Data analysis and utilization leads you business to new heights. Weather it is email marketing or online ad campaigning, analyzing the market helps you target the right mass.

In the process of data analysis, marketers face various challenges and make mistakes. MOZ columnist Tom Capper has shared four data analysis pitfalls and has provided ways to avoid them.

Capper says, “Digital marketing is a proudly data-driven field. Yet, as SEOs especially, we often have such incomplete or questionable data to work with, that we end up jumping to the wrong conclusions in our attempts to substantiate our arguments or quantify our issues and opportunities.

In this post, I’m going to outline 4 data analysis pitfalls that are endemic in our industry, and how to avoid them.

1. Jumping to conclusions

Earlier this year, I conducted a ranking factor study around brand awareness, and I posted this caveat:

“…the fact that Domain Authority (or branded search volume, or anything else) is positively correlated with rankings could indicate that any or all of the following is likely:

  • Links cause sites to rank well
  • Ranking well causes sites to get links
  • Some third factor (e.g. reputation or age of site) causes sites to get both links and rankings”
    ~ Me

However, I want to go into this in a bit more depth and give you a framework for analyzing these yourself, because it still comes up a lot”.

Don’t Be Fooled by Data: 4 Data Analysis Pitfalls & How to Avoid Them

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