Integrating Qualitative Data into Business Strategies

Effective marketing strategy is all about balance: short-term gains and long-term planning, adhering to brand identity and adapting to change, evidence-based insights and intuition, and lastly, qualitative and quantitative data.  

Some marketers often focus exclusively on numerical data (quantitative). However, incorporating qualitative insights is necessary to recognize the nuanced human elements of consumer behavior and not miss valuable deeper understandings needed to innovate and grow. 

Let us explore data collection and how to effectively blend qualitative data and quantitative insights to create a richer narrative and make data-driven marketing decisions. 

Qualitative vs Quantitative Data 

Quantitative research data is based on numbers and can be counted, measured, and interpreted through statistical analysis. Examples of quantitative data in digital marketing include website traffic metrics, conversion rates, ad performance statistics, sales data, and more.  

Qualitative data is expressed in words (text, audio) and helps gather more profound insights into subjective aspects such as customers' emotional triggers, behaviors, and purchase motivators. Examples of qualitative data include reviews, interviews, surveys, customer support tickets, feedback, demo recordings, live chat transcripts, and sales call recordings. 

Quantitative data tells you what is happening, focusing on who/what/when, and how many/how often, while qualitative data tells you why and how. 

Like quantitative data, qualitative insights are only valuable if you can transform your findings into actionable and clear steps for improvement and growth.  

Effective Qualitative Data Analysis 

While quantitative data is typically faster to gather, analyze, and act on, qualitative data is where you find the gold. 

Analyzing qualitative data often comes with challenges—if not done strategically, it can be slower and more expensive to gather, difficult to scale, and harder to base objective marketing decisions on. However, qualitative data allows you to understand customers’ true wants and needs, generate ideas for improving services, and provide actionable insights that may not necessarily be found in numerical data. 

Methodologies for Collecting Qualitative Data 

A common misconception is that collecting and analyzing qualitative data is inherently slow and costly. Blending the traditional methodologies for data collection with innovative techniques helps overcome this challenge. Here are some proven methods:  

Observational Group Interviews 

Instead of traditional focus groups, common in market research, we recommend using an improved research method we call observational group interviews. This method still involves a small number of predefined participants but transforms the typical focus group into a more interactive workshop-style activity. It combines elements of focus groups and one-on-one interviews allowing participants to share their opinions both individually and as part of a group.   

This approach helps reduce the attitudinal bias often present in traditional focus groups and provides a more comprehensive understanding of user experiences. 

Additionally, these observational group interview sessions can be conducted online to speed up and improve the organization of qualitative data collection. 

The observational group interview is a candid conversation with target audience members about their impressions and experiences. Unlike traditional focus groups that often gather opinions in a controlled group setting, this process is dynamic and flexible. You can use observational interviews when: 

• You want to engage users in their actual environment and observe how they interact with a website/application/feature/product in real-time. 
• You need immediate feedback. 
• The matter you are researching is complex and requires detailed answers.  

One-on-One Interviews 

Individual customer interviews are one of the most effective qualitative data-gathering methods. When setting up customer interviews, we suggest including different customer types, such as:  

• Loyal fans of the product/brand. 
• Customers who switched to your product from a competitor. 
• Prospects who almost bought but did not. 
• Customers who hated the product are considering switching to something else. 

Follow these best practices for your customer interview to be effective:  

• When asking questions, your goal is to find out what the customer has already done, as past behavior is a predictor of future behavior. 
• Try to limit the number of questions to 8 to 10. 
• Ask open-ended questions to avoid “yes” and “no” answers. 
• Avoid leading questions. 
• Let them do the talking. 

Below are sample questions to conduct an insightful customer interview that you can pick and customize depending on the goals/objective of your research: 

• What is your role? 
• What are your current priorities/biggest challenges? 
• Can you describe a recent situation where you felt you needed a product/service like ours? 
• What specific problem did you try to solve when searching for our product/service? 
• How did you first hear about our product/service? 
• Can you walk me through your steps, from discovering our product/service to purchasing it? 
• What specific features or benefits were you looking for in a solution? 
• Were there any obstacles or frustrations you faced during this process? 
• Did you consider any alternatives to our product/service? If so, what were they, and what made you choose ours over the others? 
• What factors were most important to you when you made your purchasing decision? 
• How has the product/service met or not met your expectations? 
• Would you consider purchasing from us again or recommending our product/service to others? Why or why not? 
• Since purchasing, have you discovered any new uses or benefits from the product/service you had not considered before? 

Contact Forms with Text-Entry Fields  

Including forms on your website that ask open-ended questions such as “Why are you canceling your subscription?” or “How did you hear about us?” can also yield valuable insights. A/B tests different versions to identify which questions provide the most useful insights. 

Recorded Calls, Meeting Notes, and Emails 

Customer interactions from demos/sales calls, onboarding, and customer support conversations are also invaluable sources of qualitative data. They can provide insights into customer satisfaction, demographics, preferences, and more.  

It is important to ensure that mechanisms are in place to capture feedback from the methodologies you employ, such as call recording and transcribing via Otter.ai or similar tools. It’s best practice to always obtain consent before recording meetings or using third-party tools for automatic transcription and note-taking. 

If processed and analyzed effectively, customer interactions can provide enough data and standard patterns to determine ideas for converting copy, new ads, compelling emails, updated website structure, content, and more. 

Product Testing and Feedback Sessions 

Creating a safe and welcoming space for the testers to honestly share feedback and take it as an opportunity to improve the pain points of your product is crucial for successful product testing. Try to encourage all feedback—it is better to hear negative comments and address them during testing than after the feature or product launches. Remember that negative feedback can be far more valuable in qualitative research than positive. 

We recommend utilizing tools such as Userlytics for remote research and testing, particularly for website and application UX and usability testing. This tool helps compare websites and applications and gather feedback on user interactions, providing a comprehensive view of usability and user experience issues and areas of improvement. 

Hotjar is another platform we recommend for user behavior and sentiment testing. It helps capture user feedback through forms and tracks interactions through heatmaps. Use Hotjar to review user behavior in real-time and gather sentiments about different aspects of a new product, website, or application. With Hotjar you can identify trends and areas needing attention, allowing for rapid iterations and improvements. 

Usability Testing and UX Evaluation 

When preparing for usability testing and UX evaluation, the best route is to break down your approach conceptually to ensure thorough and effective data collection. We suggest the following breakdown. 

We recommend beginning with user research interviews, which can be conducted individually or in groups. These interviews aim to gather insights about the target audience, including their past experiences, common pain points, motivations, and needs. This information is crucial for creating detailed personas that represent the various segments of your audience. 

Next, focus on observational and contextual interviews. Here, the attention shifts from what users say to what they do. Observe participants as they interact with a website or app, verbalizing their thoughts and actions and look for patterns. Additionally, for some niche apps or digital tools, contextual observations can involve shadowing users in their real environments while they use the product.  

By combining these methods, you can gain comprehensive insights: user research interviews help understand personas and their backgrounds, while observational interviews reveal user behaviors in real-time. 

Customer Support Tickets Review 

Customers engaging with you through your help desk is a goldmine of data that can help inform your customer experience and support agents’ performance.  

To effectively use the data provided by customer tickets:  

• Categorize your tickets into themes or issues (e.g., product issues, service delays, billing, usability feedback). 
• Assign labels and tags to tickets based on their impact on the customer (low priority, moderate, critical, etc.).  
• Try going beyond the superficial details to analyze the root causes of the complaints. The user may be dissatisfied with a specific product feature, but deeper analysis might reveal user interface or design flaws.  

Social Media Insights 

Here are some practical ways to analyze social media for qualitative insights:  

• Define the exact problem you are trying to solve (e.g., improving product/service based on feedback, evaluating brand perception, understanding campaign performance beyond quantitative metrics, identifying and addressing customer concerns, etc.). 
• Use a social media tool (such as HubSpot) to collect data from the various social platforms. 
• Like support tickets, categorize your social media data and analyze it separately. 
• Always look for ways to translate findings into actionable steps. This might involve adjusting marketing strategies, addressing service flaws, or creating content that aligns with audience preferences and addresses their significant concerns.  
• Consider the social insights from your competitor’s platforms. Look for patterns and opportunities to offer something your competitor’s users wanted but have not received yet. 

Customer Reviews 

When analyzing your online reviews, do not forget to check what your competitors’ customers say through their own (negative and positive) reviews, also checking social media and online forums or discussions. Look for patterns and trends in the complaints and use that information to bolster your own strengths in the areas where the competitors are underperforming.

Actively communicate any improvements or changes made in response to industry feedback through social media, your website, and direct communication. 

We recommend experimenting with a combination of the methods discussed to effectively gather and analyze qualitative data. This approach can help derive deep insights that advance your business and marketing strategy. By blending these techniques, you ensure that qualitative research is efficient, impactful, and delivers the best possible outcomes. 

Combining Data for Deeper Insights 

To properly analyze and integrate qualitative data, you must aggregate your findings and identify the patterns and trends that align with what you see in the numerical (quantitative) data. Relying solely on one or another can result in a limited understanding of your situation.  

Remember to dig beyond surface data to find the “why” behind it. For instance, your analytics may show users abandoning their shopping carts on the payment method page. While this may be valuable information, it does not tell the story of “why.” Maybe the answer waits for you in the customer feedback, session recordings, or other qualitative data you have gathered. Armed with a comprehensive understanding of your data, you can strategize to implement targeted improvements. 

There are multiple options for effectively reviewing and quantifying the qualitative data you have collected to determine recurring themes, patterns, and suggestions and combining it with quantitative data for a comprehensive understanding of the business question. Thematic analysis is key! 

Categorizing and Analysis  

When it comes to analyzing qualitative data, there are several methods available, each with its own advantages and challenges. Below are some key approaches to categorizing and analyzing text data: 

• Manual coding: This method involves reading text data and manually coding it according to themes or categories. It is labor intensive but allows for a more nuanced understanding and works well with small amounts of data.  
• Using text analysis software: Tools like NVivo and ATLAS.ti support coding, query bidding, theme detection, etc. However, text analysis tools often come with complex interfaces, learning curves, and substantial costs, which might be prohibitive for individual researchers or small organizations. 
• Using Artificial Intelligence (AI) tools: If you are just starting with your qualitative analysis, you can export your insights as text and use AI tools to help identify patterns or trends. Use the below process and ChatGPT prompts for analyzing qualitative data:  
  • Clean your data of any sensitive or personal information or identifiers. 
  • Set your goals and objectives, outline the outcomes of your research. 
  • Identify the type of analysis you want to conduct - Pareto, SWOT, etc. 
  • Use the following ChatGPT prompt: “Using Pareto analysis, show the top 20% of all the themes within the data below. Summarize the outcomes of your study in a table.” 
  • Or “Using Pareto analysis, show the top 20% of all the themes about (insert topic) within the data below. Summarize the outcomes of your study in a table.” 
  • Or: “Conduct a SWOT analysis and summarize the data in the text.” 
• Refine and optimize your prompts until you get the desirable outcomes.  
• Keep in mind that when using AI for sentiment analysis, your results can sometimes lack accuracy as AI may not correctly interpret nuances, sarcasm, or context-specific meanings in text data. 

In Summary 

To summarize, this simple process for integrating qualitative and quantitative data can help you make the most of them.  

• Set your goals and define your objectives. Determine what you are hoping to achieve by combining the data.  
• Collect, organize, and clean your data. 
• Analyze quantitative data and outline the trends and patterns. 
• Analyze qualitative data and identify themes, patterns, and sentiments.  
• Integrate the data using one of these strategies. 
   
  • Use one type of data to inform the other. For instance, qualitative findings can explain anomalies found in quantitative analysis. 
  • Analyze both datasets separately but identify correlations. 
  • If resources allow, use data analysis tools to convert qualitative data into quantifiable formats (frequency, themes, etc.). 
• For insight visualization, create graphs, tables, or charts that juxtapose quantitative and qualitative results to show how they complement or contradict each other. 
• Interpret and draw insights based on the results. 
• Report the results to your team. 
• Improve your business strategy and reap the rewards! 

Important note: Unlike quantitative data, qualitative data does not require absolute stats, just enough data to make informed decisions. As marketers say, if you are not going to do something about it, it is not worth measuring. So, always make sure you translate your findings into actionable steps for improvement and growth. 

Happy analyzing!