How to Design Amazing Apps for Survey & Research

We’ve written a lot about UI and UX design trends, techniques, tips and much more over the years. However, an aspect of design which we run into quite often which has not been covered nearly as much is designing systems that are focused on collecting data from users to aid with research. These can be survey applications in which users give answers to specific questions, or systems in which users are consuming information and reacting in a certain way. The variations are plentiful, and the importance of these applications is paramount. However, most people don’t realize that there is a different element of thinking that goes into designing such applications in order to gather the highest quantity & quality of information that will aid the ultimate goal. Let’s discuss some of the things to consider when designing apps & products for survey and research.

Direct vs. Indirect data

When we design an application for the purpose of gathering data from the user, such as a survey application, the most obvious data to gather would be the information the user is visibly volunteering through the features found in the application, i.e. answers to the questions posed to them, or filling out their profile information. While this data is of the utmost importance, there is an underlying layer of data that can be gathered which will further enhance the direct data that is being collected. This indirect data (or meta-data) could be the amount of time taken by a user to answer a specific question, or the number of attempts they may take to correctly answer a math problem posed to them. Another example of this could be a video that the users are being asked to watch. You will certainly collect data on whether a user has watched the video or not (the total views count of the video), but you may also go a level deeper and gather information based on how much of the video each user watched. So, if people are abandoning the video mid-way through, it is telling you a very important story, and that pattern will emerge thanks to the collection of this indirect data.

Design considerations

When designing an application with the purpose of gathering information from its users in order to better inform future decisions at the company or the product, it is important to keep the focus on the information and avoid distractions or extraneous variables that may taint the data integrity. For example, a survey application may ask a question and present the user with a choice of four possible answers to choose from. If the design was such that the fourth answer required the user to scroll down in order to access it, there is a high likelihood that the users will either not know this option exists, or simply not bother with it out of laziness. There could be other deterrents as well. This would be a cloud over the data gathered and put the entire study’s results at risk. When designing a survey application (Moms Talk Shots) for John Hopkins University, we had to scrutinize in great detail how we presented the questions to the users, how they would be viewed on different devices and screen sizes, and how convenient / inconvenient it was for users to access all the possible options, without being distracted by variables that were unrelated to the question at hand. These are just some of the many things to take into consideration. Put yourself in the mind-set of putting the data first.

A/B testing with direct & indirect data

One of the tried and tested exercises for gathering data, analyzing it, and taking action is A/B testing. When you are looking to quickly test a hypothesis, A/B testing has a proven track record of being one of the most valuable methods. By serving two different versions of a prototype to a random & equal sample of users, and collecting both direct & indirect data regarding their usage of the system, you will be able to quickly identify which version is more effective, and why. Information such as engagement level can be found based on the amount of time a user spends watching a video, or how many times they interacted with the different components on the screen. The data behind the scenes often ends up telling the hidden story that may otherwise go unnoticed. But in order to be able to adequately leverage this valuable information, it is important to design the system to facilitate this collection.

Presenting or using the data gathered

We’ve spoken about how to gather direct & indirect data and its importance. The final piece of the puzzle is utilizing this data by either presenting it to the relevant stakeholders or taking specific actions based on the story uncovered through the information gathered. A combination of the direct & indirect data gathered can be used to generate real-time dashboards for the more technically savvy decision makers. However, a collection of this data can be presented in an executive summary form for stakeholders such as the CIO or CEO of a company to show them a big picture overview of the trends analyzed, allowing them to make data driven decisions on pivoting the product or the company, based on real-world insight gathered from the end-users.

Conclusion

While a lot of the important ‘best practices’ of design do apply to applications with a focus towards research & data gathering, there are several nuances to keep in mind which are specifically applicable to this genre of products. They may not make or break the product, but they will definitely add value, especially when it comes to preserving the integrity of the data collected, and enhancing the insight gained from the information gathered in order to provide the stakeholders with actionable data.