Concept for improving the search feature



This project was a group work, developed in User research for interaction design course (2018, part of the Human-Computer Interaction master program at Umeå University. We had to choose a novel technology, do a research to identify problems and develop and evaluate a concept to solve the problem. As students we all like to watch tv series and movies on different online platforms in our free time. We choose Netflix, because all team members have used it and managed to find various problems. We all agreed that there is space for improvement. Our solution is a concept for additional search filter for Netflix aimed towards people who don’t really know what they want to watch.

The problem

We started the research by interviewing friends and other students who also use Netflix. The results showed that most of the time people want to watch something but they find it difficult to choose from all of the suggestions that Netflix provides.



The idea is to answer a few quick questions and based on what’s popular on the platform now, to choose a movie from several options that correspond to the users’ mood and available time at the moment. The concept is inspired by the game Akinator - the web genius, where the user answers yes/no questions. As part of the concept we decided to give the user the option to stop at any of the questions but in this case the results will be more broad (like the current situation). In case they have absolutely no idea what to watch, we included a Random button, which will show random movies, based on what the user has already watched and liked but instead of showing hundreds of title, the search filter will show a few.

Empathy maps

For this project we developed 2 personas and empathy maps that show how the use and non-use of our concept will benefit them.



The prototype was low-fidelity, developed on Adobe XD and used only to test the concept –> LINK to the prototype


User testing

During the project we conducted online and in-person interviews with friends and family. Later on the we tested the solution with students from Umeå University.

Time frame

September - December 2018


On the project I worked with Na-Hyun Kim, Philip Björkstrand, Arvid Horned