What is customer experience analytics?
Customer experience (CX) analytics involves systematically collecting and analyzing customer data to gain insights into customer behavior toward a product or service. By understanding these behaviors, you can make informed decisions to enhance customer journeys and improve overall satisfaction.
Customer experience analytics helps you identify pain points, predict customer needs and tailor experiences to foster loyalty and customer retention. Today, relying on customer experience analytics is crucial as it enables you to stay ahead by optimizing your customer interactions based on real-time data.
The stakeholders who supervise and utilize customer experience analytics data include customer experience leaders, heads of customer service, managers and head of customer onboarding. These professionals leverage the insights to drive strategic initiatives, improve service delivery and ensure seamless customer onboarding for new customers.
Why is customer experience analytics important to businesses?
Customer experience analytics is crucial if you aim for strong customer relationships. Here’s how it helps:
Improves customer satisfaction: Customer experience analytics uses customer experience metrics like NPS, CSAT and CES to measure customer satisfaction and provide actionable insights to improve the customer experience journey.
Example: Starbucks' reward program data informs the company about customer's usage and preferences. Based on these insights, Starbucks decides which products suit its new and existing customers to create superior customer experiences.
Read More: 11 proven customer service tips to master customer satisfaction
Reduces customer churn: Customer lifetime value (CLV) is a key metric that predicts the revenue that a single customer can contribute to a business. On the other hand, customer attrition or customer churn impacts business revenue. So, taking steps to retain customers is imperative. Customer experience analytics helps identify at-risk customers, acknowledge their problems and take proactive measures to solve them.
Must Read: 7 proven ways to reduce customer churn rate
Increases customer loyalty and retention: Higher customer loyalty and retention reflect a consistent increase in revenue and provide a competitive edge to businesses. CX analytics helps identify customers likely to leave and uses sentiment analysis to identify and address their problems, improving the customer experience.
Increases revenue and profitability: Customer experience analytics tools enable leaders to devise action plans that enhance customer satisfaction, operational efficiency and loyalty. These improvements directly translate into a significant increase in revenue and profitability, providing a clear financial benefit.
Take the example of Netflix. According to Forbes, Netflix used customer experience analytics to boost its revenue from $3.2 billion in 2011 to $33.7 billion by 2023. The company leveraged predictive analytics to segment customers who might churn and took preemptive steps to avoid that. It used data to identify viewers’ habits and preferences and suggested content that resonated with them.
Provides competitive advantage: Businesses that invest in personalizing customer interactions and providing proactive customer service boast a loyal customer base. If you satisfy customers, your business enjoys a competitive advantage.
Example: Amazon is known for its exceptional customer experience, which is largely driven by customer experience analytics. The company provides personalized shopping experiences using data such as customer purchase history. It applies sentiment analytics to improve customer service and develop innovative products that cater to customer needs and market trends.
Key metrics of customer experience analytics
Customer experience analytics uses metrics to evaluate data and improve the quality of interactions between a business and its customer base. The eight key metrics are listed below:
1. Customer satisfaction score (CSAT)
CSAT is a metric used by businesses to gauge the level of satisfaction that customers have towards a product or a service.
2. Net promoter score (NPS)
Net promoter score informs you about the likelihood of your customers recommending your business to others. Typically, the customer’s score becomes the basis for classifying them as either promoters, passives or detractors. Here’s how they are categorized.
- Promoters are satisfied, happy customers who give a score of 9 or above.
- Detractors are customers who are unhappy with their experience and give a score between 0 and 6.
- Passives are satisfied but not fully engaged customers who give a score of either 7 or 8.
Must Read: How to Improve the Net Promoter Score of Your Brand
3. Customer effort score (CES)
The customer effort score showcases the time and effort a customer puts into resolving issues. You can get related data by sending customer survey questions after interactions.
Typically, you ask customers how easy or difficult it was for them to get their issues resolved and rate you on any of the following scales.
1. 1-10 scale: On a 1-10 scale, a rating above 7 means the customer easily found the solution to their problem.
2. Emoji scale: This method may ask the customer, “How easy was the checkout process?” and rate using three emojis – happy face, neutral face and sad face. The happy face emoji represents minimum effort, while the sad face represents maximum effort.
3. Likert scale: The Likert scale can be a 5- or 7-point rating scale. A statement such as, “The company made it easy for me to solve my problem,” is presented to the customer. A multiple-choice question follows, “Do you agree?” The customer can select an option from a list that ranges from strongly disagree to strongly agree.
4. Churn rate
Customer churn rate refers to the percentage of customers who have stopped using your product due to concerns such as poor customer service, product value, unmet expectations and billing issues.
5. Customer lifetime value (CLV)
Customer lifetime value is the potential revenue a business can expect from a customer over the entire duration of their relationship with the company. This underscores the importance of nurturing long-term customer relationships.
6. First contact resolution (FCR)
First contact resolution (FCR) measures the number of cases that agents resolve in their first interaction with customers.
7. Average handling time (AHT)
Average handle time (AHT) is the average time a business spends interacting with the customer, from start to finish, including hold time and follow-up actions.
8. Customer retention rate
The customer retention rate is the percentage of customers that stay with your company over a specific time.
How to implement customer experience analytics
Customer experience (CX) analytics is a multi-step process involving data collection, analysis and implementation plans that align with your business as well as customer service objectives. Here are a few steps on how to implement it:
1. Define objectives
Analyze your company’s annual performance and define a list of goals to be accomplished by using analytical inputs. Most businesses include objectives like enhancing customer satisfaction, building customer loyalty and decreasing the churn rate.
2. Establish a measurement framework
Identify the key performance indicators that align with your business goals. Common customer experience metrics include net promoter score, customer satisfaction score, customer lifetime value, churn rate and more as discussed above.
💡 Pro Tip: You can combine quantitative metrics (like NPS and CLV) with qualitative ones (like sentiment analysis and customer feedback) to get a holistic view of a customer’s experience. Score new opportunities across various customer touchpoints. Don’t forget to review and adjust your metrics based on changing business goals and market conditions.
3. Collect and integrate data
Identify data sources such as customer surveys, support tickets, customer transactions and behavioral data from websites and applications. Use a centralized platform to integrate data from various sources. This could involve using contact center CRM systems, data lakes or customer data platforms (CDPs).
💡 Pro Tip: Standardize your data formats and ensure data quality and consistency are not compromised. Before working on actual data, test and validate the data integration processes by managing workflows. It's also crucial to set up alerts to track data health in your integration pipelines. This continuous monitoring ensures that any issues are promptly addressed, maintaining data quality.
4. Use advanced analytics techniques
Several techniques can be employed to derive insights from collected data. These insights will help you map your business plans with key customer service trends. Predictive and prescriptive analytics successfully predict future trends in customer behavior and suggest actionable insights. Utilize the contact center dashboard to navigate through the data chunks, enhancing the ease of interpretation.
5. Visualize and interpret results
Modern reporting and analytics tools provide a wealth of data, making it crucial to segment and present this information in an easily digestible format. For instance, customer experience dashboards typically encompass a variety of metrics from both the customer and agent perspectives.
Customer experience metrics such as response time and resolution time illustrate the performance of your contact center agents. On the other hand, scores like CSAT, CES and NPS reflect how your customer base perceives your brand. By effectively visualizing and interpreting these results, you can gain comprehensive insights into both operational efficiency and customer sentiment, enabling you to make informed decisions to enhance the overall customer experience.
😊 Good to know
Sprinklr’s reporting and analytics software allows you to tailor your dashboards using a comprehensive widget library. You can select from over 5,000 metrics and customize elements such as colors, layouts, labels, and annotations to suit your needs.
Additionally, Sprinklr ensures data security by enabling you to set user access and permissions. You can also filter data based on user groups and properties, ensuring that the right information is accessible to the appropriate team members.
Get Started with Customizable Dashboards for Improved Customer Service Reporting Today!
5 tips to get the best out of customer experience analytics
The ultimate goal of using experience analytics is to keep customers happy. Here are a few tips on how to leverage analytical information to delight your customers:
🏹 Go beyond averages: Embrace segmentation & storytelling
Averages obscure the real story. Segment your customer data by behavior, demographics and sentiment. Analyze how different groups experience your brand. Uncover hidden insights - like frustration points for high-value customers or unexpected satisfaction triggers for a specific demographic.
Similarly, don't just report numbers. Craft data-driven narratives that resonate with stakeholders. Highlight the "why" behind the data. Let's say you figured, "Millennials on mobile devices are twice as likely to abandon a purchase due to a slow checkout process." Find out what the possible reasons are and solve the problem.
🔭 Focus on the "Whys" behind the "Whats"
Integrate customer experience analytics with operational data such as call center interactions, website heatmaps and more. Uncover the root causes of customer pain points. Did a confusing form lead to abandonment? Can long wait times be traced to understaffing?
🔍 Become a data detective
Set up proactive alerts for unusual spikes in customer churn, negative sentiment on social media or drop-offs in key customer journey stages. Don't wait for problems to become crises. Early detection allows for swift intervention and course correction.
Prioritize the metrics that matter most to your business goals, such as net promoter score for customer loyalty. Tailor alerts for actionable thresholds—a 5% dip might be a blip, but a 15% plunge requires immediate attention.
📊 Foster a data-driven culture
Break down data silos. It’s essential for your customer-facing teams, such as marketing, sales and support, to access and interpret customer experience analytics. A unified data perspective drives better customer experiences. Sales can tailor pitches based on customer needs, while support can anticipate common issues. You can also conduct data visualization workshops and train teams to translate complex data sets into clear, actionable insights.
🎯 Align CX metrics with business goals
Link customer experience metrics to KPIs like customer acquisition cost (CAC) or customer lifetime value (CLV). Demonstrate the financial impact of CX improvements—metrics with a clear ROI secure buy-in from leadership. Show how improving customer experience translates to a healthier bottom line.
Top 4 customer experience analytics tools
To implement customer experience analytics effectively, you need a robust tool that collects data from multiple sources and provides real-time analysis. Here are the top four customer experience analytics tools that can help you foster positive customer relationships:
1. Sprinklr
Sprinklr Service is a unified customer experience platform that offers real-time insights to help build strong customer relationships. Its dashboard showcases what's on point and what's amiss. Built on the unified CXM platform that offers a holistic view of how things work across channels, here is why Sprinklr stands out:
With Sprinklr's customer service dashboards, supervisors gain insight into customer sentiment and can identify potential issues and trends before they affect your company's reputation.
Sprinklr AI+ analyzes data in real-time to detect problems such as missed SLAs, generating automatic alerts for supervisors so they can address issues proactively and maintain high-quality customer service.
Sprinklr also helps you understand the reasons behind customer contacts and allows you to customize bots to handle common inquiries efficiently.
Sprinklr Service provides enhanced visibility into crucial customer service metrics such as case resolution time, response time, cases resolved with customer service automation; customers authenticated with automation and unmet SLAs.
Exclusive Study: How Sprinklr Service Can Deliver a 210% ROI
2. HubSpot
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HubSpot’s marketing reporting solution uses multi-touch revenue attribution and data from customer journeys to measure and optimize marketing investments.
Key features:
HubSpot maps each marketing effort with revenue by analyzing how leads react to marketing efforts through email marketing campaigns, social media and website landing pages.
With customer journey analytics, you can assess the impact of your marketing efforts and determine whether you have achieved the desired conversion rates.
3. Qualtrics
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Qualtrics supports data collection, analytics and actionable insights. It provides a robust set of features that support CX analytics including real-time dashboards and omnichannel feedback collection.
Key features:
Qualtrics has customizable surveys that consist of a range of questions to gather specific insights.
Text analysis uses natural language processing (NLP) to analyze open-ended feedback.
Qualtrics also supports role-based reporting. This ensures that relevant data is accessible to the right people.
4. Medallia
Medallia helps you analyze events, detect newer trends, predict customer needs and measure and prioritize action areas.
Key features:
You can get precise insights based on your roles and responsibilities, irrespective of location or language.
Uncover trends before trending by exploring real-time themes across any data set.
Athena Studio helps create analytics for unstructured data without any coding.
Why Sprinklr is your best fit
Organizations today face numerous data-centric challenges that can impede their operational efficiency. From data silos and integration issues across feedback channels to the inefficient management of real-time data processing and analysis, these obstacles can significantly affect customer experience.
Sprinklr Service offers a robust solution to these challenges. Sprinklr unifies all your feedback channels into one seamless system using omnichannel feedback collection. With AI-driven insights, Sprinklr analyzes sentiments, identifies trends and predicts customer behavior, providing you with the data you need to make informed decisions. Real-time analytics enable you to act on customer feedback instantly, ensuring you stay ahead of potential issues and continuously improve the customer journey.
Request a personalized demo today and discover how Sprinklr can transform your customer interaction and experience.
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