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If you are a regular reader of our blog or newsletter, you know that we’ve been writing a lot this past month on our GutCheck approach to research (agile research using on-demand communities) and how it compares/contrasts with other research methodologies. So far I’ve tackled traditional focus groups, online focus groups, and online communities. Today’s blog topic is online quantitative research.  There’s so much to unpack with this topic that we’ll cover in two blog posts, this one and then another early next week.

As I suspect you know, quantitative research (much of which is online these days) gives consumer insight professionals the answer to their question; qualitative research gives the why and how to improve the concept or copy in question. In today’s research world, online quant accounts for the largest part of the market at 22 percent (source:  Global Market Research 2012). That means a lot of you are engaging in online quant.   

What I want to challenge you with today is how to make that investment even more effective.

Here’s an example of a research challenge you may have faced. If you have three concepts, should you do a 400-person quant study or a 40-person qualitative study, such we employ at GutCheck with our IRCs?  Too often it is a one or the other decision. But it really should be both. 

When our clients combine qual and quant, they can get to the finish line with an optimized concept, and haven’t wasted time and money testing concepts that are not optimized. I’ll expand on that in a moment.

So when is quant a good way to go? As you probably know, this approach is good to use when the team requires:

  1. Statistically significant analysis
  2. Predictive analysis, such as predicting potential sales
  3. Data that is segmented (i.e., parsed by customer segments)

A more rigorous quantitative study is often the final phase of a concept test that our clients might take.

Here's an example of a methodology we use that we highlighted in our Quirk’s webinar yesterday (look for a webinar replay link on our blog next week):

  1. Directional quant to screen a whole bunch of concepts coming out of ideation to choose concepts those that merit further study (GutCheck)
  2. Take winning concepts into a qual IRC to optimize them (GutCheck)
  3. Optimize the winning concepts (Client)
  4. Take the optimized concepts into a large-scale, rigorous quantitative analysis to see if it’s ready to go to market and predict its success (Bases or other quant shop)

Quant can also be an important tool to convince internal teams about the validity of a concept. The challenge remains – why is that concept the right one? Good research needs to answer both the what and the why.

Quant provides researchers the answer to their question; qual sheds light on why a concept appeals more than another and how to improve that concept to make it a winner.  Tune in next week for part II of this blog where we’ll share our tips on how to use quant and qual to optimize a concept into a winning one.

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