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Customer Experience Analytics: A Complete Guide
Customer Experience Analytics: A Complete Guide
Customer Experience Analytics: A Complete Guide
Customer Experience Analytics: A Complete Guide
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May 29, 2024
May 29, 2024
May 29, 2024
May 29, 2024
Customer experience analytics: A complete guide
Customer information is key to starting your CX transformation. With generative conversation intelligence (CI), you can analyze millions of interactions in real time, leveraging valuable insights to create a customer-centric approach across all areas — from product development to sales.
Let’s review what customer experience analytics is and how generative AI enables a data-driven revolution in your CX practices.
Customer experience analytics: A complete guide
Customer information is key to starting your CX transformation. With generative conversation intelligence (CI), you can analyze millions of interactions in real time, leveraging valuable insights to create a customer-centric approach across all areas — from product development to sales.
Let’s review what customer experience analytics is and how generative AI enables a data-driven revolution in your CX practices.
Customer experience analytics: A complete guide
Customer information is key to starting your CX transformation. With generative conversation intelligence (CI), you can analyze millions of interactions in real time, leveraging valuable insights to create a customer-centric approach across all areas — from product development to sales.
Let’s review what customer experience analytics is and how generative AI enables a data-driven revolution in your CX practices.
Customer experience analytics: A complete guide
Customer information is key to starting your CX transformation. With generative conversation intelligence (CI), you can analyze millions of interactions in real time, leveraging valuable insights to create a customer-centric approach across all areas — from product development to sales.
Let’s review what customer experience analytics is and how generative AI enables a data-driven revolution in your CX practices.
What is customer experience analytics?
Customer experience analytics is the practice of collecting and analyzing data related to customer interactions with a business. It allows you to gather insights into customer behavior to improve their overall experience.
Here's a breakdown of the steps involved in CX analytics:
Collection: Typically a system gathers data from multiple customer touchpoints like phone calls, emails, reviews, and chat support interactions.
Analysis: The system evaluates structured data to identify trends and patterns, classifying them according to certain criteria (e.g., topics discussed, problem resolution).
Interpretation: Generative CI platforms extract actionable insights into customer data, helping organizations address customer issues and identify needs and pain points. This intelligence supports data-driven decisions to improve CX.
Customer experience analytics is the practice of collecting and analyzing data related to customer interactions with a business. It allows you to gather insights into customer behavior to improve their overall experience.
Here's a breakdown of the steps involved in CX analytics:
Collection: Typically a system gathers data from multiple customer touchpoints like phone calls, emails, reviews, and chat support interactions.
Analysis: The system evaluates structured data to identify trends and patterns, classifying them according to certain criteria (e.g., topics discussed, problem resolution).
Interpretation: Generative CI platforms extract actionable insights into customer data, helping organizations address customer issues and identify needs and pain points. This intelligence supports data-driven decisions to improve CX.
Customer experience analytics is the practice of collecting and analyzing data related to customer interactions with a business. It allows you to gather insights into customer behavior to improve their overall experience.
Here's a breakdown of the steps involved in CX analytics:
Collection: Typically a system gathers data from multiple customer touchpoints like phone calls, emails, reviews, and chat support interactions.
Analysis: The system evaluates structured data to identify trends and patterns, classifying them according to certain criteria (e.g., topics discussed, problem resolution).
Interpretation: Generative CI platforms extract actionable insights into customer data, helping organizations address customer issues and identify needs and pain points. This intelligence supports data-driven decisions to improve CX.
Customer experience analytics is the practice of collecting and analyzing data related to customer interactions with a business. It allows you to gather insights into customer behavior to improve their overall experience.
Here's a breakdown of the steps involved in CX analytics:
Collection: Typically a system gathers data from multiple customer touchpoints like phone calls, emails, reviews, and chat support interactions.
Analysis: The system evaluates structured data to identify trends and patterns, classifying them according to certain criteria (e.g., topics discussed, problem resolution).
Interpretation: Generative CI platforms extract actionable insights into customer data, helping organizations address customer issues and identify needs and pain points. This intelligence supports data-driven decisions to improve CX.
Why is CX analytics important?
When customer experience and analytics come together, you gain a holistic understanding of the interactions with your company. It improves CX by:
Increasing customer engagement: Engaging experiences reduce customer churn — according to a PwC report, one in three customers walk away from a brand they love after one bad experience. Analytics offer a better view of what makes customers interact with your brand, leaving better reviews and showing more interest in your products.
Boosting sales performance: McKinsey says there’s a strong correlation between high CX ratings and revenue growth. Companies that increased satisfaction scores by at least 20% delivered cross-sell rates by 15% to 25%. With CX analytics, you create offers tailored to customer preferences, increasing conversions and driving higher sales performance.
Improving visibility on agent performance: Analytics platforms also evaluate agent performance in customer interactions. They empower leaders to identify skill gaps, deliver targeted coaching, and develop training programs to support goal achievement.
When customer experience and analytics come together, you gain a holistic understanding of the interactions with your company. It improves CX by:
Increasing customer engagement: Engaging experiences reduce customer churn — according to a PwC report, one in three customers walk away from a brand they love after one bad experience. Analytics offer a better view of what makes customers interact with your brand, leaving better reviews and showing more interest in your products.
Boosting sales performance: McKinsey says there’s a strong correlation between high CX ratings and revenue growth. Companies that increased satisfaction scores by at least 20% delivered cross-sell rates by 15% to 25%. With CX analytics, you create offers tailored to customer preferences, increasing conversions and driving higher sales performance.
Improving visibility on agent performance: Analytics platforms also evaluate agent performance in customer interactions. They empower leaders to identify skill gaps, deliver targeted coaching, and develop training programs to support goal achievement.
When customer experience and analytics come together, you gain a holistic understanding of the interactions with your company. It improves CX by:
Increasing customer engagement: Engaging experiences reduce customer churn — according to a PwC report, one in three customers walk away from a brand they love after one bad experience. Analytics offer a better view of what makes customers interact with your brand, leaving better reviews and showing more interest in your products.
Boosting sales performance: McKinsey says there’s a strong correlation between high CX ratings and revenue growth. Companies that increased satisfaction scores by at least 20% delivered cross-sell rates by 15% to 25%. With CX analytics, you create offers tailored to customer preferences, increasing conversions and driving higher sales performance.
Improving visibility on agent performance: Analytics platforms also evaluate agent performance in customer interactions. They empower leaders to identify skill gaps, deliver targeted coaching, and develop training programs to support goal achievement.
When customer experience and analytics come together, you gain a holistic understanding of the interactions with your company. It improves CX by:
Increasing customer engagement: Engaging experiences reduce customer churn — according to a PwC report, one in three customers walk away from a brand they love after one bad experience. Analytics offer a better view of what makes customers interact with your brand, leaving better reviews and showing more interest in your products.
Boosting sales performance: McKinsey says there’s a strong correlation between high CX ratings and revenue growth. Companies that increased satisfaction scores by at least 20% delivered cross-sell rates by 15% to 25%. With CX analytics, you create offers tailored to customer preferences, increasing conversions and driving higher sales performance.
Improving visibility on agent performance: Analytics platforms also evaluate agent performance in customer interactions. They empower leaders to identify skill gaps, deliver targeted coaching, and develop training programs to support goal achievement.
Top 4 customer experience analytics tools to level up CX
CX analytics tools are a make-or-break differentiator for meeting high customer expectations. Here are our favorite four options for collection and analysis powered by gen AI:
1.Quality assurance (QA)
While traditional quality assurance relies on manual review of interaction samples, gen AI automates call, email, or chat evaluations, allowing for faster analysis of large datasets. Gen AI scores conversations instantly, and analytics detects issues such as low rates of first-call resolution (FCR) or script adherence.
2. Customer churn prediction
This type of analysis allows businesses to proactively address patterns that may result in customer loss. Gen AI detects churn drivers like fewer interactions with your product or sudden changes in behavior. Solutions that incorporate churn prediction like Echo AI automatically trigger offers or strategies to retain customers before they churn.
3.Customer sentiment analysis
Imagine going beyond the positive, negative, or neutral classification of a conversation. Gen AI detects sentiments like anger and frustration to uncover reasons behind a call with a 1-star rating or a product return. Customer sentiment analysis can also identify the highest satisfaction rates within chat logs to share CX best practices with your team.
4.Voice of Customer (VoC) tools
Leveraging feedback is a powerful way to learn and improve CX. Through customer analytics software, gen AI gathers VoC data from various channels (e.g., calls, chats, emails) and analyzes it. VoC tools help your customer service team prioritize and address critical issues.
Check out 7 voice of customer examples to drive CX excellence.
CX analytics tools are a make-or-break differentiator for meeting high customer expectations. Here are our favorite four options for collection and analysis powered by gen AI:
1.Quality assurance (QA)
While traditional quality assurance relies on manual review of interaction samples, gen AI automates call, email, or chat evaluations, allowing for faster analysis of large datasets. Gen AI scores conversations instantly, and analytics detects issues such as low rates of first-call resolution (FCR) or script adherence.
2. Customer churn prediction
This type of analysis allows businesses to proactively address patterns that may result in customer loss. Gen AI detects churn drivers like fewer interactions with your product or sudden changes in behavior. Solutions that incorporate churn prediction like Echo AI automatically trigger offers or strategies to retain customers before they churn.
3.Customer sentiment analysis
Imagine going beyond the positive, negative, or neutral classification of a conversation. Gen AI detects sentiments like anger and frustration to uncover reasons behind a call with a 1-star rating or a product return. Customer sentiment analysis can also identify the highest satisfaction rates within chat logs to share CX best practices with your team.
4.Voice of Customer (VoC) tools
Leveraging feedback is a powerful way to learn and improve CX. Through customer analytics software, gen AI gathers VoC data from various channels (e.g., calls, chats, emails) and analyzes it. VoC tools help your customer service team prioritize and address critical issues.
Check out 7 voice of customer examples to drive CX excellence.
CX analytics tools are a make-or-break differentiator for meeting high customer expectations. Here are our favorite four options for collection and analysis powered by gen AI:
1.Quality assurance (QA)
While traditional quality assurance relies on manual review of interaction samples, gen AI automates call, email, or chat evaluations, allowing for faster analysis of large datasets. Gen AI scores conversations instantly, and analytics detects issues such as low rates of first-call resolution (FCR) or script adherence.
2. Customer churn prediction
This type of analysis allows businesses to proactively address patterns that may result in customer loss. Gen AI detects churn drivers like fewer interactions with your product or sudden changes in behavior. Solutions that incorporate churn prediction like Echo AI automatically trigger offers or strategies to retain customers before they churn.
3.Customer sentiment analysis
Imagine going beyond the positive, negative, or neutral classification of a conversation. Gen AI detects sentiments like anger and frustration to uncover reasons behind a call with a 1-star rating or a product return. Customer sentiment analysis can also identify the highest satisfaction rates within chat logs to share CX best practices with your team.
4.Voice of Customer (VoC) tools
Leveraging feedback is a powerful way to learn and improve CX. Through customer analytics software, gen AI gathers VoC data from various channels (e.g., calls, chats, emails) and analyzes it. VoC tools help your customer service team prioritize and address critical issues.
Check out 7 voice of customer examples to drive CX excellence.
CX analytics tools are a make-or-break differentiator for meeting high customer expectations. Here are our favorite four options for collection and analysis powered by gen AI:
1.Quality assurance (QA)
While traditional quality assurance relies on manual review of interaction samples, gen AI automates call, email, or chat evaluations, allowing for faster analysis of large datasets. Gen AI scores conversations instantly, and analytics detects issues such as low rates of first-call resolution (FCR) or script adherence.
2. Customer churn prediction
This type of analysis allows businesses to proactively address patterns that may result in customer loss. Gen AI detects churn drivers like fewer interactions with your product or sudden changes in behavior. Solutions that incorporate churn prediction like Echo AI automatically trigger offers or strategies to retain customers before they churn.
3.Customer sentiment analysis
Imagine going beyond the positive, negative, or neutral classification of a conversation. Gen AI detects sentiments like anger and frustration to uncover reasons behind a call with a 1-star rating or a product return. Customer sentiment analysis can also identify the highest satisfaction rates within chat logs to share CX best practices with your team.
4.Voice of Customer (VoC) tools
Leveraging feedback is a powerful way to learn and improve CX. Through customer analytics software, gen AI gathers VoC data from various channels (e.g., calls, chats, emails) and analyzes it. VoC tools help your customer service team prioritize and address critical issues.
Check out 7 voice of customer examples to drive CX excellence.
How to use analytics to improve customer experience: 3 Steps to get started
Follow our 3-step approach and leverage data analytics to improve customer experience:
Step 1: Enable ongoing monitoring of customer metrics
The foundation of digital customer experience analytics lies in establishing a system for continuous monitoring of key customer metrics. These metrics act as vital signs of customer satisfaction, engagement, and behavior. Here are the top 5 essential indicators to consider:
CSAT score: The rate of customer satisfaction with a specific interaction
Net promoter score (NPS): The likelihood of a customer recommending your brand
Customer effort score (CES): The ease with which customers complete tasks like getting help through chat support or completing the purchase process
Customer churn rate: The percentage of customers who discontinue using your product or service over a given period
Customer lifetime value (CLV): The total revenue a customer generates over their relationship with your business
With CX analytics, you track these metrics while receiving AI-generated reports with emerging trends. For example, if negative conversations about a specific product come up, you can use filters to uncover patterns like quality complaints or stock-outs. This proactive approach enhances CX by empowering your organization to solve issues faster.
Step 2: Find the gaps in your customers' journey
The customer journey covers all the interactions a customer has with your business, from initial awareness to purchase, use, and post-sale interactions. Identifying blind spots in this journey eliminates friction, like when a customer struggles to understand how to use a product or waits a long time to reach customer service.
Here's how CX analytics detects these gaps to enhance your customer experience:
Identify key conversation topics: The most recurrent subjects of your interactions may indicate the kind of issues your customers face. Gen AI analytics enables journey mapping with keywords, filters, and search. If your customers are constantly asking for assistance with technical support or product returns, these may be signs of friction to prioritize.
Feedback analysis: Focus on identifying which issues are more critical for your customers. With dashboards and QA scorecards, you detect situations like a sudden increase in negative comments about access to your service on mobile devices. Echo AI alerts on critical trends to help you tackle these issues quickly.
Step 3: Tailor personalized experiences
Gartner reports that customers are 3.5 times more likely to advocate for companies when they deliver high-value experiences. Personalization means sales conversations that address customer pain points, product recommendations tailored to their preferences, and even customer service agents who handle issues with an empathic approach.
Offer personalized customer experiences with:
Customer segmentation: By analyzing information like demographics, purchase history, and website behavior, you segment your customer base into distinct groups with shared characteristics. It allows you to tailor marketing messages and overall experiences to the specific needs and preferences of each segment.
Targeted recommendations: With predictive analytics, Gen AI can generate highly targeted product suggestions based on a customer's past behavior to increase customer retention.
Proactive outreach: Instead of waiting for your customers to reach out to your business, identify potential dissatisfaction and offer solutions to address their concerns before they arise. This approach not only reduces the number of inquiries but also delivers a positive customer experience.
Follow our 3-step approach and leverage data analytics to improve customer experience:
Step 1: Enable ongoing monitoring of customer metrics
The foundation of digital customer experience analytics lies in establishing a system for continuous monitoring of key customer metrics. These metrics act as vital signs of customer satisfaction, engagement, and behavior. Here are the top 5 essential indicators to consider:
CSAT score: The rate of customer satisfaction with a specific interaction
Net promoter score (NPS): The likelihood of a customer recommending your brand
Customer effort score (CES): The ease with which customers complete tasks like getting help through chat support or completing the purchase process
Customer churn rate: The percentage of customers who discontinue using your product or service over a given period
Customer lifetime value (CLV): The total revenue a customer generates over their relationship with your business
With CX analytics, you track these metrics while receiving AI-generated reports with emerging trends. For example, if negative conversations about a specific product come up, you can use filters to uncover patterns like quality complaints or stock-outs. This proactive approach enhances CX by empowering your organization to solve issues faster.
Step 2: Find the gaps in your customers' journey
The customer journey covers all the interactions a customer has with your business, from initial awareness to purchase, use, and post-sale interactions. Identifying blind spots in this journey eliminates friction, like when a customer struggles to understand how to use a product or waits a long time to reach customer service.
Here's how CX analytics detects these gaps to enhance your customer experience:
Identify key conversation topics: The most recurrent subjects of your interactions may indicate the kind of issues your customers face. Gen AI analytics enables journey mapping with keywords, filters, and search. If your customers are constantly asking for assistance with technical support or product returns, these may be signs of friction to prioritize.
Feedback analysis: Focus on identifying which issues are more critical for your customers. With dashboards and QA scorecards, you detect situations like a sudden increase in negative comments about access to your service on mobile devices. Echo AI alerts on critical trends to help you tackle these issues quickly.
Step 3: Tailor personalized experiences
Gartner reports that customers are 3.5 times more likely to advocate for companies when they deliver high-value experiences. Personalization means sales conversations that address customer pain points, product recommendations tailored to their preferences, and even customer service agents who handle issues with an empathic approach.
Offer personalized customer experiences with:
Customer segmentation: By analyzing information like demographics, purchase history, and website behavior, you segment your customer base into distinct groups with shared characteristics. It allows you to tailor marketing messages and overall experiences to the specific needs and preferences of each segment.
Targeted recommendations: With predictive analytics, Gen AI can generate highly targeted product suggestions based on a customer's past behavior to increase customer retention.
Proactive outreach: Instead of waiting for your customers to reach out to your business, identify potential dissatisfaction and offer solutions to address their concerns before they arise. This approach not only reduces the number of inquiries but also delivers a positive customer experience.
Follow our 3-step approach and leverage data analytics to improve customer experience:
Step 1: Enable ongoing monitoring of customer metrics
The foundation of digital customer experience analytics lies in establishing a system for continuous monitoring of key customer metrics. These metrics act as vital signs of customer satisfaction, engagement, and behavior. Here are the top 5 essential indicators to consider:
CSAT score: The rate of customer satisfaction with a specific interaction
Net promoter score (NPS): The likelihood of a customer recommending your brand
Customer effort score (CES): The ease with which customers complete tasks like getting help through chat support or completing the purchase process
Customer churn rate: The percentage of customers who discontinue using your product or service over a given period
Customer lifetime value (CLV): The total revenue a customer generates over their relationship with your business
With CX analytics, you track these metrics while receiving AI-generated reports with emerging trends. For example, if negative conversations about a specific product come up, you can use filters to uncover patterns like quality complaints or stock-outs. This proactive approach enhances CX by empowering your organization to solve issues faster.
Step 2: Find the gaps in your customers' journey
The customer journey covers all the interactions a customer has with your business, from initial awareness to purchase, use, and post-sale interactions. Identifying blind spots in this journey eliminates friction, like when a customer struggles to understand how to use a product or waits a long time to reach customer service.
Here's how CX analytics detects these gaps to enhance your customer experience:
Identify key conversation topics: The most recurrent subjects of your interactions may indicate the kind of issues your customers face. Gen AI analytics enables journey mapping with keywords, filters, and search. If your customers are constantly asking for assistance with technical support or product returns, these may be signs of friction to prioritize.
Feedback analysis: Focus on identifying which issues are more critical for your customers. With dashboards and QA scorecards, you detect situations like a sudden increase in negative comments about access to your service on mobile devices. Echo AI alerts on critical trends to help you tackle these issues quickly.
Step 3: Tailor personalized experiences
Gartner reports that customers are 3.5 times more likely to advocate for companies when they deliver high-value experiences. Personalization means sales conversations that address customer pain points, product recommendations tailored to their preferences, and even customer service agents who handle issues with an empathic approach.
Offer personalized customer experiences with:
Customer segmentation: By analyzing information like demographics, purchase history, and website behavior, you segment your customer base into distinct groups with shared characteristics. It allows you to tailor marketing messages and overall experiences to the specific needs and preferences of each segment.
Targeted recommendations: With predictive analytics, Gen AI can generate highly targeted product suggestions based on a customer's past behavior to increase customer retention.
Proactive outreach: Instead of waiting for your customers to reach out to your business, identify potential dissatisfaction and offer solutions to address their concerns before they arise. This approach not only reduces the number of inquiries but also delivers a positive customer experience.
Follow our 3-step approach and leverage data analytics to improve customer experience:
Step 1: Enable ongoing monitoring of customer metrics
The foundation of digital customer experience analytics lies in establishing a system for continuous monitoring of key customer metrics. These metrics act as vital signs of customer satisfaction, engagement, and behavior. Here are the top 5 essential indicators to consider:
CSAT score: The rate of customer satisfaction with a specific interaction
Net promoter score (NPS): The likelihood of a customer recommending your brand
Customer effort score (CES): The ease with which customers complete tasks like getting help through chat support or completing the purchase process
Customer churn rate: The percentage of customers who discontinue using your product or service over a given period
Customer lifetime value (CLV): The total revenue a customer generates over their relationship with your business
With CX analytics, you track these metrics while receiving AI-generated reports with emerging trends. For example, if negative conversations about a specific product come up, you can use filters to uncover patterns like quality complaints or stock-outs. This proactive approach enhances CX by empowering your organization to solve issues faster.
Step 2: Find the gaps in your customers' journey
The customer journey covers all the interactions a customer has with your business, from initial awareness to purchase, use, and post-sale interactions. Identifying blind spots in this journey eliminates friction, like when a customer struggles to understand how to use a product or waits a long time to reach customer service.
Here's how CX analytics detects these gaps to enhance your customer experience:
Identify key conversation topics: The most recurrent subjects of your interactions may indicate the kind of issues your customers face. Gen AI analytics enables journey mapping with keywords, filters, and search. If your customers are constantly asking for assistance with technical support or product returns, these may be signs of friction to prioritize.
Feedback analysis: Focus on identifying which issues are more critical for your customers. With dashboards and QA scorecards, you detect situations like a sudden increase in negative comments about access to your service on mobile devices. Echo AI alerts on critical trends to help you tackle these issues quickly.
Step 3: Tailor personalized experiences
Gartner reports that customers are 3.5 times more likely to advocate for companies when they deliver high-value experiences. Personalization means sales conversations that address customer pain points, product recommendations tailored to their preferences, and even customer service agents who handle issues with an empathic approach.
Offer personalized customer experiences with:
Customer segmentation: By analyzing information like demographics, purchase history, and website behavior, you segment your customer base into distinct groups with shared characteristics. It allows you to tailor marketing messages and overall experiences to the specific needs and preferences of each segment.
Targeted recommendations: With predictive analytics, Gen AI can generate highly targeted product suggestions based on a customer's past behavior to increase customer retention.
Proactive outreach: Instead of waiting for your customers to reach out to your business, identify potential dissatisfaction and offer solutions to address their concerns before they arise. This approach not only reduces the number of inquiries but also delivers a positive customer experience.
Get the best customer analytics with Echo AI
Echo AI is a generative conversation intelligence platform that collects and analyzes conversations with human-level depth. It processes vast amounts of data, extracting customer insights to help you deliver exceptional CX.
Echo AI's customer experience analytics features include:
Interaction analytics to transform raw data into actionable insights that drive engagement and conversions
AutoQA scorecards to review 100% of interactions, keeping consistent monitoring of key customer metrics
Churn prediction to identify root causes behind customer complaints and product returns
Dashboards and reporting to detect CX emerging trends in real-time
Integration with +30 platforms to centralize data in one place
Start your CX transformation with Echo AI. Book a demo now.
Echo AI is a generative conversation intelligence platform that collects and analyzes conversations with human-level depth. It processes vast amounts of data, extracting customer insights to help you deliver exceptional CX.
Echo AI's customer experience analytics features include:
Interaction analytics to transform raw data into actionable insights that drive engagement and conversions
AutoQA scorecards to review 100% of interactions, keeping consistent monitoring of key customer metrics
Churn prediction to identify root causes behind customer complaints and product returns
Dashboards and reporting to detect CX emerging trends in real-time
Integration with +30 platforms to centralize data in one place
Start your CX transformation with Echo AI. Book a demo now.
Echo AI is a generative conversation intelligence platform that collects and analyzes conversations with human-level depth. It processes vast amounts of data, extracting customer insights to help you deliver exceptional CX.
Echo AI's customer experience analytics features include:
Interaction analytics to transform raw data into actionable insights that drive engagement and conversions
AutoQA scorecards to review 100% of interactions, keeping consistent monitoring of key customer metrics
Churn prediction to identify root causes behind customer complaints and product returns
Dashboards and reporting to detect CX emerging trends in real-time
Integration with +30 platforms to centralize data in one place
Start your CX transformation with Echo AI. Book a demo now.
Echo AI is a generative conversation intelligence platform that collects and analyzes conversations with human-level depth. It processes vast amounts of data, extracting customer insights to help you deliver exceptional CX.
Echo AI's customer experience analytics features include:
Interaction analytics to transform raw data into actionable insights that drive engagement and conversions
AutoQA scorecards to review 100% of interactions, keeping consistent monitoring of key customer metrics
Churn prediction to identify root causes behind customer complaints and product returns
Dashboards and reporting to detect CX emerging trends in real-time
Integration with +30 platforms to centralize data in one place
Start your CX transformation with Echo AI. Book a demo now.
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