Voice of Customer (VoC) analytics seeks to understand and improve customer experiences. In this blog, we will discuss components of VoC data collection, why it is important and methods to collect VoC data. We will also share some best practices with you. 

What is Voice of Customer Analytics?

Voice of Customer Analytics is a structured approach for gathering and analyzing customer feedback that comes in the form of media (voice responses). It contains both quantitative and qualitative data to understand customer sentiment, preferences, and pain points. A customer’s voice data is used for making data-driven decisions for product development, marketing, and customer service.

Why is VoC Analytics Important?

Here’s why brands need to implement voice of customer analytics:

1. Improve customer satisfaction and loyalty

Voice data analytics can pinpoint areas where customers are unhappy or delighted. This will help you build targeted improvements. Marketers can also understand customer needs and make improved marketing decisions. 

2. Develop better products and services

Product development teams rely on user generated feedback and survey responses to understand the role, the product plays in their day to day timeline. Systematic VoC data can help teams identify user preferences and requirements in the form of new upgrades.  

3. Increase sales and revenue

Satisfied customers are more likely to make repeat purchases and recommend the brand in a positive light. Better sales equals higher revenue streams. Additionally, VoC insights can help in crafting marketing strategies that resonate with the target audience. 

Key Components of Voice of Customer Analytics

The cornerstone of effective voice of customer analytics lies in its key components, each playing a critical role in extracting actionable insights.

Customer Feedback Collection

• Customer feedback surveys: Use both open-ended questions and close-ended questions to gather detailed feedback. Closed-ended (quantitative data) questions can map numerical metrics. Open-ended questions (qualitative data) can map customer sentiments in the form of expressive words and audios. 
• Interviews and focus groups: Engaging directly with customers to pick up data that surveys might miss.
• Social media monitoring: Track customer conversations and brand mentions across social media platforms. These platforms are charged with customer’s emotional metrics since people can directly interact with their favourite brands.
• Customer support interactions: Examine customer feedback from call centers and chat systems to understand common issues and sentiments.

Data Integration

Combining feedback from:

• Internal surveys: Data collected from survey channels such as WhatsApp surveys, Facebook messenger surveys and chatbot surveys.
• External sources: Third-party review sites (website reviews, Google reviews) and social media platforms.
• Operational data: Integrating feedback with purchase history, website interactions, and interactions with customer support.

Data Analysis

• Trend analysis: Identifying patterns in customer feedback over time.
• Sentiment analysis: Analyzing the emotional tone of customer comments.
• Text mining: Extracting meaningful information from text data.

Actionable Insights

• Reporting: Creating comprehensive reports that highlight key findings.
• Visualization: Using charts and graphs to make data more understandable.
• Action planning: Converting insights into measurable actions to be undertaken by different departments.

Real-world Application

• Automotive industry: A popular automotive company in India used VoC analytics to identify grievances. Customers were frequently complaining about long waiting times for car maintenance. Using this data, they streamlined their service process, reducing wait times by 30%.
• E-commerce industry: An e-commerce website used a combination of surveys and social media monitoring to capture cart abandonment rates. The insights led them to optimize their checkout process and reduced their cart abandonment rates by 25%.
• Hospitality industry: A global hotel chain implemented VoC analytics to improve their guest experience. The marketing department used a comprehensive data collection strategy to identify key areas for improvement such as room cleanliness and staff responsiveness. The changes they implemented based on these insights led to a 15% increase in guest satisfaction scores

How to Collect Voice of Customer Data?

Collecting data effectively is the first step in Voice of Customer Analytics. Here are some tried-and-tested methods:

1. Customer feedback surveys 

• Open-ended questions: Allow respondents to freely express their thoughts. Useful for gaining rich, qualitative insights.
• Close-ended questions: Offer structured response options. Beneficial for quantitative analysis across rating scales and Likert scales. Also ideal for benchmarking metrics of Net Promoter Score NPS and Customer Satisfaction Score CSAT .

2. Interviews and focus groups

• Structured interviews: Structured interviews have a predefined set of questions aimed at extracting specific information.
• Unstructured interviews: Unstructured interviews are more like candid conversations among people. This is more conversational, allowing the discussion to flow naturally.
• Focus groups: Focus groups engage a group of customers in a discussion to explore their opinions and feelings in detail.

3. Monitor social media conversations

• Listening tools: Use platforms to track mentions and conversations, sentiments, and trends on social media.
• Engagement analysis: Assess how customers interact with your social media content.

4. Customer support interactions

• Call center data: Analyze call records to identify common issues and sentiments.
• Chat logs: Review conversations from live chats to uncover pain points and areas for improvement.
• Customer Effort Score: Customer effort scores can gauge the level of effort a customer had to go through, to get their problems resolved. CES can identify high effort touchpoints. 

5. Innovative Methods

• Feedback widgets: Incorporate feedback widgets into your website or mobile apps for real-time insights.
• Net Promoter Score (NPS) systems: Send automated NPS surveys post-purchase or service interaction to gauge customer loyalty.

Steps to Implement Voice of Customer Analytics

Implementing a robust Voice of Customer Analytics strategy requires a structured approach. Here are the steps to follow:

Define objectives

Determine what you want to achieve with VoC analytics. Brands can focus on improving customer satisfaction, identifying pain points, or enhancing product features. Focus on market standard metrics of NPS, CSAT or CES numbers. 

Select data collection methods

Choose survey channels that are interactive and responsive. Use messenger surveys, chatbot surveys or in-app customer feedback collection methods. You can also collect customer experiences at various touch points especially if the customer journey is a long one.

Determine data collection frequency

Be mindful of the touchpoints and frequency of feedback collection. Most people can share their experiences while they are in the middle of a purchasing experience. However, avoid over surveying people. It can cause respondent fatigue and give you inaccurate answers. Make sure the CRM systems can capture and store the person’s previous answers.  

Gather and analyze data

Create surveys that ask the right questions to elicit meaningful responses. Ensure you cover a diverse range of customer touchpoints. Leverage speech-to-text analytics, sentiment analysis, and trend analysis tools to interpret respondent data. Look for recurring themes, common complaints, and areas of excellence

Generate reports

Create graphs and charts from Merren CX dashboard that you can share it across teams. This gives you a holistic view of your current competitive stance. This will increase transparency between stakeholders and other team members. However, automated analysis is efficient but manual inputs can offer a humanized view.

Monitor and take action

Analyze responses in real time on the Merren CX dashboard without any hassle. Keep a tab on the insights and curate data-driven decisions. Take actions on pending responses and close the feedback loop on customers. Refine your VoC process as a part of scaling a business.  

Best Practices for VoC Analytics

Implementing best practices in Voice of Customer Analytics ensures the accuracy, consistency, and effectiveness of your efforts. Here are some essential practices to follow:

Focus on goal oriented data

• Regular feedback collection: Make it a routine to gather customer feedback at regular intervals.
• Uniform methods: Use standardized data collection methods across different channels for consistency.

Focus on market standard metrics

• Net Promoter Score (NPS): Measures customer loyalty and the likelihood of them recommending your product or service.
• Customer Satisfaction Score (CSAT): Gauges short-term satisfaction with a product or service.
• Customer Effort Score (CES): Assesses how easy it is for customers to get their issues resolved.

Integrate customer data

• Combining sources: Integrate VoC data with other business data for a holistic view. For instance, combine survey results with sales data.
• Cross-functional analysis: Conduct analysis across different departments to uncover deeper insights.

Identify areas of improvement 

• Focus on insights that can bring the most significant benefits or mitigate major pain points.
• Ensure that the insights you act upon are clear, specific, and actionable.

Use AI-driven analytics

• Predictive analytics: Use machine learning and predictive models to foresee potential customer behavior.
• sentiment analysis: Employ NLP tools to analyze open-ended feedback. This will give details on pain points, frustration metrics and positive indicators.
• Word cloud segregation: word cloud segregates key words and sentiments from open-ended questions in a survey. This will give an idea of current themes, emotions and immediate requirements. 

Engage CX teams across

• Inclusive approach: Involve employees from various departments in VoC initiatives to ensure well-rounded insights and implementation.
• Feedback loop: Share VoC insights with stakeholders and close the feedback loop with customers by updating them on actions taken based on their feedback.

Conclusion

Voice of Customer Analytics is an invaluable tool for any organization looking to enhance customer experience and drive business success. Systematically collect and assess customer feedback and gain deep insights into customer preferences, pain points, and expectations. Ready to publish your first voice of customer survey? Sign up with Merren and get access to all the features for free. Get a 14 day trial today.