A Short Guide to Marketing Model Alignment & Design: Advanced Topics in Goal Alignment – Model Formulation (Volume 1) - Softcover

Young, David

Softcover

ISBN 10: 1543912591 ISBN 13: 9781543912593

Publisher: BookBaby, 2017

Synopsis

How this book is different from other Marketing Modeling books and what you can get from it

This book integrates Marketing and Statistical concepts and is written for Marketing Modelers, Model Users, and Purchasers of marketing models.

Most books on Marketing Modeling are slightly modified statistical texts.

If you're looking for a book that talks about the "logic of marketing" and the "design of statistical models" in an integrated way to increase model accuracy and improve business profits, then this book was written for you.

Marketing Models are neither just Statistics nor just Marketing, but a synthesis of the information sources creating a cohesive predictive system, and the broader you cast your net for useful information the better your models will be.

Nevertheless, anyone who's worked around Marketing Models at all will have heard people talk about modifying models for "statistical reasons" or modifying them for "business reasons" as though the two sets of criteria are from Mars and Venus, respectively. In this book, I try to help readers develop a deeper understanding of the reasoning behind both sets of rules to put themselves in a better position to weigh the value of all evidence and define the most applicable business goals for their models to address. And after defining those goals, design the best models for achieving them.

Too often, modeling objectives are defined quickly and without much thought. In many cases, standard statistical techniques are pulled from the "tool box" and applied without aim. Oftentimes the models resulting from that process are reasonable, although typically not optimal. Other times they're clearly lacking, however the business users (and sometimes competent modelers) are fooled by the façade of science surrounding the modeling process. Hence, criticism is often deflected and the models can live on, even if their efficacy has become dubious.

If you'd like to better understand:
•how to define dependent variables to maximize business goals;
•how business logic should influence your model design;
•when lower R-Squared statistics can represent better models;
•how much information you can reasonably expect from your data;
•how to safely work with imperfect data that may offer partial information but that shouldn't be naively relied upon, and;
•ultimately how to create models offering superior business value
… then read on.

About this title

About the Author

David Young has 25 years of experience in Marketing Modeling applied to Marketing Mix Modeling, Choice Modeling, Market Segmentation, Propensity Models, etc. He currently works as a Senior Group Director at Neustar in McLean, VA managing a team of 10 modelers whom optimize about 2 billion dollars of annual advertising dollars across multiple, often multinational clients. A native of the USA, he also lived in Madrid, Spain for ten years and speaks Spanish passably well. He's an invited speaker at various Data Science venues.

From the Back Cover

Marketing Models are neither just Statistics nor just Marketing, but a synthesis of the information sources creating a cohesive prediction system. If you're looking for a book that talks about the "logic of marketing" and the "design of statistical models" in an integrated way to increase model accuracy and improve business profits, then this book was written for you.

Praise for "Marketing Model Alignment & Design"

"Your upfront emphasis on Marketing Model Alignment...aligning and balancing the business reasons and the statistical reasons is refreshing...I believe many authors and colleagues frequently overemphasize the data-analytics technology (i.e., data science & engineering) processes at the expense of the need for alignment of business-marketing goals and analytics-modeling goals as the foundational context to achieving material incremental business, brand and customer value."
Karl W. Lendenmann, President, DecisionTree Analytics & Services, North America

"I thought the section on Information Adequacy is very, very, relevant to the practitioners of everyday marketing analytics. This will be a great guideline book for the beginners and even for the advanced modelers."
Gurkan Senner, Advanced Analytics Leader, Accenture

"I think the Information Adequacy section makes some really great points!"
Randy Bartlett, Author of "A Practitioner's Guide to Business Analytics", Blue Sigma Analytics

"Your book brings important and subtle marketing issues from the analytical subconscious into the intuitive forefront."
Panagiotis (Panos) Ventikos, Owner, Delta Analytics

"Very practical and very real world"
Natalie Robb, Principal, Wavelength Analytics

"Really enjoyed the read."
Chris Checco, Managing Director - Advanced Analytics & Monetization Solutions, Synchronoss Technologies

Edition details

• Publisher: BookBaby
• Publication date: 2017
• Language: English
• ISBN 10: 1543912591
• ISBN 13: 9781543912593
• Binding: Paperback
• Number of pages: 68