CX
Apr 23, 2024
7 voice of customer examples to drive CX excellence
Businesses are taking CX to the next level by using artificial intelligence (AI) to get a deeper understanding of customer needs and actions. This is when AI-powered voice of the customer (VoC) tools come to help.
VoC is the collection of feedback about your company, products, or services. It enables your business to increase conversion, boost satisfaction rates, and build stronger relationships with customers. But how to effectively turn VoC data into actionable knowledge?
In this blog, we explore seven voice of customer examples to help you expand your VoC best practices with gen AI:
Table of Contents
1. Email
According to HubSpot, email is customers' favorite channel to engage with a business. By email, you collect data in different formats, such as:
Personalized surveys
Post-purchase forms
Feedback requests on preferences
While surveys provide valuable insights, gen AI systems help you go deeper into customer feedback. Solutions that integrate text and speech analytics scan your email conversations to detect pressing topics that require your attention.
2. Phone calls
Calls are an effective VoC method to conduct customer interviews and collect stories showcasing the positive impact of your solutions. With contact center analytics software, you make the most out of this voice of customer example. Features include:
Recording and transcription: The software automatically records your calls and converts spoken words into text, streamlining your VoC program.
Customer sentiment analysis: Gen AI provides a deep understanding of the emotional nuances of a call, including frustrations and satisfaction. By automatically scoring each interaction based on its content, leaders also gain a clear view of priorities.
3. Chat
Live chat and chatbots are rich sources of VoC data, revealing common customer pain points and questions along their journey. Leverage this example of voice of customer data to achieve:
Real-time insights: Gen AI-powered analytics software empowers leaders to leverage instant messaging channels. AI analyzes VoC data in real time, helping them make data-driven decisions and act quickly to address priorities.
Conversation rating: In-chat ratings are less intrusive and seamlessly integrated into the conversation flow. Customers are more likely to evaluate quality and satisfaction as a natural part of the interaction.
Cost-effectiveness: For your business, chat is a more economical way to handle customer inquiries. Agents can efficiently manage multiple conversations simultaneously, leading to faster resolution and reduced wait times.
4. Customer satisfaction (CSAT)
By surveying customers at multiple touchpoints throughout their journey, businesses gain helpful insights into customer satisfaction (CSAT). The goal is to understand why customers are happy (or not) with your product or service. Gen AI tools help you with:
Tracking CSAT: It allows you to monitor the score evolution over time across all interactions and channels.
Filtering: It enables you to create filters by individual agents to check who is achieving CSAT goals.
Interaction analytics: It evaluates the content of the conversation that led to specific scores, identifying keywords and examining customer sentiment.
5. Customer effort score (CES)
How easy is it for customers to get the help they need from your business? This is exactly what the customer effort score indicates. Typically, businesses collect CES data through post-interaction customer surveys.
With a quality management system, like what we have in Echo AI, you automatically track it after interactions. This metric contributes to identifying touchpoints that create friction, enabling your company to streamline processes and reduce customer effort.
6. Customer churn rate
Monitoring churn rate is a best practice for businesses to drive customer retention. In fact, a PwC global survey reveals that 54% of companies are increasing their budgets dedicated to customer loyalty and retention. With consistent tracking, you proactively address customer concerns before they churn.
Gen AI tools identify early signs of customer turnover. With AI churn prediction software, you detect emerging trends and better understand the causes of tickets and complaints.
7. Net promoter score (NPS)
Net promoter score (NPS) is a metric to understand how likely your customers are to recommend your company to friends or colleagues.
You track NPS at every interaction with gen AI solutions, just like other key metrics to monitor CX. AI allows you to find hidden topics and sentiment patterns within both the highest and lowest NPS scores. It helps you to create VoC strategies for keeping your promoters close and winning detractors back.
8. Leverage the best VoC examples with Echo AI
Understanding VoC through analytics is a top priority for customer service leaders in 2024, according to Gartner. Echo AI is a conversation intelligence platform that extracts meaningful insights from the VoC examples on our list.
With these features, you enhance your understanding of customer needs:
Customer sentiment analysis: Gain in-depth insights into customer sentiment by reviewing each conversation. Echo AI notifies you of critical trends as they emerge.
QA scorecards: Evaluate interactions across all touchpoints with automated scoring. Track key metrics and use VoC data to improve agents' performance and CX.
Insights to boost engagement: Echo AI transforms VoC insights into automated actions that drive engagement, conversions, and customer retention.
Integration with your CRM and ticket systems: Echo AI integrates with over 30 platforms to centralize all your customer data in one place
Leverage the best voice of the customer examples in your business. Book a demo now.
