Abstract
Smartphone apps are part of daily life for many people. It is essential for app developers' success to understand how users choose which apps to install.
Before choosing which apps to install, users may consider the app description, screenshots, ratings, and reviews. When users evaluate the information cues presented by the app stores, they tend to apply shortcuts to reduce the cognitive burden. These shortcuts lead to quicker decisions but ignore some available information.
We conducted an observational lab study with semi-structured interviews of 26 participants who viewed 84 apps using the Google Play Store during app selection tasks.
We created a model based on 13 information cues and four factors that influenced users when choosing which apps to install. Using data mining approaches, we created two models using Weka and Rapidminer to discover the frequent itemsets or patterns among the dataset using Apriori and FP-Growth algorithms.
Our findings indicate that users do not usually rely on a single cue or factor but instead consider a combination of cues and factors. We found that some cues are used as a starting point in the decision process, and the core of these cues is the app reviews. After viewing multiple app, in 8% of instances, participants concluded that the first app they viewed was ultimately the best option to download.