Customer Experience Analytics: How To Measure & Improve CX

Despite brands with superior customer experience reporting 5.7 times more revenue than their competitors, CX champions sometimes face an uphill battle. Often, that’s because it isn’t as easy to see the value or ROI of customer experience and voice of customer investments without a customer experience analytics solution and strategy.

Measuring and improving CX starts with gathering as much customer intel as possible. This guide covers the key components of customer experience analytics, what to consider when evaluating a customer experience analytics solution, and how to use customer insights to build long-lasting, meaningful, and mutually beneficial customer relationships.

Understanding customer experience analytics

What is customer experience analytics?

Customer experience (CX) analytics involves collecting, processing, and analyzing customer data to measure and improve CX.

The overall goal of customer experience analytics is to get a better, deeper understanding of your customers – what they need, want, and value – and their experiences with your products and services. This information can be analyzed in many ways to help your business create great customer experiences. Marketing and customer-facing teams can use the insights gained to boost customer engagement, satisfaction, and loyalty. Product teams can resolve issues, improve products and services, and identify opportunities.

What data does customer analytics use?

Customer experience analytics uses data from direct and indirect feedback sources.

Direct feedback sources refer to the data and information you’ve requested directly from your customers, including:

• Net promoter score (NPS)
• Customer effort score (CES)
• Customer satisfaction (CSAT)
• Voice of customer (VOC)
• Open-text feedback from customer surveys
• Customer responses on social media

Indirect feedback is the data you collect from the interactions you have with your customers, including:

• Average handle time (AHT)
• Customer lifetime value
• Average spend
• Customer churn rate
• Customer renewal rate
• Voice and chat metadata, transcripts, and analysis
• Social listening
• Customer review monitoring

Importance of measuring customer analytics

Measuring customer experience analytics is important because it provides insight into the critical moments within the entire customer journey that, when improved or amplified, create a memorable customer experience. Not only do your customers benefit from a better, more personalized experience that meets or exceeds their expectations, but there are many business benefits, too.

Enhanced customer satisfaction

Customer experience analytics involves pulling and consolidating customer data from multiple sources, including direct and indirect feedback. By analyzing this data, you get a more well-rounded and detailed picture of what your customers want and need – and what steps your business can take to improve their satisfaction levels. You can do this for specific business functions like product, customer service, or sales and marketing, or your brand as a whole.

Driving customer loyalty and business growth

Creating and delivering more personalized customer experiences is about meeting their specific preferences. Doing this helps cultivate a deeper sense of belonging and appreciation – both of which are key drivers of customer loyalty. And, when 83% of customers say they feel more loyal to brands that respond to feedback, and 68% of consumers are willing to pay more if a brand is well-known for its customer experiences, it becomes apparent just how much impact customer experience analytics can have on revenue growth and profitability.

Keeping a competitive advantage

Using customer data to improve CX is essential for standing out in today’s ultra-competitive business market. When customers feel like their voice is heard and you put the voice of the customer (VOC) at the center of your decision-making, you’ll build long-lasting relationships with your customers, increasing the likelihood of repeat purchases, a higher customer lifetime value and more positive word-of-mouth.

Key components of CX analytics

Customer experience analytics has three key components – collecting customer feedback, data integration, and analytical techniques.

Collect customer data

There are a myriad of ways you can engage with your customers, directly and indirectly, to elicit their thoughts on what you’re doing right and wrong. The more feedback you collect, the clearer and more specific your insights will be when reviewing your customer experience analytics data.

Common ways of gathering customer feedback:

Surveys

People are much more likely to share their honest opinions when they can respond to prompts anonymously. Asking your customers to complete surveys like NPS, CSAT, or CES along various stages of the customer journey allows them to submit feedback regularly, which you can collect, analyze, and summarize using feedback analytics software.

Customer support

Customer support interactions like phone calls, support tickets, chats, and emails are another great source of feedback data. A big part of this is conversational analytics, which helps you dig into metrics like call response times, resolution times, and ticket volumes to uncover trends and issues.

Online reviews and social media

What people say through online reviews and on social media platforms can also tell you a lot about your business and the quality of your customer service. A feedback analytics tool will help you find common themes within that data, which you can use to build a strong VOC program.

The importance of data integration

There are a multitude of channels and sources where you can collect customer feedback. But collecting that data isn’t enough – it must be consolidated for analysis. And it's not just about having everything in one place (although that reduces manual intervention and improves data management). Integrating feedback data is essential for ensuring the highest quality CX insights based on a complete, accurate picture of your customer interactions.

Advanced customer experience analytical techniques

As new technologies like Generative AI and machine learning continue to evolve, so does the impact of data and analytics on customer experience – and the number of companies utilizing advanced analytical techniques.

Sentiment analysis

Explicit feedback is great, but some of the most powerful insights come from what your customers say implicitly. Sentiment analysis uses natural language processing to assess the underlying emotions, feelings, and thoughts in the feedback you receive. This type of analysis is useful for identifying areas where there is growing negative sentiment, so you can make proactive changes before minor issues become big problems.

Predictive analysis

This is the process of forecasting future behavior using data. It uses a mix of artificial intelligence (AI), machine learning, statistical models, and data analysis to find patterns and predict trends or behaviors based on historical data.

Applying predictive analysis to customer feedback can help you predict and proactively address customer issues and interactions. For example, you may want to know which customers are most likely to respond to a particular marketing campaign and improve your ROI – and that’s where predictive analytics can give you confidence in your decision-making.

Thematic analysis

As Alyona Medelyan, CEO and co-founder of Thematic, writes, when it comes to customer feedback, three things matter:

1. Accurate, specific, and actionable analysis
2. The ability to see emerging themes fast
3. Transparency around how results are determined

Thematic analysis ticks all of those boxes. It’s a qualitative data analysis method that identifies phrases or themes and organizes them into insights that are easy to validate and understand. When combined with sentiment analysis, it’s one of the most powerful ways to turn high volumes of unstructured feedback into actionable intelligence that improves CX, user experience, and profitability.

Key metrics for customer experience analytics

Customer Satisfaction Score (CSAT)

Customer Satisfaction Score (CSAT) is a pivotal metric in customer experience analytics that indicates customers' overall satisfaction. Typically, CSAT is measured by asking customers to rate their satisfaction on a scale, with higher scores indicating greater satisfaction. This metric is invaluable for businesses, offering direct insights into customer behavior and what you can do to increase customer satisfaction.

Net Promoter Score (NPS)

Net Promoter Score (NPS) measures customer loyalty by asking how likely people are to recommend your business to others on a scale from 0 to 10. In customer experience analytics, it helps gauge overall customer satisfaction, identify areas for improvement, and track customer sentiment changes over time.

Customer Effort Score (CES)

Customer Effort Score (CES) assesses how easy it is for customers to interact with your company or resolve issues. It's used in customer experience analytics to pinpoint friction points across the entire  customer journey, helping businesses streamline processes and enhance overall satisfaction.

Customer Retention Rate

Customer retention rate measures the percentage of customers a company retains over a specific period. In customer experience analytics, this metric is used to evaluate the success of initiatives aimed at improving satisfaction and reducing churn.

Customer Churn Rate

Customer churn rate indicates the percentage of customers who stop engaging or doing business with you during a specific timeframe, serving as a key indicator of customer dissatisfaction or competitive pressures.

Customer Lifetime Value (CLV)

Customer Lifetime Value (CLV) represents the total revenue a business can expect from a single customer over the entire duration of their relationship. In customer experience analysis, CLV helps companies understand the long-term value of customer relationships, guiding marketing efforts, retention strategies, and resource allocation to maximize profitability.

Customer experience analytics tools & software

What do customer experience tools do?

Customer experience analytics solutions enable businesses to interact with their customers at various stages along the customer journey. Some tools focus solely on surveys and feedback collection, while others offer broader analytics features. However, they all aim to enhance your customer experience by doing the following:

• Consolidate and organize customer data
• Capture voice of the customer through feedback collection
• Track key CX metrics and performance indicators
• Extract valuable insights from all the data you have on your customers

Choosing the right CX tool for your business

Every business is different, so when adding any software to your tech stack, it’s important to follow these best practices:

Set clear objectives

The first step is defining what you want to achieve with your customer experience analytics.

• Do you want to focus on product development and improvement?
• Are you working on establishing a voice of the customer program?
• Is digging into your contact center data and its goldmine of insights top priority?

The answers to these questions will help narrow down the tools best fit for your business. You’ll also want to consider the size of your CX team and their experience using customer experience analytics tools.

Prioritize data quality

The accuracy of your customer experience analytics will largely depend on the quality of your customer data. That’s why it's critical that once you have your data sources, you put strategies in place to maintain clean, validated data. This means removing errors, duplicates, missing values or irrelevant data that will skew your results. You must also update and refresh your data regularly to keep it current and accurate. With the right CX analytics tool, you can automate some or all of these tasks.

Regularly monitor reporting

One of the most important foundations of customer experience analytics is establishing a system for continuously tracking and analyzing key metrics.

Key customer experience metrics are vital signs of customer satisfaction, engagement, and behavior. Customer experience analytics software automates tracking these metrics and produces AI-generated reports detailing recurring issues and trends in customer interactions.

You’ll be able to use this information to proactively address the root causes of dissatisfaction or disengagement quickly while empowering your organization to improve the overall customer experience. Once you’ve made changes, assess their effectiveness and refine them based on ongoing monitoring and reporting to further improve and optimize the customer experience.

Popular CX analytics tools & software

For many organizations, the challenge isn’t so much about collecting customer feedback. It’s transforming CX data into actionable insights. CX and user experience teams are often overwhelmed with data and don’t know how to understand it, use it, or report on it effectively.

Measuring and improving CX with Thematic

Thematic’s platform can analyze large volumes of unstructured data from direct and indirect sources, including social media, support centers, and CX channels like open-ended survey responses, reviews, interviews, and NPS, and transform them into high-quality, actionable insights with accurate coding and analytics.

Thematic’s powerful AI with LLMs discovers and quantifies what matters most to your customers. The platform extracts recurring themes, performs sentiment analysis within a few hours, analyzes feedback consistently, and automatically alerts you to new themes.

You spend less time training models or manually coding data and more time using the insights to improve all components of the customer experience.

Other popular CX analytics tools commonly used for feedback analysis:

• Social media analytics. UnitQ and Sprout Social specialize in analyzing conversations on your social platforms and messaging apps.
• Support center analytics. Tools like Enterpret, SentiSum, CallMiner, and Zendesk focus on analyzing customer support data and provide insights that improve the support center experience.
• Feedback collection tools. SurveyMonkey and InMoment can be used to gather relevant data from a wide range of channels.
• Customer feedback analytics. TextIQ, Relative Insight, and XM Discover analyze qualitative data in different ways to draw out insights into what your customers want and need.

Thematic

AI-powered software to transform qualitative data into powerful insights that drive decision making.

Book free guided trial of Thematic

Strategies to improve customer experience through analytics

Get personal

A study by Epsilon found that 80% of customers are more likely to buy something from a business that offers personalized experiences. Using CX data and analytics, you can tailor experiences to your customers’ preferences, improving satisfaction and customer engagement. You can even anticipate what they need based on past interactions to ensure every experience feels thoughtfully curated.

Build better customer journeys

Consumers are more tech savvy than ever before and they expect targeted experiences. With customer experience analytic insights, you can optimize individual customer touchpoints and elevate every interaction from merely transactional to meaningful. The result is a highly personalized and engaging customer-brand experience.

Solve problems quickly

Customer experience analytics helps identify pain points so you can proactively resolve issues, improve customer satisfaction and effectively reduces customer churn.

Get better ROI from your customer experience insights

Improving customer experience and developing deeper relationships with your customers is 100x easier when you know what they want and need from you. That’s really the crux of customer experience analytics – discovering insights that enable you to personalize different touchpoints along the customer journey in a way that exceeds expectations and solves customer or product issues before they escalate. And with the right customer experience analytics tool, you can save time and reduce the manual work burden on CX and UX research and insights teams.

Uncover the insights that will transform your customer experience. See how Thematic works, or get a free guided trial on your data today.