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Who should attend Forecasting Models for Customer Behavior and Lifetime Value
Marketing research managers, research analysts, customer satisfaction managers, customer loyalty managers, marketing researchers
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Forecasting Models for Customer Behavior and Lifetime Value  

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Seminar Summary:

During this 2-day in-depth analytical seminar you will learn how to use readily available purchasing data to examine forward-looking aspects of customer behavior.  (see full course description)

 
 
 

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print the agenda print agenda for the Forecasting Models for Customer Behavior and Lifetime Value seminar

 

Training Course Syllabus:


Specifically you will learn:
• What is the correct way to approach the calculation of customer lifetime value (CLV) and why standard practices are inadequate.
• How the nature of the firm’s relationship(s) with its customers influences the development of appropriate models of buyer behavior.
• What are the key “building-block” probability models for counting, timing, and choice phenomena and how to implement these basic models from scratch in Excel.
• How these basic “building-block” models are combined to create integrated models of buyer behavior.
• What are the key criteria for evaluating the performance of integrated models of buyer behavior.
• What factors we need to take into consideration when implementing these models.

8:30 - 8:45 Introduction

8:45 - 10:15 INTRODUCTION TO PROBABILITY MODELS (I): How to develop (and implement in Excel) a simple probability model for projecting customer retention. Comparing and contrasting this approach with more traditional regression models.

10:15 - 10:30 Coffee Break

10:30 - 12:00 INTRODUCTION TO PROBABILITY MODELS (II): Stepping back: what are probability models and what kinds of managerial decisions can they address? Two more live applications: forecasting new product adoption (models for duration data) and projecting media exposure (models for count data).

12:00 - 1:15 Lunch Break

1:15 - 3:00 MAKING INDIVIDUAL-LEVEL PREDICTIONS: Introducing and using “conditional expectations” to create our best guess of what an individual will do in the future as a function of past behavior. Application in the area of predicting response to a direct marketing offer (models for choice data).


3:00 – 3:15 Coffee Break

3:15 – 5:00 BRINGING IN COVARIATES: How to introduce demographics, marketing mix effects, and other external factors into these probability models. Assessing the statistical and managerial significance of these variables.

8:30 - 10:15 USING PROBABILITY MODELS FOR CUSTOMER-BASE ANALYSIS: Comparison of modeling approaches; classifying analysis settings; the right way to think about computing customer lifetime value (CLV).

10:15 - 10:30 Coffee Break


10:30 - 12:00 MODELS FOR CONTRACTUAL SETTINGS: Basic models of contract duration. Application: valuing an existing customer base. The perils of ignoring heterogeneity when valuing customers and determining retention elasticities.

12:00 - 1:15 Lunch Break

1:15 - 3:00 MODELS FOR NONCONTRACTUAL SETTINGS (I): Modeling the basic transaction process; modeling the spend process. Criteria for evaluating models. Use models to compute CLV given RFM measures. Case study.

3:00 – 3:15 Coffee Break

3:15 – 4:30 MODELS FOR NONCONTRACTUAL SETTINGS (II): Modifying basic models to facilitate implementation in Excel. Modifying models for discrete-time settings. Review of all tools and Excel spreadsheets. How to start applying these models at your firm.

4:30 Concluding Remarks

FORECASTING MODELS FOR CUSTOMER BEHAVIOR AND LIFETIME VALUE What Past Participants Have Said About This Seminar Verbatim evaluations from participants who have attended the “Forecasting Models for Customer Behavior and Lifetime Value” seminar. Names of evaluators have been left out as a matter of professional courtesy. The content was extremely innovative and is not something you would hear about in 99% of other marketing research seminars, workshops, or conferences. (Speakers) were EXCELLENT teachers/facilitators. I have taken a number of statistics courses and workshops and these were two of the best teachers at being able to explain complex statistics in an a fairly intuitive manner. The plethora of real world examples definitely helped. Vice President, Statistical Sciences Walker Information I really like this seminar. (Speakers) are real experts in this field and the seminar expanded my knowledge in this field. However, their models are based on individual-level data while my job is to analyze aggregate data, which the models can not apply to. But I do think Burke should have more of this kind of high level seminar that definitely stimulate intellectual understanding of marketing and also boost the level of statistical skills. (Speakers) have very strong background and I feel like I was sitting in my graduate class and was taught by the best in this field. Motorcycle Market Analyst Honda R&D Americas, Inc. The seminar pulled together years of research on the topic of forecasting and consumer choice, in a clear understandable format. I have completed undergraduate work in mathematical probability & the course was perfect for my level of understanding. (Speakers) are lively and interesting presenters. Their styles complement each other quite well. They involve the class in the process of problem-solving, which keeps interest & alertness at a fairly high level. Senior Research Specialist Northwestern Mutual

Seminar Summary:

During this 2-day in-depth analytical seminar you will learn how to use readily available purchasing data to examine forward-looking aspects of customer behavior.  (see full course description)

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