Please allow me to shed some light towards a frequent misnomer in today's vocabulary and in data marketing– the word, correlated. The expression has been specifically used in marketing for years, both behind the scenes or when marketing a product to a target audience. Check out high cholesterol medication, for instance. Marketers have skillfully suggested that these goods help stop heart problems because cholesterol and cardiovascular disease are correlated. A little something is not really right here though.
Marketers, specifically those focused on data marketing, have to beware that a correlation among two groups of data does not reveal that that one dataset affects the other. Simply put, a correlation does not supply statistical proof of a cause-and-effect connection. I'm not pointing out that it was not great marketing to mention the correlation involving cholesterol and cardiovascular disease, however beware deriving your marketing judgments simply on correlations in your database.
Did you know that the event of diaper rash and construction is exceptionally correlated? Does this indicate that one leads to the other? No. The missing connection is hot climate. Diaper rash and street construction both happen to transpire through the hot times of the year, but neither one is immediately associated with one another (at least to our knowledge).
Regrettably, marketers have contributed to creating some complexity about this topic, so think of this our effort to help put the record straight at the very least in the marketing world. Correlations can help direct your marketing selections, but do not ever always totally trust in them. When you investigate your audience and exactly how they reply to your marketing, take a minute to think about one level below what the correlations are explaining to you. Is it actually only because they're males that they are responding far better? Is the real cause the aspect that they're in between the ages of 18 and 24? Digging deeper utilizing sophisticated data marketing or having a closer look at your target audiences' qualities will certainly reveal a clear image of what honestly leads them to act.
If you have time and capacity, run a statistical regression analysis to help discover the variables that unquestionably create much higher bids to react. With adequate information and time, a profitable data marketing crew can forecast the actions of a target audience with exceptional correctness, letting you to segment groups that openly respond.
And keep in mind, next time you check out that cholesterol commercial do not be so speedy to drop your delectable bratwurst grinder. You can eat with a much less sense of guilt, recognizing that unhealthy fate is simply correlated.