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Why You Should Second Guess Data

We can all agree that nothing makes a droll presentation or seemingly mindless business conclusion more exciting than a pretty bar graph. And eMarketer makes a mint on producing them. Unfortunately, when data gets simplified into a chart or graph, a lot is lost. Sometimes, what’s lost is the entire meaning of the data in the first place.

A recent eMarketer bar graph and accompanying mindless analysis article declared paid social advertising to be more than twice as effective at converting customers as organic social content. If you don’t already know why the conclusion is flawed, you need to think harder about your marketing.

Paid social advertising, if done well, is focused on converting the customer. The purpose is to lead them to a conversion point. Organic social content, if done well, is only supposed to do this every so often. The point of organic content is less about conversion and more about conversation, engagement and relationship building.

Saying paid social is more effective at driving conversion than organic social content is like saying a fishing pole is more effective at catching fish than a socket wrench.

If you look at the eMarketer’s chart, which is based on data from Convertro, the conversion rate comparison on Twitter, Facebook and Pinterest was less than one percent apart with the exception of Twitter, where it was 2.4 percent. Looking at these numbers, and understanding the context of paid and organic social content, I’d be more apt to conclude that paid social is a pointless endeavor than the opposite – which is the direction eMarketer seems to take.

There’s a big difference in having data and understanding data. Let’s think harder as marketers, shall we?

If you need help figuring your data out, drop us a line. We’d love to work with you.

One Response to Why You Should Second Guess Data

  1. Data and graphs can actually be quite useful when trying to convey a point, but I do agree with you Jason that data just for data sake isn’t really helping. People need to go beyond just a few numbers and look at they why, what causes certain data and what the real correlation is.
    Data is very helpful in helping to draw conclusions, but conclusions need to be more thought out than just “here’s a big pile of data.”
    AND, I do agree with your thoughts on the chart presented above.

    Sheldon, community manager for Sysomos

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