Learning on the job
Teachers can’t tell you everything you need to know. James Verrinder asks researchers to share the things they had to discover for themselves.
Head of research
One thing I’ve experienced a lot on the clientside is agencies dressing up results because they want to please, to the point where they will sensationalise fairly average findings or focus on the one thing that’s not so bad in an otherwise negative report. So you quickly learn not to take what an agency tells you at face value and to challenge them a bit. If I feel that there is an integrity issue with an agency not being completely honest with the data, then it is addressed before it is presented. Earlier in my career I didn’t have the savvy to know how to do that.
Regional MD, EMEA
It was the Eighties, early in my career, and I was working on a new product launch for a major FMCG producer. For the first time I was working with folks way above my pay grade. To make matters worse, the client had made it very clear that they were really betting the bank on this one. The research results, however, were even clearer that this would be a losing bet. I was very worried at the time about presenting such bad news, and I shared my trepidations with my boss. He said: “Decent clients don’t shoot the piano player if he’s doing the best he can.” I later found out that he had appropriated this line from Oscar Wilde, but it certainly had a lasting effect on me. I’ve come up with my own twist on it: “Deal the news fairly and you will be fairly dealt with.”
Like most people, I fell into research. It wasn’t even a career option when I was at university. Some training from the MRS gave me a useful, theoretical overview of research, but most of my training was on-the-job mentoring on live projects. The main things I’ve learned on the job have been the softer aspects of client management. There’s nothing like presenting research you’re really proud of to a lukewarm reaction from an uninspired client to sharpen your efforts to give them something that meets their needs better in future. Bringing insights to life is something that has come from experience rather than textbooks or formal training.
When I joined BMRB as a graduate trainee in the 1980s, it was at the end of the era of punch cards and the beginning of the age of personal computing. My initial introduction to research felt more like a manufacturing line process – brief, research design, costing, proposal, sampling, questionnaire design, printing, dispatch etc. I should also have been told the following: what you do with research is ultimately far more important than the precise details of what has been done. Our industry is too insular for its own good. It’s important to mix with a wide range of people in business to counteract this career-limiting tendency: good researchers tend to be marketers as much as researchers. Also, the world doesn’t revolve around customer understanding, but that’s for another time.
Based on my experience as a marketer who has made extensive use of research I’d suggest the following: don’t let market research get in the way of listening to your customers. Whenever I’m stopped in the street by a researcher I always make a point of getting past the screener questions and not telling them I work in marketing. I do this in the hope that one day I’ll witness a piece of fieldwork that allows me as a consumer to tell them what I really think – rather than be forced to answer questions about stuff the research designer wants to hear about.
I was lucky because MR featured as a module in my management degree and I did a year’s placement at SE Johnson Wax that involved using a lot of Nielsen-type data in continuous projects. But the thing that has come to life since is the importance of inference, which is certainly something that I learnt on the job. What you learn as you grow in research is that you can’t just ask people questions and expect to get an answer. People are unable to provide a real response because so much of it is from the unconscious, and it shows the real importance of control cells and being able to match those and to look for underlying shifts in data that are the result of seeing advertising, for example.