Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market

Reimers, Imke; Xie, Claire

doi:10.1287/mnsc.2017.2934

Cited by 50 publications

(15 citation statements)

References 14 publications

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“…Similarly, recent studies suggest that monetary promotions negatively influence brand choice and attitude in the long term (Yi and Yoo, 2011). Indeed, the effort may not pay off in the long term if many of the new customers abandon and shift to other competitors after the monetary promotion expires (Reimers and Xie, 2018). Therefore, we recommend that OTAs expand their strategies beyond economic incentives by combining them with other actions, such as draws and contests, to differentiate themselves from other companies and obtain the benefits derived from supporting customers.…”

Section: Practical Implicationsmentioning

confidence: 99%

Social media promotions and travelers’ value-creating behaviors: the role of perceived support

Casaló

Romero

2019

IJCHM

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Purpose Encouraging travelers to create value that benefits firms is of great relevance for companies that operate in online contexts. The purpose of this study is to investigate, focusing on online travel agencies, how monetary promotions (i.e. economic incentives) and non-monetary promotions (i.e. draws and contests) conducted through social media enhance customers’ voluntary behaviors (i.e. suggestions, word of mouth, and social media interactions) that go beyond brand choice, which may provide benefit to firms. Design/methodology/approach The research model draws on the social exchange theory, equity theory and the concept of perceived support – how customers perceive that companies care about their well-being. The authors collect information from 491 users of online travel agencies in Spain and test their hypotheses using partial least squares. They also evaluate the existence of indirect effects. Findings Promotions developed by companies make customers more likely to perform, voluntarily, the helping behaviors of suggestions, word of mouth and social media interactions, through the influence of perceived support. Research limitations/implications Use of a single survey to collect measures and restriction of the sample to Spanish-speaking travelers suggests caution in generalizing the results. Future research could investigate other company-initiated actions and other value-creating behaviors of travelers. Practical implications Promotions help develop perceived support for customers, which leads to voluntary, valuable traveler behaviors. Promotions may be also sufficient to trigger some customer behaviors, such as word-of-mouth. Originality/value Based on the social exchange and equity theories, this paper investigates the influence of social media promotions on customers’ voluntary behaviors via perceived support.

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Section: Practical Implicationsmentioning

confidence: 99%

Social media promotions and travelers’ value-creating behaviors: the role of perceived support

Casaló

Romero

2019

IJCHM

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“…We consider promotional campaigns that aim at maximizing sales revenues in e-commerce through issuing digital coupons (e.g., Reimers & Xie, 2019). The prevalence of coupons suggests that coupon targeting is a relevant task.…”

Section: Introductionmentioning

confidence: 99%

Response transformation and profit decomposition for revenue uplift modeling

Gubela

Lessmann

Jaroszewicz

2020

European Journal of Operational Research

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Uplift models support decision-making in marketing campaign planning. Estimating the causal effect of a marketing treatment, an uplift model facilitates targeting communication to responsive customers and an efficient allocation of marketing budgets. Research into uplift models focuses on conversion models to maximize incremental sales. The paper introduces uplift modeling strategies for maximizing incremental revenues. If customers differ in their spending behavior, revenue maximization is a more plausible business objective compared to maximizing conversions. The proposed methodology entails a transformation of the prediction target, customer-level revenues, that facilitates implementing a causal uplift model using standard machine learning algorithms. The distribution of campaign revenues is typically zero-inflated because of many non-buyers. Remedies to this modeling challenge are incorporated in the proposed revenue uplift strategies in the form of two-stage models. Empirical experiments using real-world e-commerce data confirms the merits of the proposed revenue uplift strategy over relevant alternatives including uplift models for conversion and recently developed causal machine learning algorithms. To quantify the degree to which improved targeting decisions raise return on marketing, the paper develops a decomposition of campaign profit. Applying the decomposition to a digital coupon targeting campaign, the paper provides evidence that revenue uplift modeling as well as causal machine learning can improve campaign profit substantially.

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“…Clearly stochastic policies such as π H can explain a coupon redemption ratio below 1 when we have p x ≥ v. However, coupon redemption ratios from such policies are sensitive to the coupon value v, at least in the cases with only one coupon. We can illustrate the intuition of this claim by looking at equation (32): given the sameλ j ,P j and T , one can show by induction on T that the gap between v and V (v, T ) increases monotonically as v increases. Therefore, the redemption ratio under the condition p x /v ≥ 1 should also increase monotonically with v. However, this is not fully consistent with our observations in Figure 5: the redemption ratio under v = 30 is not significantly greater than the one under v = 20.…”

Section: Observations On the Coupon Redemption Behaviormentioning

confidence: 99%

“…Therefore, recent research mostly focused on reduced-form models or even data-driven approaches. For example, Reimers and Xie [32] proposed reduced-form models for coupons' market expansion and revenue cannibalization effects. The authors estimated their models using restaurant coupon data from Groupon.…”

Section: Customer Behavior With Couponsmentioning

confidence: 99%

An Inattention Model for Traveler Behavior with e-Coupons

Qiu¹

2018

SSRN Journal

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In this study, we consider traveler coupon redemption behavior from the perspective of an urban mobility service. Assuming traveler behavior is in accordance with the principle of utility maximization, we first formulate a baseline dynamical model for traveler's expected future trip sequence under the framework of Markov decision processes and from which we derive approximations of the optimal coupon redemption policy. However, we find that this baseline model cannot explain perfectly observed coupon redemption behavior of traveler for a car-sharing service.To resolve this deviation from utility-maximizing behavior, we suggest a hypothesis that travelers may not be aware of all coupons available to them. Based on this hypothesis, we formulate an inattention model on unawareness, which is complementary to the existing models of inattention, and incorporate it into the baseline model. Estimation results show that the proposed model better explains the coupon redemption dataset than the baseline model. We also conduct a simulation experiment to quantify the negative impact of unawareness on coupons' promotional effects. These results can be used by mobility service operators to design effective coupon distribution schemes in practice.

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Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market

Cited by 50 publications

References 14 publications

Social media promotions and travelers’ value-creating behaviors: the role of perceived support

Social media promotions and travelers’ value-creating behaviors: the role of perceived support

Response transformation and profit decomposition for revenue uplift modeling

An Inattention Model for Traveler Behavior with e-Coupons

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