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Don't Just Monitor Behavior, Understand Why

In today's business world, data is everything. Anyone who has ever worked with data knows that it can be easy to get lost in the numbers. When trying to understand user behavior, it is important to remember that quantitative data is only part of the story. In order to get a full picture of how users are interacting with your product, you need to supplement quantitative findings with qualitative data. Qualitative data can help to give meaning and context to numbers, helping you to identify potential areas of opportunity and growth. As a result, incorporating qualitative data into your analysis can help give you the full story to improve important business metrics, such as conversion rates and customer satisfaction levels.

A common process that growth focused teams will engage in is as follows:

Step 1: An analytics team discovers a detrimental metric via quantitative data analysis (Eg. Low app engagement).

Step 2: The metric is brought to the awareness of the rest of the team.

Step 3: Together, the team brainstorms solutions and features they “think” will remedy that dwindling KPI. 

Step 4: The effects of the new features are measured to see if they positively impacted the KPI.

There is nothing inherently wrong with the above process of course, yet, companies often find themselves running costly experiments via lengthy design/dev cycles that end up yielding lackluster results in Step 4. Why is that? 

The quantitative finding in Step 1 above is very useful in identifying issues, however it often fails to give any insights as to why that issue is happening, and doesn’t give any direction towards solving it. When companies try to enhance KPIs based on nothing more than quantitative findings, the outcomes are often dull, usually due to solutions being built on conjecture and flawed assumptions, rather than real user input. 

Instead, a simple step that could be inserted into this process to help get a richer understanding of the issue is qualitative research. Qualitative research can help give insights into why KPIs are the way they are. It can also give real, unbiased direction towards features and solutions that will have a better effect on KPIs. 

Let’s explore this further by using the following example scenario of an Investment App looking to increase transactions of new users. 

Step 1: Data analysis shows that a high volume of new users are signing up for an investment app, however they are leaving the app after getting to the “Make Your First Investment” page. This page prompts users to make their initial investment. 

Step 2: In an attempt to increase investments on this page and prevent drop offs, this finding was brought to the attention of the product team to find a solution.

Step 3: The team thinks that if the investment page on the website was easier to use, it would increase investments and lower the number of new users dropping off. Everyone agreed since the website is 7 years old and doesn’t follow the best and latest UX/UI trends. 

Step 4: After months of design and development, the team released the slick, newly designed and very “User Friendly” investment page only to realize there were no significant changes to the KPIs after all (bummer). 

Now, picture the same scenario, however, this time user interviews (a qualitative research method) were conducted before the team decided to invest time and money into building a solution. The user interviews revealed that new users were leaving the page because they didn't know how much money to invest and which stocks would be best for them. It's clear now why a solution like making an “easier to use” web page wouldn’t fix this serious user pain point! Instead, the team used this new insight to create a questionnaire that asks users simple questions about their risk tolerance and investment goals. Based on these answers, they suggest which stocks would be best for each individual based on what the person needs or wants in order to make an initial purchase with confidence! Transactions went up by 50% (woo-hoo!), simply because the team took the time to listen to and be guided by their users’ needs, wants, and pain points. 

To design your best product, you need to get the complete picture. Numbers alone don't tell us everything. Through simple qualitative research such as user interviews, we can uncover ‘a-ha!’ moments that will help direct us to building win-win features that benefit both our users and our businesses.