In customer research, more than numbers will give you the full picture. You’ll also need qualitative data to make smart decisions about improving customer experiences.
Qualitative data is gathered from open-ended interview questions and surveys’ free text fields. It is analyzed to reveal meaningful patterns and themes.
1. Mixing the two
Collecting quantitative and qualitative data can be done in various ways, such as through interviews or online communities. However, it is best to mix these two types of research upfront to get a holistic view of customers’ behavior and preferences.
Quantitative data is any information that can be counted or measured and given a numerical value (i.e., how many customers attended last week’s webinar, how much revenue was generated last year by a specific product, etc.). It is easier to analyze quantitative data because it gives us numbers that are easily compared and statistically tested.
Understanding Motivations and Emotions
Qualitative data, on the other hand, is feedback that reflects how customers feel about a product or service. It can include narrative answers to open-ended questions and ratings and comments based on shared experiences. It is difficult to translate into a number and statistically test, but it does help you to understand the underlying motivations for customer behavior.
You can simultaneously employ an exploratory sequential design to collect qualitative and quantitative data to overcome this issue. This allows you to test initial hypotheses through qualitative exploration and then widen your scope with more data collection and analysis to obtain quantitative results.
Combining these two approaches can also help you better illustrate and contextualize your findings, giving you a deeper understanding of your customer insights.
2. Quantitative Data
Quantitative data consists of numbers and can be collected via various methods, including surveys, polls, and behavioral observations. It is useful to measure trends and cycles over time, such as weekly sales figures or monthly email signups.
Quantitative data can also identify the underlying cause of a particular issue, such as a high bounce rate on a website page. However, it is important to note that quantitative data alone cannot make business decisions. Qualitative data must be collected and analyzed to understand why a particular issue occurs.
Exploratory Sequential Design
Qualitative data can be collected through various methods, including interviews, focus groups, and thematic analysis software (such as MAXQDA or NVivo). These tools allow researchers to collect rich insights into customers’ feelings and experiences.
Often, qualitative data reveals unexpected patterns and can help create new hypotheses and theories. For example, suppose the number of visitors who leave a website after visiting one page is high.
In that case, qualitative data may reveal that this problem could be caused by a poor content strategy or lack of user guidance. Marketers can use this information to create and implement strategies to improve the site’s user experience.
3. Qualitative Data
While quantitative data offers a clear picture of what customers want and need, qualitative feedback allows for a deeper understanding of customer motivations and emotions.
Gaining Customer Empathy
Qualitative data can be collected through various methods, including one-to-one interviews, focus groups, and surveys. It offers a direct customer perspective with narrative answers and helps you develop customer empathy. To analyze qualitative data, you must first determine the meaning of each response.
This is done through coding, which involves assigning words or phrases to categories of meaning. There are two main coding methods: deductive and inductive. Deductive coding uses pre-defined codes, while inductive coding creates codes based on the data.
The Coding Process
Once the coded responses are organized, they can be analyzed for trends and patterns. A common method is to look for narrative blocks, which are the components of a story: plot, core message, setting, and resolution. Identifying these narrative blocks in your qualitative data will allow you to see themes that can be used to improve user experience.
While qualitative data is incredibly valuable, it can be difficult to manage and analyze. It takes time to collect, organize, and analyze and is more susceptible to observer bias (like the Hawthorne effect). Additionally, gaining team alignment when interpreting qualitative data can be hard since everyone will have their own interpretation.
4. Analysis
One of the biggest advantages of quantitative data is that it’s measurable and tangible. It’s easy to compare and track daily, weekly, or monthly. It’s also more straightforward to interpret and present your findings. Quantitative data is also easier to replicate, which can be helpful when trying out new research methods.
However, while quantitative data helps gain insights into customer behavior, it only sometimes tells the whole story. For example, knowing that your website’s bounce rate is high can be valuable, but you may need to understand the reasons behind it.
Quantitative Data Clarity
Qualitative data, on the other hand, can help you understand your customers’ motivations, emotions, and decisions. It’s often collected through open-ended questions and in-depth interviews but can also be found on social media or in product reviews.
Addressing the Challenges
However, while qualitative data can be invaluable, analyzing them and taking time can be challenging. In addition, it’s impossible to run statistical tests on qualitative information, so there’s a higher risk of bias. This can be mitigated by using a tool that automatically analyzes your feedback and finds key insights. It’s an excellent way to save time and ensure you get the most out of your feedback.
Conclusion
In the world of customer research, numbers alone cannot provide the complete picture. To truly understand your customers, it’s imperative to incorporate qualitative data alongside quantitative metrics. By merging these two approaches, you gain a holistic perspective of customer behavior and motivations, enabling you to make informed decisions that enhance customer experiences.
