Building NLP theory into research practice: Easy does it!

Over the past thirty years there has been much debate over the validity of using NLP techniques in market research. Does NLP represent an exciting way of thinking by providing a framework that will revolutionise our work, or does it actually re-package what we, as good researchers, are already saying and doing? Both promoters and detractors have had their say; however, we believe that NLP provides useful tools but that these should be chosen carefully and (as a technique) handled with care.

In research, getting to grips with the reality of what respondents are telling us should always be our holy grail. We seek to access both the rational and emotional reasoning behind decisions and actions by asking those difficult questions and responding to any challenges. NLP positions itself as a tool that promises access to this success via a number of different techniques designed to model and therefore replicate excellent behaviours. This NLP framework ranges from supporting improved moderation to mapping out your own model of reality.

However, tempting as it is to lift NLP’s full mantra, this presents inherent risks. Indiscriminate and ill-thought out use could throw up barriers. An otherwise clear and incisive discussion could be impacted as a consequence of us feeling duty bound to ensure we are sticking to an ‘NLP code’. Therefore, does following NLP unquestioningly lead to less room for independent thought and prevent us from following our ‘gut reactions’? Is this a risk worth taking?

This is not to say that NLP should be discounted. Being aware of techniques and how they could expand and even improve our offering is part of our job. Certain areas of NLP do raise interesting points and can raise awareness to ensure best practice is top of mind. However, I believe its value is only assured if we ‘cherry-pick’ from this toolbox. Enthusiastically telling your colleagues that you plan to monitor blood flow, eye movement patterns and face colour cues during intense interview scenarios might be met with a raised eyebrow. And why should NLP get the credit for already established practices, such as gaining rapport by using similar, and therefore relevant, language in order to engage your audience. Is this not what we do already or seek to achieve?

Perhaps what NLP does is explain, trademark and package these skills for us, selling them back to us at £1000 per training session. This leads us to question the adage, what came first, NLP or our own skills?

Another consideration, that may not seem so obvious at first glance, is that NLP is not a new idea. It is likely that the majority of us have heard of it and may even be using it to greater or lesser extents. As such, to advertise your use of NLP with much ‘pomp and circumstance’ could be a risky strategy. You can imagine the responses can’t you…?

“This is a bit behind the times isn’t it?
Why are you only thinking about this now?
Are these sets of ideas and approaches not a bit gimmicky?”

So, ultimately, should researchers dive headfirst into the world of NLP? I would advise caution and perhaps not to believe in all the hype.

For more information on approach to incorporating NLP into our research approach, please contact us.


By Kirsty Page

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