Implicit Research Methods, resources on those you should consider using

Following Katie’s useful introduction to behavioural research, this post surveys implicit research techniques. Given the relevance of implicit research techniques, to monitoring behaviour, it makes sense to dig deeper.

In this post, I will share the breadth of such techniques, current usage & their academic basis. As we’ve shared before, learning in the field of Behavioural Economics (and related fields) has raised the bar for researchers.

The annual Behavioural Economic Guide, reveals how much work is happening. How can Customer Insight leaders best ensure, they have behavioural evidence, as well as just self-report? Due consideration needs to be given, to permission for data capture, as outlined in GDPR. Once that is addressed, implicit methods can help.

Here are some of the blog posts & resources that I’ve discovered on this topic. I hope you find them useful…

Breadth of Implicit Research techniques to consider

As a start, let us consider the range of implicit research techniques now available. In her recent post, Katie focussed on the relevance of passive metering.

This helpful overview, from Neil Cole, makes the case for needing implicit research methods. Including the neuroscience basis. It then expands on 5 potential methods & agencies working in this specialism.

I particularly like the visualisation of implicit motivations model, from Beyond Reason. A useful reminder that the goal of researchers is not limited to accurate behavioural data, but beyond that to “the why” question.

Top 20 emerging research methods, now used, include Implicit Research

 Whenever sharing technology innovations, or theoretical best practice methods, there is a caveat. Although that may be ideal, this blog is focussed on pragmatic advice & resources for customer insight leaders. So, what is actually happening, how are these being used in practice.

To help with that question, I’m glad to share a recent update from GreenBook’s twice yearly survey. Entitled GreenBook Research Industry Trends (or GRIT), it captures a snapshot of current practice. Surveying across both client side & agency research leaders, it is a helpful sense check of reality.

Within this blog update, on H2 2017 GRIT results, Ray Poynter provides a useful summary of usage of new methods. He starts with an important caveat. The GRIT sample is skewed to those most engaged with CPD & innovative best practice. So, what we see here is probably the most advanced usage in current practice.

That said, it is interesting to note that amongst the Top 20 emerging methods in use, 10-15 could be termed implicit. Depending on how that category is applied, each captures behavioural usage as well as explicit answers. I hope this is food for thought:

Given our previous posts, it’s encouraging to see use of text analytics, mobile-surveys & gamification.

Academic rigour to considering behavioural biases across 4 Marketing Ps

At this point, it would be fair to question whether there is any academic basis for these innovations. Customer Insight Leaders should always be cautious of hearing new best practice solely from suppliers. Is there independent academic work, to support such an application of theory, in new practice?

Given much of the application of these implicit research methods is for Marketing, let’s focus on that area. We have shared before, 10 behavioural biases published by the Financial Conduct Authority. We also included a book review of “Thinking Fast & Slow“, a classic book on Behavioural Economics.

But, none of that work included an academic basis, for applying the science of behavioural biases, to Marketing. Given the traditional models of marketing theory, what is the relevance of implicit research methods?

To help close that gap, I’m delighted to include this paper on “Behavioural Biases in Marketing” by Daniel Guhl et al. A collaboration between academics at two leading German universities (LMU & Berlin University).

In this paper, the writers both review current understanding in both fields and share a model of how they overlap. Built on the framework of 4 Ps (Product, Price, Placement & Promotion). This helps explain the relevance of biases (and thus implicit research), to different decisions consumer make. A useful framework for reviewing the marketing research needed:

Implicit Research Methods: Which are you using and why?

I hope you found that review of implicit research methods was helpful.

Beyond that, I’m interested in your perspective on this topic. What is your experience of implicit research methods. Which (if any) are you using & why? Have you discovered any drawbacks to these methods, that this post has not highlighted?

As always, feel free to share below in out comments boxes, via social media, or approach me directly if you have a post to share with us.