Data-Driven Marketing

Jeffery, who taught at Kellogg, argues that most marketing spending is not measured and that a small number of metrics would let executives distinguish what works from what does not. His central claim is that roughly half of marketing spending in the companies he studied could not be connected to any outcome.

His framework identifies fifteen metrics organised into classic marketing measures and internet-specific ones. The classic set includes brand awareness, test drive meaning trial, churn, customer satisfaction, take rate, profit, net present value, internal rate of return, payback and customer lifetime value. The internet set includes cost per click, transaction conversion rate, return on advertising spend, bounce rate, word of mouth and its measurement through referral behaviour.

His argument for customer lifetime value as the central measure is that it connects acquisition spending to the actual return, which allows a company to determine what it can afford to pay for a customer rather than setting a budget by precedent.

He covers the organisational obstacles, including that marketing departments resist measurement because it exposes ineffective spending, that data is held in incompatible systems, and that the incentives reward campaign activity rather than measured return. His testing material argues for controlled experiments with holdout groups rather than before-and-after comparisons, since the second cannot separate the campaign from everything else that changed. The reference has verified the framework rather than every case. The book is from 2010 and the internet metrics and the attribution technology have changed considerably. The fifteen metrics and the argument for holdout testing remain applicable.