Eva Ascarza
Eva Ascarza
Harvard Business School
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Cited by
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Retention futility: Targeting high-risk customers might be ineffective
E Ascarza
Journal of marketing Research 55 (1), 80-98, 2018
In pursuit of enhanced customer retention management: Review, key issues, and future directions
E Ascarza, SA Neslin, O Netzer, Z Anderson, PS Fader, S Gupta, ...
Customer Needs and Solutions 5, 65-81, 2018
A joint model of usage and churn in contractual settings
E Ascarza, BGS Hardie
Marketing Science 32 (4), 570-590, 2013
The perils of proactive churn prevention using plan recommendations: Evidence from a field experiment
E Ascarza, R Iyengar, M Schleicher
Journal of Marketing Research 53 (1), 46-60, 2016
Beyond the target customer: Social effects of customer relationship management campaigns
E Ascarza, P Ebbes, O Netzer, M Danielson
Journal of Marketing Research 54 (3), 347-363, 2017
When talk is “free”: The effect of tariff structure on usage under two-and three-part tariffs
E Ascarza, A Lambrecht, N Vilcassim
Journal of Marketing Research 49 (6), 882-899, 2012
Some customers would rather leave without saying goodbye
E Ascarza, O Netzer, BGS Hardie
Marketing Science 37 (1), 54-77, 2018
The value of first impressions: Leveraging acquisition data for customer management
N Padilla, E Ascarza
Harvard Business School, 2019
Marketing models for the customer-centric firm
E Ascarza, PS Fader, BGS Hardie
Handbook of marketing decision models, 297-329, 2017
Why you aren’t getting more from your marketing AI
E Ascarza, M Ross, BGS Hardie
Harvard Business Review 99 (4), 48-54, 2021
Eliminating unintended bias in personalized policies using bias-eliminating adapted trees (BEAT)
E Ascarza, A Israeli
Proceedings of the National Academy of Sciences 119 (11), e2115293119, 2022
The customer journey as a source of information
N Padilla, E Ascarza, O Netzer
Available at SSRN 4612478, 2023
The twofold effect of customer retention in freemium settings
E Ascarza, O Netzer, J Runge
Columbia Business School Research Paper Forthcoming, 2020
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
TW Huang, E Ascarza
Marketing Science, 2024
Detecting routines: Applications to ridesharing customer relationship management
R Dew, E Ascarza, O Netzer, N Sicherman
Journal of Marketing Research 61 (2), 368-392, 2024
Debiasing treatment effect estimation for privacy-protected data: A model audition and calibration approach
TW Huang, E Ascarza
Available at SSRN 4575240, 2023
Overcoming the cold start problem of crm using a probabilistic machine learning approach
N Padilla, E Ascarza
Beat unintended bias in personalized policies
E Ascarza, A Israeli
Available at SSRN, 2021
New Insights From Emerging Types of Retail Loyalty Programs
V Stourm
University of Pennsylvania, 2016
Modelling customer behaviour in contractual settings
E Ascarza
University of London: London Business School, 2009
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