Analytics or intuition? What’s most important? There’s a spirited debate around this question. Are the big data and analytical “quants" really going to rule the new world? Or, will the more intuitive and creative types offer leading companies the competitive edge? A quick review of three independent surveys across thousands of companies yields this answer: analytics is your winner. Let’s take a look at our three sources: Bain & Company, MIT Sloan Management Review, and the Product Development Institute (related to Stage-Gate International).

We’ve already blogged about the challenges life insurance marketers will face this year, and how these insurers can effectively reach untouched consumer segments (e.g. low to middle markets) and adapt to changing consumer bases. Since then, FGI surveyed over 1,500 consumers about their perceptions of life insurance (LI) coverage. From this data, we discovered consumer attitudes towards purchasing LI and found common patterns among those who do and don’t choose coverage. Below is an overview of some key findings.

If you would like to see more results from our study, you can sign up for a walk through. Find out how the insured and uninsured compare, and get suggestions on how to reach the "not right now, but someday" consumers.

It's not a secret that we like grocery infographics.

Health insurance companies need to understand their changing market landscape in order to prepare for a time when the population has greater choice under the Affordable Care Act (ACA) and providers are forced to compete for members.   And there are certain fundamental questions that face a company when competing for these customers

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Want to know more about grocery trends and digitally active grocery shoppers? Check out our Grocery Voice Panel.

We often use SPSS or R tables to conduct hypothesis testing—also known as testing for statistical significance—between means.  These outputs generally provide t-test results, and in SPSS at least, produce a little alphabetical footnote when a difference is statistically significant.   It’s quick and easy, but the problem is that it’s wrong.  Even using the Bonferroni adjustment (which compensates for the fact that there are more than 2 groups being compared), it will commit Type II errors (it says something is not significant when it is) as well as the more common Type I errors (saying something is significant when it’s not).  So what do we do?

Online communities are among the most important qualitative tools driving online market research today. But, how can you use it and prove ROI? Many success stories start with creating personalized studies to gain information about your audience. And with an online community, you can make your own activities, tasks, and discussion forums to gain beneficial findings. Additionally, you can target and engage a specific segment of participants to further mine data and feedback on products, services, concepts, or ads. To do that, follow these 4 key steps for creating your awesome online community:

Google’s announcement and launch this week of a market research offering has had the market research and technology industries buzzing. And understandably so. As this article from the GreenBook blog points out, the world’s biggest search engine company already has access to millions of consumer data points (thanks to Gmail and Android phones), and now they are going to ask those millions of users and their friends about their shopping, product, and marketing preferences one question at a time.