Innovative thinking in research supports insight generation
To accompany our recent 2 part series, on how to generate deeper insight for proposition development, here we review some of the innovative thinking within the research community that can help.
Unlike the caricature of market/consumer research as outdated compared to Data Science, research blogs & events showcase something quite different. Reading some of the wealth of material out there, I see a community that’s both evolving & thinking more deeply about the potential applications of innovations in technology & social changes than many data or analytics ‘experts’.
So, for this post, I’m sharing a few examples of interesting ideas or reflections, related to the insight generation approach proposed in our latest series. Hopefully this has the added benefit of giving additional perspective on the business challenge of how you best innovate & design propositions your customers actually want/need/use.
Let’s start with process. Another take on the step we have called ‘Identify key consumer questions/challenges/barriers’ is this article by Scott Garrison. In more detail, he proposes a useful 3 step process for eliciting consumers triggers & barriers with regard to your proposition. The illustrations & examples really help & I particularly like the consideration of the need for triggers & reassurances:
Another challenge during the early stages of insight generation, right up to running an immersive ‘brown paper exercise‘ workshop, can be helping your business leaders empathise with consumers. It’s often worth keeping an eye out for innovative thinking that might help with this challenge, as novelty also has a power to engage senior execs or hardened stakeholders. So, it was interesting to read this piece by Simon Jones on the role Virtual Reality can play in helping bring designers closer to their customers. Realising that the technology can be as basic as a smart phone & cardboard viewer, helps remind you that you could ’try this at home’:
One of the challenges that organizations face is how to gain a deeper understanding of their customers. As researchers, one way to deliver this understanding is through storytelling. We go to great lengths to convert our insights into digestible snippets.
When it comes to the later stage of idea generation & designing real world propositions (products or services) to respond to the insights you have generated, a number of commercial challenges loom large. Often these include the pressure to automate in order to make mass market service interactions cost-effective. How can such a design approach be an appropriate response to what may well be emotional insights & the need to connect with your potential customers at an emotional level? This short post by Parry Bedi gives a fascinating glimpse into the evolution of Artificial Intelligence into Emotional Machines. Perhaps research can help machines deliver emotional interactions:
Editor’s Note: This post is part of our Big Ideas Series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. Parry Bedi will be speaking at IIeX North America (June 13-15 in Atlanta). If you liked this article, you’ll LOVE IIeX NA.
The goal, of course, of all proposition development is a winning proposition that can be launched & appreciated by consumers. So, beyond the insight generation process that is outlined in our latest 2 part series, further work is needed by marketers to launch & measure success. All too often such measurement is limited to sales or even just marketing effectiveness, in terms of response & purchase funnels. However, to understand if a proposition is impacting consumers as intended (based on deeper insights), a marketer also needs to consider the emotional impact.
This post on emotions research, from Meagan Peters & Curt Fedder, gives some interesting examples of how facial expressions & body language analysis can help measure emotions. If a key trend for 2016 will be emotional marketing, researchers & marketers will need to become more adept at understanding this type of data too:
I hope those were interesting & gave some wider context to our insight generation series. There are many great research blogs out there & it’s well worth keeping a ‘weather eye’ on innovative thinking in this discipline too.