Generative AI is transforming CX, but not every application is advancing the industry. Many tools can create more noise than clarity, and introduce risk rather than results. Sustainable impact comes not from chasing hype, but from enabling smarter decisions and faster action at the front line.

Today’s popular GenAI tools like ChatGPT, Microsoft Copilot, and Gemini are incredibly powerful, but they are not built for broad enterprise CX deployment. They require prompt engineering expertise, they assume technical fluency, and when used incorrectly, they can generate . For frontline users—those in retail, service, operations, and customer care roles—this complexity creates a barrier to adoption and trust.

Frontline teams should not have to become prompt engineers on top of their day jobs.

That is exactly why we focused on building a suite of solutions that are predictable, reliable, scalable, and secure—designed specifically for non-technical, non-analyst users. These solutions deliver intuitive, context-aware intelligence that is embedded directly into existing CX workflows to drive fast, smart decisions at scale, without the need to be an AI expert.

We call it .

Frontline-Ready AI:
Built for speed, scale, and security

The incredible power of GenAI for customer experience is exponentially multiplied when the technology helps frontline employees—like store managers, front desk managers, and bank branch staff— actually work better, smarter, and faster.��

We’ve built a suite of tools that are as brilliant as they are practical. analyze a full conversation in less than 60 seconds, a staggering 400% time savings for managers. makes discovering emerging trends effortless, putting real-time insights at our users’ fingertips. With , we’ve automated empathy and personalization at scale for faster and more relevant customer follow-up. And bypasses hours of dashboard analysis to provide immediate, actionable answers.��

We designed our Frontline-Ready AI solutions to confidently equip your customer-facing workforce. Our technology delivers reliable and accurate insights by focusing on four key principles: It provides predictable and reliable answers by using only your company’s data, significantly reducing the risk of hallucinations. The solutions are also highly scalable and secure, integrating seamlessly across large teams with minimal rollout time and training.

Ultimately, ����ԭ�� provides an enterprise-grade platform that protects your most sensitive information while providing your teams with the insights they need.

Early success stories using Frontline-Ready AI

We’re already seeing the profound impact of these solutions in action. 

For example, a national pet supply retailer using our Themes with GenAI feature was able to pinpoint a previously hidden source of customer frustration and attrition: a specific surcharge on a subset of delivery orders. This critical insight was identified and addressed in mere hours.

Another customer, leveraging our Smart Response feature, has seen an 80% reduction in average response times. This isn’t just a small improvement; it translates to an annual savings of 3.4 years of work for their team compared to their previous templated responses. The key is accuracy: the AI-generated responses have a 92% match rate with the brand’s voice and needs. This allows employees to simply review, make minor edits, and send, streamlining the entire process.

Transform frontline CX, only with ����ԭ��.

There’s a massive difference between general-purpose AI and a generative AI solution tailored for frontline employees. While general models like ChatGPT can be useful for brainstorming or content generation, they can also cause confusion and provide inconsistent information when used in customer support, sales, operations, or field service. This often leads to subpar experiences for both employees and customers.

The best generative AI solutions for frontline teams, however, are designed to fit seamlessly into employees’ existing workflows. These purpose-built tools empower your team to make smarter, faster decisions, whether they are in the field or on the floor, all without requiring them to become AI experts.

����ԭ��’s AI now empowers millions of employees to act on customer and employee insights directly from our platform. By democratizing AI on an unprecedented scale, we help businesses improve individual customer interactions while also identifying and resolving friction points to drive cost savings and revenue growth.

Check out our next wave of Frontline-Ready AI innovations! Sign up for our on October 23, 2025.

AI sounds fancy. Probably because it’s every tech company’s favorite buzzword. But in reality, it’s pretty simple.

So let’s do the Michael Scott thing: “”

People love to hype up AI. But when it comes to actually helping your customers, one of the most useful things you can do is also one of the simplest: listen to what they’re telling you.

Every day, your customers call, chat, and text. They tell you exactly what’s confusing, broken, or frustrating. But most companies only catch bits and pieces — maybe a survey here, a quick complaint there — and the rest gets buried in thousands of customer service conversations no one has time to review.

That’s where speech analytics comes in.

It’s not magic. It’s a signal amplifier.

Think of every customer call like a detective clue.

One clue by itself? Not much help.

Thousands of clues together? You see the real story:

• Why customers keep calling about the same thing
• Why your new policy is confusing
• Why you’re paying more to fix problems you could have prevented

Speech analytics is the big detective wall where you pin all the clues and see how they connect. Suddenly, what seemed random makes sense. 

How it works, with no fancy jargon

Here’s the deal:

1. Every call, chat, or text gets turned into text data.
2. AI scans it for keywords, topics, tone, and patterns.
3. You get a summary of what’s driving repeat calls, churn, or even praise.
4. The system flags stuff you’d never catch by skimming a few calls a week.

It’s basically Ctrl+F for your entire contact center.

So what’s in it for you? (Yes, you)

Contact Center Leaders: Find and fix what drives repeat calls, long handle times, or agent burnout, so you can boost performance and protect the bottom line.

CX & Ops Leaders: Uncover the real root causes behind churn, friction, and costly mistakes, so you can solve problems once and for all.

Digital & Marketing Teams: Find out why people drop off — and fix it before it tanks conversions, kills ROI, or sends customers running.

Insights & Analytics: Go beyond surveys. Tap into what customers actually say to spot trends, predict churn risks, and share insights that get teams moving.

Execs: Happier customers, lower costs, and more revenue you’d otherwise leave on the table.

What smart teams do differently

Here’s the kicker: the best teams don’t hoard these insights in a dusty dashboard.

They share what they hear across CX, Ops, Digital, and Product, so everyone fixes the real problem, not just the symptom.

They fix problems while they’re still small, seeing them in near real time, not weeks too late.

They automate what they can, like flagging repeat issues or coaching gaps. So they don’t drown in manual work.

And they treat conversations like gold because that’s what they are. No more flying blind. No more guessing games.

The bottom line

Speech analytics isn’t about listening for listening’s sake. It’s about fixing customer headaches before they cost you trust, money, or talent.

So yeah, AI hype is loud. But the smartest thing you can do right now?

Listen better. Act faster. And turn that contact center (the place where frustrated customers call you at your worst) into your best source of insight and action.

Oscar, explain speech analytics like I’m five.

Sure, Michael:

Customers talk. Speech analytics listens.

It spots patterns you’d otherwise miss.

It helps you fix problems before they snowball.

It connects the dots with all your other experience data and shows you what really matters.

Basically, it’s like having a super-smart detective helping your whole company stay connected and act on what matters most.

Everyone wins: your agents, your customers, your CFO.

It’s not hype. It’s smart CX.

Ready to turn your conversations into real revenue?

Download Smart CX Starts in the Contact Center to see how top brands use everyday calls to reduce churn, drive growth, and unlock ROI, fast.

Artificial intelligence (AI) capabilities are advancing faster than ever, promising to eliminate even the most complicated operational workflows. But this can only be achieved with the trust and oversight of your employees, who are uniquely capable of making or breaking this transformation. Often, it’s their willingness to participate and collaborate that leads to the successful adoption of AI initiatives.��

So how do you gain their buy-in? 

Your organization should focus on three key actions: show genuine empathy for employee concerns, present AI as a tool that enhances rather than replaces human work, and promote a culture that prioritizes people-first, human-centric work.��

Let’s explore each of these three actions to help your organization successfully implement AI initiatives that employees trust and are eager to embrace.

Empathize with Your Employees’ Situation

Have you ever been left out of a decision that directly affected you? You probably felt inconvenienced, undervalued, or frustrated. In the workplace, the effects of these exclusionary decisions can run even deeper: Our jobs , so being left out can impact how we see ourselves as much as our financial future.��

That impact is so deeply felt that even the most helpful AI, backed by clear guarantees of safety and responsible use, will struggle to gain traction if employees feel uninformed or excluded.��

Business leaders must be empathetic to their employees in general, but especially when new initiatives have the potential to make them feel threatened and uncertain. By genuinely listening to employees’ concerns and understanding their perspectives, organizations can build a foundation of trust, paving the way for smoother AI adoption and creating goodwill that extends to future initiatives.

For your AI adoption strategy to be successful, your organization must adopt measures that foster trust. According to , “29% of AI decision-makers said trust is the biggest barrier to generative AI adoption in their organization. Organizations that prioritize transparency, accuracy, and ethics will be best positioned to leverage genAI responsibly.”

Judy Bloch, VP, Executive Advisor for Financial Services at ����ԭ��, who has held customer experience leadership roles at Sprint, Citi, and UMB, saw this happen with one of her financial services clients. The organization was attempting to roll out a conversational AI bot. The tech wasn’t flawed, but the initiative failed because employees didn’t trust it. The second rollout of the bot turned this missed opportunity into a success by taking a different approach: this time, employees were included, empowered, and given the time they needed to understand the technology. This shift fostered a sense of ownership and psychological safety, turning skeptics into champions.��

AI success isn’t just about algorithms — it’s about people.

Position AI as an Enhancement, Not a Replacement

“AI’s greatest value isn’t what it can do, but what it can free us up to do,” says Melissa Arronte, PhD and VP, Executive Advisor for Employee Experience at ����ԭ��, who previously served as a leader in HR and analytics at Liberty Mutual Insurance and Citizens Bank. She believes AI can eliminate routine, low value-add tasks from workflows, empowering employees to focus on providing empathetic, personalized service to customers.��

The techniques and capabilities of AI are advancing so quickly that , enabling these conversations to become rather routine. That frees up humans to do higher-value tasks, particularly those that require empathy and human-to-human interaction. “The biggest promise of AI right now is to take off work that’s really time-consuming and repetitive, and allow us to do work we didn’t have time for before,” Arronte explains. “This gives us the ability to use our brain in a way that AI can’t.”

Many such tasks require flexible problem-solving that considers the full context of individual experiences with a business to deliver the best possible resolution to their problems. AI lacks this flexibility because it can only mimic humanity without true warmth and empathy. People can feel that difference, and those feelings impact customer loyalty and satisfaction with brands. While AI may certainly be able to aid in these higher-value tasks, it cannot fully replace the human intuition and planning capabilities that enable people to more holistically understand and act on problems.��

In short, businesses should enable AI to handle the mundane, so humans can do what is most meaningful. Whether it’s solving problems that require flexible thinking, connecting with customers on a personal level, or imagining new solutions — these are still uniquely human capabilities. AI is therefore not a threat to human creativity, flexibility, or empathy. Instead, AI is a tool that can amplify these qualities by reducing tedium and stress, which increases employee motivation and ability to deliver better service.��

Promote a People-First, Human-Centric Work Culture

Lastly, and most importantly, the previous two actions are only possible with a human-centric, people-first work culture that empowers employees to go above and beyond for customers, even if that means taking a bit longer to arrive at a holistic resolution to a customer problem, according to Arronte. Customers can immediately sense if a company culture prioritizes their employees. When employees feel confident enough on customer service calls to make recommendations, guide customers to the right solutions, and even gently point out mistakes, it sends a strong message: their organization has empowered them with the time, training, and tools they need to deliver truly helpful service.��

For example, I recently bought a camera with a couple of lenses, only to find out a newer version of the camera was being released just days later. Canceling my order required a call into customer service. Not only did they let me know the lenses I’d bought wouldn’t work with the newer model, but they also helped me cancel the original order and place a new one. The agent expressed genuine excitement for me. They even followed up with a personal email to confirm everything was squared away. Never did I feel rushed or inconvenienced. In fact, I actually felt good about spending more with them, instead of going with one of the other brands I’d been considering. That experience made me a customer for life.��

The AI in this example was hiding in plain sight. The instant my call was received, all of my details were readily available for the customer service agent. We could get right to talking about what I needed, and the agent had all the context needed to help me out. AI expands employees’ capabilities and gives them more time to focus on solving the root of customer issues – instead of getting bogged down by repetitive tasks like re-identifying the customer. However, what ultimately made the difference was that the agent was empowered to spend more time actually connecting with me – all while solving my problem in under 10 minutes. It spoke volumes about the kind of culture the organization fostered, and the support they’re willing to give their employees so that they can deliver empathetic service.��

Make Your Employees Champions of AI

AI may be evolving at lightning speed, but its true potential lies in how well people are empowered to use it. Organizations that prioritize trust, empathy, and a human-centric culture are the ones best positioned to unlock AI’s full value – not by replacing people, but by supporting them.��

When employees feel heard, supported, and equipped with the right tools, they become more than just users of technology — they become champions of it. And when that happens, AI becomes more than a productivity tool; it becomes a catalyst for better service, stronger loyalty, and more meaningful work.

Whether you’re AI-curious or already all-in, check out to help you learn, apply, and level up your AI game for faster insights, smarter actions, and bigger impact.

Artificial intelligence (AI) was one of the biggest trends in customer experience in 2024. Our experts predict it will continue to dominate customer experience trends in 2025 as brands leverage its capabilities to anticipate and meet customer needs across each and every interaction.��

Though it’s been talked up for the past few years, especially with the rise of generative AI (genAI), it’s more than just a buzzword. We’ve seen firsthand how AI is transforming customer experiences, and we’ve been eager to learn more about how customer experience professionals across industries really feel about AI, how they’re using it, what their AI strategies look like, and what concerns they might have.��

For answers, we conducted a ����ԭ�� Market Research survey of over 800 customer experience practitioners across a balanced set of industries, company sizes, and role levels in the U.S., UK, Australia and New Zealand, and Canada.��

The major takeaways from this study are now available in our new report: Beyond the Hype: What CX Practitioners Really Think of AI. Here are the highlights:

How brands are using AI in customer experience

If we had to pick one finding that most clearly demonstrates just how AI is a lot more than hype, it would be this: When we asked CX practitioners what the impact of AI has been so far on their businesses, an impressive 60% of our survey participants told us it has exceeded their expectations. Nearly everyone — 96% of customer experience professionals — answered that it has met or exceeded expectations.

Even when asked about the newest form of AI, genAI, the vast majority of participants say they’ve given this technology a try at least once, and nearly half (42%) say they’re regular users of genAI.��

And that’s only the beginning. Analyzing this survey’s results, I uncovered four unique themes that reveal a comprehensive picture of how CX professionals think about and use AI. Let’s dive into these now.��

CX professionals are optimistic about AI in customer experience 

Most (86%) of the leaders we surveyed believe AI will change what their organizations are able to achieve when it comes to the customer experience. And more than half say AI will outperform humans in as little as five years in two key areas: looking up information across various data sources, and summarizing and explaining larger sets of information.

In other areas, such as completing actions, identifying accurate insights and drawing conclusions from data, creating or editing content, figuring out what steps to take based on information, and understanding and answering customer questions, the professionals we gathered insights from do not feel AI will exceed human capabilities in the near-term.��

Most companies have established an AI roadmap

Three in four CX practitioners believe their companies have a clearly defined AI strategy that is comprehensive of customer experience use cases and benefits for their organizations.

Similarly, investing in AI is important to most of the professionals (84%) we surveyed, with the fastest-growing companies being 4.2 times more likely to agree that their investment in AI will be “very high” in the next 12 months compared to companies with the lowest-reported revenue growth rates.

Given the degree to which companies are embracing artificial intelligence in customer experience across their strategies and areas of investment, it should come as no surprise that AI-focused roles are becoming standard practice, with more than half of professionals (51%) reporting their organization has an AI-focused exec on board — and even more (70%) reporting having one or more roles dedicated to genAI.

AI is being embraced for a variety of evolving CX use cases

Currently, AI is most likely to be used to enhance backend analysis and streamline workflows. That said, things are likely to change this year, as more organizations embrace using artificial intelligence — genAI, specifically — for customer interactions.��

When we asked CX practitioners how they’re using AI right now, “enhancing the quality of data analysis” was the most frequently selected objective. One in five participants chose this as their top use case, two times more than any other option. The next top responses include “automation as a means of labor cost reduction” and “improving data analysis speed.” However, when we inquired about how organizations plan to use AI in the future, “using genAI for customer-facing issues” was the answer that came out on top. Other frequently cited future use cases include “simulating and predicting customer behavior or outcomes” and “automating actioning of comms” (for example, closing the loop).

CX professionals have data security concerns

We also asked CX leaders to share their priorities when selecting or developing AI tools. Data security and data privacy were the top two drivers influencing their choices, with the third being the potential return on investment of the AI solution.

It’s promising to see so many organizations approaching AI adoption thoughtfully. Data security and privacy are must-haves when selecting AI vendors. They’re areas ����ԭ�� is deeply committed to, with our company focused on implementing the highest standards for security of data storage and transmission, utilizing AI security best practices, and maintaining an internal AI Moderation Council that has oversight over all of our AI products at ����ԭ�� and an external AI Advisory Board that’s dedicated to the responsible and ethical use of AI.��

What’s on the horizon for artificial intelligence in customer experience?

Most organizations recognize that AI is vital to their business. Most say AI’s capabilities have met or exceeded their expectations. But how are companies evaluating the impact of AI — and in which areas do CX practitioners think they need to step up their investment in AI? 

Check out the complete report, Beyond the Hype: What CX Practitioners Really Think of AI, for more insights into the current and future state of the use of artificial intelligence in customer experience, according to your fellow CX professionals.

Customer experience (CX) is all about connecting with people, solving their problems, and building the kind of loyalty that helps brands grow. But as customer needs and expectations change over time, businesses must keep up with trends — which often means adopting new strategies and smarter tools.

From delivering more personalized experiences to streamlining everyday customer-facing processes, artificial intelligence (AI) is helping deliver faster, more efficient, and tailored service to the consumer. Customers expect rapid and thoughtful interactions when they deal with a company — and organizations that leverage AI to meet these expectations may be able to provide better service more quickly.

�ѱ�岹��������’s industry experts recently sat down to discuss all the ways AI is shaping CX. Here, they weigh in with examples of how artificial intelligence is working across verticals.

The evolution of traditional CX to AI-driven strategies

CX has come a long way. Long gone are the days of relying on gut instincts and hindsight. Traditional CX approaches often struggled to keep up with real-time needs or forecast what customers might want next.��

Now, companies can use AI and predictive analytics to stay ahead of the curve and wow potential buyers before any money changes hands. This shift from reactive to proactive means better service overall, from quicker solutions to more personalization.

Today’s consumers expect fast support, sometimes even available 24/7, and interactions that feel custom-made for them. AI is making it easier for businesses to meet these expectations, bridging the gap between what customers want and what companies can deliver.

How AI is transforming CX across industries

From healthcare to finance, companies are adopting AI tools in every industry imaginable. In some cases, these technologies have been on the backend for years now, and customers likely had no idea. In other scenarios, AI tools are now front-and-center as part of a reimagined experience for the consumer. Here are some industry-specific examples of how AI can be put to great use, regardless of the vertical.

Healthcare: Smarter care and happier patients

Providing a great CX in healthcare can be a challenge. Patients rely on their providers for something incredibly personal: their well-being, which makes the patient-provider relationship both unique and deeply meaningful — and very delicate to maintain.

In many use cases, AI tools have helped medical organizations provide better support and more personalization to their patients.��

As , Vice President and Industry Executive Advisor for Healthcare at ����ԭ��, explains, “AI can enhance efficiency, accuracy, and personalized care. AI can improve patient-provider communication, streamline workflows, and automate data analysis for better patient outcomes.” 

For instance, uses AI-powered translation tools to support their non-English-speaking patients. By making healthcare more accessible, the hospital increases trust and builds stronger patient-provider relationships. These tools also improve accuracy and comprehension on both sides of the exam table, leading to improved outcomes.

Similarly, launched an ambient transcription technology to capture conversations between patients and doctors, reducing the administrative burden on clinicians. With more time to focus on patients, providers can easily elevate the overall quality of their care.

Hospitality: Taking loyalty to the next level

Hospitality brands are also increasingly leveraging AI to improve the guest experience. For instance, uses multilingual AI chatbots that can answer customer questions instantly. This frees up staff to handle more complex tasks and improves guest satisfaction.

produces AI-driven analysis of guest feedback to deliver more personalized services. The tool summarizes insights from surveys and social media and uses that data to refine travelers’ experiences.

Along the same lines, also uses AI to analyze user data and recommend accommodations that match each guest’s unique preferences. This more personalized approach makes booking easier and helps customers have a better overall travel experience.

“When experiences feel personal, loyalty becomes authentic and long-lasting,” says , Vice President and Executive Advisor for Hospitality at ����ԭ��. Ryskamp explains that other travel industry businesses have jumped aboard the AI train, too. Lufthansa has developed Swiftly, a chatbot travel agent that handles everything from booking to planning, while Royal Caribbean uses AI-powered facial recognition to speed up the boarding process. Alaska Airlines is also deploying AI to update flight schedules by factoring in weather, aircraft availability, and passenger demand.��

Telecommunications: Staying one step ahead

AI is helping telecom companies anticipate and solve problems before they arise, which boosts customer satisfaction in a big way. This vertical harnesses tools like predictive analytics to identify customer churn or other patterns that could hurt business. From there, businesses can attempt proactive retention efforts through targeted outreach.

In addition, telecom organizations use AI to monitor network performance in real time, detecting and addressing congestion issues before they affect users. With smoother service and less downtime, customers tend to stick around for the long haul.

Financial Services: Customized for every client

In finance, personalization is a critical aspect of customer retention, more so now than ever. Many institutions are finding AI tools to be transformative in how they engage with clients.��

“When financial providers align their offerings with clients’ lives, they strengthen connections,” explains , Vice President and Industry Executive Advisor for Financial Services at ����ԭ��. AI enables firms to do just that, meeting client needs with precision.

For , this personalization comes in the form of robo-advisors that offer personalized investment advice, making financial planning accessible to everyone from beginners to seasoned investors.

Trending wins, strategies, challenges, and considerations for AI integration

As businesses adopt AI to transform their CX, they should proceed with caution and be aware of the trends. Getting things set up properly across departments before implementing an AI plan will mean better results in the long run. Here are some areas where businesses have succeeded and struggled so far.

Hyper-personalization

AI can help companies get to know their customers on a deeper level, and this is the way many organizations have leveraged AI so far. These tools can create highly personalized experiences by analyzing customer behaviors and preferences to help businesses foster emotional connections and brand loyalty.��

Data infrastructure challenges

AI’s effectiveness hinges on the quality of the data systems that feed it. Many companies struggle with outdated or disorganized data infrastructures, particularly in sectors like banking. Addressing these challenges requires investments in robust data management systems, which can be extremely expensive. As with many things, when it comes to AI, quality in definitely equals quality out (and vice versa).��

Collaboration across teams

Successful AI implementation typically requires close collaboration between CX, IT, and dev teams. Misalignment between these groups causes inefficiencies and missed opportunities, or even bad data and unhappy customers. Clear communication and shared goals are extremely important at the enterprise level to make AI work for your organization.

Experience orchestration

AI is most impactful when it integrates seamlessly across customer touchpoints for a more unified experience. If organizations can align data, tools, and teams, they can expect both improved CX and a better data feed for future initiatives.��  

The future of CX: AI as a competitive advantage

Thanks to AI, the sky’s the limit when it comes to improving CX — and companies that don’t jump on board the AI train are likely to get left behind.��

, Vice President and Industry Executive Advisor for Telecom and Media at ����ԭ��, highlights the stakes: “As reveals — 84% of customers see personalized experiences as essential as the product itself.” 

AI makes this level of personalization possible, enabling businesses to anticipate needs and solve problems before they occur, helping to foster lasting brand loyalty. Across industries, it’s no longer a nice-to-have — AI is likely a requirement for future CX success.��

For even more insights on AI and CX trends, read our guide: 5 Real Ways AI is Transforming Customer Experiences, which explores five practical use cases for using AI and genAI to revolutionize customer experiences and drive real results for businesses like yours.

Artificial intelligence (AI) promises to revolutionize the world of work. Yet, many people are wary about its rising popularity. Concerns about job displacement, privacy breaches, and ethical risks are omnipresent in discussions of AI. But fears about rising automation aren’t new — whether you’re an 1800s textile designer looking at an automated loom or a modern-day backend developer looking at ChatGPT.��

Because we understand the value and risks of AI, we at ����ԭ�� have always strived towards creating responsible AI that keeps humans in the loop and improves their daily flow of work.

So, what is responsible AI? Responsible AI is an approach to artificial intelligence that ensures AI-powered features are developed, tested, and maintained with a focus on mitigating bias, discrimination, and privacy violations, while promoting accountability and transparency.

And how should you implement responsible AI? Let’s start with some principles for creating responsible AI that we believe every organization should follow.

The Main Principles of Responsible AI

Transparency

AI systems should be easily understood — meaning that all users can comprehend its processes and outcomes. This includes being extra clear about how data is collected, decisions are made, and models are trained.

Accountability

Organizations — and the teams responsible for AI development — must be accountable for the system’s behavior and outcomes. If AI has the potential to cause harm or other problems, mechanisms should be in place to address the situation so that somebody is always accountable.

Privacy & Security

Privacy and security are essential pillars of responsible AI. Sensitive information should be safeguarded, ensuring AI systems and the companies overseeing them are resilient to breaches and attacks through robust, consistent vulnerability testing.

Ethical Data Usage

To ensure that data is being used and collected ethically, and that AI isn’t trained with bias and discrimination, organizations must implement diverse data collection, develop fair machine learning models, reprocess data to remove bias, monitor and test AI models with human review and oversight, and continuously monitor and audit their AI systems. Businesses should create a set of ethical and legal guidelines that models and data usage are measured against.��

The Importance of AI Governance for Responsible AI

Companies need to oversee a robust AI moderation and security process to solidify truly responsible AI. This must apply to all current and future technology, prohibit law violations, and adhere to other strict rules and regulations.

Your organization should define teams and roles that handle your own AI governance processes to ensure you’re using and building responsible AI, especially as AI comes to the forefront of conversations about privacy and security. Your vendors should, too!

As an example, �ѱ�岹��������’s intake process follows the below guidelines:

1. Documentation: The new AI use case is described, including the features, purpose, and training.
2. Risk Management: Any foreseeable risks are flagged, including potential misuse of the AI system.
3. Compliance: Ethical and legal use of the data and compliance with applicable obligations are ensured.
4. Safety, Moderation, Ethics: Global experts help create robust safeguards, focusing on human-centered AI to mitigate bias further.

AI Governance: How ����ԭ�� Addresses Responsible AI

�ѱ�岹��������’s External AI Advisory Board

Our advisory board is a diverse collective that demonstrates thought leadership in AI policies, regulations, and technologies to promote safe, secure, and fair AI solutions.��

The AI Advisory Board is made up of ten customer and partner representatives with backgrounds in every use case we service. Members are well-seasoned experts who provide input on AI privacy, ethics, and security for ����ԭ�� and the broader experience management community. The board focuses on diverse representation across markets, with an emphasis on enterprise and small-to-medium enterprises worldwide.��

“It is important for us that the AI Advisory Board includes people from diverse backgrounds,” said Rahul Kamdar, SVP of Product Management at ����ԭ��. “By bringing in different viewpoints and unique contributions, we hope to understand and solve complex problems, avoid biases, and address ethical issues to build AI solutions that truly benefit all.”

�ѱ�岹��������’s Internal AI Moderation Council

The internal AI Moderation Council is a team of diverse professionals across the wide spectrum of AI expertise, from legal to data acquisition. The team handles internal ����ԭ�� queries about our governance processes. They keep up to date on new and pressing issues in AI regulation, ethics, and anything else pertinent to building AI that is simultaneously human-centric, responsible, and able to generate value for our clients.��

At ����ԭ��, the Moderation Council is a key part of our AI feature development process, validating models against our responsible AI principles and relevant legal requirements. Together, our experts are able to have a tangible impact on the growth of our AI in a changing world. The AI Moderation Council has a tough job, but it’s one that every organization should seriously consider creating their own internal team to tackle.��

Ensuring Responsible AI in the Modern Age

Responsible AI encompasses principles such as transparency, accountability, privacy, and security, which are vital for ensuring ethical AI development.��

These principles matter. �ѱ�岹��������’s approach to responsible AI includes a robust governance framework that focuses on documentation, risk management, and compliance, as well as a diverse AI Advisory Board that brings varied perspectives to address biases and ethical issues. By adhering to these principles, ����ԭ�� ensures all of its AI solutions are safe, secure, and equitable.

����ԭ�� has deeply integrated AI into the core of our platform for over 15 years, starting with the 2008 release of our industry-leading text analytics. Our AI is a key differentiator that enables us to scale and democratize high-quality CX and EX insights across the world’s largest enterprises.

To learn more about �ѱ�岹��������’s approach to AI, check out our AI leadership page.

AI in customer experience (CX) presents a significant opportunity for the world’s leading brands. With customers interacting across a still-growing number of touchpoints, AI is now an integral part of any CX strategy. Just look at the rising volume of customer signals and the high costs of hiring a limitless number of employees to analyze data.

With AI in customer experience, your brand can analyze data in seconds and obtain immediate, actionable insights.

The Role of Artificial Intelligence in Customer Experience

Today’s AI technology offers personalized interactions, automates customer support, and predicts customer behavior — and this is just the beginning.

Through AI-powered insights, companies can analyze customer data to deliver tailored recommendations, creating a more engaging and relevant experience. AI-driven chatbots and virtual assistants automate routine customer support tasks, taking the burden off of contact center agents and ensuring quick response times. AI also analyzes customer preferences and behaviors to forecast trends, enabling brands to anticipate needs and improve customer satisfaction through proactive service.

The Benefits of Artificial Intelligence in CX

Delighting customers isn’t easy, yet doing so is worth every bit of time and resources. AI quickly provides the direction necessary for brands to offer unrivaled experiences throughout the customer journey.

Here is why you should use AI in customer experience:

1. Get to know your customers quickly

Interactions between your brand and its customers are frequent, right? So just imagine needing to analyze every signal — whether it’s direct or indirect customer feedback — manually. It’s impossible; no amount of employees assigned to the task would keep up.

AI in customer experience tackles data analysis with ease. As part of your CX program, artificial intelligence sifts through customer feedback���ڰ��dz���surveys,��online reviews,��social media posts, and other channels to ensure it’s capturing the full spectrum of what customers say and how they feel.

Remember that signals, wherever they emerge, should flow seamlessly between����dzܰ���customer experience management (CEM) platform and customer relationship management (CRM) platform to pinpoint who a customer is, what their behaviors and preferences are, and how they interact with a brand.

2. Provide faster resolutions

Customers aren’t interested in how you achieve a resolution as long as it’s satisfactory and achieved in a timely manner. The longer a customer waits, the more at risk customer satisfaction (CSAT)������.

Artificial intelligence in CX reduces the amount of time a customer spends jumping through channels or from agent to agent trying to have their concerns addressed. AI pinpoints the customer’s needs and, behind the scenes, figures out what occurred, why, and what the best resolution is. It prevents agents from spending too much time researching the customer’s ticket and figuring out a resolution that might not be well received.

With AI,��customer service is proactive rather than reactive — as such, AI in customer experience increases productivity for agents and happiness for customers.

3. Simplify feedback analysis to drive action

Tracking current behaviors and predicting future trends? If you’re not doing it with artificial intelligence, you’re not doing it effectively at all. AI in customer experience simplifies the analysis of feedback to present insights worth acting on. You’ll know the challenging pain points causing friction in the customer journey and the opportunities that will take experiences to the next level.

4. Personalize every experience

Aiming to make experiences unique for every customer with personalization? There’s no doubt your brand needs artificial intelligence. AI in customer experience gives brands the chance to craft an experience for individuals, forgoing the one-size-fits-all approach that too many brands continue to rely on.

Consumer behaviors are shifting at a rapid pace, and each customer’s preferences are different. By using artificial intelligence within your CX strategy through experience orchestration, you’re personalizing every experience at scale and strengthening customer loyalty.

The Future of AI in Customer Experience

Looking ahead, the future of artificial intelligence in CX is closely tied to the rise of digital experience (DX). While some brands will continue to maintain in-person experiences at physical locations, every brand needs digital channels such as websites and mobile applications to be optimized.

Online channels are heavily utilized in most industries already, and thus it’s important for experiences across them to be frictionless — and personalized. Artificial intelligence empowers an organization to remove barriers preventing customers from completing their activities, and it personalizes experiences — at scale — for every customer.

Increases in customer signals may seem overwhelming, but artificial intelligence in CX automates the path from collecting feedback to analyzing words and sentiment to acting on insights.

Get Started with �ѱ�岹��������’s AI-Driven Capabilities

Now, it should be clear: AI is a game-changing technology for customer experience. It makes an organization run more efficiently, and it leads to breakthroughs that improve CX for customers across the channels they choose to interact with a brand.

That’s why leading brands in top industries choose ����ԭ�� Experience Cloud to leverage scalable AI-driven capabilities trained by more than 60 billion experience signals for their customer experience programs.

With the benefits of personalized customer experiences including increased customer satisfaction and loyalty, stronger sales and revenue potential, and an improved brand image and reputation, it’s clear there’s value in finding the best personalization examples and adding them to your overall customer experience strategy. You’ve come to the right place for inspiration.

We’ve rounded up winning personalization examples from leading brands like Walgreens and advanced customer experience (CX) practitioners like Fred Reichheld, the top types of personalization that are most likely to have a positive impact on CX, and the kinds of personalization capabilities brands are investing in now to improve outcomes.��

According to our 2024 State of CX Personalization Report, making customer experiences more personalized is a top 2024 priority for CX professionals. With these examples as your guide, you’ll be well on your way to achieving this goal.

4 Real-World Personalization Examples from CX Experts

With personalization a key area of focus for brands looking to increase trust and customer loyalty, ����ԭ�� recently sat down with , EVP and President of Walgreens Retail and Chief Customer Officer at Walgreens, and Fred Reichheld, co-founder of the Net Promoter® System (NPS) and an Advisory Partner at Bain, for their insights on investing in personalization and best practices for creating successful personalization strategies.��

Here are four personalization examples they shared from brands in the real world that are offering more meaningful interactions and experiences for customers at the individual level.

1. Personalized prescription pickup experience

Walgreens has done extensive research into the omnichannel customer experience and has found that their company’s typical customer journey involves eight steps, with four crucial touchpoints including when customers come in the store, the navigation experience, the checkout experience, and when customers pick up or purchase items.

“We’ve got to get those four touchpoints right because we know those are the ones that will drive people back to our store or pharmacy again, and those are the things where if we get those right, they will recommend us to a friend,” explains Brown.

That’s why the company decided to introduce a new initiative focused on one of these priority areas. To improve the prescription pickup experience for customers, Walgreens rolled out in-store kiosks that allow customers to check in before they get their items. Once the customer checks in, an algorithm works in the background to automatically triage their need and send the appropriate data to the pharmacy counter in real time. That way, by the time customers arrive at the checkout counter, the pharmacist has everything they need to tailor the experience.��

2. Personalized in-flight experience

A leading international airline is going the extra mile to personalize experiences for frequent fliers by leveraging the company’s digital loyalty program data on site at the airport. Flight attendants have access to the information and are able to personalize their greetings for frequent fliers as a way to demonstrate that the brand cares about their customer loyalty. They may also share a special offer with frequent flyers who aren’t seated in first class, as an extra way to make them feel valued.��

In addition, the flight crew takes the time to connect with travelers who may not have had the best experience on a previous flight to get feedback about their experience to share with leadership.

“It’s the melding together of the human with the digital that I think is most impressive,” explains Reichheld.��

3. Leveraging employees to personalize experiences

Before brands had access to the technology that exists today, true customer experience pioneers personalized every interaction by getting to know their customers through human-to-human interactions. Brown shared that the founder of Walgreens, Charles Walgreen, famously would chat with customers over the phone to build relationships over time, and that’s still possible today for frontline staff.��

Walgreens maximizes human interactions between employees and customers to improve personalization by democratizing individual team member knowledge about customers across the organization at scale, so that anyone can provide an intimate, personal interaction.��

“The secret sauce for us is unlocking that human touch at the front line when the customer or patient is there interacting with our team,” says Brown.

This is an approach Reichheld says can be highly effective. He recommends getting started by finding out where customer-facing employees see the most opportunity.��

Walgreens uses �ѱ�岹��������’s employee crowdsourcing platform to gather these kinds of insights by asking questions like, “What’s getting in the way of adding value for our customers?”

The team is “overflowing” with ideas straight from the front line that the corporate team is prioritizing, says Brown.

4. Listening to referring customers to personalize communications and experiences

AI-powered tools like �ѱ�岹��������’s Text Analytics�����Ի���Speech Analytics can be incredibly powerful in listening in to customer conversations with your brand — across social, email, phone, video, SMS, in-app, and live chat — at scale.��

Reichheld recommends using AI to find out what referring customers are saying about your company, and using these insights to personalize customer experiences, marketing outreach, advertising, and content based on what high-value customers appreciate about your products, services, and brand.

“The best way to understand how you’re being relevant to your customers is by listening to them when they’re telling other customers about you,” he explains.��

Organizations can use these insights to train generative AI to build new content based on the emotions, sentiments, and themes that come up in conversations among your brand’s promoters.

“That’s a very powerful opportunity for generative AI,” says Reichheld.

Best Practices for Ensuring Personalization Success

Use Agile Prototyping

Walgreens implements agile prototyping to test out strategies designed to improve the experience at a pilot location. From there, they assess outcomes, make tweaks, and determine how to best scale their efforts.

Capture Customer and Employee Feedback and Refine Strategies Based on Insights

When launching new initiatives, the Walgreens team uses ����ԭ�� to capture feedback from employees and customers about the experience.

“We’ve enabled all of our frontline team members to actually have this tool front and center so that we can get real-time NPS® and really understand and assess what is actually not working from a customer perspective” while also hearing from team members about what’s not working for them, explains Brown.

Prioritize Personalization Efforts for High-Value Customers

Brown recommends investing in personalization efforts that are centered on improving experiences for high-value customers with the greatest potential to add more value to the organization.��

For example, at Walgreens, a customer that regularly picks up prescriptions but doesn’t cross shop in the store presents untapped potential. Lower-priority segments might be those customers who are already bringing a lot of value to the business but who have more limited untapped potential and customers who bring no value today and who are not likely to bring value in the future.

“If I only have a dollar to spend, I’m going to allocate maybe 60 cents of that dollar to that group of customers that I know they’re spending well with us today, but they still have a lot of untapped potential,” says Brown. “That’s how we…think through personalization and designing experiences that are personalized. We use our value segmentation to help us with resource allocation.”

Tie Employee Performance Bonuses to CX Outcomes

At Walgreens, the company is prioritizing personalization and CX efforts by tying more of employees’ bonuses to the performance of the store — based on factors like NPS® and team member engagement.��

6 Types of Personalization That Have a Positive Impact on the Customer Experience

As part of our special report,��How Consumers Really Feel About Personalization, we asked 2,000 U.S. survey participants to rate a range of personalization examples on a scale of 1 to 5, indicating how positive an impact each has on their experience. Of 34 choices included, these are the top personalization factors consumers selected:

• Receiving special recognition, rewards, or treatment for customer loyalty (69% agree)
• Not having to repeat the information that’s already been provided when transferred to a new customer service agent (68% agree)
• Being offered forgiveness or understanding for late payments, returns, etc. (68% agree)
• Getting proactive help when an error or issue is detected (e.g., account is locked or service is down) (65% agree)
• Customer service agents being able to see customers’ full history of the times they’ve contacted the company (65% agree)
• Being treated to a special offer or free item on a customer’s birthday (65% agree)

Examples of CX Personalization

According to a ����ԭ�� and Customer Experience Professionals Association survey of 305 global CX professionals published in our 2024 State of CX Personalization Report, the majority of CX teams say they currently:

• Deliver proactive customer feedback requests based on interactions (76%)
• Serve up personalized content and recommendations (63%)
• Use personas or segmentation profiles to personalize experiences (58%)
• Leverage personalized experience orchestration tools��(55%)
• Use automated marketing/closed loop communications for personalization (53%)
• Offer rewards and recognition based on individual customer information (50%)

Examples of customer data that brands are currently using for personalized experiences

As part of our ����ԭ�� and CXPA survey, we asked CX teams about the customer data they’re leveraging for personalization and the most frequently cited examples include:

• Product purchase history information (35%)
• Customer demographics (33%)
• Duration of being a customer (31%)
• Customer preferences/settings (30%)
• Prior transaction volume/spend amount (28%)

Personalization practices in use at fast-growing companies

Brands reporting 10% of higher revenue growth rate are more likely to personalize customer experiences by doing the following, according to our 2024 State of CX Personalization Report:

• Offering flexibility of payment options (e.g. methods, channels, timing, etc.) (61%)
• Making customizable preferences available by service type and channel (54%)
• Ensuring continuous recognition of customers based on their unique attributes (51%)
• Delivering targeted offers based on unique customer attributes (48%)
• Providing rewards and recognition based on unique customer attributes (47%)

Unlocking the Power of Personalization with ����ԭ��

Over the past few years, ����ԭ�� researchers have explored the financial value of personalization, and we’ve found that:

• Most consumers are willing to spend more with companies that offer a customized experience (61%) 
• The majority of consumers (82%) say personalized experiences influence the brand they choose at least half of the time when shopping
• Companies with top-performing customer experience programs are 2x more likely to prioritize improving personalization across interactions than laggards and are also 26x more likely than laggards to report year-over-year revenue growth of 20% or more

Personalization’s impact is clear, but few brands are taking full advantage of it. Only 24% of CX practitioners rate their personalization capabilities as advanced and only 26% of consumers rate the level of personalization of their last interaction with a brand as advanced, according to two recent ����ԭ�� studies.��

For more insights on what your team can do to offer more tailored experiences for your customers, be sure to watch our on-demand webinar  — and check out our complete 2024 State of CX Personalization Report for even more personalization examples that deliver an impact.

Personalization is a top priority for companies across industries, but what is personalization, anyway? Personalization is possible when brands collect customer data and use these insights to create unique interactions, experiences, products, content, and services for customers at the individual level.

Examples of personalization in business can be found throughout history, dating back hundreds of years — before the rise of the kinds of technologies that are driving personalized experiences today. 

For instance,  of customer sizes and style preferences to personalize future product offerings and experiences for repeat buyers. 

For another example from more than 100 years ago shared in a , Charles Walgreen, the founder of Walgreens, is said to have grown his business in the early 1900s by taking the time to get to know and build relationships with his customers on a one-on-one basis. By learning about their families and personal lives, he was able to establish the kind of trust that kept customers coming back.

The ways in which brands are able to tailor experiences have evolved dramatically since these early days, but one thing has remained the same — the power of personalization. 

Ahead, we’ll explain why that’s the case by exploring what personalization means for customers and businesses, the benefits of personalization, and what companies can do to build out successful personalization strategies. 

But first, let’s jump into that personalization definition you’ve been looking for. 

Personalization Definition

What is personalization? It’s the process of collecting comprehensive customer data, behaviors, interests, and preferences from across channels and touchpoints and leveraging these insights to tailor content, interactions, experiences, and outreach for customers at the individual level.

Personalization happens when brands shift from a one-size-fits-all approach to business to successfully creating the most relevant and meaningful experiences, content, products, communications, and services for a given customer based on what the company knows about the individual. 

Personalization requires gathering qualitative and quantitative customer data from across channels and interactions, from digital and in-person channels, and keeping this information up to date in real time. This includes demographic information, observed behaviors from digital experience analytics, customer feedback, customer loyalty program membership data, insights from contact center interactions, and more. 

What Types of Personalization are Companies Investing in?

Personalization has a wide variety of business use cases. Brands can use personalization technologies to customize the products and services they offer, to tailor customer service interactions, to create unique website and app experiences at the individual level, and to target marketing campaigns and content. 

Where are businesses focusing their efforts these days? The majority of brands are investing in the following types of personalization strategies and technologies, according to a ����ԭ�� Market Research and Customer Experience Professionals Association survey published in our 2024 State of CX Personalization Report:

• Delivering proactive customer feedback requests based on customer interactions
• Serving up personalized content and recommendations
• Using personas or segmentation profiles to personalize experiences
• Leveraging personalized experience orchestration tools
• Using automated marketing/closed loop communications for personalization
• Offering rewards and recognition based on individual customer information

Personalization Meaning for Customers?

What personalization means varies depending on who you ask. While companies may focus on the financial advantages of personalization — and see it as a means to drive repeat business and loyalty — when taking the customer’s point of view into consideration, personalization is meaningless if it doesn’t result in an improved customer experience. 

����ԭ�� recently sat down with , EVP and President of Walgreens Retail and Chief Customer Officer at Walgreens, and , co-founder of the Net Promoter System (NPS) and an Advisory Partner at Bain, to get these experts’ insights on personalization. As part of this conversation, Brown and Reichheld shared what personalization means to customers and how brands can use personalization to improve the customer experience. 

1. Being treated as a person

When it comes to personalization, brands often focus on tools and tactics, says Reichheld. “We can track people in a digital way, ‘We know so much about them, we can fine tune our offers.’”

But that’s not what matters to the end consumer. What they care about is when companies treat them like a person, “like a human being, like they deserve to be treated,” he explains.

2. Receiving added value and having their lives enriched

Brands need to think about the ultimate purpose of personalization, says Reichheld. And that shouldn’t be to simply sell something — the end goal should be to enrich customers’ lives.

That’s how Brown approaches personalization at Walgreens. She’s always thinking about how to add more value for customers and patients, whether that’s saving customers time or money, better educating them, or helping them lead healthier lives.

3. Having individual needs met

Too often, organizations approach personalization from a siloed perspective. The digital team may be focused on increasing conversions while the contact center prioritizes cutting costs or hold times. 

“In some ways, the greatest challenge of personalization is to get back to a view and understanding of the customer that is truly from the customers’ eyes and not from the organizational control system,” says Reichheld.

When brands get this right and serve customers the types of experiences they’re looking for, people are more likely to refer that company to their friends and family, he explains. 

The Types of Personalization That Matter to Customers

As part of our 2023 ����ԭ�� Market Research report How Consumers Really Feel About Personalization, survey participants rated the most impactful types of personalization strategies brands can use to improve their customer experiences. Based on our findings, these include:

• Offering customers special recognition, rewards, and treatment for their customer loyalty
• Sharing important customer information across teams so that customers don’t have to repeat what they’ve already said if they’re transferred to a new customer service agent
• Providing forgiveness or leniency for late payments, returns, etc.
• Proactively detecting errors or issues and offering help in the moment (i.e. when an account is locked or service is down)
• Treating customers to a special offer or free item on their birthday

Personalization Meaning for Businesses?

Personalization is something the vast majority of companies in business today are already investing in — or plan on investing in. One study finds that as many as  to tailor experiences for individual customers, and, according to our 2024 State of CX Personalization Report, making customer experiences more personalized is the #1 priority for customer experience (CX) professionals in 2024, ahead of any other area.

So why’s that the case? What does personalization mean for businesses?

In a recent ����ԭ�� webinar about personalization, Brown and Reichheld discuss what personalization can mean for business outcomes, explaining how brands that successfully personalize experiences are better positioned to grow, add shareholder value, and generate referrals.

1. The ability to acquire, retain, and grow customers

When brands are able to harness customer data for personalization efforts that grow trust, forge emotional connections, and add value for customers, they’re better positioned to attract, retain, and grow their customer base, says Brown. 

2. Adding shareholder and employee value

In his book , Reichheld looked at companies’ NPS® scores and in every case found that brands with higher NPS scores — that is, those with the greatest number of promoters and smallest share of detractors — generate stronger shareholder returns. 

“Real value for investors really comes only when you get this flywheel going, which drives the economic prosperity of the business, not just for investors but for employees as well,” he explains.

Promoters are individuals whose lives have been so enriched by an experience that they want to share it with others and recommend it to a friend. That’s the link that exists between companies effectively executing personalization strategies, adding value for customers, and generating desired results for their shareholders, Reichheld adds. 

3. Generating referrals

When looking at the net present value of a customer, for many the greatest value comes not in what they spend on purchases with a brand but in the business they generate for a company through their referrals, he explains. 

That’s why organizations should pay attention to referrals generated as a critical measure of success of any personalization effort.

The Top Benefits of Personalization for Businesses

Over the past few years, ����ԭ�� researchers have explored the financial value of personalization, and we’ve found that personalization drives customer spend, brand choice, and revenue growth:

• CX leaders who self-rate their brand personalization capabilities the highest are 2x as likely to achieve major revenue growth (10%+).
• Most consumers are willing to spend more with companies that offer a customized experience (61%).
• The majority of consumers (82%) say personalized customer experiences influence the brand they choose at least half of the time when shopping.
• Companies with top-performing customer experience programs are 2x more likely to prioritize improving personalization across interactions than laggards and are also 26x more likely than laggards to report year-over-year revenue growth of 20% or more.

Essential Building Blocks of Personalization

Now that we’ve shared our comprehensive personalization definition and explored personalization’s meaning for customers and businesses, let’s dive into some of the fundamentals of personalization.

1. Setting the right end goal — building trust, emotional connections, adding value, and enriching customers’ lives

The true power of personalization lies in driving stronger connections, meaningful engagement, and consumer trust.

Walgreens has studied their quantitative and qualitative customer data to determine there’s an eight-step journey that matters to customers. 

“We know that there are two points of friction in this eight-step journey and two moments of truth. And for us, those points are the actual visit when they actually come into the store, how they actually navigate the store, the checkout experience, and then the actual collection or receiving of the goods,” explains Brown. 

“We’ve got to get those four touchpoints right because we know those are the ones that will drive people back to our store or pharmacy again, and those are the things where if we get those right, they will recommend us to a friend,” she adds.

That’s why the team focuses their personalization efforts in these areas that have the greatest potential to forge trust and connections and add value for customers. 

2. Bringing the right data and technology together

This starts with creating a single source of truth for each customer that’s continuously updated in real time and encompasses the customer’s entire history across interactions, channels, and touchpoints, such as:

• Contact center interactions (chat, calls, emails, SMS, social media, etc.)
• Transaction histories
• Digital histories (app and website browsing, transactions, etc.)
• Engagement with marketing campaigns
• Customer feedback and survey responses
• Loyalty program membership histories

Beyond gathering the right data, brands need to invest in customer experience personalization technologies capable of:

• Creating rich profiles based on customer interactions across touchpoints, channels, and journeys
• Segmenting customers by groups
• Leveraging AI to detect patterns and trends, analyze customer journeys, predict customer behavior, and orchestrate next best actions, experiences, and individual omnichannel customer journeys
• Providing personalized customer service
• Creating more relevant campaigns powered by experience-based segmentation

3. Creating products, services, and experiences for the individual

Brown explains that leading companies are embracing adaptive design, “where designing for the average user is no longer the standard.” This is in line with customer expectations — today’s consumers want to be treated differently than the standard because they don’t see themselves as average. 

Another trend that’s at play, she adds, is deep personalization, which happens when brands not only use demographic and behavioral data, but integrate individuals’ purchasing behavior, habits, and preferences to design tailored experiences and communication. 

By using AI-powered Text Analytics and Speech Analytics to collect the right customer data and instantly uncover the meaning behind every customer interaction across touchpoints, brands can shift from a one-size-fits-all approach to using real-time insights to:

• Surface the next-best actions and experiences at the individual level
• Personalize customer service interactions
• Develop dynamic content and optimize marketing promotions and messaging across digital touchpoints based on the latest customer behavior and intent

4. Allocating investments in personalization strategically

“Focusing in on the areas that matter first is most important,” says Brown.

She and her team start with looking at the value of each segment to determine resource allocation, prioritizing high-value customers with greatest potential to add more value to the organization. For example, at Walgreens, a customer who regularly comes to pick up prescriptions but doesn’t cross shop in the store offers a lot of “untapped potential,” she explains.

Lower-priority segments might be those customers who are already bringing a lot of value but have no untapped potential and customers who bring no value today and have no potential to bring value tomorrow.

“If I only have a dollar to spend, I’m going to allocate maybe 60 cents of that dollar to that group of customers that I know they’re spending well with us today, but they still have a lot of untapped potential,” she says. “That’s how we actually start to think about when we’re trying to think through personalization and designing experiences that are personalized. We use our value segmentation to help us with resource allocation.”

Elevate Your Personalization Outcomes with ����ԭ��

�ѱ�岹��������’s leading customer experience personalization technologies help brands deliver personalized customer service interactions and customer experiences across omnichannel journeys. 

Connect with a ����ԭ�� expert today to learn how we can help your team improve your personalization strategies and results. 

At Experience ’24, we brought together the world’s leading experience professionals to discuss the latest trends and advances in our field, the rising prominence of generative artificial intelligence (gen AI), the impact of automation, and the increasing importance of personalization. It’s clear that gen AI and other artificial intelligence (AI) are critical, omnipresent forces that are shaping interactions across channels and touchpoints. We heard from real-world customer experience (CX) leaders from UBS, Volvo, and Walgreens about how the acceleration of AI within our industry is unfolding and what organizations need to consider when adopting AI technologies to power their CX strategies.

A clear takeaway is that for long-term success, having the right people, practices, and (responsible, trusted) systems in place will be vital to (survive and) thrive in this new landscape. Let’s dive into some of our most important learnings from the week related to using AI in customer experience.

2024 Trends in CX and AI

Top 4 CX and AI Key Use Cases in 2024

�ѱ�岹��������’s time-tested foundational AI capabilities, which have been around for 15 years, and latest AI breakthrough technologies have been thoughtfully developed to help CX practitioners accomplish four impactful uses cases, translating data into meaningful, actionable insights; enabling more efficient customer interactions; empowering employee productivity through tailored training; and guiding nest best actions for customers and the business.

1. Using AI to improve the quality of data analysis.

Ask Athena, one of �ѱ�岹��������’s new AI innovations, is designed to help brands get more value and insights out of their customer experience data. This AI assistant uses large language models to answer any question related to your customer data on the spot, providing instant data analysis in the form of a summary, graph, chart, or other module, without employees having to spend hours digging into reports and dashboards for answers.

2. Using AI to accelerate the speed of data analysis.

�ѱ�岹��������’s Themes feature will use generative AI to surface more granular emerging trends in an instant, helping employees save time on root-cause analysis to pinpoint important trends, elevate them to a topic if needed, and empower teams to quickly track and trend them to investigate how and why KPIs are changing.

3. Using AI for content generation for customer communications.

By using AI solutions like �ѱ�岹��������’s new Smart Response, teams can scale the power and productivity of their people across contact center, customer experience, and employee experience teams. Smart Response automatically generates personalized, empathetic, and accurate responses to a customer feedback record that employees can review and modify before sending as a reply, helping increase personalization while also saving time on writing responses.

4. Using gen AI to create concise, relevant summaries of conversational data.

�ѱ�岹��������’s Intelligent Summaries saves employees thousands of hours of time with AI composed summaries that instantly recap any customer interaction providing details, such as reason for contact, issue resolution information, and the content of the conversation, increasing consistency across millions of records so users can spend less time scrolling through interactions to find the right insights.

CX and AI Benefits for Organizations

At Experience ’24 �ѱ�岹��������’s Senior Vice President and Executive Advisor, , moderated an exciting panel about the future of CX with , Head of Client Services, US Wealth Management, at UBS; , Global Head of Customer Experience Insights and Analytics at Volvo Cars; and , EVP and Chief Customer Officer at Walgreens. They discussed how they’re using AI now and how they are thinking about its application going forward. Here are some of the top use cases they discussed:

1. Making things easier for employees

At Volvo, customers value human interactions, and Kowalczyk explained that she sees the value of AI not in replacing these human interactions with knowledgeable retailers with bot-driven experiences but instead in using AI to increase efficiencies and standard knowledge among staff who interact with customers.

That’s the potential Couvillon at UBS said she sees as well. She said she thinks of AI as “the great assist” or “the great accelerator” for financial advisors, enabling them to be more effective and efficient in their roles. One area they’re using AI is in synthesizing the company’s proprietary research around market data, risk data, and personal risk appetite for financial advisors so they can “ultimately make better decisions for the client and deliver that insight to clients.” She said she sees a huge opportunity in taking all of the company’s training and process documents and FAQs and using AI to make this content more “snackable” for employees for learning purposes.

2. Improving the customer experience

For Walgreens, Brown and her team are thinking of ways to use AI that add value for customers — specifically to address points of friction in the customer journey. The company has identified four areas where friction can occur — when customers come to visit, navigate, check out, and receive products or services — and, according to Walgreens research, what their customers want to happen during these interactions is to be able to save time and money; receive insights, products, and services to feel smarter and feel better; and be recognized and treated as an individual by the brand. In addition, Walgreens research indicates that customers want clean stores, fast and friendly service, stocked shelves, and the ability to get their prescriptions quickly and accurately. As such, the brand is using AI and technology across these areas to create a better experience. They’ve started by partnering with ����ԭ�� and building these drivers of excellence into their reporting within ����ԭ��, so they can instantly analyze how each one of their 9,000 stores is performing across these factors.

3. Delivering personalization

Walgreens has over 100 million customers in their database, and Brown said the retailer is using AI to predict what these individuals need to serve up the right experiences at the right time for the right individuals.

4. Increasing operational efficiency and driving cost savings

Brown explained that there are plenty of opportunities to use AI to add value across the retail ecosystem, from merchandising and operations to product development, marketing, and supply chain management.

One of the ways Walgreens is using AI to drive operational efficiencies and cost savings is by combining external data sources, such as weather and event data localized to each of the company’s retail stores, along with customer data, including in-store visit data and health and wellness data, for demand forecasting to help the company prevent out-of-stock issues and to manage inventory levels so that only what’s needed is kept on hand. “These kinds of things have allowed us to reduce out of stocks for the customer by 15% and reduce inventory by 5%,” said Brown.

CX and AI Best Practices: Using Artificial Intelligence the Right Way

Brands that use artificial intelligence the right way adopt a people-first, platform-second approach, explained Couvillon. They’re not investing in AI for technology’s sake, but to solve real customer and employee challenges using AI responsibly and ethically.

Establish internal guidelines for using AI

Volvo has established an AI committee responsible for determining the AI principles for the brand and this is a must-have for using AI the right way, according to Kowalczyk.

These types of guidelines should set parameters for using AI responsibly, from a privacy, compliance, sharing, and transparency perspective, added Brown.

Prioritize data quality

Organizations need to bring together all of their data from across sources — from in person interactions to digital touchpoints — and structure it in a way that can be used by AI, said Kowalczyk.

As �ѱ�岹��������’s CEO explained in his keynote, the insights you unlock from AI “will only be as good as the data that it can access.”

Choose technology partners that focus on data security and trust

�ѱ�岹��������’s Director of Service Operations and Security, Scott Gorman, a member of �ѱ�岹��������’s AI Moderation Council, recently wrote about how AI security needs to be a priority for experience programs, and how “security considerations are — and will always be — foundational to how we design and implement AI models.”

In his article, he explained that brands can mitigate against any potential risks associated with AI by choosing partners that are actively building their platforms with the latest legal, data security, and compliance standards, regulations, and concerns in mind. You can read more about �ѱ�岹��������’s approach to building a robust, secure foundation for AI into our experience platform in Gorman’s blog here.

In her Experience ’24 keynote, explored how ����ԭ�� is building “trust into every experience.” We focus on trust so our customers can rest assured that “as we incorporate new AI technologies, we are protecting your data, security and privacy,” she added.

That’s why we created an AI Moderation Council, consisting of members from our legal, privacy and security, compliance, product and engineering, and customer organizations, to provide oversight, guidance, and policy as it relates to AI. The goal of this group, Turek explained is “to ensure that, for example, we think about data controls so that we respect security and data access policies, and that we eliminate hallucinations, and filter for bias, and toxicity in our AI models.”

As part of her presentation, she also announced the launch of an AI Advisory Board at ����ԭ�� that will consist of customer and partner members focused on the responsible and ethical use of AI.

Leverage the best of human intelligence and artificial intelligence

There was one consistent theme among Experience ‘24 discussions of using AI for CX: AI shouldn’t be used to replace high-value human interactions.

After all, as , Senior Product Marketing Manager at ����ԭ��, described in her keynote, “Artificial intelligence can’t replace the human touch, but working alongside AI, humans can do what they do best — connect.”

Final Thoughts

At ����ԭ��, we’re focused on bringing responsible AI solutions that enable companies to unleash new levels of personalization and productivity for employees that drive efficiency, cost savings, and sustainable growth for organizations. As brands decide when and how to use AI for understanding and enhancing experiences, it’s essential they do so with great thought.

As Turek said in her keynote, “enduring success will be enjoyed by those who adopt responsible AI proactively, rather than reactively.”

To learn more about how ����ԭ�� is approaching CX and AI and our latest AI breakthroughs, check out our .