Voices: the CMB Blog

The recent research study showing that marketers rank lower than politicians on the “respectability scale” might feel like a kick in the gut for most of us in this role. 

From the research: only 13% of consumers agree that marketing benefits society.  It’s no surprise that teachers, scientists and engineers are the top of the list, but marketing even falls below bankers (32%), lawyers (34%), and politicians (18%). One point of solace, marketers are tied with actors and dancers; so, we’re not alone.

If we deconstruct the research, we can find plenty to take issue with.  What research study isn’t immune to that?  For instance, the focus of the research is about online advertising, while the questions about professional respectability come after questions about the effectiveness of different marketing methods.  To what extent has this approach primed respondents in a certain direction?

Additionally, when you look more deeply at the results, you find that people still “respect” the need for marketing within business.  Most, in fact, consider it “strategic” and necessary for sales.

So, the research findings shouldn’t be taken too personally.  As noted earlier, marketers are in the same boat as actors and dancers.  It makes me think of Ode by Arthur O’Shaughnessy:

We are the music makers,
And we are the dreamers of dreams,
Wandering by lone sea-breakers
And sitting by desolate streams;—
World-losers and world-forsakers,
On whom the pale moon gleams:
Yet we are the movers and shakers
Of the world for ever, it seems.

Or, as the great Willy Wonka puts it:

Who but a marketer would ever create lickable wallpaper with snozzberry flavor???

So marketers, don’t give up on your role and profession. And remember that without you, the world would be a place with much less flavor and much less fun.

When Jeff's not busy contributing to society at large, he serves as a senior consultant and methodologist for CMB; making sense of big data, and speaking on topics like mobile and the future of market research.

We hear a lot about Big Data—from Target using predictive analytics to tell which of its customers are pregnant, to MIT and Intel putting millions behind their bigdata@CSAIL initiative. Yet, I’m struck by the fact that most of what I read, and hear at conferences, is about  the wealth of data technology can provide researchers, managers and analysts. There is very little about how these folks can avoid drowning in it, and most importantly make the decisions that address business challenges.

• Volume - Technology has led to an exponential increase in data we have available

• Diversity - We can aggregate data from a wide range of disparate sources, like customer relationship management (CRM) systems, social media, voice of the customer, and even neuro-scientific measurement.

• Speed – We are able to field and compile quantitative studies within days; before online, IVR, and mobile data collection methods were available this took weeks

While there may be other definitions of Big Data, it is clear that technology is making data, larger, wider, and faster. What we need to think about is how technology can make our response to and analysis of data larger, wider and faster as well, and avoid drowning in it.

The water metaphor is often used to describe Big Data, and the folks at the GreenBook Consulting Group use the term “oceans of data.”  They describe three business models driven by data: The Traditional (based on Data Ponds), Transitional (based on Data Rivers), and Future (based on Data Oceans).

Traditional market research based on small discrete amounts of data has its place – but as the folks at GreenBook point out, market researchers must face the fact that progression from these Data Ponds to Data Oceans is inevitable.  The Traditional mindset is faced with inertia and will decline in relevance in the next five to ten years.

Those who are in the Transitional phase are moving forward, folks here are in a “reactive” position.  They are seeing these changes around them and applying some big data solutions in their word.  They might have tried one or two tools or are even using them now on a regular basis. But when faced with large amounts of data, they think about technology only in terms of how to collect more data – not in how to manage and apply it quickly and in big ways.  In contrast, the Future mindset takes a proactive approach; these are the people who think about how technology will be the fundamental basis for applying the ideas and solutions to lead companies.

In the coming weeks I’ll be discussing specific examples of technologies that are helping push market researchers towards this future. I’d love to hear from you about things you’re doing to respond to Big Data and the challenges and opportunities you are facing as we confront these Data Oceans.

Watch our webinar Using Technology to Help your Entire Company Understand and Act on Customer Needs here

Posted by Jeff McKenna, Jeff is a senior consultant at CMB and team leader for Pinpoint Suite-our innovative Customer Experience Management software. Want to learn more about how Pinpoint Suite can help you make sense of your "Big Data," schedule a demo here.

Earlier this month I had the chance to present at the Market Research Technology Event in Las Vegas. Beyond the fact I just could not get accustomed to watching people walk by conference rooms swigging beer and wearing in flip flops; for me the event raised more questions than provided answers.

During the conference, one of the most quoted reports was McKinsey’s: Big data: The next frontier for innovation, competition, and productivity.  For me, one of the most striking takeaways from the report was a prediction that by 2018, the US will have a shortage of talent necessary for organizations to take advantage of big data—the US alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis to make effective decisions.

After we market researchers take a moment to celebrate our job security, we should consider that skilled market researchers will be asked to fill the space by taking on more tasks and working longer hours.  As the gap widens between the influx of data and the analysts we need to make sense of it, are 80 hour weeks inevitable? Certainly workforce globalization will be a key to filling “big data” needs, but I was very surprised to hear little discussion of how technology will help us deal with this shortage.

I left the conference with the theory that the “new technology” we need is the yet-to-be-realized application of a tool to change a process to yield a quicker, lower cost, or better quality outcome.  I think market researchers have yet to focus on how technology can act as a surrogate for the role they play within their organizations

So what might the future hold? I expect technology will allow market researchers to develop “analytical bots” to make sense of the vast ocean of data to answer specific business questions raised by internal clients. Watching Watson and Siri answer questions of fact with extremely high accuracy makes me wonder what our role will be.  If these machines “have all the answers” then what purpose do we have?  I don’t believe technology will replace market researchers; their skillset and output are still critical for companies to be competitive.  The purpose is to create the rules and algorithms that convert the facts into relevant information.  This is where market research skills will combine with technology to fill the resource gap.

We’ve heard a lot about expert systems—computer systems that emulate human decision-making. It’s my view that the market researchers who will lead in the next 5 to 7 years will be those who are setting up and managing expert systems, that take all of the facts and computations within large sets of data and apply what is relevant, to make decisions quickly, anywhere, and at any time.

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Posted by Jeff McKenna, Jeff is a senior consultant at CMB and team leader for Pinpoint Suite-our innovative Customer Experience Management software. Want to learn more about how Pinpoint Suite can help you make sense of your "Big Data," schedule a demo here.

On Sunday, The New York Times Magazine published a piece: How Companies Learn Your Secrets, by Charles Duhigg, author of the forthcoming The Power of Habit: Why We Do What We Do in Life and Business.  It’s an interesting article, especially for market researchers, and I recommend everyone take the time to read it.

Consumer "habits” are a big focus of the work we (market researchers) do as we seek to understand consumer behavior. From the perspective of the article, a large part of what we do is identify behavioral habits to help marketers find ways to insert their product or service into people's habit processes. 

In this blog, I want to focus on the insights the story shared about predictive analytics. Much of Duhigg's article looks at how Target conducts advanced analytics to identify data within their CRM system to predict whether a shopper is expecting a baby.  From a business process POV, and how we think about using predictive analytics, it’s important to point out a few relevant facts for market researchers:

1. It wasn’t a “fishing expedition”: The analysis started with a clear marketing benefit as the outcome – Target wanted to begin promoting itself to expectant mothers before the baby is born. As the article points out, by marketing to these families before the baby becomes public knowledge, Target can get beat the flood of marketers that begin pitching a range of products and services once the birth is entered into public record.  It was the marketing team that came to the analyst with a high-value opportunity.  The analyst did not create the winning marketing idea (“Hey! Let’s market to expectant mothers before the baby is born!”).  Instead, the analyst looked under every stone and in every corner of the data to find the key to unlock the opportunity.

2. The research didn’t stop with finding the key: The application of these insights required a lot more research to determine the best method of implementing the campaign.  For instance, Target ran several test campaigns to identify the best offers to send to the expectant mothers, and cycled through several messages to find just the right one in order to avoid revealing that Target was prying into the data.  Although the predictive analytics found the key, Target still relied on a comprehensive plan to make sure the findings were used in the best possible manner.

3. Don’t let this story increase your expectations: The Target approach has had a big impact on how the company markets to a highly valuable segment of shoppers.  It's a great success story, but it's also something that happened ten years ago.  While I’m sure the Guest Market Analytics team achieves many victories along the way, they also spent a lot of time reaching “dead-ends,” unable to find that magic key.  And most of the time, the predictive solution yields valuable but incremental gains, these high-profile stories are few and far between.

The article shares many interesting ideas and insights; the story about the re-positioning of Febreze highlights another great research success. I'm looking forward to reading Duhigg's book, and if it covers more of these thought provoking business cases, I expect we will be seeing Charles Duhigg’s name popping up in other discussions on market research.

Did you read the article? What do you think?

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Posted by Jeff McKenna, Jeff is a Senior Consultant at CMB, and the creator and host of our Tools and Techniques Webinar Series.

A topic near and dear to my heart just became nearer and dearer. Take a look at one of the classroom assignments my kindergarten daughter recently brought home from school:

Isn’t this amazing? Kindergartners are learning the basics of market research! Ever since I got into this business of market research, whenever someone asked me about my job, the answer nearly always comes down to: “I write the survey questions that people ask when calling you during dinner time.”

But, not anymore! My answer can now be: “You know how you might want to learn what is the most popular animal at the carnival? I’m the one who writes the questions, counts the tally marks, and creates the bar charts to show you what is most popular.” How cool is that?

Wish your research had more pictures of ponies, or just more visual interest? Check out our webinar: Appearance Counts: How to Tell a More Visually Compelling Story with your Data

Posted by Jeff McKenna, Jeff is a Senior Consultant at CMB, and the creator and host of our Tools and Techniques Webinar Series.