This guide was previously written for Community Managers. The same thinking applies to bloggers and small business owners. These statistical analysis techniques will help you make sense of a content strategy for your marketing and social media. I use them to this day in all my content marketing efforts as well as my community strategies.
I remember going to a CMX Summit and watching Evan Hamilton speak. He did a presentation on measuring the ROI of your community. In his talk, Evan used pictures of kittens to keep things entertaining. I remember a feeling of anger over it.
Why do we need kittens?
I get upset at things like this because it encourages the stigma around math and science. That you have to be a genius to like it. Math is valuable in and of itself and carries its own beauty.
There is a lot to gain from even minor uses of mathematics in your daily work. That is what I want to talk about today. How to make important decisions about your community. Using simple statistical techniques that you learned in High School.
I recognize that this article is not about traditional KPI. We will instead be working with raw data collected manually. I have yet to encounter a community platform that gives strong analytic insights. Most focus on vanity metrics which are easy to track. They don’t give us much information that dictates a course of action.
You will be learning techniques that will give you concrete answers. They will tell you how behavior impacts your community.
Here is why there will be kitties.
I know why we need kittens.
There are many people who experience emotional and physical pain over mathematics. A research study from the University of Chicago used FMRI to understand math anxiety. They looked at areas of the brain involved. They saw that areas associated with pain were active. Even when subjects anticipated doing mathematics. They didn’t actually have to do the math because the anticipation was enough.
The current theory is that math anxiety chokes working memory. Making problems more difficult to solve. This has nothing to do with math ability. Those with math anxiety solve problems as correctly as those who don’t have a phobia.
Many people falsely believe that I have a natural talent or ability because I like math. That it comes easily to me. The truth is far starker. I hated mathematics as a child. I flunked my fourth-grade math class and had to repeat it in 5th grade. It was this year that I discovered that I could play games with math. That has helped me learn new concepts ever since.
It has taken me considerable time and effort to learn the techniques which I want to discuss with you today. I cannot promise that you will love mathematics the way that I do now. I do think these methods will improve your work as a community manager. It will help you answer questions about the health of your community and its value.
So let’s dive in.
It’s all about your methodologies.
When I was in school at Humboldt State, I took classes taught by William Reynolds. You may recognize that name if you have ever taken courses in Psychology. He is most well known for his childhood depression scale. It is still a standard used today for diagnosis in adolescents. He’s a big deal.
The most challenging course he taught was the methodology. This is the class where you learn how to design research studies. This is different than statistics where you are learning hypothesis testing. The methodology is about how you set up your experiment so that it answers your questions.
There are things that we need to keep in mind.
- The metrics we measure must relate to the outcome we want to observe.
- They must measure what we say they measure and not explained in other ways
- They must be completed such that important factors are not missing.
- What we decide to measure will impact what we observe.
- What we choose to measure supports our conclusions.
- Repeated measures should have the same outcome.
- Researchers should be able to replicate your results using the same methods.
- Research methods should not be subjective (based on one person’s point of view.)
- Outcomes should not differ between different observers.
- Those doing observations should agree on what is being measured.
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Featured Image Clark Tibbs