The Design and Targeting of Compliance Promotions
This paper addresses how and when to extrapolate experimental results for normative policy analysis, particularly in the context of compliance promotions in which consumers can self-select into treatment. This paper considers an experiment-based approach to the optimal design and targeting of compli...
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Veröffentlicht in: | Marketing science (Providence, R.I.) R.I.), 2023-09, Vol.42 (5), p.866-891 |
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creator | Daljord, Øystein Mela, Carl F. Roos, Jason M. T. Sprigg, Jim Yao, Song |
description | This paper addresses how and when to extrapolate experimental results for normative policy analysis, particularly in the context of compliance promotions in which consumers can self-select into treatment.
This paper considers an experiment-based approach to the optimal design and targeting of compliance promotions. Compliance promotions involve optional participation on the behalf of customers. For example, physicians must consent to see detailers, and consumers must redeem coupons to obtain discounts. Individual compliance decisions affect the mix of customers participating in the promotion and, therefore, how the promotion affects sales. Optional compliance is an especially acute problem in the context of field experiments as policy optimization often necessitates extrapolation beyond the observed cells of the experiment to a different mix of complying customers. Our approach to optimizing the design and targeting of compliance promotions involves (i) an experiment to exogenously vary promotion features; (ii) a means to identify which promotion features can be causally extrapolated; (iii) an approach to extrapolate those causal effects; and (iv) an optimization over the promotion features, conditioned on the extrapolation. The approach is easy to estimate, accommodates two-sided noncompliance due to unobserved heterogeneity, and establishes partial identification bounds of causal effects. When applying the approach to a hotel loyalty promotion, wherein customers must visit enough hotels to earn bonus loyalty points, we find profits are improved considerably.
History:
Olivier Toubia served as the senior editor for this article.
Supplemental Material:
The data files are available at
https://doi.org/10.1287/mksc.2022.1420
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doi_str_mv | 10.1287/mksc.2022.1420 |
format | Article |
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This paper considers an experiment-based approach to the optimal design and targeting of compliance promotions. Compliance promotions involve optional participation on the behalf of customers. For example, physicians must consent to see detailers, and consumers must redeem coupons to obtain discounts. Individual compliance decisions affect the mix of customers participating in the promotion and, therefore, how the promotion affects sales. Optional compliance is an especially acute problem in the context of field experiments as policy optimization often necessitates extrapolation beyond the observed cells of the experiment to a different mix of complying customers. Our approach to optimizing the design and targeting of compliance promotions involves (i) an experiment to exogenously vary promotion features; (ii) a means to identify which promotion features can be causally extrapolated; (iii) an approach to extrapolate those causal effects; and (iv) an optimization over the promotion features, conditioned on the extrapolation. The approach is easy to estimate, accommodates two-sided noncompliance due to unobserved heterogeneity, and establishes partial identification bounds of causal effects. When applying the approach to a hotel loyalty promotion, wherein customers must visit enough hotels to earn bonus loyalty points, we find profits are improved considerably.
History:
Olivier Toubia served as the senior editor for this article.
Supplemental Material:
The data files are available at
https://doi.org/10.1287/mksc.2022.1420
.</description><identifier>ISSN: 0732-2399</identifier><identifier>EISSN: 1526-548X</identifier><identifier>DOI: 10.1287/mksc.2022.1420</identifier><language>eng</language><publisher>Linthicum: INFORMS</publisher><subject>Brand loyalty ; Compliance ; compliance promotions ; Consumer behavior ; Consumers ; Coupons ; Customers ; Discounts ; Extrapolation ; field experiments ; Hotels & motels ; IV estimation ; Loyalty ; Loyalty programs ; marginal treatment effects ; Noncompliance ; Optimization ; Profits ; Sales ; two-sided noncompliance</subject><ispartof>Marketing science (Providence, R.I.), 2023-09, Vol.42 (5), p.866-891</ispartof><rights>Copyright Institute for Operations Research and the Management Sciences Sep/Oct 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-cdcc2b4903dad9c48b60c8576e169607f19a9879bbdd62af4583cd834c12f1793</citedby><cites>FETCH-LOGICAL-c362t-cdcc2b4903dad9c48b60c8576e169607f19a9879bbdd62af4583cd834c12f1793</cites><orcidid>0000-0001-9764-5128 ; 0000-0002-0339-9649 ; 0000-0002-3897-2935 ; 0000-0001-7893-6966</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubsonline.informs.org/doi/full/10.1287/mksc.2022.1420$$EHTML$$P50$$Ginforms$$H</linktohtml><link.rule.ids>314,776,780,3679,27901,27902,62589</link.rule.ids></links><search><creatorcontrib>Daljord, Øystein</creatorcontrib><creatorcontrib>Mela, Carl F.</creatorcontrib><creatorcontrib>Roos, Jason M. T.</creatorcontrib><creatorcontrib>Sprigg, Jim</creatorcontrib><creatorcontrib>Yao, Song</creatorcontrib><title>The Design and Targeting of Compliance Promotions</title><title>Marketing science (Providence, R.I.)</title><description>This paper addresses how and when to extrapolate experimental results for normative policy analysis, particularly in the context of compliance promotions in which consumers can self-select into treatment.
This paper considers an experiment-based approach to the optimal design and targeting of compliance promotions. Compliance promotions involve optional participation on the behalf of customers. For example, physicians must consent to see detailers, and consumers must redeem coupons to obtain discounts. Individual compliance decisions affect the mix of customers participating in the promotion and, therefore, how the promotion affects sales. Optional compliance is an especially acute problem in the context of field experiments as policy optimization often necessitates extrapolation beyond the observed cells of the experiment to a different mix of complying customers. Our approach to optimizing the design and targeting of compliance promotions involves (i) an experiment to exogenously vary promotion features; (ii) a means to identify which promotion features can be causally extrapolated; (iii) an approach to extrapolate those causal effects; and (iv) an optimization over the promotion features, conditioned on the extrapolation. The approach is easy to estimate, accommodates two-sided noncompliance due to unobserved heterogeneity, and establishes partial identification bounds of causal effects. When applying the approach to a hotel loyalty promotion, wherein customers must visit enough hotels to earn bonus loyalty points, we find profits are improved considerably.
History:
Olivier Toubia served as the senior editor for this article.
Supplemental Material:
The data files are available at
https://doi.org/10.1287/mksc.2022.1420
.</description><subject>Brand loyalty</subject><subject>Compliance</subject><subject>compliance promotions</subject><subject>Consumer behavior</subject><subject>Consumers</subject><subject>Coupons</subject><subject>Customers</subject><subject>Discounts</subject><subject>Extrapolation</subject><subject>field experiments</subject><subject>Hotels & motels</subject><subject>IV estimation</subject><subject>Loyalty</subject><subject>Loyalty programs</subject><subject>marginal treatment effects</subject><subject>Noncompliance</subject><subject>Optimization</subject><subject>Profits</subject><subject>Sales</subject><subject>two-sided noncompliance</subject><issn>0732-2399</issn><issn>1526-548X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNqFkDtPwzAAhC0EEqWwMltiTvArfoyoPKVKMBSJzXJsp7g0drHDwL8nUZAYmW757k76ALjEqMZEiuv-o9iaIEJqzAg6AgvcEF41TL4dgwUSlFSEKnUKzkrZIYQEQXIB8Obdw1tfwjZCEx3cmLz1Q4hbmDq4Sv1hH0y0Hr7k1KchpFjOwUln9sVf_OYSvN7fbVaP1fr54Wl1s64s5WSorLOWtEwh6oxTlsmWIysbwT3miiPRYWWUFKptnePEdKyR1DpJmcWkw0LRJbiadw85fX75Muhd-spxvNREckE5QpyNVD1TNqdSsu_0IYfe5G-NkZ606EmLnrToSctYgHPB2xRD-cMlVyMwOhuRakZC7FLuy3-TP28Cba0</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Daljord, Øystein</creator><creator>Mela, Carl F.</creator><creator>Roos, Jason M. T.</creator><creator>Sprigg, Jim</creator><creator>Yao, Song</creator><general>INFORMS</general><general>Institute for Operations Research and the Management Sciences</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8BJ</scope><scope>FQK</scope><scope>JBE</scope><orcidid>https://orcid.org/0000-0001-9764-5128</orcidid><orcidid>https://orcid.org/0000-0002-0339-9649</orcidid><orcidid>https://orcid.org/0000-0002-3897-2935</orcidid><orcidid>https://orcid.org/0000-0001-7893-6966</orcidid></search><sort><creationdate>20230901</creationdate><title>The Design and Targeting of Compliance Promotions</title><author>Daljord, Øystein ; Mela, Carl F. ; Roos, Jason M. T. ; Sprigg, Jim ; Yao, Song</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-cdcc2b4903dad9c48b60c8576e169607f19a9879bbdd62af4583cd834c12f1793</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Brand loyalty</topic><topic>Compliance</topic><topic>compliance promotions</topic><topic>Consumer behavior</topic><topic>Consumers</topic><topic>Coupons</topic><topic>Customers</topic><topic>Discounts</topic><topic>Extrapolation</topic><topic>field experiments</topic><topic>Hotels & motels</topic><topic>IV estimation</topic><topic>Loyalty</topic><topic>Loyalty programs</topic><topic>marginal treatment effects</topic><topic>Noncompliance</topic><topic>Optimization</topic><topic>Profits</topic><topic>Sales</topic><topic>two-sided noncompliance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Daljord, Øystein</creatorcontrib><creatorcontrib>Mela, Carl F.</creatorcontrib><creatorcontrib>Roos, Jason M. T.</creatorcontrib><creatorcontrib>Sprigg, Jim</creatorcontrib><creatorcontrib>Yao, Song</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><jtitle>Marketing science (Providence, R.I.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Daljord, Øystein</au><au>Mela, Carl F.</au><au>Roos, Jason M. T.</au><au>Sprigg, Jim</au><au>Yao, Song</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Design and Targeting of Compliance Promotions</atitle><jtitle>Marketing science (Providence, R.I.)</jtitle><date>2023-09-01</date><risdate>2023</risdate><volume>42</volume><issue>5</issue><spage>866</spage><epage>891</epage><pages>866-891</pages><issn>0732-2399</issn><eissn>1526-548X</eissn><abstract>This paper addresses how and when to extrapolate experimental results for normative policy analysis, particularly in the context of compliance promotions in which consumers can self-select into treatment.
This paper considers an experiment-based approach to the optimal design and targeting of compliance promotions. Compliance promotions involve optional participation on the behalf of customers. For example, physicians must consent to see detailers, and consumers must redeem coupons to obtain discounts. Individual compliance decisions affect the mix of customers participating in the promotion and, therefore, how the promotion affects sales. Optional compliance is an especially acute problem in the context of field experiments as policy optimization often necessitates extrapolation beyond the observed cells of the experiment to a different mix of complying customers. Our approach to optimizing the design and targeting of compliance promotions involves (i) an experiment to exogenously vary promotion features; (ii) a means to identify which promotion features can be causally extrapolated; (iii) an approach to extrapolate those causal effects; and (iv) an optimization over the promotion features, conditioned on the extrapolation. The approach is easy to estimate, accommodates two-sided noncompliance due to unobserved heterogeneity, and establishes partial identification bounds of causal effects. When applying the approach to a hotel loyalty promotion, wherein customers must visit enough hotels to earn bonus loyalty points, we find profits are improved considerably.
History:
Olivier Toubia served as the senior editor for this article.
Supplemental Material:
The data files are available at
https://doi.org/10.1287/mksc.2022.1420
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subjects | Brand loyalty Compliance compliance promotions Consumer behavior Consumers Coupons Customers Discounts Extrapolation field experiments Hotels & motels IV estimation Loyalty Loyalty programs marginal treatment effects Noncompliance Optimization Profits Sales two-sided noncompliance |
title | The Design and Targeting of Compliance Promotions |
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