May 14, 2013 Jaclyn Bickerton
A came across a great article on Inbound Marketing Agents a few weeks ago called “5 Tips for Interpreting Marketing Data Like Dr. Sheldon Cooper” written by Jasmine Henry that I’d like to share with you. Now I personally don’t watch The Big Bang Theory, but as Jasmine puts it “Sheldon and website analytics are both brutally honest to the point of disregarding other people’s feelings.” Let’s take a look at the simplified version:
Lesson 1: Never Make Assumptions
Marketing data allows you to make some pretty educated guesses about what’s to come in the future. There are various predictive techniques, ranging from very simplistic to the PhD-type of advanced. Jasmine gives us a great example: “By looking at a number of data points about how many people read and share articles I’ve written about inbound marketing analytics in the past, I’m able to make a fairly accurate prediction of how well the content you’re reading will do. However, I’m a lot less accurately able to assume how the dinner I’m making tonight will turn out, because I’ve never made that type of quinoa salad before and have zero data points.” Marketing allows you to make accurate predictions, but only if you have accurate data behind it.
Lesson 2: Be Prepared for Surprising Results, but Have a Healthy Skepticism
Data can be surprising, which is why you need to be aware of biases. If you want to convince your boss that you need to blog less about lawnmowers and more about lawn care, omit a data point that skews results. Being aware of biases before analysis is critical to ensure nothing is inaccurate.
Lesson 3: Know Your Data
When your business blog develops a following, you will get called out if your sources are not up to par. Chad Giddings, VP of Marketing at J. Schmid & Associates recommends the following to ensure your analysis is solid:
– Know Your Data Sources. Know when your data was published, who was surveyed, and read the footnotes.
– Know Your Nomenclature: Marketers have a disadvantage here. There are few universal abbreviations in marketing. Check and double check your acronyms, and make sure you are citing “gross web visits” not something else.
– Know That Not All Data is Useful: Balance the quality of data with its ability to help you tell a story. Just because you have quality data, doesn’t mean you should cite it in your next blog article.
Lesson 4: Compare Apples with Apples
Whether you’re analyzing a set of data collected by someone else, or preparing your own numbers for publication, it can be helpful to use other high quality studies as a point of reference. This can help ensure your numbers aren’t too far off. Be cautious about comparing apples with bananas, in data analysis and content creation.
Lesson 5: Explain Yourself, Please
Don’t cite a bunch of stats or plug some charts into your blog articles. Use this data to tell a story, convey emotion, or convince your readers of something. Back this up with your analysis, so that nothing is lost in translation.
Jaclyn Bickerton, Social Media, Raven5 Ltd, Oakville & Toronto, Ontario, May 2013