An intelligent system for customer targeting: a data mining approach
Decision Support Systems
Bias and variance in value function estimation
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
A decision support system for direct mailing decisions
Decision Support Systems
Bias and Variance Approximation in Value Function Estimates
Management Science
Marketing Models of Service and Relationships
Marketing Science
Customer Metrics and Their Impact on Financial Performance
Marketing Science
Dynamic Catalog Mailing Policies
Management Science
Optimizing the Marketing Interventions Mix in Intermediate-Term CRM
Marketing Science
How to Compute Optimal Catalog Mailing Decisions
Marketing Science
A fuzzy mathematical programming approach for cross-sell optimization in retail banking
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Optimizing marketing planning and budgeting using Markov decision processes: an airline case study
IBM Journal of Research and Development - Business optimization
Competing for consumer's attention
Automatica (Journal of IFAC)
Real-Time Evaluation of E-mail Campaign Performance
Marketing Science
Dynamic Customer Management and the Value of One-to-One Marketing
Marketing Science
Toward a successful CRM: variable selection, sampling, and ensemble
Decision Support Systems
Expert Systems with Applications: An International Journal
Marketing Optimization in Retail Banking
Interfaces
Expert Systems with Applications: An International Journal
Churn management optimization with controllable marketing variables and associated management costs
Expert Systems with Applications: An International Journal
Incorporating Direct Marketing Activity into Latent Attrition Models
Marketing Science
Direct mailing decisions based on the worst and best practice cross-efficiency evaluations
International Journal of Business Information Systems
| Hi-index | 0.01 |
We investigate the key determinants of the optimal direct mail policy in a dynamic environment where customers maximize utility and the direct mailer maximizes profits. We measure the sensitivity of the customers to receiving a catalog in the mail, while controlling for customer characteristics such as elapsed time in responses and number of purchases. We apply our model to a database from a national cataloger that markets nonseasonal products. We summarize the results of our model that are valid for these types of products. We find that the dynamic model significantly outperforms its single-period counterpart. We find that it is not optimal to mail to individuals at low recency levels because they are likely to buy anyway. It is better to save the mailing dollars for customers at higher recency levels. We find that it is optimal to mail to customers who have purchased only a small or a medium number of times to induce them to continue to buy from this catalog and not switch to others. It is not necessary to mail often to customers who have purchased many times before from the company unless they have high recency values. We find that under the optimal mailing policy the cataloguer enjoys higher profits than under the current mailing policy.