for CX
AI is greatly impacting the customer experience across industries, with major brands making significant investments in AI-driven technologies, leveraging AI to personalize interactions, automate tasks, and gain deeper customer insights. AI-powered analytics tools and sentiment analysis are enabling businesses to make data-driven decisions and respond more effectively to customer needs.
As AI continues to evolve, businesses that strategically integrate these technologies into their CX strategies will be well-positioned to thrive in an increasingly competitive, customer-centric market.
