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Consumer Insights. Market Innovation.

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What Will We Do When Market Research is Outlawed?

Don't panic. CASRO's government affairs committee isn't warning this will happen and I don't have any evidence that it will. The point of the question is along the lines of "necessity is the mother of invention".

For example, over the past 15 years we have seen a move away from phone data collection and toward the web. Initially the focus was on cutting costs and ensuring the quality of the data were the same. As the industry embraced web, however, we began to use all kinds of innovative techniques that we simply could not do on the phone (or by mail for that matter). So, as we face a future with more and more access to data, I thought it would be interesting to think about what we would do if our traditional tools were simply taken away and we had to go cold turkey.

A good place to focus is Satisfaction research, which is already showing signs of decline. According to Inside Research (February, 2011), spending as a percentage of all MR has dropped in Europe (from 18% in '06 to 13% last year) and is stagnant at best in the states (11% last year which is in line with 12% in '09 and 10% in '08). I suspect this decline is not an indication that firms no longer care about satisfaction. More likely it reflects cheaper data collection methods and a realization that it need not be measured as intensively as in the past.

So in a world with no traditional MR, how will firms measure and impact satisfaction?


  • Internal Company Data - Companies today know their customers better than they ever have before. Already, firms like mine are integrating these data into results of satisfaction and other efforts. Taking the MR data out will make the models less effective, but not by any means worthless. For example, an insurance company could use data on sales, claims, applications and so on and overlay it with characteristics of each agent (years of experience, hours of operation, number of employees, location...) to model what factors drive better outcomes. So to the extent that these characteristics are correlated with success, we don't really have to worry too much about satisfaction. At the same time, such a model can't take into account things like a rude staff. Still, managers could probably be pointed at agencies worth a closer look by identifying those whose success is out of line with its characteristics (offering more convenient hours might not help if the staff is rude).
  • Text Mining - Already massive amounts of information are available to companies for free on the web. Smart ones are encouraging open forums on their sites so customers can comment, both positively and negatively. In the last week I've seen two postings on my Facebook page which mentioned companies by name. A cousin who had knee surgery posted how great Comcast's IPAD App was and a friend complained about the high price of furniture at a chain whose name (the Dump) implied low prices. Data such as these can be used to understand factors that are not in the company database.

So, with just two data sources we can provide a lot of the same insight that traditional tools do. No doubt there are other data points that could add value (for example response cards) and new ones will be created in the future.

Do I think these and other data points fully replace traditional techniques? No. First, I am only looking at satisfaction work here. Not every type of research will be as easily replaced. Second, I believe that traditional methods provide a depth of understanding that these data cannot match.

Ultimately we should be looking for ways to add new sources of data to make our models better and be willing to discard sources that prove to be too time-consuming or expensive to justify the effort. Change like that is never easy, but it will come, whether we want to or not.

President, TRC

Rich brings a passion for quantitative data and the use of choice to understand consumer behavior to his blog entries. His unique perspective has allowed him to muse on subjects as far afield as Dinosaurs and advanced technology with insight into what each can teach us about doing better research.  


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Guest Saturday, 24 October 2020

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