What is Customer Experience Analytics?

Customer experience analytics enables you to collect and analyze data from every customer interaction. This includes pooling information from real-time social media interactions, calls with users in contact centers and customer feedback on surveys and websites.

Analyzing this data can help you better understand your customers’ needs, monitor their interactions with products and services and assess their changing viewpoints. You can then use the data to make informed decisions about improving customer journeys, developing new products and services and increasing engagement and loyalty.

Why is CX analytics important?

Customer expectations have shifted dramatically over the last few years, primarily driven by the need for immediacy and the rise of digital channels. As little as 20 years ago, companies’ primary customer interaction was in-store or over the phone. But now, the user experience occurs through channels like social media, WhatsApp and live web chat, and customers expect a personalized, joined-up service on every channel.

What’s more, the consequences of getting the customer experience even slightly wrong are increasingly harsh as people are increasingly willing to switch allegiances. However, the emergence of new tools and technologies, like advanced analytics and conversational AI, is transforming customer experience to help brands fully understand their customers and perfect every interaction.

Benefits of CX analytics

Customer experience analytics offers many advantages depending on your specific goals, be it reducing churn or getting better online reviews. Using the technology will help you reap benefits like:

Data-based decision-making

CX analytics unlocks smarter insights based on the customer data you collect. Analyzing this information lets you understand why customers behave a certain way, discover bugs and areas for product improvement, identify potential product feature updates and unlock revenue growth opportunities.

Deeper understanding of customer behaviors and preference

One of the most critical benefits of CX analytics is fully understanding customers and how they perceive your brand. The technology provides real-time insights into what customers want, what they think of your products and services and how they think you could improve.

Enhanced personalization of customer interactions

Customers increasingly expect personalized service across every interaction they have with brands. Users’ preferences aren’t always apparent until you analyze data across every interaction, which helps you provide customized responses whenever you interact with them.

Improved customer satisfaction and retention rates

Customer churn often occurs when users grow frustrated with not receiving the support they need or a company takes too long to solve their issues. CX analytics helps you use data to quickly address these challenges and keep users happier than ever.

Identification of pain points and opportunities for improvement

Analyzing data from CX analytics enables you to identify areas where your team is struggling or elements of your customer journey that people don’t like. CX analytics is crucial to providing insight into where things aren’t quite working or product bugs that frustrate users and, most importantly, how you can address them to improve customer satisfaction.

Optimized customer journey across all touchpoints

The rich data obtained through CX analytics allows you to tweak your customer journey and launch new product lines. These insights are crucial to delivering optimal customer service on every digital channel, which will help you boost customer satisfaction and loyalty.

More efficient resource allocation and CX strategy

With a clear picture of what’s happening across your contact center, you can manage resources and develop a robust customer experience strategy. And, with CX analytics doing the hard work of crunching the data, your agents are free to focus on what they do best—engaging with customers.

More effective agent training

Contact center agents are critical to operational success as the first point of customer interaction. The data gleaned from CX analytics enables you to provide better training to agents, which in turn helps them deliver a better user experience.

Who needs customer experience analytics?

CX analytics is crucial for any organization that wants to deliver exceptional customer experience. Simply collecting data isn’t enough; you must actively analyze that information to understand what’s happening across your contact center. You can then recognize customers’ changing needs and constantly evolve your approach accordingly.

Armed with CX analytics, you can gain real-time insight into customers’ behavior and engagement with agents. So, whether your goal is to boost customer retention or increase advocacy, CX analytics can help you reap immediate benefits.

6 customer experience KPIs to track

CX analytics is crucial to navigating customer experience transformation and shaping your customer journeys. The most important KPIs to monitor through customer experience analytics include:

Net Promoter Score (NPS)

NPS measures how likely a customer is to recommend your products and services to a friend or colleague. The metric explores how target audiences view your brand and gains their insight into what you could do better. NPS categorizes survey respondents into promoters, loyal customers who speak positively of your brand, neutral passives and detractors, who actively talk poorly of your company.

Customer Satisfaction Score (CSAT)

CSAT looks at how happy customers are at every stage of your customer journey. However, CSAT scores come with a caveat: the surveys are typically only completed by customers who are very happy or very angry about a service, which can sometimes skew the results.

Customer Effort Score (CES)

CES measures how much time and effort customers must make to resolve a problem. This insight is vital to understanding your CX performance and identifying opportunities to simplify the customer journey.

Customer Churn Rate

Onboarding new customers is more expensive than keeping current ones happy, so monitoring customer churn rate is crucial to understanding how many users leave the brand over a specific period.

Customer Lifetime Value (CLV)

CLV allows you to understand how profitable a customer or group of customers have been through their relationship with your brand. This metric can also identify your highest-value customers to help you target users who drive the most significant long-term revenue.

Customer Retention Rate (CRR)

CRR refers to how many loyal customers your brand retains over a specific period. This metric is influenced by customer churn and how many customers joined your brand during that time.

8 steps to conducting a customer experience analysis

Before implementing any new product, it’s crucial to analyze how well it will integrate with your existing technology stack and do your due diligence. Before deploying a customer experience analysis, you’ll need to:

Define objectives and KPIs

It’s vital to have clear goals and objectives for using a customer experience analysis tool. Define why you want to use CX analysis, which KPIs you want to improve and set targets you want to achieve over a specific period.

Collect multi-channel data

A CX analysis tool needs access to all the data collected across every channel on which you interact with customers. This multi-channel approach should also gather feedback from various CX surveys, such as CES, CSAT and NPS, to immediately spot any potential friction points. Allowing CX analysis to glean data from multiple channels will help fine-tune your customer journey, fully understand users’ needs and deliver their desired experiences.

Integrate and consolidate data

Simply collecting data isn’t enough to optimize your customer journey. CX data must be integrated and consolidated to fully understand what’s happening across your contact center and recognize customer preferences.

Analyze data qualitatively and quantitatively

It is also vital to pool all data within your CX analysis tool. For example, quantitative data, which is fixed, numbers-based and measurable, and qualitative data, which is subjective, interpretation-based and related to language, helps you understand different consumer behaviors. Tracking both forms of data is essential to truly understanding your customers and their needs.

Map customer journeys

Mapping the customer journey helps you identify potential friction points in users’ interaction with your brand. It provides greater visibility into inefficient processes, onboarding failures or gaps in your CX approach. When applied correctly, a data-powered journey map allows you to automate digital touchpoints to optimize every customer interaction and resolve issues immediately.

Identify patterns and trends

CX analytics excels at discovering patterns and trends in your data—so long as you have the right type of high-quality data. Using AI to analyze this data will enable you to spot common trends in customer behavior, predict their future needs and actions and develop strategies to enhance customer satisfaction and loyalty.

Develop actionable insights

Recognizing these trends is only half the job; you must also implement processes to act on the insights the CX analytics tool provides. CX analytics enables your contact center managers to track pain points, develop strategies to rectify problems and use automation to immediately activate simple tasks.

Implement and monitor changes

The more data and digital channels your CX analytics has access to, the deeper insight it can provide into the performance of your customer journey. Ensure you constantly monitor its performance to discover new customer trends, evolve your CX strategy and identify new opportunities.

Maximize your impact with Uniphore’s customer experience analytics

An AI-powered contact center analytics solution transforms unstructured data into actionable insights to help you solve your biggest CX challenges. Uniphore’s AI-powered CX analytics technology enables you to identify needs and trends across your contact center, boost customer satisfaction and loyalty and improve the performance of your agents. It can also help you recognize customer emotions, intent and sentiment in real time to optimize every conversation you have with every customer on every digital channel.

For example, our speech analytics technology, U-Analyze, identifies human speech and text and turns it into structured, actionable data. The solution enables you to analyze every minute of every customer conversation across your contact center, which would be impossible to monitor manually. Using conversational AI, you can use that data to enhance your CX strategy, automate compliance and improve agent performance to delight customers in every interaction.

Learn how Uniphore’s speech analytics software can transform your contact center into a data-driven powerhouse.