Software companies work hard to learn what users want so they can deliver an excellent user experience. We research their preferences, collaborate with them to design applications, and ask for their feedback on products. Even so, do we really know enough about how people use our software?
Years ago, when I worked as a software developer, I had the opportunity to find out. As I watched from behind a one-way mirror, a highly satisfied customer sat down at the computer and used the application I’d helped create. What I saw shocked me. Our customer was interacting with the user interface in a completely different way than I’d intended. He used only about 30 percent of the features I’d designed — and he used those inefficiently.
Clearly, we didn’t have enough insight into the user experience to improve it. We had designed business processes and incorporated them into the software. Our customers changed their internal processes to meet our standards. Although we refined the user interface over time to become more friendly and intuitive, we never knew how users really worked within the software.
Experience management solutions offer a good starting point for collecting this information. These solutions allow developers to ask users how they feel about the software and collect sentiment data that helps vendors improve the user experience.
But we need to take this effort a step further. What if software could sense a person, understanding a user’s activity or intentions without having to ask those questions? Instead of predicting the types of questions we would like to ask the user and then expecting the user to respond to those prompts, we could just measure what the user is doing at various points during the software interaction.
That’s how user behavior mining works. Software tracks the interaction between the user and the application interface. After capturing that data, it analyzes or “mines” it to determine how each person uses the software. We can map the captured interactions to the business objects to understand how a business process is executed through the user interface.
The insight delivered by this analysis can help us predict which steps the user might take next. It also highlights any tasks that are difficult to perform and provides guidance on whether the user interface should be modified to create a better experience.
For example, imagine a user who creates 20 or 30 product orders per day. If the user repeatedly changes the year value for each order, user behavior mining would indicate this and trigger the system to predefine the year value for this user. The application could also learn that this user never uses certain fields and it could hide those fields on the user’s display to reduce the complexity.
User Behavior Mining, Defined
To deliver the best user experience, enterprise software must meet three needs.
First, it must recognize the user, the way my cell phone does when I tap the screen or press the home button. In real life, we trust people we know and that knowledge tells us how we want to behave or react to them.
Second, the software must understand the user. Think about your personal relationships. The longer you’ve known someone, the easier it can be to sense a behavior or a need. Sometimes a certain look alone is enough to convey what someone is thinking. Software should be able to pick up on equivalent cues based on the longevity of experience serving a particular user.
Third, applications should be able to predict what the user wants to do next. Some software uses learned insights to anticipate user needs. But most of those features are based on a cluster of users, not an individual enterprise worker
Deeper User Knowledge
User behavior mining offers tremendous potential. Current technology allows us to understand where a user clicks, but we don’t yet know the meaning of those clicks — or the overall interaction path.
We know that the way software developers design processes and the way people use them is quite different. If we can capture the behavior and then use tools to translate that data into understanding, we could intuit what a user wants to do. We can develop software that matches user needs and automatically delivers a customized user experience — absent any bias from the software vendor about the “right” way to perform a task.
Innovative technology can help. For example, what if we include biometrics in user behavior mining? Whether we use a camera, motion tracking, or a sensor measuring the user’s blood pressure, the interface between human and machine could be eye-opening. Not only could we track where a user clicks within the software, but we could also correlate those clicks with user stress levels.
This insight could help us learn whether the application actually serves the process preferred by the user or if the user has just developed a work-around to use the software. Perhaps the way the user is doing the task is actually cumbersome, but the software offers no better way to do it.
That’s not something that users often tell us. Sometimes they think it’s not an issue worth raising with the vendor. Often they just make adjustments and keep using the software. If we could use tools to sense how users feel, we could identify problems and refine processes to better them.
Although user behavior mining is still in its earliest stages, our group focused on new ventures and technologies is already working with it in productive use cases.
The Spotlight by SAP solution analyzes system usage logs in just a few minutes — with no installation or implementation required. It then calculates the amount of effort required to perform any business processes running through an SAP solution, identifying candidates for automation. By augmenting back-end data with data collected through user behavior mining, the solution will eventually provide insight into the user journey through the application.
Data Privacy Challenges Ahead
One important consideration in the application of user behavior mining is the issue of data privacy. Obviously, the data we collect is very personal and must be protected.
At SAP, we anonymize all user data immediately upon collection. The software clusters data into patterns that are not user-specific.
For our early use cases, this form of data anonymization works well. As the software becomes more able to personalize its approach to unique users, we may need to focus more on the nonanonymized data of individual users. It’s not clear yet how software vendors can strike a balance between personalized offerings and data privacy.
I do know one thing, however. We need to deal with the human ethics around this from the very beginning — not after a problem arises and we are sitting in a lawyer’s office. We must understand which behaviors act in favor of humans. It’s not enough to approach this strictly from the technology perspective.
There is no one right answer when it comes to ethics. With technology, there is always a trade-off between what you give and what you get. If I use Web mapping services, for example, I gain location intelligence and targeted advertising, but I pay with data about my behavior. We all know this. As humans, we can decide whether we are ready to share data about ourselves.
Vendors also have a choice: we can hide this reality about data privacy or we can be fully transparent.
My recommendation is that we should be completely transparent about which data we collect, what we do with the data, and how we treat the data. If we are open about what we are doing, people will trust us to make good decisions on their behalf, without misusing their data or taking advantage of it. Creating an exceptional user experience is valuable, but only if users remain in control of their data.
About Horizons by SAP
Horizons by SAP is a future-focused journal where forward thinkers in the global tech ecosystem share perspectives on how technologies and business trends will impact SAP customers in the future. The 2020 issue of Horizons by SAP focuses on Context-Aware IT, with contributors from SAP, Microsoft, Verizon, Mozilla, and more. To learn and read more, visit www.sap.com/horizons.
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Torsten Zube is vice president and head of SAP Cloud Platform Business Services at SAP SE.