“When you have mastered numbers, you will in fact no longer be reading numbers, any more than you read words when reading books. You will be reading meanings.” – W.E.B. Du Bois
Numbers can be intimidating, which can often prevent people from fully utilizing and understanding quantitative research results. When used correctly, numbers can sometimes be more accurate than words, but it is the quality of the analysis process that brings meaning to those numbers. Numbers do not speak for themselves. Interpretation and analysis bring quantitative results to life and help them to positively impact your business decisions.
Start With the Basics
The first step in analyzing quantitative results is to realize that analysis comes in two phases – before and after the research is conducted. Prior to conducting the research, you need to think through what key questions you want to answer and what form the data needs to be in to correctly answer those questions. Quantitative research should be structured in a way to address the key questions and provide the necessary data in the correct form. For instance, if you are wondering if consumers would recommend your new product to a friend, you can’t gather that by asking the overall appeal of the product and even if you do ask likelihood to recommend, you won’t know the fervency in which it will be recommended unless you use the correct scale.
Identify Your Metrics
The three fundamental metrics we find to be most effective in the majority of quantitative tests are purchase intent, uniqueness, and believability. After conducting analysis on the various metrics we use, including correlation analyses, we found the combination of these metrics to be the least correlated and the most descriptive.
Once the correct structure and metrics have been chosen, the post analysis becomes the main focus. When interpreting quantitative results, I would argue that the most crucial part to look at is actually not the individual metrics, but rather the relationships between the metrics. Those relationships reveal much more about how consumers feel about the item in totality and how it will actually perform in market.
The chart below shows the different relationships between purchase intent, uniqueness, and believability. Once you understand the relationship between the three metrics, you are able to unlock key implications and arrive at the appropriate next steps. For instance, if purchase intent is low but uniqueness and believability are high, the general market is not ready for it yet. A lot of new technology products fall into this category.
|Purchase Intent||Uniqueness||Believability||Key Takeaways||Action|
|High||High||Low||Too Good to be True||Focus on Credibility|
|High||Low||High||A Good Option||Differentiate or Win on Value|
|High||Low||Low||Doubtful||Rework to Increase Both Differentiation and Credibility|
|Low||High||High||Not Ready for this Niche||Explain the Need or Set the Niche Strategy and Expectations|
|Low||Low||High||Not Needed in the Market||Scrap|
Companies overcome this by explaining what the product does and why the consumer needs to have it in his or her life. Just because a product does not score high in every metric tested within a study, does not mean that it should be scrapped and not pursued. A great example of this is when purchase intent and believability are high but uniqueness is low. These results do not necessarily imply that the product/concept/marketing material won’t be successful; they simply imply that the item being tested needs to focus on differentiating itself from others in the market and/or focus on providing better value than other alternatives.
Wrap It All Together
As the opening quote commented, mastering numbers goes beyond understanding a percentage or a mean. Quantitative results requires understanding the relationship between the numbers and the implications that they reveal.
Partnering with a vendor that has flexible quantitative and qualitative research is critical for the success of each individual study. Companies want their results to answer critical business questions, including questions that come up both planned or unexpectedly. GutCheck’s quick consumer reads help brands get the answers to these key questions, fast! If you would like to learn more about how GutCheck can assist with your research plan, request a demo today!
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