During a series of candidate interviews yesterday, I took notice of one particular facet of the resumes that got me thinking. Every candidate listed their academic standing – what degree, plus their GPA (grade point average). For those not familiar with the American university system, GPA is a numerical score between 0 and 4.0 that is supposed to indicate a student’s overall academic achievement, with 4.0 being perfect marks and 0.0 being something along the lines of setting fire to the dean’s car and using all your exam papers as toilet tissue.
What got me thinking was just how deeply irrelevant that score is. GPA tells me overall how good you are at school, but it masks so many variables that it’s nearly useless. For example, let’s say I’m hiring for a marketing intern whose job it is to create content. Compare these two GPAs:
Student A: 3.0
Student B: 3.1
Which student should I hire? Basic common sense says, hire the higher score. But what if you broke down the scores some?
If I’m hiring someone as a content creator, Student B, despite the higher GPA, is clearly the worse choice, because content creation demands outstanding writing skills, but the homogenized GPA score masks that entirely.
Think carefully about homogenization of metrics! Are you masking critical details? One valid criticism of Klout scores, for example, is that they don’t tell you what the person is influential about. A Klout score of 60 is meaningless if I’m marketing B2B software and you’re influential about beer making.
Even our most basic analytics should be called into question. Segment out your data! All web traffic is not the same. You may have an average number of visitors to your website, but perhaps visitors specifically from social media convert at a higher or lower percentage than the rest of your traffic. Find out which segments of your audience truly want what you have to offer and focus your attention and analysis on them. As I often say in my marketing metrics talk, if you’re selling Gulfstream airplanes, you really only need 3 people to read your blog a year… as long as two of them buy an airplane from you.
Beware homogenization. It’s convenient to want to wrap everything up in one big number. Ask questions of scores and averaged measures to see what’s behind the averages. You might find some very profitable, highly un-average niches in there that could change your business overnight.
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- Cómo decide Google Analytics el seguimiento de atribuciones - Christopher S. Penn - Orador principal de ciencia de datos de marketing
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