I recently published a short piece for WARC Best Practice on “How to set marketing metrics effectively”. The basic idea behind the piece is an explanation of how to decide upon what marketing metrics to use. This work introduces a new acronym that I’ve produced called the WAITA model. Hopefully, this is easy to remember. Why call it the WAITA model? It just like a server (waiter) in a restaurant. It helps you decide what you need.
The WAITA Modle
The WAITA model covers five things to think about:
1) Who is the metric designed to help? Specifically, who is the person making a decision that the metric will be reported to? For example, a junior marketer will probably need the metric at a much lower level of granularity than a CMO.
2) The assumptions behind the metric. To use a metric effectively you must know what it is telling you, without knowing the assumptions you really can’t know what it means.
3) The ingredients, this includes the sources of data. Many problems with metrics trace back to where the data is coming from. This also includes the formula.
One should always expect to see the formula for a given metric being discussed. If the formula is not clearly documented ask for it. If the presenter can’t quickly access the formula or shows signs of not understanding the formula any recommendations cannot be well supported.
Bendle, 2016
4) The theory behind the idea. A number without any theory about what it means is a bit meaningless. We generally are looking for causal links. This metric is going up because of something else, i.e. good performance. Is this theory reasonable?
5) Finally, what actions can I take once I know the metric? A metric that doesn’t influence an action is a bit of waste of everyone’s time.
Improving Metric Use
Hopefully, the WAITA model will help people choose better metrics.
For more on marketing metrics see most of the website. Especially check here.
Read: Neil Bendle (2016) How to set marketing metrics effectively, WARC Best Practice