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Customer experience is the sum of every interaction a customer has with your brand, from their first visit to your website to their latest purchase. When executed well, CX transforms customers into brand advocates. When done poorly, it can drive them straight to your competitors.

Studies show that 86% of customers are willing to pay more for a great experience, while 76% will switch to a competitor after just one bad experience. To meet these expectations, businesses must deliver personalized, seamless, and proactive experiences. But achieving this level of CX excellence is easier said than done, especially when dealing with fragmented, unstructured data.

By 2025, 80% of all data is expected to be unstructured. This includes everything from customer feedback and social media posts to website interactions and email conversations. While this data is rich with insights, its unstructured nature makes it challenging to analyze using traditional methods. Organizations need an omni-channel analytics solution that not only consolidates this data but also makes sense of it in real time.


The Role of Voice of the Customer (VoC) in CX

Voice of the Customer (VoC) refers to the process of capturing and analyzing customer feedback to understand their preferences, expectations, and pain points. Modern CX strategies rely on it for a clear picture of what their customers truly value.

Recognized as a leader in the Gartner® Magic Quadrant™ for Voice of the Customer (VoC) 2024, Qualtrics continues to innovate with the launch of XM/os2, embedding generative AI across its platform. It empowers businesses to deliver personalized experiences and real-time recommendations throughout customer journeys, powered by one of the world’s largest databases of human sentiment.

Each year, Qualtrics processes over 3.5 billion interactions from sources like call center conversations, social media posts, and surveys, turning them into actionable insights. Features like Qualtrics Assist make it easy to query data using natural language, while Intelligent Summaries provide quick, actionable overviews of customer feedback.


How AI Enhances CX and VoC?

AI, VoC, and Qualtrics are reshaping CX, offering actionable insights into how businesses can leverage these tools to turn unstructured data into a goldmine of customer insights. Here’s how:

1. Predictive insights

AI excels at analyzing massive amounts of data to predict customer behavior and outcomes. Instead of reacting to issues, businesses can now anticipate customer needs and take proactive measures with:

  • Pattern recognition: AI detects subtle trends in customer behavior, such as declining engagement, repeated complaints, or reduced purchase frequency, that may indicate dissatisfaction or churn risk.
  • Proactive retention: Predictive models suggest timely interventions, like personalized offers or support outreach, to retain customers before they leave.
  • Opportunity identification: AI pinpoints upsell or cross-sell opportunities by analyzing customer preferences and purchase history.

For example, an e-commerce company uses Qualtrics AI to track browsing behavior. The AI identifies customers who frequently abandon carts and sends personalized discount codes or product recommendations, leading to increased conversions.

2. Sentiment and emotion analysis

Understanding customer sentiment is the important for building strong relationships. AI-powered sentiment and emotion analysis can extract deeper insights from text, voice, and even visual data with:

  • Sentiment detection: AI categorizes customer feedback (e.g., positive, negative, neutral) from channels like surveys, reviews, and social media posts.
  • Emotion analysis: It goes beyond words to interpret emotions like frustration, happiness, or confusion, providing a clearer picture of the customer’s state of mind.
  • Contextual understanding: AI analyzes the tone and context of interactions, enabling businesses to respond more empathetically and appropriately.

For example, a telecom provider analyzes call center transcripts with sentiment analysis. The AI identifies recurring themes of frustration regarding billing and recommends simplified invoices, significantly improving customer satisfaction scores.

3. Automated workflows for efficiency

AI eliminates bottlenecks by automating repetitive and time-consuming tasks, ensuring CX teams can focus on strategic initiatives rather than manual processes. Here's how it works:

  • Feedback routing: AI automatically classifies and sends customer feedback to the appropriate department for resolution.
  • Real-time alerts: It generates alerts for critical feedback, ensuring quick action on high-priority issues.
  • Follow-up automation: AI triggers personalized follow-up emails or surveys based on customer sentiment or actions.

For example, a hospitality brand uses Qualtrics AI to monitor post-stay surveys. When a negative review is submitted, the AI alerts the hotel manager, who reaches out to resolve the issue immediately, turning a dissatisfied customer into a loyal advocate.

4. Personalization at scale

Customers increasingly expect brands to understand their needs and deliver experiences that feel personal. AI makes it possible to achieve this level of personalization across vast audiences with

  • Hyper-personalized recommendations: AI suggests products, services, or content based on individual customer preferences and behaviors.
  • Dynamic content: Marketing campaigns and CX interactions adapt in real-time to align with customer interests.
  • Customized support: Customer service agents receive AI-driven insights about the customer’s history and preferences, enabling them to provide highly personalized assistance.

For example, a subscription service uses Qualtrics AI to analyze customer preferences. Based on past orders, the AI recommends new products tailored to each subscriber, boosting renewal rates and average order value.

5. Simplifying research

AI transforms the time-consuming process of analyzing open-ended feedback into a streamlined, efficient task, enabling teams to focus on actionable insights:

  • Text mining: AI analyzes thousands of open-ended survey responses to identify common themes and emerging trends.
  • Topic modeling: It groups similar feedback into categories, such as product quality or customer service, helping businesses pinpoint areas for improvement.
  • Insight prioritization: AI ranks issues based on frequency and sentiment, allowing teams to prioritize the most pressing concerns.

For example, a retail chain uses Qualtrics AI to analyze customer feedback from in-store surveys. The AI identifies a recurring complaint about long checkout times and suggests staffing adjustments, leading to improved operational efficiency and customer satisfaction.


What’s next?

AI and VoC tools like Qualtrics offer incredible capabilities to transform customer experience, helping you analyze data, predict outcomes, and automate processes. But at the heart of every great customer interaction is the human touch. Qualtrics helps bridge the gap by giving your team deep insights into customer emotions and needs, empowering them to respond with empathy and build genuine connections. With predictive analytics, you can stay ahead by addressing concerns before they arise and creating experiences that feel seamless and proactive. By using Qualtrics, you’re not just making your CX strategy more efficient, you’re making it smarter, more personal, and more human.

Our partnership with Qualtrics customer experience platform empowers us to provide a comprehensive approach to CX management. Together, we help you capture valuable insights, optimize customer journeys, and measure the impact of your CX initiatives. If you want to explore how Altudo and Qualtrics can elevate your customer experience and business KPIs, schedule a 1:1, no-obligation consultation call with our CX experts today.

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