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Research of the effectiveness of launching functionality in mobile applications based on big data

https://doi.org/10.46914/1562-2959-2023-1-1-325-335

Abstract

The issues of increasing the success of launching a new feature in mobile applications are quite acute, especially during the post-pandemic period, as a result of the implementation, development and improvement of technologies. This period of time has shown how much the market and consumer behavior has changed in terms of using mobile applications. This article discusses the definitions and issues of application and user engagement. The process of consumer engagement is described in detail. From the theoretical perspective, the concept of lean production, first described by Eric Rice, was studied and analyzed, and later was applied in practice at Innoforce, which is the developer of the mobile application called “Avtobys”. The survey method was chosen as the research method. A user base has been assembled for conducting interviews. Several semi-structured interviews with users were conducted to compile and test the questionnaire. The feedback received from the test group allowed us to change the wording of some questions. With the help of the company’s official resources, a call for the study was published. The development of the new feature took 3 weeks of working time. After one month a comparative analysis of the level of engagement, the number of engagement events per user and an analysis of the effectiveness of the concept was carried out. The results were obtained about the effectiveness of the lean manufacturing methodology using databases and business intelligence systems. As a final result, not only economic effect, but also an increase in engagement, events and key application metrics from the application of this concept in production was obtained. This work will help businesses to launch more successful functionalities in mobile applications with low production cost risks.

About the Authors

E. L. Khegay
University of International Business
Kazakhstan

PhD student.

Almaty



S. R. Essimzhanova
University of International Business
Kazakhstan

d.e.s., professor.

Almaty



References

1. Ob#em beznalichnyh platezhej v Kazahstane vyros v 2,6 raza v 2020 godu // Kursiv – delovye novosti Kazahstana. URL: https://kursiv.kz/news/finansy/2021-02/obem-beznalichnykh-platezhey-v-kazakhstane-vyros-v-26-raza-v-2020-godu (data obrashhenija: 26.09.2022). (In Russian).

2. Number of mobile app downloads worldwide from 2016 to 2021 // Statista. URL: https://www.statista. com/statistics/271644/worldwide-free-and-paid-mobile-app-store-downloads/ (data obrashhenija: 27.09.2022). (In English).

3. 25% of Users Abandon Apps After One Use // Localytics. URL: https://uplandsoftware.com/localytics/resources/blog/25-of-users-abandon-apps-after-one-use/ (data obrashhenija: 27.09.2022). (In English).

4. Du R.Y., Netzer O., Schweidel D.A., Mitra D. (2021) Capturing Marketing Information to Fuel Growth // Journal of Marketing. No. 85(1). P. 163–183. URL: https://doi.org/10.1177/0022242920969198. (In English).

5. Neumann N., Tucker C.E., Whitfield T. (2019) Frontiers: How Effective Is Third-Party Consumer Profiling? Evidence from Field Studies // Marketing Science. No. 38(6). P. 918–926. (In English).

6. Cechetti N.P., Bellei E.A., Biduski D., Rodriguez J.P.M., Roman M.K., De Marchi A.C.B. (2019) Developing and implementing a gamification method to improve user engagement: A case study with an m-Health application for hypertension monitoring // Telematics and Informatics. No. 41. P. 126–138. (In English).

7. Konecný J., McMahan H.B., Ramage D., Richtárik P. (2016) Federated Optimization: Distributed Machine Learning for On-Device Intelligence. URL: https://arxiv.org/abs/1610.02527. (In English).

8. Yudan Liu, Kaikai Ge, Xu Zhang, Leyu Lin. (2019) Real-time Attention Based Look-alike Model for Recommender System. SIGKDD International Conference on Knowledge Discovery & Data Mining. No. ACM. P. 2765–2773. (In English).

9. Cui T.H., Ghose A., Halaburda H., Iyengar R., Pauwels K., Sriram S., Tucker C., Venkataraman S. (2021) Informational Challenges in Omnichannel Marketing: Remedies and Future Research // Journal of Marketing. No. 85(1), P. 103–120. URL: https://doi.org/10.1177/0022242920968810. (In English).

10. Hernandez B., Jimenez J., Martın M.J. Really moderate online shopping behaviour? P. 22. (In English).

11. Liu Z., Lu Z. (2017) Research on Influence of Shopping APP’s Characteristic on Consumer’s Impulse Buying. Mod. Econ. No. 12. P. 1484–1498. (In English).

12. Kumar V., Rajan B., Venkatesan R., Lecinski J. (2019) Understanding the Role of Artificial Intelligence in Personalized Engagement Marketing // California Management Review. No. 61(4). P. 135–155. (In English).

13. O’Brien H.L., Toms E.G. (2008) What is user engagement? A conceptual framework for defining user engagement with technology. J. Am. Soc. Inf. Sci. P. 938–955. doi:10.1002/asi.20801. (In English).

14. Meire M., Hewett K., Ballings M., Kumar V., Van den Poel D. (2019) The Role of Marketer-Generated Content in Customer Engagement Marketing // Journal of Marketing. No. 83(6). P. 21–42. URL: https://doi.org/10.1177/0022242919873903. (In English).

15. O’Brien H.L., Bassett R. (2009) Exploring engagement in the qualitative research process // American Society for Information Science and Technology Annual Meeting. Vancouver: BC. (In English).

16. Ries E. (2011) The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to CreateRadically Successful Businesses. New York: Crown Business. (In English).

17. Womack J.P., Jones D.T., Roos D. (1990) The Machine that Changed the World // Harper Perennial, New York. (In English).

18. Blank S., Dorf B. (2012) The startup owner’s manual. The Step-by-step Guide for Building a Great Company. (In English).

19. Ladd T. (2016) The limits of the lean startup method // Harvard Business Review. No. 3. P. 2–3. (In English).

20. Naselenie stran mira // Aznations. URL: https://ru.aznations.com/population/kz (data obrashhenija: 29.09.2022). (In Russian).


Review

For citations:


Khegay E.L., Essimzhanova S.R. Research of the effectiveness of launching functionality in mobile applications based on big data. Bulletin of "Turan" University. 2023;(1):325-335. (In Russ.) https://doi.org/10.46914/1562-2959-2023-1-1-325-335

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ISSN 1562-2959 (Print)
ISSN 2959-1236 (Online)