Looking for a quick way to get started understanding the results of your research?
Projects that are survey research-based can be daunting. So can projects that involve the analysis of sales, promotional activity, advertising, or other marketing-related activity.
We live in a world of complexity and big data. Simple guidelines and a keen eye can reveal patterns that you might have otherwise overlooked. Here are a few tips to help you start analyzing your project:
Take a walk through your data.
Scroll through the data and see where values “pop” – that is, where are they high and where they are low? Do your tables flow in the same way that you think about your business? If so, you will begin to see numbers that imply relationships. As a result, visual outliers can become major insights.
Compare those who are interested versus not.
In the research business, we refer to this as “acceptor-rejecter” analysis. If, for example, you have a five-point purchase scale, group the “fours” and “fives” and compare them to “ones” or “twos”. Throw the neutrals in with the rejecters to compare positives vs. everyone else. Are there larger differences? If so, wWhat can you infer?
Mine the gap.
The benefit of acceptors vs. rejecters is that you are looking more vs. less extreme. The difference between them is valuable in identifying a compelling story. Typically, this is done in the form of point gaps. A large gap between acceptors and rejecters points to an insight.
Sort your data.
you attributes of various features and benefits, sort them from high to low and compare the acceptors and rejecters, or particular demographic groups, such as Millennials vs. Baby Boomers. Sort them on ratings and on point gaps. Larger point gaps can identify attributes that are choice drivers.
Array group you are interested in analyzing by order of magnitude. For example, a variable like education is easy: college educated vs. not. For income, low, moderate, and high income groups make sense and these are easy to compare across. The same is true for any continuous variable, like age. Your eye will see patterns quickly, especially if interest is correlated with your dependent measures.
These little tricks will get you on your way!