Incorporating Statistics into Your Marketing Strategy

October 14, 2021

Last month we discussed the benefits and methodology of understanding your audience’s interests, and today, we'll be discussing another foundational element of marketing strategy: statistics! Yes, we're going back to math class, because interpreting statistics is the basis of any successful campaign. Don’t worry, you don’t have to be a mathematician. We’re only going to be scratching the surface, but feel free to use what you learn here about data management and build from it.

Establishing a Specific Goal

It almost seems unnecessary to note that you need to have a goal in mind before conducting research, but it’s too often that steps like this are skipped! First, think about why you are assessing your market statistics, to improve your business of course, but get more specific than that! Are you looking to better relate to your community? Do you want to update your color scheme to something trendier? Figure out what area of your business could benefit the greatest from dedicating time to research and build your goal around that.

Here’s a helpful analogy: think of your goal like the hypothesis to an experiment. You can’t proceed without a well thought out goal, just like you can’t conduct an experiment without a well thought out hypothesis.

Hunting for Raw Data

Collecting information can be either the most exciting portion of statistical analysis or the most grueling. You should be familiar with this one, because we explored some of the ways you can gather information about your audience in the last blog post. Here, we’ll be putting that data to use! First, however; we must delineate raw data and how it differs from what you end up with after you put it through analysis.

“Raw” or unrefined data refers to information you’ve gathered without influencing it in any way. As an example, we’ll use the students in preschool class as our sample. Each of those students’ favorite color is our raw data. Now, this doesn’t do much on its own— that’s what this next part is all about!

Organizing Raw Data into Something Useful

Comprehending data is a matter of turning it into a valuable form. We’ve assembled our data, now we’ll make it useful by expressing it in a structured manner. Let’s continue with our preschool example: say five of our students told us their favorite color was red, seven said blue, and three said green. While it can be easy to make inferences based on this simple set, we’ll pretend that this data needs to be organized to be properly utilized. There are multiple ways you can depict data: line graphs, pie charts, bar graphs, each with their own advantages. These are all excellent methods of depicting data, but before you make any of them, you’ll need to construct a frequency table.

Frequency tables are the easiest of the bunch to build, in a visual sense and in terms of complexity. Pictured here is a table using the data above. With the assumption that your raw data won’t resemble a table already, assembly is still quite easy. Construct two columns and label them accordingly: the left column is your qualitative data, meaning that it represents a category rather than a numerical value, which is your quantitative data. Your quantitative data goes in the right column. Continuing with our example, you can see the categories aligned in separate rows on the left, and their frequency recorded in each respective row.

From here you can extrapolate data as needed: divide each quantitative value by the sum of frequencies and multiple by one hundred, and you have each category’s percentage frequency! Calculating percentages can be a lot easier than trying to move around six, seven, and eight-plus digit numbers. Again, our example is fairly simple on its own, but if we had been working with a greater number of categories or larger frequencies, then building a table like this and calculating percentage is a useful tool! To plug this all back into our example, however, we would determine the percentage frequency of each category using the above method, which gives us a result of: 46.67% Blue, 20% Green, and 33.33% Red. 

There is a plethora of ways the information we gathered and assessed can be useful! Perhaps you’re a teacher who wants to make sure they have enough crayons for everybody to use. If you only have one or two shades of blue, then this data may prompt you to get more blue crayons. Or maybe you want to help you students with a mural and need to know what colors the students will appreciate most. The possibilities truly are endless, and the benefits of analyzing your business this way are endless as well!

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