Online Marketing Research

Imagine the pool of data that can come back from a market research survey:

• 85% Male, 15% Female
• 70% use Windows, 22% use Mac OS, 8% use Other
• 12% C-Level Executives, 39% Managers, 49% Non-Managers
• 8% Highly Interested, 29% Interested, 42% Somewhat Interested, 21% Not Interested

Without connections, or associations, between these data points, this market research can lead to poor decision making. At first glance, a software company executive might think, “We should cater our product toward a male audience with appropriate advertising. The CD that comes with the product should be for Windows. After all, look at all the decision makers (51%) and those showing interest (79%)!”

Again, at first glance, this may seem viable, but without tabulating the correlation values between each of the data points, it is impossible to make such assumptions! What if the 15% of females surveyed constituted all the C-Level Executives and many of the decision making managers, while those who stated a high interest were mostly Mac users?

The only way to identify such connections is to use cross-tabulation analysis with your survey data, which can reveal valuable associations between any two data points of your choosing. Commercial grade survey technology should have built-in cross tabulation capability so you can avoid doing complicated statistical calculations in multiple applications.

Make sure you can quickly and efficiently reveal these connections before relying on your market research to make decisions.