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(Dis)functional Insight

Insight functions are functionally driven to dehumanize their subjects. When it comes to insight, the very structure of the organization is specializing the human out of the customer. If any function in a company should be empathetic to the full customer experience, it should be insight.

 

Assortment Of Bizarre Road Signs Isolated

 

Editor’s Note: There are few things I enjoy more as Editor of GreenBook Blog than showcasing brilliant new voices in the industry dialogue, and today is a happy day indeed because joining us today as an author is Alec Maki.

Alec is one of the brightest rising stars we have (as the AMA recognized in 2012 by awarding him the “4 Under 40″ award). I’ve been following Alec’s blogging for a while, but recently he has been on a real roll, posting frequently with each one being thoughtful, provocative, and leaving me wanting more. I finally decided that I was being a bad social sharer by not exposing more folks to Alec ( I admit I was being a bit selfish!) and  reached out to him to see if he would be interested in posting here on GBB. Thankfully he agreed and today I get the privilege of introducing him to a wider audience. He deserves it.

I think you’ll be as impressed as I have been, and I predict that Alec will soon become one of your favorite authors too.

Enjoy!

 

By Alec Maki

Large companies tend to create multiple insight functions: consumer, shopper, digital, product, etc. Each function has a piece of the marketing mix it owns. Awkward dances ensue across initiatives and, even, within studies as each function avoids stepping on one another’s toes. When the inevitable toes get stepped on, dances morph into pissing contests over who owns what piece of data and, therefore, who funds what.

Lost amidst all this dancing and pissing is a large, looming presence on the dance floor — the thing each insight function is dancing around and pissing all over. It’s large like a tree.  But you can tug on it like a rope. It’s sturdy like a wall. Yet it moves like a snake. And, interestingly, it’s pointy like a spear or stake.

Each function has a different perspective on this vast presence in the room, the thing that takes up much of the dance floor.  Yet, like in the story of the blind men and the elephant, they are all blind to what this large presence really is.  When it comes to insight functions, it’s the elephant in the room. [BTW, you've got to check out this awesome video on blind men and the elephant, even if you already know the story.]

So, what is the elephant in the room for insight functions?

It’s the end customer.  The person who visits your website, shops in the store for your brand, uses your product and tells her friends about it.  Each insight function has a partial view of the customer and her experience. As with the blind men, a partial view does not the whole make.  What can we learn from the moral of this story?

Each of these insights functions 
disputed loud and long;
each in their own opinion
exceedingly stiff and strong.
Though each was partly in the right,
they all were in the wrong!
In the real world, the consumer is the shopper is the person viewing the ad is the person collecting the coupon is the person posting to Pinterest. It’s the same person. By seeking to “own” parts of her actions, insight functions lose sight of who she is and why she makes the choices she makes in various moments.

 

In other words, specialization of insight functions leads to disfunctional insights.

Insight Functions = Disfunctoinal Insights

Each insight function seeks to “own” a piece of the customer.  In the name of organizational structure, specialization, and budgetary procedure, insight functions have a mission to break the customer into pieces that each owns and fiercely protects.

However, people cannot be broken apart like this and then, by a marketing team, stitched back together again; it’s unnatural. Slapping pieces of person back together doesn’t give you a human being.  It gives you a zombie.  Something humanoid but lacking in humanity.

Think about this. Insight functions are functionally driven to dehumanize their subjects. When it comes to insight, the very structure of the organization is specializing the human out of the customer. The irony cuts to the bone. If any function in a company should be empathetic to the full customer experience, it should be insight.

Specialization is not bad, per se.  The business needs of shopper vs. consumer vs. digital vs. product insight are different. They typically go to different constituencies to make different decisions. However, they should be pulling from the same source: a unified view of the consumer and her world.  Insight functions should be working together to paint a vibrant portrait of who she is, what she does, why she does those things, where she’s going in life, how she’s going to get there, what she aspires to be and  what holds her back. It is within this context that your brand and products have meaning.

Without an empathetic view of the full customer experience, you’ll likely miss out on that meaning and, therefore, miss the mark on execution.  The outcome?  Mediocrity.

To create and deliver meaningful customer experiences, we need a shared canvas upon which each specialized function can jointly paint this picture. Each function should work to create a single portrait — and all should mutually benefit from its use.  This canvas can (and should) unify insight functions, marketing, sales, and R&D with a common purpose: create and deliver value for the full customer, regardless of where she’s at, what she’s doing, what she needs, wants and desires. This common purpose, rooted on a shared view of the customer, is the basis of what Joel Rubinson calls simplicity.

An example of a company that had done a brilliant job keeping a one canvas approach is Apple (which is the poster child for good market execution, I suppose). Each element of execution is built on common customer understanding: product, package, retail, website. It all aligns. Their understanding of the customer is acutely humanized.

This is what Peter Drucker meant when he said “the aim of marketing is to know and understand the customer so well the product…sells itself.”

In large organizations, how do we achieve this level of empathy?  Well, it starts with common information frameworks, which I wrote about in my last blog post. In particular, we need a common framework, or “lens,” from which to view the customer and her behavior. This framework of information can be populated based from multiple information sources and different insight functions. The data goes to the same place rather than being confined to silos that serve only to break customer understanding into pieces.

To do this properly, we must have a template for understanding customers and their behavior. As we conduct research to better understand the marketplace and our customers, we can fill in the template.  Every insight function can use their own brush. Eventually, a rich picture of customer understanding should emerge, helping bring to life the meaning of brand and new products — regardless if you’re focus is shopper, consumer, product or digital.

One canvas. Many painters.

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2 Responses to “(Dis)functional Insight”

  1. John Griffiths says:

    January 15th, 2013 at 6:41 am

    nice post – but following that through does that mean that research has got too locked into consumption behaviour which is a tiny proportion of the actvities in which human beings find meaning. Undoubtedly this kind of specialisation does work to a point. My question is how much more accurate would research be if we relayed purchase and consumption in its proper place – as only part of consumers lives and not a particularly important one either.

  2. The Quiet rEvolution In Marketing Insights | GreenBook says:

    February 26th, 2013 at 12:02 pm

    [...] The issue for brands is complex, but the goal strikingly clear: to understand its customers, they need to listen to them, and not just what they have to say, but also why they feel they have to say it. And, they need to do it in real time and at web scale. To do that, they need a model that allows for the aggregation & synthesis of data into (to borrow a term from my friend Alec Maki) a common information framework. [...]

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