With the wealth of social media and sentiment data available yto marketeers it is all too easy to look at the wrong data or dismiss findings that seem challenging. Here are some good tips
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When data analysis suprises you have courage to look at it in different ways
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Suppose a piece of marketing content receives a large volume of likes or retweets, for example. Many marketers would assume the content must be effective. But a marketing piece’s goal generally isn’t to accrue likes; it’s to increase revenue. Revenue doesn’t correlate with retweets any more than the number of bullet holes on a 1940s bomber correlated with vulnerabilities in the plane’s design. When a marketer celebrates retweets and likes without understanding how they affect revenue, he or she is just like the Naval researchers who saw a cluster of bullet holes and assumed, “We should put more armor there.”
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