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Many marketing researchers work with standardized proprietary methodologies and wonder why all research can’t be done that way. There are many reasons. Standardized proprietary methodologies have been part of marketing research almost from the very beginning. Significant investment has been required for the development of some of these methodologies, and academics may have been directly involved. There are a number of advantages to these methods over customized research, i.e., research that has been tailored to a specific client’s needs at a particular time. Here are a few that are frequently cited:
- Data norms that can be used by clients as benchmarks
- Higher quality
- Consistent quality
- Easier to sell
- Less need for experienced, highly-trained researchers
- Operationally more efficient
- Higher margins
For background, I have been a member of two marketing science teams responsible for developing standardized proprietary methodologies, one at Nielsen and the other at Kantar. However, I am a customized researcher at heart, and over the years have found that the need for customized research is actually growing.
Rapid changes in marketing technology, such as mobile and online retailing, can make proprietary methods out of date very quickly. Also, an increasing number of clients around the globe are doing marketing research for the first time and need many of the fundamentals explained to them, step-by-step. Some proprietary methods can be used for this purpose but many, if not most, these days are “black box” and difficult to explain to clients or to use for instructional purposes.
In addition, the necessity to protect proprietary technology places limits on what can be revealed to clients. Even when told that the method is set in stone, many clients will still ask for details about how it works. They will do so for several reasons. One is simply because they are curious. Secondly, most proprietary methods have competitive products (including customized research) and some clients want to be able to compare competing methods on more than price and how the output looks. Lastly, in rare cases they want to learn just enough about how it works to be able to approximately reverse-engineer it and run it (or something similar) themselves. With the explosion of “data science” in recent years, more clients may have the internal capacity to do this, compared with a few years ago.
I personally have found it very challenging to sell a product if I have not been involved in its development, and other marketing science people I know feel the same way. Another weakness is that inexperienced marketing researchers with little or no background in customized research often struggle to answer questions from clients, especially if they lack university-level coursework in research methods and statistics. Presentations of findings may also seem “canned” to clients who are looking for more in-depth analysis and insights.
Standardized methodologies can address important client needs that customized research in unable to, but there are many gaps left by them that can only be filled by customized research. For instance, “segmentation” and “key driver analysis” are household words in marketing research but mean different things to different people. Moreover, it is almost accurate to say that there are as many ways to do segmentation or key driver as there are marketing researchers! See Key Driver Analysis: A Researcher’s Swiss Army Knife and Segmentation: What it is and What it does for very quick overviews of these methods.
A growing concern for me is that the proliferation of standardized methods is part of the reason why I and many other marketing research veterans sense a sharp decline in marketing and research fundamentals in recent years. I discuss this issue in An Elephant In Our Room and Preaching About Primary Research. For people selling software this might not be a worry and, perhaps, it is an opportunity for them in the short-term, but do we really want marketing research to become a suburb of Silicon Valley? Furthermore, if true marketing researchers become extinct, who will design the next generation of proprietary methods?
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