For more than three decades, Analysis Group has specialized in using academically rigorous approaches to extract useful insights from data. We help companies achieve a competitive advantage through the use of statistical tools and methods. Bringing together academic, technical, and business expertise, we have developed data-driven solutions to the problems our clients face, including:
How to Optimize Pricing
Our experience in optimizing pricing covers a range of industries. For example, we developed a model to streamline a global pharmaceutical manufacturer’s pricing decisions in the complex, interrelated global pharmaceutical market. By forecasting revenue impacts of price changes in each of thousands of SKUs across countries and over time, we can help executives gauge and manage financial risk.
In the sports industry, we developed reliable estimates of market-clearing ticket prices for teams in Major League Baseball and the National Football League. We used econometric analysis of data on secondary market transactions that led to the Miami Dolphins increasing the price for 56 percent of its seats, leaving prices the same for 31 percent, and lowering prices for 13 percent.
How to Measure the Importance of Product Features in Purchasing Decisions
The ability to identify drivers of consumer purchasing decisions is a potential differentiator for product or services companies. Analysis Group worked with a major US automobile manufacturer to evaluate and quantify consumer preferences when purchasing automobiles. The project required accurate modeling of consumer decisions and preferences through market research and delivery of data to product planners and management in an easy-to-understand format.
In another case, Analysis Group analyzed how consumer purchase decisions related to particular touchscreen-related features in the context of sales of smartphones and tablets.
How to Analyze Consumer Consumption Patterns
Analysis Group’s experience assessing consumer consumption patterns has led us to develop critical insights about consumer behavior. For example, for one client, we analyzed household-level data to determine how various features of DVR devices affected TV viewing and commercial skipping. In another case in the pharmaceutical industry, we synthesized patient and prescriber characteristics available in large administrative claims databases to create a model to predict prescription opioid abusers.
Health Care Economics and Reimbursement Strategy
- Featured Expert Peter S. Fader Frances and Pei-Yuan Chia Professor of Marketing; Co-Director of the Wharton Customer Analytics Initiative, The Wharton School, University of Pennsylvania
Using Sensitivity Analysis to Drive Pricing Strategy
Developing a New Drug Value Profile to Inform Clinical Trials
- On The Cover Big Data in Health Care