Penn Jillette did a great sketch in their show "Bullshit!" about how people see numbers. We won't go into the details, but the essence was that we don't actually use numbers that much.

This book is about how to rectify that problem.

So what is in the book?

It's a piece of work that took us a while to get out there into the world. But to break it down we took the view that the whole world sucks at using data including us (at least when we started) so it's not a criticism of anyone. It's just part of a process we had to go through to get to where we are and now we're sharing that with you.

1. Defining the problem. When we lose interest, we become mentally disabled and we start making decisions that suck.
2. Why do we Suck? The 10 big reasons we have for not using data well.
3. Defining the terms. As much as we'd like to avoid acronyms, they exist. So we listed what they mean.
4. Metric definitions. We listed these too. At least the most important ones.
5. Common myths. We dispel some common myths like "I need to measure everything".
6. The Model. The whole point of this book came about after Markus had been pestering Steve for years, demanding respect for the scientific method and hypotheses and urging him to create measurable, repeatable laws for online advertising and metrics. Now we have one. It's simple, but damn effective.
7. Goals and objectives. How to set goals, objectives and tie them to why you're in business.
8. Working out your costs. Working the metrics and KPIs into your business.
9. Benchmarking. Internal and external benchmarks to know how you're doing
10. Customer Testing Lifecycles. When it comes to marketing, we have tons of different life cycles we are dealing with, but often leave unnoticed or neglect to give them the value they deserve.
11. What is the value created. We have made calculating your costs per click and acquisition quite easy already, but how much value is each conversion really creating? Even more, where and how is it created? Can we improve it?
12. Phased sending. Why would you send all messages out at once without testing?
13. Quality versus Quantity. What would happen if you doubled or halved your campaign budget?
14. The Costs Involved. Including the business operating expenses (OPEX).
15. Case Study: GlobalBrand. A case study we had to anonymise but which was a massive brand we worked on.
16. Imaginary Use Case. Scenarios where the methodology can be applied.
17. Everyday applications. Twelve examples of how you can use data in your business from the CEO to the analyst.