John Hayes posted on January 09, 2013 |
My son gave me “The Signal and the Noise”, by Nate Silver this Christmas. It talks about why predictions are so hard. And it relates directly to engineering marketing.
We all make predictions in our marketing jobs. We anticipate how many times a certain piece of content will be viewed. We predict our conversion rates. We count on old distribution channels and distrust new ones. But Silver’s book says that our predictions are biased in every case and that these biases can have a catastrophic effect on our accuracy.
The most common biases we hear from engineering marketers are:
- Leads convert into sales at the same rate regardless of the lead source
- Awareness advertising is neither measurable nor worthwhile
- The more data you have about a lead (ie, the more fields they have filled in) the more valuable the lead is
- There is no connection between the quality of the marketing asset you offer (webinar, white paper, free download, etc) and the propensity of a lead to convert
Our research suggests that all of these assumptions are false. However, these biases are likely to persist because most marketers are evaluated by the number of leads they generate rather than by the sales that eventually convert.
Thankfully, many of our clients are implementing marketing automation tools that track leads through to sales. The data these provide should reduce our biases going forward.
Do you agree with the risks of these biases? Any others I've missed?