Voice of Customer (VoC) Metrics: Methods and Tools Explained

Explore key VoC metrics, methods, and tools to capture and analyze customer feedback effectively.

10 mins read
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The voice of the customer (VoC) is the loudest. If you listen to it, you’ll cut through assumptions and get to clear product decisions.

But without a plan to capture and act on this voice, you risk getting it all wrong.

In this guide, we explore how to use VoC metrics to design better products. As a consequence, you’ll reduce churn and create experiences users love. We’ll show you how to:

  • Spot and monitor the metrics that make a difference (spoiler: it’s not all of them)
  • Turn feedback into a competitive edge with automated AI analysis

Speaking of AI analysis, our AI research assistant provides an all-in-one platform for capturing customer data. It’s an excellent helper for extracting VoC insights with accuracy and speed.

Why wrestle with messy data when Marvin can do the hard work for you? Create your free account to simplify VoC data collection and analysis starting today.

What Are Voice of Customer (VoC) Metrics, and Why Do They Matter?

VoC metrics are structured ways to capture and analyze what customers say, think, and feel.

These metrics collect feedback and measure emotions, effort, and satisfaction in actionable terms. They typically focus on three core areas:

  1. Satisfaction: Measure how happy users are with specific interactions.
    • Did you get poor ratings on a dashboard redesign? The Customer Satisfaction Score (CSAT) is your usability red flag.
  2. Loyalty: Track how many users would recommend your product.
    • Is your dashboard about to get ghosted for a competitor’s? The Net Promoter Score (NPS) is the friend who’ll tell you this.
  3. Ease of Use: Evaluate how easy users find your product to use.
    • Does onboarding feel like a slog for your users? The Customer Effort Score (CES) will flag this issue without delay.
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Benefits of Tracking VoC Metrics

Voice of customer metrics brings focus and accountability to user feedback. They connect abstract opinions to measurable actions, helping you prioritize changes for improved CX.

Here are the key benefits of tracking them:

  • Prioritize the right fixes: Instead of spinning your wheels, you find and fix what frustrates users most.
  • Link feedback to ROI: Use metrics to show how changes based on user feedback improve retention and revenue.
  • Uncover unmet needs: Read between the feedback lines and spot the gaps in your product. You’ll notice what users can’t or won’t put into words.
  • Build user trust: Customers feel heard when their input leads to changes.
  • Track success over time: Measure progress with trends in CSAT, NPS, or CES scores.
  • Justify design decisions: Use data to support your recommendations and win stakeholders’ buy-in. No more “Because users hate it.” 
  • Improve cross-team alignment: Share metrics to get everyone — devs, designers, and marketing — on the same page.
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Key Voice of Customer Metrics Every Business Should Monitor

If you’re not listening to your users, you’re leaving money on the table. 68% of customers say they’d spend more with brands that understand them. 

The good news? Guiding your product development with VoC metrics proves you genuinely understand and care about your customers.

Here’s what key metrics you should monitor to make smarter, user-driven decisions:

Net Promoter Score (NPS)

One of the most important indicators of customer loyalty and sentiment is NPS. 

This metric is your product’s popularity poll. It only asks one question: “On a scale of 0-10, how likely are you to recommend this product to others?” Responses split into three groups: 

  • Promoters (9–10): Your product’s advocates
  • Passives (7–8): Neutral users
  • Detractors (0–6): Unhappy users

Knowing exactly how users feel about your product, you can take targeted action with each group:

  • Promoters: Rally them for testimonials, referrals, and feature ideas they’ll adore.
  • Passives: Nudge them into promoter territory by smoothing out minor frustrations or offering rewards.
  • Detractors: Understand their pain points (through surveys or interviews), prioritize fixes, and follow up to rebuild trust.

Analyzing NPS data can quickly become overwhelming, especially when there are many responses. 

However, Marvin can speed up survey analysis. Our AI-powered research assistant automates NPS analysis by sorting feedback into groups. It also spots trends and helps you link scores to actionable insights quickly.

Customer Satisfaction Score (CSAT)

Unlike NPS, which measures overall loyalty and satisfaction, CSAT focuses on immediate, moment-specific feedback.

It captures satisfaction with a particular interaction, feature, or experience. It also uses a 1–5 or 1–7 scale tied to a clear question. Usually, it’s “How would you rate your satisfaction with our onboarding?

As a designer or developer, CSAT is your go-to for testing changes. Use it to track satisfaction before and after updates to see if you’ve improved the experience.

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Customer Effort Score (CES)

CES asks users how hard or easy it was to achieve a goal (find a feature, complete a task, etc.)

There are two different ways you can formulate CES questions:

  1. You ask: “How easy was it to complete your purchase today?” They rate the experience on a 5-point or 7-point scale, ranging from “Very Difficult” to “Very Easy.”
  2. You assume: “The website made it easy for me to make a purchase.” They rate your assumption on a scale from “Strongly Disagree” to “Strongly Agree.”

CES is particularly helpful for iterative design. You can use it to test navigation, checkout, or other key flow tweaks.

When answers indicate low effort, your product does well with intuitive interactions. 

However, high effort shows that users are frustrated, and you should look for ways to smoothen their experience. They might need three clicks to access a feature. Simplifying navigation to one click can dramatically lower CES.

Sentiment Analysis

As the name suggests, sentiment analysis uses text data to identify user emotions. That data may come from surveys, reviews, or chat logs. 

Do they seem excited, angry, or confused? 

You can get these insights by manually reviewing the feedback. Alternatively, you can use a tool that measures overall sentiment. It will classify user emotions as positive, negative, or neutral.

Marvin can handle the entire qualitative analysis for you. This UX research tool does thematic, emotional, and trend analysis.

Sentiment analysis, especially when AI-powered, is ideal for sifting through large volumes of data. It can help you tell if the negative sentiment rises after a redesign. Or it can indicate patterns you might otherwise miss (recurring complaints about a bug or feature).

Time to Value (TTV)

This metric is your timer between “I signed up” and “Love it, this is amazing!”. It measures how long it takes a user to experience your product’s core value. It’s great for onboarding and first-time user flows.

A short TTV means users grasp your product’s value quickly. A long TTV signals roadblocks — maybe your onboarding is too complex, or key features are buried.

For example, users need 10 steps to set up their account. Cutting that to 5 can boost your TTV.

First Contact Resolution (FCR)

This metric tracks whether a user’s issue was resolved in a single interaction. Although primarily a support metric, FCR also says a lot about your product.

Low FCR rates often mean unclear instructions, confusing UI, or hidden bugs. Your development team can use FCR data to:

  • Prioritize fixes that reduce friction
  • Spare users from all the back-and-forth with support when all they want is a solution

Churn Rate

While the churn rate isn’t actual feedback, it’s a clear signal something’s wrong. That’s because it tracks the percentage of users who stop using your product within a given time. 

Did churn spike after a feature update? Drill down to your VoC data to understand what went wrong. 

Then, you can combine churn analysis with NPS or CSAT to get a fuller picture of user behavior. Because fixing churn is all about:

  • Listening to your users to understand why they left
  • Giving them a reason to stay
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Methods to Collect VoC Data

Since people communicate in different ways, you need diverse collection methods. 

Here are the most effective ways to capture feedback at every stage of the user journey:

  1. Surveys: These are the bread and butter of VoC data collection. A product feedback survey is versatile and lets you ask questions about satisfaction, usability, or preferences.
  2. User interviews: Qualitative interviews give deep insights into user thoughts and emotions. They’re great for uncovering why users feel the way they do.
  3. Focus groups: If you want multiple perspectives in a single session, organize focus groups. They’re invaluable for brainstorming and testing concepts before development.
  4. Support tickets and chat logs: Customer support data is a goldmine of unfiltered feedback. Analyze it for recurring problems and areas for improvement.
  5. Social media listening: Users often share their opinions on social media. Monitor Twitter, LinkedIn, or other relevant platforms to catch trends and spot what’s resonating.
  6. Feedback widgets: These live inside your product, allowing users to share spontaneous, task-specific thoughts and insights.
  7. Product usage analytics: Behavioral data shows how users actually interact with your product. It’s not feedback in the traditional sense, but it can translate into VoC analytics. It shows friction and tells you where users click, stop, or drop off.
  8. Online reviews and forums: Users often leave detailed feedback on review sites or discussion forums. These sources can give you both praise and pain points.
  9. Ethnographic research: This method observes users in their environment, navigating your app during a work session. The goal is to see how they interact with your product in context.

Collecting the voice of the customer data using multiple methods will help you:

  • Get a balanced mix of quantitative and qualitative data
  • Hear what users are saying
  • Uncover what they’re not saying outright
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Best Tools for Measuring VoC Metrics

With all these research methods, you have plenty of tools to capture and analyze VoC data. 

Below, we look at some of the most valuable instruments. Each has unique strengths and is worth adding to your UX tech stack.

Pairing them will help you cover all aspects of VoC research. Here’s what you can use for data collection, analysis, visualization, and action: 

1. Marvin

HeyMarvin Homepage

Marvin is a powerful tool for capturing and analyzing the voice of the customer data. It packs advanced AI into a centralized research repository. This means it uses smart workflows to simplify research while delivering deep, actionable insights.

At its core, Marvin is a UX research platform. It can quickly process any data you upload, such as surveys, interviews, audio, video, Excel files, etc. With Marvin’s seamless integrations, even passive feedback like sales calls and Slack messages flows directly into your research.

Why Marvin Stands Out for VoC:

  • Automates NPS calculations and links scores to specific user feedback.
  • Runs sentiment analysis in surveys and interviews.
  • Tags your research and organizes it into themes, analyzing trends.
  • Centralizes all data, making it easy to search and share with stakeholders.
  • Generates visual reports to give you a quick understanding of the research.
  • Integrates with tools like Zoom, Miro, and Notion to fit into your workflow.

If you only want to add one tool to your workflow, pick this one. Create your free account today and see how easy your VoC research becomes, powered by Marvin.

2. Google Forms

Google-Forms Homepage

This popular tool for creating surveys is simple and free. Google Forms works well for collecting structured VoC data, especially satisfaction scores or feature feedback.

You also have Google Sheets, where you can easily share forms and analyze responses for basic insights. It’s a great starting point for quick feedback loops or pre-launch testing.

3. Miro

Miro Homepage

Every VoC analysis eventually needs visualization, and Miro offers you a digital whiteboard for this purpose. Use it to map user journeys, group feedback into themes, or plan focus group outcomes.

Miro’s collaborative features let teams work in real-time so everyone stays aligned on VoC insights. It also integrates seamlessly with Marvin to make your research even smoother.

4. Zendesk

Zendesk Homepage

Zendesk captures VoC data from support tickets and customer interactions. It’s a valuable tool for identifying recurring issues or uncovering usability challenges.

With built-in analytics, you can track trends in complaints or requests. This helps you understand which fixes or new features to prioritize.

Core Challenges in Using VoC Metrics

You’d think that hearing directly from users would make everything crystal clear. However, the voice of the customer metrics can leave you with more questions than answers. 

After all, capturing feedback is only the first step. The real challenge is to make sense of it. Then, you must also connect it to real-world problems and act on it before it loses value.

Here are five challenges of collecting and using VoC metrics that can trip you up:

  • Getting high-quality feedback: Low response rates or vague answers can make data less actionable. If users skip surveys or answer “It’s fine,” you’ll have gaps big enough to drive a truck through.
  • Linking metrics to actions: VoC data is only helpful if you can tie it to specific improvements. Metrics like NPS or CSAT might highlight an issue. But they’re not telling you why it’s happening, slowing down your ability to fix issues.
  • Overloading teams with data: Too much feedback, especially from multiple sources, can overwhelm teams and make some insights go unnoticed.
  • Balancing quantitative and qualitative data: Quantitative metrics like NPS are easy to track. However, you still need qualitative feedback, which is harder to analyze. Also, you may struggle to combine both without the right tools.
  • Acting on insights quickly: VoC metrics lose value if they sit unused. And turning data into actionable changes often requires buy-in from stakeholders. Talk about slowing down progress.
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Frequently Asked Questions (FAQs)

To make the most of your VoC research, here’s what else you should know:

What is the Best Time to Collect VOC Data?

The best time depends on the customer’s journey, but you should aim to do it after:

  • Key touchpoints (onboarding)
  • Feature launches
  • Support interactions

Doing it at regular intervals also helps. Quarterly surveys track changes in satisfaction, loyalty, and overall experience over time.

How Can VOC Metrics Reduce Customer Churn?

VoC metrics highlight pain points that cause users to leave. Metrics like CES and CSAT show where customers struggle or feel dissatisfied. 

By acting on this data, you can address frustrations early. Fix issues, improve workflows, or enhance support, and you’ll:

  • Build loyalty
  • Reduce the likelihood of churn

How Do You Ensure Accuracy in VOC Data Collection?

There’s a lot you can do to ensure accurate VoC collection. For starters, use a tool – Marvin – to automate analysis and reduce human error in interpreting qualitative data. 

On top of that, consider the following tips:

  • Start with clear, unbiased questions that match your goals.
  • Avoid leading questions and test surveys with small groups first.
  • Use multiple channels to collect feedback — surveys, interviews, and VoC analytics.
  • Use triangulation in qualitative research to cross-check results.

Conclusion

The numbers in your VoC metrics don’t lie. But you still have to do the math if you want to create products that users truly value.

Track the right metrics with the right tools and address common challenges if you want to:

  • Transform raw feedback into actionable insights.
  • Improve product features.
  • Build trust with your customers.
  • Offer experiences so good that users keep coming back for more.

Our research assistant, Marvin, helps you achieve all that through a centralized system and AI-driven analysis. It makes capturing and acting on VoC data seamless.

Create a free Marvin account today to unlock smarter VoC insights that drive real impact.

Indhuja Lal is a product marketing manager at HeyMarvin, a UX research repository that simplifies research & makes it easier to build products your customers love. She loves creating content that connects people with products that simplify their lives.

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