As people move from experience and gut feel to hard facts, numbers and mathematics are taking a pivotal place across marketing departments. What only a field executive could judge and tell the managers is now collected through various apps and open to use to predict the right type and time of a specific advertising campaign or product launch.
Data by itself is useless. Unless, you know how to use it in context and apply the right analytical model to get the information that you want. Marketing Analytics by Mike Grigsby helps you with this critical problem. Not everyone working in the marketing field has extensive understanding of statistics and probability or understanding of the advanced modeling techniques required to get reliable information.
Mike Grigsby has worked in marketing analytics for nearly three decades with Dell, HP, Sprint, the Gap and now as a consultant at Targetbase. His PhD is in marketing science, he has taught marketing analytics at UTD, UD, St Edwards, etc.
Author: Mike Grigsby Series: Marketing Science Pages: 248 pages Publisher: Kogan Page; 1 edition (June 28, 2015) ISBN: 0749474173, 978-0749474171
Marketing Analytics is for executives who want to harness the power of statistics and data availability to make decisions that will give them the results they are aiming. The first couple of chapters take the reader through the basics of statistics that you have studied in school and may have long forgotten. Along with the basic statistical measures and what they really mean in context of the consumer and markets, the author also talks at length about probability. A, B, or C – anything can happen, but it is most important to know which of these three are most likely to occur.
Even when you have a basic understanding of statistics and analysis, it is not always obvious to match a particular type of analysis or model to a specific problem to get the information that you need. The author mainly talks about applied marketing analytics and helps the reader make this connection. The detailed business cases with datasets and calculations show the readers how they can use the data that they have to get specific information from their data.
For example, Who Is Likely to Buy and How Do I Target? Answers this critical question every marketer asks. The case study focuses on database or email marketing campaigns. The author explains which model is most suitable to identify potential customers in a list, and how to sort the list so that the marketers get maximum ROI for their campaign.
In Part IV, Marketing Research, the author introduces Conjoint Analysis to determine important product features for a new product. He also cautions the reader and points out the differences between survey data and data extracted from a marketing database.
Statistical evaluations are the right way to go, but they need to be performed in a very specific manner and conditions. One of the most important and primary question in any experiment is the population sample size. Who and How many? The author talks about how to design a test so that the results you get are accurate in Statistical Testing.
Marketing Analytics is a good resource for someone who has just started out in analytics or has interest in marketing analytics. The introduction to the theory and concept behind using a particular technique to solve a specific problem helps the reader better understand the application of statistical methods. The detailed business cases, explained in story form help see the real-world example of the analytical model adopted for the problem.