User-Centric Data: Transforming Decision-Making at Bontouch

Explore how Bontouch prioritizes user happiness over traditional metrics. Dive into our approach to data-driven decision-making through the eyes of Sebastian Gahlin, data analyst at Bontouch, and learn how we focus on optimizing user experiences every step of the way.

At Bontouch, a significant source of joy and satisfaction in my role comes from our focus on the user experience of the products and services that we work with. Looking outside our organization and speaking to my peers, this focus seems to diverge somewhat from the more conventional emphasis on more business-minded metrics such as revenue, engagement time, and user retention, along with all the KPIs & acronyms that get bandied around. 

Embracing User-Centricity

While these metrics are undeniably important and are certainly discussed within our teams, they are not our North Star metrics to the same extent. Instead, we often try to minimize user engagement time and maximize user happiness. This could, of course, be down to the partners we work with, but we still hold these more user-centric metrics as an important and central part of our work. 

We’re not here to waste users' time; we want them to accomplish their tasks as fast and conveniently as possible. We don’t run A/B tests to increase the time users spend in the app, just as we don’t introduce changes with the sole purpose of trying to get them to open the app as often as possible. On the contrary, we often consider increases in those metrics as big failures. While having more UX-centric metrics as our focus is a fun and rewarding way of working, it also introduces some interesting challenges.

There is a predominant focus around the industry on the more business-centered metrics. These are extensively covered in literature and articles, have their methodologies, and take up most of the discussion space in which data analysts and designers might find themselves. Much revolves around nudging the typical business KPIs in the right direction. User experience metrics are more often overlooked, or at least quite rare, in comparison. To our annoyance, finding examples of A/B tests that have been conducted to reduce app usage time is much harder.

Obviously, there are examples of UX-centric initiatives and methodologies, such as Google’s HEART framework, which we also talk about and use internally at Bontouch. Shining the light on our UX goals and how we measure these gets us a long way in finding even more value from the data we have. It’s also a great support when prioritizing between different initiatives. If we are to run a series of A/B tests, are we focusing on our most important UX metrics, and can we even expect this to impact the user experience?

Addressing Biases in Data

Qualitative data is often referred to as ‘subjective data,’ while quantitative data is called ‘objective.’ This is not strictly true, as subjectivity is rife in the world of data analysis as well. Biases and subjectivity can infiltrate data work at many levels, including the work of the data analysts themselves and the tools they use.

People analyzing data may allow their personal perspectives to skew and influence their interpretation of the information, a phenomenon commonly referred to as confirmation bias. Given enough time and data, one could probably find support to back up virtually any preconceived notion or personal opinion.

The tools and software we use to crunch numbers and visualize data also have biases built into them simply because they are, in turn, built by people with their subjective ideas and biases. All these biases mean it's really important to be as careful and balanced as possible when working with data to ensure the insights are fair and trustworthy.

While these models enable us to make predictions and forecasts about various things and their outcomes, there exists a filter, or layer, between this abstract world of data and the more tangible world that we live in. Consequently, some nuances are inevitably lost in translation at some point in the process.

Data's Role in Problem Solving

Acknowledging that data alone isn't the only or ultimate solution to each and every problem is crucial, even if it might sound counterintuitive coming from a data analyst. Employing a mix of quantitative and qualitative data gives us the best shot at identifying the most effective way of tackling problems.

Using data to inform our decision-making has taught us quite a few valuable lessons along the way, often through old-fashioned trial and error. We've realized that the initial questions we ask often barely scratch the surface of the vast iceberg of potential insights that could be uncovered and utilized in decision-making. The best answer to a seemingly straightforward question is not necessarily just an equally straightforward answer.

A recent example serves as a case in point. A team member asked about the number of users who logged in the previous weekend. While producing these figures is relatively straightforward for any analyst worth their salt, I realized I had missed an opportunity to delve deeper by posing the very simple follow-up question: “Is there a particular reason why you are asking this?”

Luckily for me, my colleague was wise enough to fill me in on the details after getting their answer, letting me know that there had been a few reports of issues logging in. A few furrowed brows and SQL queries later, we realized that one particular combination of platform and app version actually had some issues with the login flow. Great!

One of our goals as data analysts should be to foster a culture of meaningful engagement with the data within the team. How do we do this? We make sure that the documentation and dashboards are easy to find and access, that the data is as easy to read as possible, that we have regular syncs, that we demo and show things we are working on, as well as we make sure that we have communication channels where we can openly and without judgment pose the smallest or biggest questions imaginable.

There should not be, and there mustn't be, a battle between quantitative and qualitative data. There are things that we can pick up from user interviews and user testing that we can only dream about getting from the analytics data that we track. Conversely, there are things that users do that they don’t even think about themselves, which they would never be able to relay during a user interview, that we can discover from the quantitative data.

Empowering Partners Through Data

Improving how we work and understand data has already yielded significant benefits, both within our product team and positively influencing our partners. Through engaging in discussions on data highlighting the use cases and conducting A/B tests regularly, we've observed a significant increase in our partners' interest and appreciation for our more data-driven approach. Where previous discussions about the solution to a problem often started with statements along the lines of “I think that…” or “I recall that…”, we now often start from the point of “Do we have any data on this?” 

Ultimately, our partners are the decision-makers, and they are in charge. We support them by providing data and emphasizing its importance, contributing to more informed decision-making. Often, we work with business-oriented stakeholders rather than data specialists. It’s our responsibility to ensure that the data is not only accurate but also accessible and applicable. By shifting discussions from anecdotal evidence to data-based claims, we foster a deeper understanding of the challenges faced by both us and our users. This approach allows for the most informed and strategic decisions possible. 

Our mission at Bontouch is fundamentally about our commitment to the users and their experiences of the services that we build. When working with data, we have found that fostering a culture of data use really goes a long way toward making the best decisions and products that we possibly can. We believe that the compounding effect of working in a data-driven manner will significantly improve every product over time.

Conclusion

At Bontouch, our commitment to user-centric metrics over conventional business KPIs underscores our dedication to enhancing user experiences. By prioritizing user happiness, reducing engagement time, and balancing qualitative and quantitative data, we've fostered a culture of meaningful data use within our teams and partners. This approach has empowered us to make more informed, strategic decisions that benefit our users and partners.

Ready to transform your user experience with a data-driven approach? Contact us today at curious@bontouch.com to see how we can collaborate and create meaningful impact together. Don't forget to check out our other insightful articles to stay updated with the latest industry trends and practices.