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Do Traditional Marketing Research Methods Still Have a Place in a Researcher’s Toolkit?
Submitted by Larry Praml on February 10, 2011 - 16:15
To answer the question in the title of this blog post: Yes. Or at least some of them do. Probably. But let’s back up for a minute.
There is no shortage of bell-tollers signaling the death of traditional market research. (Check out blogs from Forrester’s Tamara Barber, “The Market Research Deathwatch”, and LinkedIn groups Next Gen Market Research and NewMR.) To deny that change is afoot in the Marketing Research industry would be foolish.
Technology is driving some wonderful advances and new opportunities in market research: Mobile technology is promising us in-the-moment access, social media offers unprecedented access to stream of consciousness feedback, and new, powerful algorithms are being developed to mine terabytes of existing data for insights yet untapped.
These are all big ideas, or more accurately, these are all potentially new market research platforms from which big ideas and new methods will spawn. And people are still trying to wrap their heads around how to tap into these new platforms.
Unlike the last game-changing advance in the industry (moving traditional research methods online), these are whole new frontiers. For now, the visionaries are leading the way, experimenting, learning and showing us the potential.
Once end-user adoption is widespread enough that development of these platforms can be justified as potential revenue generators and not purely for the altruistic purpose of moving our industry forward, the race will be on and we should see some really cool stuff.
But I think calling it “the death of market research” is a somewhat dramatic interpretation by the visionaries leading us into this new world.
Think of the venerable concept test. While this area has really evolved since the advent of online market research, it is one of the most basic tools in the marketing research toolbox, and one that should still be around (in some form) for a long, long time.
Online we can set the context of a new product or offering, provide as little or as much detail as we’d like and simulate a purchasing scenario (complete with a competitive set) where you might most likely encounter this new product in a virtual shopping environment. And we can do this in a fraction of the time and for a fraction of the cost that we could even a few years ago.
By applying analytic tools like Shapley Value, we can estimate the potential of a new launch with surprising accuracy. Technology has made these traditional analytic tools more accessible and affordable, and has made the interpretations less cumbersome and mind-numbing. (In fact, at MarketTools, we often use the Shapley Value as the key measure in our concept tests, as it provides surprisingly accurate insight into the trial potential of a new product in context with the other choices consumers have available to them.)
Moreover, the vast quantity of existing data is likely another reason the concept test will survive the market research Armageddon. Data from past tests can be used with in-market performance data to provide context on market potential, and for developing stronger predictive models for future concept potential.
For those who pooh-pooh the notion of concept testing and modeling market potential by throwing out stats about the percent of new products that fail in the first year, don’t disparage the method itself. It can’t predict how well the concept is actually executed as a new product, and that is really where the rubber meets the road.
The concept test is only one tool in the market research toolkit, and one that successful innovators will likely continue to use for years to come. Meanwhile, here is a task for data mining visionaries: create a model for understanding the translation of concepts to in-market products to help improve the new product success rate.
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