Two of my MBA professors, Paul Farris and Ron Wilcox, along with a newer Darden professor Raj Venkatesan, have a new book. This examines using marketing analytics through cases. (Raj also runs the marketing analytics initiative at Darden).
Numbers-Based Marketing
The cases describe scenarios relevant to numbers-based marketing. For example, they allow readers to see the benefits of customer analytics in retail banking. Beyond the cases, the authors share some advice on conjoint analysis. (This is a way of uncovering what people care about from their choices. For example, how powerful is brand in a purchase. You might ask people to pick one of two TVs showing various combinations at different prices, sizes and from different brands). The book also touches on logistic regression. They also impart helpful notes on marketing experimentation. A real problem is ascribing causation in marketing activities. What caused something to happen? This can be compared to what is merely associated with what happened.
The book finishes with thoughts on how to implement marketing analytics. This is important. My experience suggests that many marketers want to be more analytical. Sadly, they just don’t know where to start.
Marketing analytics powered by “big data” holds the promise to shift marketing strategy from an intuitive discipline to a fact-based, decision-making process.
Venkatesan, Farris and Wilcox, 2104, page 282
Managers can certainly benefit from improving the way they measure the effectiveness of their marketing. The professors outline some ways to get to improved analytics. They show, in the cases, how firms have, or could, use marketing analytics to drive success.
Decide Your Marketing Metrics Upfront
One helpful suggestion in the book is:
It is important that organizations decide the metrics for evaluating the effectiveness of marketing spending upfront and share those metrics widely.
Venkatesan, Farris, and Wilcox, 2014, page 284
This matters because there are so many metrics to choose from. If you don’t specify which you care about in advance it is a problem. You are bound to find ones that look good. Still, did you really care about that before it looked good?
So what should we choose? They suggest specific metrics. “Return on Investment (ROI) is, however, the most common metric in assessing the value of marketing tools because it is the easiest to use in analytical marketing mix models” (Venkatesan, Farris, and Wilcox, 2014, page 284).
Using Marketing Analytics
It seems to me that marketers are a long way off where we might be using marketing analytics. Hopefully, with this, and similar books, we’ll get there.
For more on analytics see here, here, and here.
Read: Raj Venkatesan, Paul Farris, and Ron Wilcox (2014) Cutting-Edge Marketing Analytics, Pearson