Conducting market research is a phenomenal way to learn more about your customers and discover the best use of your marketing dollars. Collecting data about their preferences, habits, demographics, and more can give you insight into parts of your business you may not have a strong breadth of knowledge in.  

Once you have created and distributed a survey and received back a sizable number of responses, you can dive into those responses.  

What are data points? 

The data points are the actual pieces of information from the responses you receive. The number of responses, the demographics by percentage, gender, and actual answers to each question are all data points. 

Even taking this a step forward, data points can also include statistical information like average answers. For example, you can calculate the average income of respondents if that is a question you have asked in your survey.  

While these data points are important, they aren’t always relevant or valuable. In theory, you have sent your survey to qualified recipients, such as existing customers or in-market buyers, so your demographic information is useful. Still, there is no way to know absolutely whether the information is valid and therefore relevant.  

Ultimately, data points can just be described simply as facts.  

What are data insights? 

Data insights are the meat and potatoes. The data gave you the ingredients you needed to make a meal, and the insights are the finished product.  

Data analysis is the second of two major parts (the second being data collection). You must know what the information means and why it matters to your market research.  

Ultimately, data analytics “is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data”  

You can see from your survey that 70% of respondents were women. That’s data.  

Let’s look at an example of data analysis: 

What you can also see is that women responded much more favorably when asked if they had a pleasant experience with your product, while men generally responded that they were disappointed in the product. This could tell you several things. First, it could show you that marketing towards women will gain you more buyers than marketing directly to men. Additionally, it could tell you that you need to improve or change your product to become more attractive to me (assuming you want to grow that market).  

You can do this same type of analysis with any information you receive from the data.  

Why bother? 

You can certainly conduct a survey as an information grab. Maybe you really just want to know what people think about your product or what your customer demographic is.  

I would venture to say, however, that gathering this information is pointless if the knowledge isn’t applied.  

Knowing you have a large customer base of women doesn’t do you any good. Knowing you have a large customer base of women despite your marketing being used to target men is good information to have.  

Conducting market research is done predominantly to gain information in order to solve a marketing problem. If you are interested in growing your market, changing your product, evaluating your competitors, etc. you will need the data and analysis to come up with a plan to execute.  

Wrap it up 

Let’s go back to my food analogy.  

You have a basic understanding of cooking fundamentals. You are tasked with making a dessert for a potluck. I will give you flour, sugar, butter, vanilla, eggs, baking soda, and a lemon. There are several things you can make with those ingredients. Bread, sugar, lemon squares, pancakes. It’s your job to decide what to make with those ingredients, and how you are going to use each one to reach your goal of creating a dessert.  

The same goes for data and insights. You can have a goal in mind for business and have all of the data ready to go, but you need to develop that information into something useful and tangible. 

That gives you the opportunity to create something amazing.  

(Also, I vote lemon squares.)