I often hear techie marketers boast about how they are “data-driven” so they don’t get caught up in the errors of human judgment – as if it is possible to make complex decisions based solely on what their computer model, formula or data shows them.
The idea is seductive because with large data sets over a large period of time it is possible to predict patterns, narrow focus and eliminate waste by optimizing marketing efforts and budgets to the predictions of the data model.
But the catch is, it will always take a thinking person to figure out what the data means and how to apply it to real-world actions.
Too many “data-driven” marketers begin relying so much on what the data says, that they ignore glaringly obvious real-world indicators that what the data tells them is incorrect, misinterpreted, or just wrong.
In general consumer markets with huge volumes of searches, transactions, and conversions along with a relatively few possible search phrases or keywords used to find the product – such as in the t-shirt market, it may be possible to see from the data that the majority of sales come from women between 18-35 during the months of March through June, using the keywords “cute tee shirts”, “cute sayings tee shirts”, and “cut t shirts women’s” – then confidently limit spend to women of that age, during those months, and for those keywords to reduce waste and increase ROI.
However, in high cost, low volume markets such as behavioral health services it doesn’t work that way.
This is because the overall volume of searches is low, the cost of clicks is extremely high, and spread over nearly 3,000 keyword variations used to search for a solution for a child’s issues.