Marketing Mix Optimization – Using Bayesian Network Modeling
Abstract
The challenge in attributing value to your marketing mix has never been greater. Today, a variety of analytic solutions related to last-touch attribution, statistical time series analysis, and market media planning tools is being used to optimize the marketing mix. Most of these solutions, however, fall short due either to reliance on imperfect information related to direct attribution or failing to take into account management assessments, brand studies, product recalls, and other business uncertainties.
At Cooler Heads Intelligence, we have developed a novel analytic modeling approach that integrates Bayesian Network modeling and traditional regression to solve this problem. It incorporates available marketing data, management decisions, business trends, and market research studies to provide a robust and predictive multichannel marketing optimization process that enables us to identify and forecast of the contribution of various offline and online media channels for client decision support and business optimization.
Here we present a client case study for a leading consumer truck rental company to show the flexibility of the approach. Our presentation will cover the following topics in detail:
- Incorporation of data and expertise as key inputs to the network model
- Understanding the contributions and Return on Investment for marketing channels in a multi-channel environment
About the Presenter
Neeraj Kulkarni President/Co-Founder, Cooler Heads Intelligence, Richmond, VA
Neeraj Kulkarni is the President and Co-founder of Cooler Heads Intelligence. He leads the data and analytics vision of the company and manages an incredible team of data scientists from varied industries that have provided cutting edge analytic solutions driving significant return on investment for our clients.
Prior to starting his own company, he had worked in powerhouse advertising agencies like Martin Agency and Havas in leading analytics roles. He speaks at various analytic conferences, writes articles, and sits on the advisory board of the DMA Analytics council, SAS users group, and other analytic associations.