Optimization with Choice Modeling
Why Choice Modeling?
Consumers can tell us what they will buy and what they will not buy. But rarely can they tell us what roles price, brand image, package color, brand name, promotional offers, and media advertising play in their purchase decisions. With choice modeling experiments, however, we can implicitly measure the influence of these marketing variables.
Consumers must make brand “choices” when they make purchases. Choice modeling simulates their shopping and decision-making process, with all of the important variables carefully controlled by rigorous experimental design, so that the role and importance of each marketing input can be determined.
“Choice modeling” refers to a family of statistical optimization techniques. Common applications are:
- Pricing Optimization
- Product Design Optimization
- Product-Line Planning
- Market Segmentation
- Brand Strategy Optimization
- Package Design Optimization
- Advertising Optimization
- New Product Concept Optimization
- Promotion Offer Optimization
Presenters
Jerry W. Thomas
Chief Executive Officer
Jerry founded Decision Analyst in September 1978. The firm has grown over the years and is now one of the largest privately held, employee-owned research agencies in North America. The firm prides itself on mastery of advanced analytics, predictive modeling, and choice modeling to optimize marketing decisions, and is deeply involved in the development of leading-edge analytic software. Jerry plays a key role in the development of Decision Analyst’s proprietary research services and related mathematical models.
Jerry graduated from the University of Texas at Arlington, earned his MBA at the University of Texas at Austin, and studied graduate economics at SMU.
Elizabeth Horn
Senior VP, Advanced Analytics
Beth has provided expertise and high-end analytics for Decision Analyst for over 25 years. She is responsible for design, analyses, and insights derived from discrete choice models; MaxDiff analysis; volumetric forecasting; predictive modeling; GIS analysis; and market segmentation. She regularly consults with clients regarding best practices in research methodology. Beth earned a Ph.D. and a Master of Science in Experimental Psychology with emphasis on psychological principles, research methods, and statistics from Texas Christian University in Fort Worth, TX.