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Eva Ascarza
Eva Ascarza
Harvard Business School
Verified email at hbs.edu - Homepage
Title
Cited by
Cited by
Year
Retention futility: Targeting high-risk customers might be ineffective
E Ascarza
Journal of Marketing Research 55 (1), 80-98, 2018
2082018
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
1842018
A joint model of usage and churn in contractual settings
E Ascarza, BGS Hardie
Marketing Science 32 (4), 570-590, 2013
1252013
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
1082016
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
1062017
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
101*2012
Some customers would rather leave without saying goodbye
E Ascarza, O Netzer, BGS Hardie
Marketing Science 37 (1), 54-77, 2018
602018
Marketing models for the customer-centric firm
E Ascarza, PS Fader, BGS Hardie
Handbook of marketing decision models, 297-329, 2017
302017
The value of first impressions: Leveraging acquisition data for customer management
N Padilla, E Ascarza
Harvard Business School, 2019
17*2019
Why you aren’t getting more from your marketing AI
E Ascarza, M Ross, BGS Hardie
Harvard Business Review 99 (4), 48-54, 2021
132021
The twofold effect of customer retention in freemium settings
E Ascarza, O Netzer, J Runge
Columbia Business School Research Paper Forthcoming, 2020
42020
The customer journey as a source of information
N Padilla, E Ascarza, O Netzer
Columbia Business School, 2019
42019
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
32022
Beat unintended bias in personalized policies
E Ascarza, A Israeli
Available at SSRN, 2021
12021
Overcoming the Cold Start Problem of CRM using a Probabilistic Machine Learning Approach
N Padilla, E Ascarza
12019
New insights from emerging types of retail loyalty programs
V Stourm
12016
Modelling customer behaviour in contractual settings
E Ascarza
University of London: London Business School, 2009
12009
When Less is More: Using Short-term Signals to Overcome Systematic Bias in Long-run Targeting
TW Huang, E Ascarza
Available at SSRN 4254202, 2022
2022
Detecting Routines in Ride-sharing: Implications for Customer Management
R Dew, E Ascarza, O Netzer, N Sicherman
Available at SSRN 3982612, 2021
2021
EXECUTIVE SUMMARY: USAGE AND ABUSAGE: FREE REIN
E Ascarza, A Lambrecht, N Vilcassim
Business Strategy Review 23 (4), 76-76, 2012
2012
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