Proactive qualitative research, or continuous insights, gives business teams the opportunity to deliver outputs with greater efficiency, deliver business value quicker, and get ahead of the curve to support innovation. But many companies still struggle to conduct qualitative research in a proactive manner. So the question is: why is it so difficult to transition from reactive research?
In this article, we’ll discuss how proactive qualitative research allows you to better understand your quantitative data, as well as drive product and design innovation.
The pitfalls of customer research when it’s reactive to quantitative data
Quantitative data and analytics have been used to inform development roadmaps and product strategies within companies for many years. Some would even consider it the bedrock for decision-making. At all levels of a business, all the way up to key executives, it’s easy to understand these quantitative performance metrics, tie them to ROI, and use them to define the way forward with clarity and focus.
All too often, qualitative data isn’t given the same level of importance in the process. This data, in the form of customer insights, feedback, and observations from interviews and usability tests (to name a few), are difficult to quantify and associate value with an ROI of customer empathy. This relegates qualitative research to an activity done sporadically, often in a way to fulfill the requirement that “we did some customer testing” during product development.
In a frustrating situation that’s been observed many times—with multiple customers—qualitative customer research would happen in two situations:
- At the start of a project in the discovery phase to identify user needs
- Or to gain deeper insight into quantitative data trends when it’s tough to understand why something is happening, and all other solution paths are exhausted
In other words, when qualitative research is done on an occasional cadence, oftentimes something has already gone wrong and we’re trying to fix it. We’re trying to react.
Reactionary customer research has an impact on its value
By being reactionary, there’s an impact on how we conduct research when it gets the greenlight. While there’s a meticulous approach to preparation, set-up, running sessions, analysis and report writing, leaving no stone unturned and pouring through the outputs with a fine-toothed comb, the results only deliver quick wins for the project. Then much of the additional insights will be put onto backlogs, becoming redundant over time. Not to mention, there’s a high time and effort cost, as well as associated monetary costs—making it unsustainable for the business to sanction it on a regular basis. Because of this, it’s saved for times of necessity—when the issues get out of control again.
When qualitative customer research is only done in reaction to quantitative data, several issues are created:
- Design and development is done with a heavy subjective influence from team members and key stakeholders
- The impact of changes are relatively unknown resulting in restricted optimisation
- It is difficult to test, learn, and iterate at pace
- Overall team efficiency is reduced as time and effort is wasted designing and developing solutions that have little or no impact when put live
Ultimately this results in the business missing out on revenue gains and innovation being stifled. So how can you deliver more incremental, continuous optimisation and nurture innovation? Your qualitative customer research needs to become proactive.
Why proactive qualitative research drives innovation
The key to proactive customer research is to test with customers early and often, from discovery through to definition, design, development, validation, and optimisation. If you’re testing solutions, they don’t have to be perfect—you can gather customer feedback from scribbles on the back of a napkin, lo-fi to hi-fi prototypes, or fully functioning websites and apps, all the while supporting objective decision-making throughout the process. The team’s effort is therefore focussed on delivering in shorter cycles, fitting neatly into Agile methodologies, and ensuring that design and development don’t go too far in the wrong direction—reducing waste.
It also fits neatly alongside quantitative data, where understanding the ‘why’ behind issues identified is done quickly, and in return, the quantitative data can validate changes made due to the qualitative customer research.
Let’s look at an example of proactive customer research
Take simple A/B testing. Rather than waiting over 2 weeks to get significant results in a live environment, and find out that your variant isn’t performing as expected, you could test with customers and get feedback in a matter of hours. This allows you to learn, iterate, and validate the design, giving you an improved variant with an increased likelihood to outperform the current design in a live A/B test. This will drive A/B testing optimisation gains in a shorter period of time, and therefore, delivering business value, and ultimately ROI.
There are many more use cases for continuous insights, but once in full flow, these insights working in harmony will deliver continuous, incremental improvements that can be relied upon. Knowing these foundational elements are motoring along in a positive manner, and with a robust ‘test, learn, and iterate’ approach in place, product teams will unlock resources and opportunities to innovate and drive business value, faster and more efficiently.
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