Skip to main content
SpringerLink
Log in

Privacy-Centric Digital Advertising: Implications for Research

  • Perspectives
  • Published:
Customer Needs and Solutions Aims and scope Submit manuscript

Abstract

Yesterday’s digital advertising relied on cross-website and cross-app user identity to measure, target, and optimize ads. Spurred by regulatory pressure, today’s digital advertising is evolving to become more privacy-protective. Apple and Google are leading this movement by sunsetting old technologies and building more privacy-centric alternatives. Marketing academics and practitioners, in turn, must learn to adapt to this new reality. We outline these new advertising approaches and their implications for advertising strategy, targeting, and measurement. We propose key questions and an agenda for researchers to help shape the privacy-centric future of digital advertising.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. Note that Facebook and Mozilla propose an alternative that relies on multi-party computation to permit cross-platform attribution modeling while preserving privacy [50].

References

  1. Ada S, Abou Nabout N, Feit EM (2022) Context information increases revenue in ad auctions: Evidence from a policy change. J Market Res, forthcoming

  2. Blake T, Nosko C, Tadelis S (2015) Consumer heterogeneity and paid search effectiveness: a large-scale field experiment. Econometrica 83(1):155–174

    Article  Google Scholar 

  3. Bleier A, Eisenbeiss M (2015) Personalized online advertising effectiveness: the inter- play of what, when, and where. Mark Sci 34(5):669–688

    Article  Google Scholar 

  4. Bleier A, Goldfarb A, Tucker C (2020) Consumer privacy and the future of data-based innovation and marketing. Int J Res Mark 37(3):466–480

    Article  Google Scholar 

  5. Braun M, Moe WW (2013) Online display advertising: modeling the effects of multiple creatives and individual impression histories. Mark Sci 32(5):753–767

    Article  Google Scholar 

  6. Bruce NI, Murthi B, Rao RC (2017) A dynamic model for digital advertising: the effects of creative format, message content, and targeting on engagement. J Mark Res 54(2):202–218

    Article  Google Scholar 

  7. Chavez A (2022) Introducing the Privacy Sandbox on Android. Google blog. [Accessed online at https://blog.google/products/android/introducing-privacy-sandbox-android/ on March 6, 2022]

  8. Chen BX (2021) The battle for digital privacy is reshaping the internet. The New York Times. [Accessed online at https://www.nytimes.com/2021/09/16/technology/digital-privacy.html on October 4, 2021]

  9. Choi H, Mela CF, Balseiro SR, Leary A (2020) Online display advertising markets: a literature review and future directions. Inf Syst Res 31(2):556–575

    Article  Google Scholar 

  10. Danaher PJ (2017) Advertising effectiveness and media exposure. In Handbook of marketing decision models (pp. 463–481). Springer, Cham

  11. Dinner IM, Heerde HJV, Neslin SA (2014) Driving online and offline sales: the cross-channel effects of traditional, online display, and paid search advertising. J Mark Res 51(5):527–545

    Article  Google Scholar 

  12. Draganska M, Hartmann WR, Stanglein G (2014) Internet versus television advertising: a brand-building comparison. J Mark Res 51:578–590

    Article  Google Scholar 

  13. Facebook (2021) Navigating change and improving performance and measurement. Facebook for Business. [Accessed online at https://www.facebook.com/business/news/navigating-change-and-improving-performance-and-measurement on October 4, 2021]

  14. Goldfarb A (2014) What is different about online advertising? Rev Ind Organ 44(2):115–129

    Article  Google Scholar 

  15. Goldfarb A, Tucker CE (2011) Privacy regulation and online advertising. Manage Sci 57(1):57–71

    Article  Google Scholar 

  16. Google Research and Ads (2020) Evaluation of cohort algorithms for the FLoC API. Google White Paper. [Accessed online at https://github.com/google/ads-privacy/blob/master/proposals/FLoC/FLOC-Whitepaper-Google.pdf on July 13, 2021]

  17. Google (2021)The Privacy Sandbox: technology for a more private web. [Accessed online at https://privacysandbox.com/ on October 3, 2021]

  18. Gordon BR, Zettelmeyer F, Bhargava N, Chapsky D (2019) A comparison of approaches to advertising measurement: evidence from big field experiments at Facebook. Mark Sci 38(2):193–225

    Article  Google Scholar 

  19. Gordon BR, Jerath K, Katona Z, Narayanan S, Shin J, Wilbur KC (2021) Inefficiencies in digital advertising markets. J Mark 85(1):7–25

    Article  Google Scholar 

  20. Green J (2021) Why a unified ID is critical to the open internet, journalism, and TV. [Accessed online at https://www.thetradedesk.com/us/news/why-a-unified-id-is-critical-to-the-open-internet-journalism-and-tv on October 3, 2021]

  21. Hartmann WR, Klapper D (2018) Super Bowl ads. Mark Sci 37(1):78–96

    Article  Google Scholar 

  22. IAB Tech Lab (2021) Taxonomy and data transparency standards to support seller-defined audience and context signaling

  23. Iwańczak P, Rumiński M (2022) The future of frequency capping in privacy-centric digital advertising. Working Paper. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3985974

  24. Johnson GA (2021) Inferno: a guide to field experiments in online display advertising. Working Paper. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3581396

  25. Johnson GA, Shriver SK, Du S (2020) Consumer privacy choice in online advertising: who opts out and at what cost to industry? Mark Sci 39(1):33–51

    Article  Google Scholar 

  26. Lambrecht A, Tucker C (2013) When does retargeting work? Information specificity in online advertising. J Mark Res 50(5):561–576

    Article  Google Scholar 

  27. Laziuk E (2021) iOS 14.5 Opt-in rate - daily updates since launch. Flurry Blog. [Accessed online at https://www.flurry.com/blog/ios-14-5-opt-in-rate-att-restricted-app-tracking-transparency-worldwide-us-daily-latest-update/ on March 12, 2022]

  28. Lewis R, Rao J (2015) The unfavorable economics of measuring the returns to advertising. Quart J Econ 130(4):1941–1973

    Article  Google Scholar 

  29. Lewis RA, Reiley DH (2014) Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo! Quant Mark Econ 12(3):235–266

    Article  Google Scholar 

  30. Lewis RA, Wong J (2018) Incrementality bidding & attribution. Available at SSRN

  31. Li H, Kannan PK (2014) Attributing conversions in a multichannel online marketing environment: an empirical model and a field experiment. J Mark Res 51(1):40–56

    Article  Google Scholar 

  32. Lin J, Halloran S (2021) Study: effectiveness of Apple’s App Tracking Transparency. Lockdown Privacy blog. [Accessed online at https://blog.lockdownprivacy.com/2021/09/22/study-effectiveness-of-apples-app-tracking-transparency.html on March 9, 2022]

  33. Lin T, Misra S (2022) Frontiers: the identity fragmentation bias. Marketing Science, forthcoming

  34. Lin X, Nair HS, Sahni NS, Waisman C (2019) Parallel experimentation in a competitive advertising marketplace. arXiv preprint arXiv:1903.11198

  35. Neumann N, Tucker C, Whitfield T (2019) Frontiers: how effective is third-party consumer profiling? Evidence from field studies. Market Sci 38(6):918–926

    Google Scholar 

  36. Rafieian O, Yoganarasimhan H (2021) Targeting and privacy in mobile advertising. Mark Sci 40(2):193–218

    Article  Google Scholar 

  37. Ravichandran D, Korula N (2019) Effect of disabling third-party cookies on publisher revenue. Google White Paper. [Accessed online at https://services.google.com/fh/files/misc/disabling_third-party_cookies_publisher_revenue.pdf on October 4, 2021]

  38. Rouzaud A (2021) FLoC origin trial: what we observed (1/4). Criteo R&D Blog. [Accessed online at https://medium.com/criteo-engineering/floc-origin-trial-what-we-observed-3f7e8f209b82 on October 4, 2021]

  39. Runge J, Geinitz S, Ejdemyr S (2020) Experimentation and performance in advertising: an observational survey of firm practices on Facebook. Expert Syst Appl 158:113554

  40. Runge J, Nair H (2021) The role of randomized control trials in online demand generation: exploratory evidence from Facebook. Proceedings of the International Conference on Information Systems (ICIS) 2021

  41. Runge J, Seufert E (2021) Apple is changing how digital ads work. Are advertisers prepared? Harvard Business Review, digital article

  42. Sahni NS, Narayanan S, Kalyanam K (2019) An experimental investigation of the effects of retargeted advertising: the role of frequency and timing. J Mark Res 56(3):401–418

    Article  Google Scholar 

  43. Schwartz EM, Bradlow ET, Fader PS (2017) Customer acquisition via display advertising using multi-armed bandit experiments. Mark Sci 36(4):500–522

    Article  Google Scholar 

  44. Seiler S, Yao S, Wang W (2017) Does online word of mouth increase demand? (and how?) evidence from a natural experiment. Mark Sci 36(6):838–861

    Article  Google Scholar 

  45. Seufert E (2022) RIP GAID: Privacy Sandbox is coming to Android. What advertisers need to know. Mobile Dev Memo. [Accessed online at https://mobiledevmemo.com/rip-gaid-privacy-sandbox-is-coming-to-android-heres-a-summary-of-the-tech/ on February 26, 2022]

  46. Seufert E (2021) Creative paralysis: ad creative production and testing in iOS 14. Mobile Dev Memo. [Accessed online at https://mobiledevmemo.com/creative-paralysis-ad-creative-production-and-testing-for-ios-14/ on October 3, 2021]

  47. Seufert E (2020) How to scale and optimize marketing spend with SKAdNetwork. Mobile Dev Memo. [Accessed online at https://mobiledevmemo.com/how-to-scale-and-optimize-marketing-spend-with-skadnetwork/ on July 13, 2021]

  48. Shapiro BT (2018) Positive spillovers and free riding in advertising of prescription pharmaceuticals: The case of antidepressants. J Polit Econ 126(1):381–437

    Article  Google Scholar 

  49. Simonov A, Hill S (2021) Competitive advertising on brand search: Traffic stealing and click quality. Mark Sci 40(5):923–945

    Article  Google Scholar 

  50. Thomson M (2022) Privacy preserving attribution for advertising. Mozilla blog. [Accessed online at https://blog.mozilla.org/en/mozilla/privacy-preserving-attribution-for-advertising/ on March 7, 2022]

  51. Tucker CE (2012) The economics of advertising and privacy. Int J Ind Organ 30(3):326–329

    Article  Google Scholar 

  52. Urban GL, Liberali G, MacDonald E, Bordley R, Hauser JR (2013) Morphing banner advertising. Mark Sci 33(1):27–46

    Article  Google Scholar 

  53. Wagner K (2021) Facebook users said no to tracking. Now advertisers are panicking. Bloomberg. [Accessed online at https://www.bloomberg.com/news/articles/2021-07-14/facebook-fb-advertisers-impacted-by-apple-aapl-privacy-ios-14-changes on October 3, 2021]

  54. Wieringa J, Kannan PK, Ma X, Reutterer T, Risselada H, Skiera B (2021) Data analytics in a privacy-concerned world. J Bus Res 122:915–925

    Article  Google Scholar 

  55. Wilander J (2021) Introducing private click measurement, PCM. Apple Webkit blog. [Accessed online at https://webkit.org/blog/11529/introducing-private-click-measurement-pcm/ on March 8, 2022]

  56. Zantedeschi D, Feit EM, Bradlow ET (2017) Measuring multichannel advertising response. Manage Sci 63(8):2706–2728

    Article  Google Scholar 

Download references

Acknowledgements

We thank Randall Lewis and Samuel Goldberg for helpful comments. All remaining errors are the authors’ own.

Author information

Authors and Affiliations

  1. Questrom School of Business, Boston University, 595 Commonwealth Avenue, Boston, MA, 02215, USA

    Garrett Johnson

  2. Fuqua School of Business, Duke University, 100 Fuqua Drive, Durham, NC, 27708, USA

    Julian Runge

  3. Mobile Dev Memo, 222 West Ave #1711, Austin, TX, 78702, USA

    Eric Seufert

Authors
  1. Garrett Johnson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julian Runge
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eric Seufert
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Julian Runge.

Ethics declarations

Competing Interests

Julian Runge was employed at Facebook as a researcher until March 2021. Eric Seufert works as a private consultant advising and investing in multiple online advertising businesses.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Johnson, G., Runge, J. & Seufert, E. Privacy-Centric Digital Advertising: Implications for Research. Cust. Need. and Solut. 9, 49–54 (2022). https://doi.org/10.1007/s40547-022-00125-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40547-022-00125-4

Keywords

Search

Navigation