Sage Journals: Discover world-class research

Abstract

Push notifications are widely recognised for their effectiveness in promoting user engagement with mobile apps. This study explores how personalised content combinations affect user engagement in a companionship-based activity-monitoring app. The field experiment was designed and executed by the pet activity-monitoring app service company itself, underscoring a practical, industry-driven approach. The dataset includes engagement data from 595 pet caregivers who engaged in this field experiment. Findings reveal that tailored push notifications yield significantly higher app engagement than generic notifications. Furthermore, personalised notifications that include both the caregiver’s and companion’s names result in greater user engagement compared to those featuring only the companion’s name. Integrating caregivers’ engagement history data into notifications also enhances engagement, although this effect was not significantly stronger than name personalisation alone. These insights underscore the value of personalised communication strategies in digital engagement, particularly within industries focused on companionships, where sustained interaction with technology supports healthy and active lifestyles.

Keywords

personalisation push notifications app engagement field experiment caregiver and companion

Get full access to this article

View all access options for this article.

References

Airship Group Inc. (2023). 2023 Mobile app push notification benchmarks. Airship Group Inc. https://www.airship.com/resources/benchmark-report/mobile-app-push-notification-benchmarks-for-2023/

Austin

P. C.

Stuart

E. A.

(2015). Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Statistics in Medicine, 34(28), 3661–3679. https://doi.org/10.1002/sim.6607

Bernritter

S. F.

Ketelaar

P. E.

Sotgiu

(2021). Behaviorally targeted location-based mobile marketing. Journal of the Academy of Marketing Science, 49(4), 677–702. https://doi.org/10.1007/s11747-021-00784-0

Bies

S. M.

Bronnenberg

B. J.

Gijsbrechts

(2021). How push messaging impacts consumer spending and reward redemption in store-loyalty programs. International Journal of Research in Marketing, 38(4), 877–899. https://doi.org/10.1016/j.ijresmar.2021.02.001

Bitler

M. P.

Gelbach

J. B.

Hoynes

H. W.

(2006). What mean impacts miss: Distributional effects of welfare reform experiments. American Economic Review, 96(4), 988–1012. https://doi.org/10.1257/aer.96.4.988

Bleier

Eisenbeiss

(2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409. https://doi.org/10.1016/j.jretai.2015.04.001

Brockman

B. K.

Taylor

V. A.

Brockman

C. M.

(2008). The price of unconditional love: Consumer decision making for high-dollar veterinary care. Journal of Business Research, 61(5), 397–405. https://doi.org/10.1016/j.jbusres.2006.09.033

Cole

S. R.

Hernán

M. A.

(2008). Constructing inverse probability weights for marginal structural models. American Journal of Epidemiology, 168(6), 656–664. https://doi.org/10.1093/aje/kwn164

Dotson

M. J.

Hyatt

E. M.

(2008). Understanding dog–human companionship. Journal of Business Research, 61(5), 457–466. https://doi.org/10.1016/j.jbusres.2007.07.019

10.

Fang

Luo

(2015). Contemporaneous and delayed sales impact of location-based mobile promotions. Information Systems Research, 26(3), 552–564. https://doi.org/10.1287/isre.2015.0586

11.

Giorcelli

(2019). The long-term effects of management and technology transfers. American Economic Review, 109(1), 121–152. https://doi.org/10.1257/aer.20170619

12.

Hayes

J. L.

Brinson

N. H.

Bott

G. J.

Moeller

C. M.

(2021). The influence of consumer–brand relationship on the personalized advertising privacy calculus in social media. Journal of Interactive Marketing, 55(1), 16–30. https://doi.org/10.1016/j.intmar.2021.01.001

13.

Hirschman

E. C.

(1994). Consumers and their animal companions. Journal of Consumer Research, 20(4), 616–632. https://doi.org/10.1086/209374

14.

Hofkens

T. L.

Pianta

R. C.

(2022). Teacher–student relationships, engagement in school, and student outcomes. In Christenson

S. L.

Reschly

A. L.

Wylie

(Eds.) Handbook of research on student engagement (pp. 431–449). Springer International Publishing.

15.

Hogg

M. A.

Turner

J. C.

(1985). Interpersonal attraction, social identification and psychological group formation. European Journal of Social Psychology, 15(1), 51–66. https://doi.org/10.1002/ejsp.2420150105

16.

Howard

D. J.

Kerin

R. A.

(2004). The effects of personalized product recommendations on advertisement response rates: The “Try this. It works!” technique. Journal of Consumer Psychology, 14(3), 271–279. https://doi.org/10.1207/s15327663jcp1403_8

17.

Jeong

Yang

Kim

H. M.

Min

(2024). Curation subscription box services: Implications for the pet industry. Journal of Retailing and Consumer Services, 76, Article 103573. https://doi.org/10.1016/j.jretconser.2023.103573

18.

Jung

Ryu

Han

S. P.

Cho

(2023). Ask for reviews at the right time: Evidence from two field experiments. Journal of Marketing, 87(4), 528–549. https://doi.org/10.1177/00222429221143329

19.

Kalyanaraman

Sundar

S. S.

(2006). The psychological appeal of personalized content in web portals: Does customization affect attitudes and behavior? Journal of Communication, 56(1), 110–132. https://doi.org/10.1111/j.1460-2466.2006.00006.x

20.

KB Financial Group Management Research Institute. (2023). 2023 Korea pet report: Preparation and health management for companion animals. https://www.kbfg.com/kbresearch/report/reportView.do?reportId=2000396

21.

KPMG Samjong Accounting Corp. (2024). Issue monitor (No. 164). https://assets.kpmg.com/content/dam/kpmg/kr/pdf/2024/issue-monitor/kpmg-korea-petmarket-trends-20240604.pdf

22.

Kunkel

Hayduk

Lock

(2023). Push it real good: The effects of push notifications promoting motivational affordances on consumer behavior in a gamified mobile app. European Journal of Marketing, 57(9), 2592–2618. https://doi.org/10.1108/EJM-06-2021-0388

23.

Kyung

Chan

Lim

Lee

(2024). Contextual targeting in mHealth apps: Harnessing weather information and message framing to increase physical activity. Information Systems Research, 35, 1034–1051. https://doi.org/10.1287/isre.2020.0119

24.

(2016). When does web-based personalization really work? The distinction between actual personalization and perceived personalization. Computers in Human Behavior, 54, 25–33. https://doi.org/10.1016/j.chb.2015.07.049

25.

Liu

(2017). A name alone is not enough: A reexamination of web-based personalization effect. Computers in Human Behavior, 72, 132–139. https://doi.org/10.1016/j.chb.2017.02.039

26.

C. R.

Zhang

Han

J. T.

(2021). Adoption of online follow-up service by patients: An empirical study based on the elaboration likelihood model. Computers in Human Behavior, 114, Article 106581. https://doi.org/10.1016/j.chb.2020.106581

27.

Liu

Santhanam

Webster

(2017). Toward meaningful engagement. MIS Quarterly, 41(4), 1011–1034. https://www.jstor.org/stable/26630283

28.

März

Lachner

Heumann

C. G.

Schumann

J. H.

von Wangenheim

(2021). How you remind me! the influence of mobile push notifications on success rates in last-minute bidding. Journal of Interactive Marketing, 54(1), 11–24. https://doi.org/10.1016/j.intmar.2020.08.002

29.

Maslowska

Smit

E. G.

van den Putte

(2016). It is all in the name: A study of consumers’ responses to personalized communication. Journal of Interactive Advertising, 16(1), 74–85. https://doi.org/10.1080/15252019.2016.1161568

30.

Pansari

Kumar

(2017). Customer engagement: The construct, antecedents, and consequences. Journal of the Academy of Marketing Science, 45, 294–311. https://doi.org/10.1007/s11747-016-0485-6

31.

Paschmann

J. W.

Bruno

H. A.

van Heerde

H. J.

Völckner

Klein

(2025). Driving mobile app user engagement through gamification. Journal of Marketing Research, 62(2), 249–273. https://doi.org/10.1177/00222437241275927

32.

Rafieian

Kapoor

Sharma

(2025). Multiobjective personalization of marketing interventions. Marketing Science, 44, 457–477. https://doi.org/10.1287/mksc.2023.0122

33.

Ren

Harper

F. M.

Drenner

Terveen

Kiesler

Riedl

Kraut

R. E.

(2012). Building member attachment in online communities: Applying theories of group identity and interpersonal bonds. MIS Quarterly, 36, 841–864. https://doi.org/10.2307/41703483

34.

Rimer

B. K.

Kreuter

M. K.

(2006). Advancing tailored health communication: A persuasion and message effects perspective. Journal of Communication, 56(S1), S184–S201. https://doi.org/10.1111/j.1460-2466.2006.00289.x

35.

Sahni

N. S.

Wheeler

S. C.

Chintagunta

(2018). Personalization in email marketing: The role of noninformative advertising content. Marketing Science, 37(2), 236–258. https://doi.org/10.1287/mksc.2017.1066

36.

Shi

S. W.

Kalyanam

(2018). Touchable apps: Exploring the usage of touch features and their impact on engagement. Journal of Interactive Marketing, 44(1), 43–59. https://doi.org/10.1016/j.intmar.2018.06.001

37.

Song

J. H.

Kim

H. Y.

Kim

Lee

S. W.

Lee

J. H.

(2016). Effects of personalized e-mail messages on privacy risk: Moderating roles of control and intimacy. Marketing Letters, 27, 89–101. https://doi.org/10.1007/s11002-014-9315-0

38.

Tajfel

(1974). Social identity and intergroup behaviour. Social Science Information, 13(2), 65–93. https://doi.org/10.1177/053901847401300204

39.

Tam

K. Y.

S. Y.

(2006). Understanding the impact of web personalization on user information processing and decision outcomes. MIS Quarterly, 30, 865–890. https://doi.org/10.2307/25148757

40.

Van Doorn

Lemon

K. N.

Mittal

Nass

Pick

Pirner

Verhoef

P. C

. (2010). Customer engagement behavior: Theoretical foundations and research directions. Journal of Service Research, 13(3), 253–266. https://doi.org/10.1177/1094670510375599

41.

Van Heerde

H. J.

Dinner

I. M.

Neslin

S. A

. (2019). Engaging the unengaged customer: The value of a retailer mobile app. International Journal of Research in Marketing, 36(3), 420–438. https://doi.org/10.1016/j.ijresmar.2019.03.003

42.

White

T. B.

Zahay

D. L.

Thorbjørnsen

Shavitt

(2008). Getting too personal: Reactance to highly personalized email solicitations. Marketing Letters, 19, 39–50. https://doi.org/10.1007/s11002-007-9027-9

43.

Wohl

M. J.

Davis

C. G.

Hollingshead

S. J.

(2017). How much have you won or lost? Personalized behavioral feedback about gambling expenditures regulates play. Computers in Human Behavior, 70, 437–445. https://doi.org/10.1016/j.chb.2017.01.025

44.

Zhang

Mehta

Singh

P. V.

Srinivasan

(2021). Frontiers: Can an artificial intelligence algorithm mitigate racial economic inequality? An analysis in the context of Airbnb. Marketing Science, 40(5), 813–820. https://doi.org/10.1287/mksc.2021.1295

45.

Zhang

Luo

Wang

(2019). Personalized mobile targeting with user engagement stages: Combining a structural hidden Markov model and field experiment. Information Systems Research, 30(3), 787–804. https://doi.org/10.1287/isre.2018.0831

46.

Zhu

Y. Q.

Chang

J. H.

(2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442–447. https://doi.org/10.1016/j.chb.2016.08.048