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Rumors, Lies and Surface Level Facebook Analytics

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It’s important to look at the whole picture when examining analytics and not look at data isolated to one environment. Reaching a conclusion after viewing a single report may cause you to miss problems in the larger ecosystem.

An Example – Facebook Analytics

We recently consulted with an online shop owner. This owner came to us for online marketing and promotion. Deeper analysis revealed an issue that more online promotion wouldn’t fix.

We used Facebook Analytics, to uncover that their Facebook page had a majority of females aged 17-25 ( a demographic many would consider to be valuable). Analysis of actual buyers revealed that most were over the age of 25. The graph below shows just how far off the Facebook page was from the actual demographic of buyers. You can’t market to 23-year-old women the same way you market to 35-year-old women. The Facebook page had a respectable number of likes, but they were targeting the wrong demographic that lead to a poor referral rate from Facebook and can result in a lot of wasted time and money.
Understand your buyer

The Fix

To rectify this situation, we had to take a different strategy than most would have given only the Facebook page insights.

We split the content into two groups: one targeting the 17-25 demographic and another targeting the 25-40 group. 

We could then test the performance of the posts to see which content resonated best. Throw in a little paid promotion to our more ideal buyer and Facebook has become a much-improved source of referrals.

Conclusion

This problem is not only relevant to Facebook Analytics but can apply to any environment a business operates in.

You can’t solve a puzzle with only one piece. The best way to understand your ecosystem is to see how the parts work together and if you have a squeaky wheel, you’ll be able to identify it.

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