Understanding Market Dynamics and Performance of Mobile Apps

This study improves the understanding of market dynamics and performance of mobile apps based on the NBD-Dirichlet model, a widely established stochastic theory of consumer behaviour. Using a standalone app for panel data collection, this study analyses 350,000ca. app accesses for 237 apps in four popular categories, over 30 days, in Brazil. It focusses on the comparison of observed and expected market size and loyalty of each app (including shared loyalty or duplication of app users). The results reveal the typical traits of stochastic behaviour. For example, the repertoire of apps consumers routinely use is predictable, and most apps share users with other apps in line with market size. However, there are some striking differences. Above all, the levels of app loyalty often vary more than the NBD-Dirichlet model predicts, given the app size. Overall, the findings significantly advance scholarly research on mobile apps, improving the understanding of the competitive structure of popular app categories. As we discuss, this intelligence can help stakeholders setting strategies for market survival and growth.

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Publication Details

Journal
Australasian Marketing Journal (AMJ)
Published
2025-04-04
DOI
https://doi.org/10.1177/14413582251329941
Citations
2
Primary Topic
Digital Platforms and Economics
Type
article
Field-Weighted Citation Impact
4.45
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article

Understanding Market Dynamics and Performance of Mobile Apps

Lara Stocchi, Rafael Barreiros Porto, Gislayne da Silva Goulart
2 citations
Australasian Marketing Journal (AMJ)
Digital Platforms and Economics
4.45
article

Understanding Market Dynamics and Performance of Mobile Apps

Lara Stocchi, Rafael Barreiros Porto, Gislayne da Silva Goulart
article en
2 citations

Abstract

This study improves the understanding of market dynamics and performance of mobile apps based on the NBD-Dirichlet model, a widely established stochastic theory of consumer behaviour. Using a standalone app for panel data collection, this study analyses 350,000ca. app accesses for 237 apps in four popular categories, over 30 days, in Brazil. It focusses on the comparison of observed and expected market size and loyalty of each app (including shared loyalty or duplication of app users). The results reveal the typical traits of stochastic behaviour. For example, the repertoire of apps consumers routinely use is predictable, and most apps share users with other apps in line with market size. However, there are some striking differences. Above all, the levels of app loyalty often vary more than the NBD-Dirichlet model predicts, given the app size. Overall, the findings significantly advance scholarly research on mobile apps, improving the understanding of the competitive structure of popular app categories. As we discuss, this intelligence can help stakeholders setting strategies for market survival and growth.

Australasian Marketing Journal (AMJ)Vol. 34(1)
Universidade Federal de Mato Grosso do Sul (BR), Universidade de Brasília (BR), University of South Australia (AU)
Openalex Percentile: Top 7%
Digital Platforms and Economics
4.45
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Understanding Market Dynamics and Performance of Mobile Apps — Lara Stocchi, Rafael Barreiros Porto, et al. · Australasian Marketing Journal (AMJ) (2025) | TGRS Research Map | TGRS