The Instagram mobile app's augmented reality filter search engine: User Centered Design-based assessment and improvements recommendations

Abstract

The Instagram app has an area called Stories. In it, users can record videos interacting with filters that use augmented reality. In 2018, the application started to allow users to produce their own filters, making the number of these increase a lot and, thus, the existing search system in such area became inefficient. The objective of this research was to identify flaws in the search system for augmented reality filters in the Stories area, in the Instagram application, and to suggest improvements in this, based on the application of User-Centered Design tools. The following techniques were applied: Stakeholder Mapping, Focus Group, User Journey Map, Flow Diagram and Affinity Diagram, in groups of users representing the audience of the application. As a result, it was possible to understand how users relate to this area, the difficulties that prevent actions and the positive points of the interaction. In this way, it was possible to establish recommendations for improvements, such as dividing the search area by tags, keywords and users, dedicating a tab for filters most used on the platform and others, in order to facilitate the use and retrieval of information in the system.