On realising the utopian potential of big data analytics for maximising return on marketing investments
Journal of Marketing ManagementPublished 12 February 2020
Dries F. Benoit, Stefan Lessmann, Wouter Verbeke
Citations29
SJR quartileQ1
SJR score1.21
SNIP1.18
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Despite the threats and obstacles, exciting challenges and opportunities for creating value are to be explored and exploited by marketing scholars and practitioners.
Abstract
This commentary explores the Big Data transition of the field of Marketing. The potential value of Big Data Analytics for both firms and customers is investigated and impediments for Marketing are identified. It is concluded that despite the threats and obstacles, exciting challenges and opportunities for creating value are to be explored and exploited by marketing scholars and practitioners.
Keywords
Business, Management and Accounting
Technological Forecasting and Social ChangeEuropean journal of operational research
5,378 Citations1990Carlos M. F. Dibb, Carlos M. F. Monteiro +2 more
It is proved the NP-completeness of the problem of minimizing the overhead for scheduling trees on m processors, and then an algorithm is proposed that provides optimal schedules when complete trees are considered.
IBM Systems JournalStrategic alignment: Leveraging information technology for transforming organizations
3,466 Citations1999John C. Henderson, Hemalatha Venkatraman
A model for conceptualizing and directing the emerging area of strategic management of information technology is developed in terms of four fundamental domains of strategic choice: business strategy, information technology strategy, organlzational infrastructure and processes, and information technology Infrastuvture and processes--each with its own underlying dimenslons.
Journal of Information TechnologyBig other: Surveillance Capitalism and the Prospects of an Information Civilization
2,882 Citations2015Shoshana Zuboff
An emergent logic of accumulation in the networked sphere, ‘surveillance capitalism,’ is described and its implications for ‘information civilization’ are considered and a distributed and largely uncontested new expression of power is christened: ‘Big Other.’
Journal of Marketing ResearchThe Customer Relationship Management Process: Its Measurement and Impact on Performance
1,670 Citations2004Werner Reinartz, Manfred Krafft +1 more
European Journal of Operational ResearchBenchmarking state-of-the-art classification algorithms for credit scoring: An update of research
1,143 Citations2015Stefan Lessmann, Bart Baesens +2 more
This study updates the study of Baesens et al. (2003) of classification algorithms in credit scoring and compares several novel classification algorithms to the state-of-the-art in credit scoring and explores whether more accurate classifiers are managerial meaningful.
Journal of MarketingMarketing Analytics for Data-Rich Environments
1,094 Citations2016Michel Wedel, P.K. Kannan
PubMedCompeting on analytics.
769 Citations2006Thomas H. Davenport
Professor Thomas H. Davenport lays out the characteristics and practices of these statistical masters and describes some of the very substantial changes other companies must undergo in order to compete on quantitative turf.
Journal of the Academy of Marketing ScienceDeveloping a customer value-based theory of the firm
705 Citations1997Stanley F. Slater
The Journal of Strategic Information SystemsUsing and validating the strategic alignment model
600 Citations2004David Avison, Jill B. Jones +2 more
The paper demonstrates that SAM has conceptual and practical value and proposes a practical framework that allows management, particularly technology management, to determine current alignment levels and to monitor and change future alignment as required.
Information Systems Research<b>Editorial</b>—Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research
599 Citations2014Ritu Agarwal, Vasant Dhar
This work addresses key questions related to the explosion of interest in the emerging fields of big data, analytics, and data science and the strengths that the information systems IS community brings to this discourse.
Marketing ScienceIdentifying Customer Needs from User-Generated Content
504 Citations2019Artem Timoshenko, John R. Hauser
This work evaluates user-generated content as a source of customer needs and proposes and test a machine-learning approach for identifying customer needs more efficiently.
ACM Computing SurveysA Survey on Bias and Fairness in Machine Learning
317 Citations2021Ninareh Mehrabi, Fred Morstatter +3 more
This survey investigated different real-world applications that have shown biases in various ways, and created a taxonomy for fairness definitions that machine learning researchers have defined to avoid the existing bias in AI systems.
Journal of Marketing ResearchRetention Futility: Targeting High-Risk Customers Might be Ineffective
265 Citations2017Eva Ascarza
It is demonstrated that customers identified as having the highest risk of churning are not necessarily the best targets for proactive churn programs, and this finding is not only contrary to common wisdom but also suggests that retention programs are sometimes futile not because firms offer the wrong incentives but because they do not apply the right targeting rules.
AEA Papers and ProceedingsAlgorithmic Fairness
237 Citations2018Jon Kleinberg, Jens Ludwig +2 more
Modern machine learning techniques substantially outperform logistic regression (the industry standard), though at the cost of being substantially harder to explain to denied applicants, regulators, or the courts.
Information Systems ResearchDoes Fit Matter? The Impact of Task-Technology Fit and Appropriation on Team Performance in Repeated Tasks
230 Citations2008Robert M. Fuller, Alan R. Dennis
This research examines how fit and appropriation (from the Fit Appropriation Model) influence performance over time, and shows that fit can predict team performance soon after technology adoption, but initial assessments of fit are temporary as teams innovate and adapt.
Production and Operations ManagementRecent Developments in Dynamic Pricing Research: Multiple Products, Competition, and Limited Demand Information
223 Citations2014Ming Chen, Zhi‐Long Chen
Journal of Services MarketingCustomer engagement in a Big Data world
213 Citations2017Werner H. Kunz, Lerzan Aksoy +7 more
Sustainability of data-driven customer engagement requires a dynamic and iterative value generation process involving customers recognizing the value of engagement behaviours and firm’s ability to capture and passing value back to customers.
International Journal of Research in MarketingPerformance implications of deploying marketing analytics
201 Citations2012Frank Germann, Gary L. Lilien +1 more
European Management JournalSuccessful customer value management: Key lessons and emerging trends
176 Citations2012Peter C. Verhoef, Katherine N. Lemon
Journal of MarketingBridging the Academic–Practitioner Divide in Marketing Decision Models
158 Citations2011Gary L. Lilien
IEEE Transactions on Knowledge and Data EngineeringA Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models
157 Citations2012Thomas Verbraken, Wouter Verbeke +1 more
A cost-benefit analysis framework is formalized in order to define performance measures which are aligned with the main objectives of the end users, i.e., profit maximization, and is applied to the customer churn problem with its particular cost- benefit structure.
Journal of Business ResearchCustomer churn prediction in the online gambling industry: The beneficial effect of ensemble learning
152 Citations2013Kristof Coussement, Koen W. De Bock
The results show that churn prediction is a valuable strategy to identify and profile those customers at risk and the performance of the ensembles is more robust and better than the single models.
Big DataConscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification
151 Citations2017Brian d'Alessandro, Cathy O'Neil +1 more
It is advocated that data scientists should be intentional about modeling and reducing discriminatory outcomes, without doing so, their efforts will result in perpetuating any systemic discrimination that may exist, but under a misleading veil of data-driven objectivity.
Marketing ScienceCompetitive Price Targeting with Smartphone Coupons
149 Citations2017Jean‐Pierre Dubé, Zheng Fang +2 more
A large-scale field experiment to study competitive price discrimination in a duopoly market with two rival movie theaters, finding an empirically large return on investment when a single firm unilaterally targets its prices based on the geographic location or historical visit behavior of a mobile customer.
Marketing SciencePredicting Customer Value Using Clumpiness: From RFM to RFMC
144 Citations2014Yao Zhang, Eric T. Bradlow +1 more
The deficiency in RFM as a basis for summarizing customer history data compression is demonstrated, and the framework is extended to include clumpiness C by a metric-based approach, finding that C adds to the predictive power, above and beyond RFM and firm marketing action, of both the churn, incidence, and monetary value parts of CLV.
Journal of the Royal Statistical Society Series C (Applied Statistics)Unravelling the Predictive Power of Telematics Data in Car Insurance Pricing
131 Citations2018Roel Verbelen, Katrien Antonio +1 more
Decision Support SystemsForecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
129 Citations2019Mathias Kraus, Stefan Feuerriegel
A structured-effect neural network is proposed for predicting the remaining useful life which combines the favorable properties of both approaches: its key innovation is that it offers both a high accountability and the flexibility of deep learning.
Creating Value with Big Data Analytics
122 Citations2016Peter C. Verhoef, Edwin Kooge +1 more
Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times.
Management ScienceDynamic Pricing in Social Networks: The Word-of-Mouth Effect
117 Citations2016Amir Ajorlou, Ali Jadbabaie +1 more
European Journal of Operational ResearchCan deep learning predict risky retail investors? A case study in financial risk behavior forecasting
116 Citations2019Allen Kim, Yaodong Yang +4 more
A deep learning model is developed for predicting whether individual spread traders are likely to secure profits from future trades, and empirical results suggest that the financial institution which provided the data can increase annual profits by 16% through implementing a deep learning based risk management policy.
Expert Systems with ApplicationsBenefits of quantile regression for the analysis of customer lifetime value in a contractual setting: An application in financial services
109 Citations2009Dries F. Benoit, Dirk Van den Poel
Expert Systems with ApplicationsSocial network analytics for churn prediction in telco: Model building, evaluation and network architecture
100 Citations2017María Óskarsdóttir, Cristián Bravo +4 more
The study statistically evaluates the effect of relational classifiers and collective inference methods on the predictive power of relational learners, as well as the performance of models where relational learners are combined with traditional methods of predicting customer churn in the telecommunication industry, and provides guidelines on how to apply social networks analytics for churn prediction in the telecommunications industry in an optimal way.
Marketing ScienceProbabilistic Topic Model for Hybrid Recommender Systems: A Stochastic Variational Bayesian Approach
93 Citations2018Asim Ansari, Yang Li +1 more
Information SciencesTargeting customers for profit: An ensemble learning framework to support marketing decision-making
75 Citations2019Stefan Lessmann, Johannes Haupt +2 more
Marketing Science<b>Practice Prize Report</b>—An Assortmentwide Decision-Support System for Dynamic Pricing and Promotion Planning in DIY Retailing
74 Citations2007Martin Natter, Thomas Reutterer +2 more
Management ScienceBehavior-Based Advertising
73 Citations2017Qiaowei Shen, J. Miguel Villas‐Boas
This paper finds that behavior-based advertising can lead to lower prices in the initial category if the annoyance of receiving advertising is large, and to higher prices if the annoyed consumers are not too large, as consumers expect a possible additional surplus from the category affected by behavior- based advertising.
European Journal of Operational ResearchA framework for configuring collaborative filtering-based recommendations derived from purchase data
67 Citations2017Stijn Geuens, Kristof Coussement +1 more
A decision support framework to help e-commerce companies select the best collaborative filtering algorithms for generating recommendations on the basis of online binary purchase data reveals that the best-performing algorithm in terms of accuracy remains consistent regardless of the input-data characteristics.
Decision Support SystemsIdentifying influencers in a social network: The value of real referral data
63 Citations2016Iris Roelens, Philippe Baecke +1 more
This study demonstrates that using traditional simulation based methods to identify influencers in a social network can lead to suboptimal decisions as the results overestimate actual referral cascades and finds that looking at the influence of the two-hop neighbours of the customers improves the influence spread and product adoption.
Expert Systems with ApplicationsImproving customer retention in financial services using kinship network information
60 Citations2012Dries F. Benoit, Dirk Van den Poel
Results show that the predictive power of the churn model can indeed be improved by adding the social network (SNA-) based variables, and contextual network based variables turn out to have the highest impact on discriminating churners from non-churners.
World Scientific-Now Publishers series in businessThe History of Marketing Science
54 Citations2014Russell S. Winer, Scott A. Neslin
European Journal of Operational ResearchResponse transformation and profit decomposition for revenue uplift modeling
49 Citations2019Robin M. Gubela, Stefan Lessmann +1 more
Evidence is provided that revenue uplift modeling, as well as causal machine learning, can improve campaign profit substantially, and a decomposition of campaign profit is developed.
Journal of the Operational Research SocietyThe Challenges of Scanner Data
17 Citations1995Steve Baron, Andrew Lock
An overview of many recent studies, predominantly in the USA, which have examined the relationship between marketing variables and customer purchasing behaviour, and the opportunities for operational researchers to further the understanding of such relationships through modelling and data handling are identified.
Marketing SciencePractice Prize Winner—ECO: Entega’s Profitable New Customer Acquisition on Online Price Comparison Sites
10 Citations2015Martin Natter, Ana-Marija Ozimec +1 more
It is demonstrated that ECO’s optimization procedure reduces ENTEGA yearly sales costs for new customer business, on average, by 35% relative to previously used pricing heuristics.
Uplift Modeling
1 Citations2017