IDEAS home Printed from https://ideas.repec.org/a/aea/aecrev/v105y2015i5p105-09.html

Messaging and the Mandate: The Impact of Consumer Experience on Health Insurance Enrollment through Exchanges

Author

Listed:
  • Natalie Cox
  • Benjamin Handel
  • Jonathan Kolstad
  • Neale Mahoney

Abstract

The ability of web-based retailers to learn about and provide targeted consumer experiences is touted as an important distinction from traditional retailers. In principal, web-based insurance exchanges could benefit from these advantages. Using data from a large-scale experiment by a private sector health insurance exchange we estimate the returns to experimentation and targeted messaging. We find significant improvements in conversions in one treatment tested. Underlying the average impact were both inter temporal and demographic heterogeneity. We estimate that learning and targeted messaging could increase insurance applications by approximately 13 percent of the baseline conversion rate.

Suggested Citation

  • Natalie Cox & Benjamin Handel & Jonathan Kolstad & Neale Mahoney, 2015. "Messaging and the Mandate: The Impact of Consumer Experience on Health Insurance Enrollment through Exchanges," American Economic Review, American Economic Association, vol. 105(5), pages 105-109, May.
    • Handle: RePEc:aea:aecrev:v:105:y:2015:i:5:p:105-09
    Note: DOI: 10.1257/aer.p20151080
    as

    Download full text from publisher

    File URL: http://www.aeaweb.org/articles.php?doi=10.1257/aer.p20151080
    Download Restriction: no
    File URL: https://www.aeaweb.org/aer/ds/10505/P2015_1080_ds.zip
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    ---><---

    References listed on IDEAS

    as
    1. Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, January.
    2. Randall Lewis & David Reiley, 2014. "Advertising Effectively Influences Older Users: How Field Experiments Can Improve Measurement and Targeting," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 147-159, March.
    3. Avi Goldfarb, 2014. "What is Different About Online Advertising?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 115-129, March.
    4. Ericson, Keith M. Marzilli & Starc, Amanda, 2016. "How product standardization affects choice: Evidence from the Massachusetts Health Insurance Exchange," Journal of Health Economics, Elsevier, vol. 50(C), pages 71-85.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kurt Lavetti & Thomas DeLeire & Nicolas R. Ziebarth, 2023. "How do low‐income enrollees in the Affordable Care Act marketplaces respond to cost‐sharing?," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 90(1), pages 155-183, March.
    2. Martin Gaynor & Kate Ho & Robert J. Town, 2015. "The Industrial Organization of Health-Care Markets," Journal of Economic Literature, American Economic Association, vol. 53(2), pages 235-284, June.
    3. Jesse M. Hinde, 2017. "Incentive(less)? The Effectiveness of Tax Credits and Cost-Sharing Subsidies in the Affordable Care Act," American Journal of Health Economics, MIT Press, vol. 3(3), pages 346-369, Summer.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lorenzo Coviello & Uri Gneezy & Lorenz Götte, 2017. "A Large-Scale Field Experiment to Evaluate the Effectiveness of Paid Search Advertising," CESifo Working Paper Series 6684, CESifo.
    2. Mariia I. Okuneva & Dmitriy B. Potapov, 2015. "The Effectiveness of Individual Targeting Through Smartphone Application in Retail: Evidence from Field Experiment," HSE Working papers WP BRP 47/MAN/2015, National Research University Higher School of Economics.
    3. Randall Lewis & David Reiley, 2014. "Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo!," Quantitative Marketing and Economics (QME), Springer, vol. 12(3), pages 235-266, September.
    4. Alexandre Chirat, 2022. "Consumer sovereignty in the digital society," EconomiX Working Papers 2022-25, University of Paris Nanterre, EconomiX.
    5. Stefan Bechtold & Catherine Tucker, 2014. "Trademarks, Triggers, and Online Search," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 11(4), pages 718-750, December.
    6. Wei Zhou & Zidong Wang, 2020. "Competing for Search Traffic in Query Markets: Entry Strategy, Platform Design, and Entrepreneurship," Working Papers 20-12, NET Institute.
    7. Peitz, Martin & Reisinger, Markus, 2014. "The Economics of Internet Media," Working Papers 14-23, University of Mannheim, Department of Economics.
    8. Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, January.
    9. Joseph Golden & John Joseph Horton, 2021. "The Effects of Search Advertising on Competitors: An Experiment Before a Merger," Management Science, INFORMS, vol. 67(1), pages 342-362, January.
    10. Garrett Johnson & Julian Runge & Eric Seufert, 2022. "Privacy-Centric Digital Advertising: Implications for Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 9(1), pages 49-54, June.
    11. Francesco Decarolis & Gabriele Rovigatti, 2021. "From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising," American Economic Review, American Economic Association, vol. 111(10), pages 3299-3327, October.
    12. Arnold, René & Marcus, J. Scott & Petropoulos, Georgios & Schneider, Anna, 2018. "Is data the new oil? Diminishing returns to scale," 29th European Regional ITS Conference, Trento 2018 184927, International Telecommunications Society (ITS).
    13. Joel Barajas & Ram Akella & Marius Holtan & Aaron Flores, 2016. "Experimental Designs and Estimation for Online Display Advertising Attribution in Marketplaces," Marketing Science, INFORMS, vol. 35(3), pages 465-483, May.
    14. Suciu Marta Christina & Năsulea Christian & Năsulea Diana Florentina, 2019. "The Long-Term Effectiveness of Advertising Driven Sales for E-Commerce SMEs," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 13(1), pages 1180-1191, May.
    15. Vilma Todri, 2022. "Frontiers: The Impact of Ad-Blockers on Online Consumer Behavior," Marketing Science, INFORMS, vol. 41(1), pages 7-18, January.
    16. Navdeep Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    17. Andrey Simonov & Shawndra Hill, 2021. "Competitive Advertising on Brand Search: Traffic Stealing and Click Quality," Marketing Science, INFORMS, vol. 40(5), pages 923-945, September.
    18. Bradley T. Shapiro, 2020. "Advertising in Health Insurance Markets," Marketing Science, INFORMS, vol. 39(3), pages 587-611, May.
    19. Batikas, Michail & Claussen, Jörg & Peukert, Christian, 2019. "Follow the money: Online piracy and self-regulation in the advertising industry," International Journal of Industrial Organization, Elsevier, vol. 65(C), pages 121-151.
    20. Aaltonen, Aleksi Ville & Alaimo, Cristina & Kallinikos, Jannis, 2021. "The making of data commodities: data analytics as an embedded process," LSE Research Online Documents on Economics 110296, London School of Economics and Political Science, LSE Library.

    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:aecrev:v:105:y:2015:i:5:p:105-09. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.