Great products don’t spring up spontaneously and magically, no matter how brilliant or innovative your team is. It takes many long hours of dedication logged by a skilled and diverse team to shape the right product. And very often, the right product is not even “the best product” or “the product that everyone loves” because it’s a compromise of solutions — one that satisfies the most users.

So, what does it take to turn a product into a “truly” great product?

We like to answer this with two words — words that carry an immense weight in the design world: process and insight.

Plan for an iterative process using insight from qualitative data

Truly great products are the result of a carefully honed process of observation, testing, feedback, and iteration. That’s the “process”. For the “insight”, it takes massive amounts of data: a blend of both quantitative and qualitative data that, when combined and analyzed, tell the team what’s going on with their product and why.

Data, you could say, illuminates everything, lighting the way toward the ultimate goal: a truly great product that serves users well for a long time.

Quantitative data gives us a snapshot of what’s happening: how many people are using the product, which design is performing better than the other, etc. But it’s the other type of data, the qualitative data, that tells the real story of how to improve your product. But qualitative data is notoriously difficult to work with.

Using qualitative data: it’s not so easy

Here’s a look at just some of the issues that researchers face when dealing with qualitative data:

  1. What questions should you ask?
  2. Should you ask open-ended questions?
  3. If you ask open-ended questions, how do you analyze the answers?
  4. Will the answers you receive contribute to the improvement of the product?
  5. How do you record responses for later analysis?
  6. What rules should be in place for how qualitative data is collected/analyzed/interpreted?

To answer these questions and more, team members must work to use their combined experience and skills. Before a single question is ever asked, before a single contextual inquiry or field study is ever initiated, before any usability testing is performed at all… the team spends many hours planning their data collection so as to get the highest quality data possible. Only when they have amassed enough of the right kind of qualitative data, and it’s consistent, repeatable and reliable, will they be able to properly analyze their findings and look for areas of opportunity for improvement.

It’s not a simple process. Every product exists within a complex ecosystem once it’s deployed. This creates interdependencies and multiple factors that will influence the way a product is received. Therefore, making product improvements that are based on a data-driven process of research takes time and energy and a talented group of researchers/testers.

Collecting qualitative data is a scientific process

First, researchers have to devise the best ways to coax the right data out of the people they talk to about the product. They use their expertise to formulate and ask the right questions, planning well in advance how to ensure high-quality data. The methods for collecting qualitative data might include:

  • Interviews. Users meet with the researcher(s) individually to have a discussion about the product.
  • Concept testing. Users give their opinion after hearing about the basic concept of the product.
  • Participatory design. Users create a model of their ideal design to communicate what matters to them.
  • Field studies. Users are observed in their natural work habitat using the product.
  • Contextual inquiries. Users provide information about the context of use.
  • Usability testing. Users are given a task to perform using the product and the results are recorded.

Even once a product has been launched, the data collection is not over with. Teams continue collecting data, seeking insight into why things are happening and how to fix problems so they can improve the product.

There’s a lot riding on this — qualitative data play a huge role in product improvement. And the outcome of this kind of research doesn’t just improve the product. It delivers business value, too.

What’s the business value of capturing qualitative data?

Qualitative research helps teams explore the behaviors of the product users and other stakeholders, allowing them to take a deep dive into their reactions to the product in its present state.

It also delivers a wide range of business benefits, besides the obvious benefit of pleasing users with a better product. Basically, qualitative research gives a glimpse into the way people think. As it turns out, when you’re doing product development, those “people” include a company’s target consumer population and/or its employees.

Insight into how both populations think is business gold. In this day and age, where the digital experience is everything, and the customer experience is king, this type of data is a valuable company resource. That’s because in every industry, companies are raising the bar on the customer experience, competing to deliver the best one possible.

For example, in any sector, give access to the marketing department and watch them create many new campaigns based on insights they extracted from qualitative data. Likewise, various business units can use the data in countless ways, including using it to create digital customer journeys to transform the customer experience.

Digital transformation is a complex, multidimensional journey but knowing more about the users is a solid foundation for building business value as you take that journey.

Qualitative data: a recap

Qualitative data is used by teams to answer questions, draw conclusions, and support a process of product improvement that is sustainable, repeatable, and effective. If you are new to user research/usability testing and UX, consider this a way of dipping your toes into the vast lake of knowledge that exists around using qualitative data the right way. If you are a seasoned pro, maybe this has been a good way to refresh your knowledge. Maybe you have been doing evaluation/research the same way for many years now and something you see here can trigger some innovation in your own practice.