Businesses today are surrounded by data—but not all data is created equal. To learn about customer behavior, customer experience professionals need to use both qualitative data and quantitative data. When combined, these two data types provide a holistic view—quantitative data shows what is happening, while qualitative data explains why it’s happening.
In this blog, we explore the differences between qualitative and quantitative data, their individual strengths, and how combining them helps businesses make smarter decisions.
What is Qualitative Data?
Qualitative data (open ended questions) is non-numerical and descriptive data. It captures people’s feelings, opinions, motivations, and experiences in their own words.
Key characteristics of qualitative data:
- Qualitative data is expressive in nature. It reflects people’s opinions based on their experiences in their own words.
- Collected through open-ended surveys, interviews, focus groups, and observations.
- Answers “why” and “how” questions from qualitative data.
- Examples include customer feedback surveys, testimonials, and social media conversations. Quantitative scales have an option for qualitative explanation (please explain the reason for your rating).
What Is Quantitative Data?
Quantitative data (closed ended questions) is numerical and structured. It provides measurable scales that are easy to analyze statistically.
Key characteristics of quantitative data:
- Quantitative data is numerical. It has rating scales, Likert scales, emoji rating and point-based rating scale.
- It is collected via customer feedback surveys that can be shared across survey channels of WhatsApp, Facebook messenger or chatbots. These survey campaigns can be automated via Merren’s CRM platforms.
- Quantitative data focuses on numerical attributes of an experience plotted on a scale. Satisfaction metrics of Net Promoter Score, Customer Satisfaction Score and Customer Effort Score are a part of quantitative data.
- Examples include survey scores, website metrics, and usage data.
Why Use Qualitative and Quantitative Questions Together?
Using both qualitative questions and quantitative questions helps you gain a deeper understanding of your customers. Here’s why combining them can give you better insights:
1. It reveals ratings and the reasons
Quantitative data can tell you what happened. But only qualitative data can reveal why it happened. For example, if 70% of customers churn after a free trial, open-ended feedback can reveal the root cause. It can be pricing, onboarding experience, or missing features.
2. Improves decision-making with data variety
When you pair numbers with narratives, you’re equipped to make more informed, balanced decisions based on both logic and emotion. Numerical scales can give results based on formula. Open-ended questions reveal the emotional motivations of a customer.
3. Customer’s voices reach brands
Quantitative surveys are easy to analyze. Qualitative responses need sentiment analysis and a human-touch. People’s voices can enable brands to form storytelling that can be embedded in marketing campaigns.
How to Analyze Qualitative and Quantitative Data
Quantitative Data | Qualitative Data |
Apply statistical techniques like regression, correlation, and hypothesis testing | Use thematic analysis, sentiment analysis, or text coding |
Spot trends, measure satisfaction, and track performance over time | Identify common patterns, concerns, and emotional triggers |
Excellent for benchmarking and predictive modeling | Great for understanding purchasing motivations, product expectations, and experience feedback |
Good Practices To Consider to Combine Qualitative and Quantitative Data
1. Define clear research goals
Start with objectives that require both types of customer data. For example, understanding “why users drop off at checkout” needs numerical metrics and experience-oriented comments.
2. Plan your data collection for every survey
Use mixed-method surveys i.e closed-ended questions for quantitative data and open-ended for qualitative responses. Supplement with interviews, focus groups, or usability tests.
3. Use tools that support data integration
Merren enables you to analyze both qualitative and quantitative data in one place. You can get access to charts, word clouds, bar graphs using AI-driven sentiment analysis. AI based tools can segregate complex amounts of information on a larger scale.
4. Collect insights on the CX dashboard
Don’t just present both datasets side by side—analyze them together. For example, if a feature is underused (quant), check feedback to understand why (qual).
5. Visualize in charts
Combine bar graphs and pie charts with quotes and themes to deliver well-rounded reports.
Where Can You Mix Both Types of Data?
1. Customer satisfaction metrics:
Customer satisfaction metrics use Net Promoter Score (NPS), Customer Satisfaction Score (CSAT) and Customer Effort Score (CES). These metrics are paired with voice of customer feedback (qualitative) to learn about the reason behind every rating.
2. Product development:
Product upgrades need constant feedback from their user base. This can be achieved by open-ended questions that gauge the usability metrics. Developers can use this data to offer upgrades and better products and apt marketing.
3. Brand perception studies:
Brand perception will assess how people feel about the brand across their customer journey. It can be a measure of experiences right from onboarding, during transaction until post-purchase. Brand-related emotional metrics are formed over time. A mix of data can offer a bird’s eye view of customer perception.
4. Employee engagement:
Pair engagement scores with qualitative feedback to understand workplace culture and morale. Employees can rate various segments from their workplace over a rating scale. They can offer anonymous comments on their ratings. This collects both numerical and expressive insights.
5. Customer segmentation:
Use quantitative demographics and behavioral data enriched with psychographic or attitudinal insights from qualitative sources.
Conduct AI-Probing with Merren
Connect with customers using Merren’s AI-probing feature. AI-based survey creates open-ended question based on respondent’s previous answer. This helps CX leaders and marketers get genuine responses from their audience. Read more AI-probing here and learn how to create your own AI-based surveys with Merren CX.
Conclusion
Quantitative data gives you the “what.” Qualitative data gives you the “why behind a research.” To build better customer experiences or refine your brand strategy, you need both. Sign up for a free trial with Merren and streamline your customer experience protocol without any technical hassle.