Abstract
With the increased digitization of businesses and consumers, it is now not unusual for consumer businesses to solely engage with their customers through digital channels. Many such app driven businesses adopt a freemium business model, whereby use of the entry level service is free, whilst provision of premium content and services is for a fee. With no person to person contact with their customers, these businesses must rely on consumer data analytics to guide decisions on consumer marketing to incentivize users to adopt the premium services. This business scenario provides the motivation for this research project. In our research, using machine learning classification techniques, the team identified the key customer app usage attributes which were the main predictors of future paying subscribers.
| Original language | English (US) |
|---|---|
| Title of host publication | HCI in Business, Government, and Organizations - 5th International Conference, HCIBGO 2018, Held as Part of HCI International 2018, Proceedings |
| Editors | Bo Sophia Xiao, Fiona Fui-Hoon Nah |
| Publisher | Springer Verlag |
| Pages | 396-412 |
| Number of pages | 17 |
| ISBN (Print) | 9783319917153 |
| DOIs | |
| State | Published - Jan 1 2018 |
| Event | 5th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2018 Held as Part of HCI International 2018 - Las Vegas, United States Duration: Jul 15 2018 → Jul 20 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10923 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 5th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2018 Held as Part of HCI International 2018 |
|---|---|
| Country | United States |
| City | Las Vegas |
| Period | 7/15/18 → 7/20/18 |
Fingerprint
Keywords
- Analytics
- Computing
- Data
- Machine learning
- Mobile apps, finance
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
A study of app user behaviours : Transitions from freemium to premium. / Mulligan, Christopher; Cruz, Carlito Vera; Healy, Donagh; Murphy, David; Hall, Margeret; Nelson, Quinn; Caton, Simon.
HCI in Business, Government, and Organizations - 5th International Conference, HCIBGO 2018, Held as Part of HCI International 2018, Proceedings. ed. / Bo Sophia Xiao; Fiona Fui-Hoon Nah. Springer Verlag, 2018. p. 396-412 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10923 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - A study of app user behaviours
T2 - Transitions from freemium to premium
AU - Mulligan, Christopher
AU - Cruz, Carlito Vera
AU - Healy, Donagh
AU - Murphy, David
AU - Hall, Margeret
AU - Nelson, Quinn
AU - Caton, Simon
PY - 2018/1/1
Y1 - 2018/1/1
N2 - With the increased digitization of businesses and consumers, it is now not unusual for consumer businesses to solely engage with their customers through digital channels. Many such app driven businesses adopt a freemium business model, whereby use of the entry level service is free, whilst provision of premium content and services is for a fee. With no person to person contact with their customers, these businesses must rely on consumer data analytics to guide decisions on consumer marketing to incentivize users to adopt the premium services. This business scenario provides the motivation for this research project. In our research, using machine learning classification techniques, the team identified the key customer app usage attributes which were the main predictors of future paying subscribers.
AB - With the increased digitization of businesses and consumers, it is now not unusual for consumer businesses to solely engage with their customers through digital channels. Many such app driven businesses adopt a freemium business model, whereby use of the entry level service is free, whilst provision of premium content and services is for a fee. With no person to person contact with their customers, these businesses must rely on consumer data analytics to guide decisions on consumer marketing to incentivize users to adopt the premium services. This business scenario provides the motivation for this research project. In our research, using machine learning classification techniques, the team identified the key customer app usage attributes which were the main predictors of future paying subscribers.
KW - Analytics
KW - Computing
KW - Data
KW - Machine learning
KW - Mobile apps, finance
UR - http://www.scopus.com/inward/record.url?scp=85050495912&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050495912&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-91716-0_31
DO - 10.1007/978-3-319-91716-0_31
M3 - Conference contribution
AN - SCOPUS:85050495912
SN - 9783319917153
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 396
EP - 412
BT - HCI in Business, Government, and Organizations - 5th International Conference, HCIBGO 2018, Held as Part of HCI International 2018, Proceedings
A2 - Xiao, Bo Sophia
A2 - Nah, Fiona Fui-Hoon
PB - Springer Verlag
ER -