How Market Research Has Evolved Over the Past Decade

Evolution of Market Research

In July 2006, I boarded a plane to Portland, Oregon. It was the beginning of my service at Market Strategies International. A decade is not a long time but long enough to witness some changes. Let me share with you a quick inventory of what has changed from 2006 to 2016 in the market research industry:

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The Secret Sauce in the Customer Behavior Recipe

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Editor’s Note: This is the first installment of a series on Little Data techniques that turn a good market research recipe into a taste sensation.

Market research is like cooking with quality ingredients. Big Data is good because it answers the fundamental what, who and how much of a customer. Little Data is good because it answers why customers make certain choices and how they arrive at their decisions. But blend Big Data and Little Data together in a thoughtful, clever way? Bam! You’ve just discovered the secret sauce in the customer behavior recipe.

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Trends to Watch for in 2016

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We kicked off December with a special webinar featuring all of our Cogent Wealth Reports authors. Using their combined 60 years of financial services experience and fueled by our research from this year, they made predictions for the industry in 2016. Here’s what they anticipate will happen in the coming year.

JJKJulia Johnston-Ketterer, Senior Director
2016 Prediction for Robo-Advisors

“In 2016 I anticipate that affluent investors are going to embrace robo-advice even more so than they do today. I think we’ll see this trend particularly among Gen Xers, who are going to be out in front in terms of investing more of their dollars into and adopting robo-advisory services. We’re also going to see an accelerated response from current robo-advisors, as well as firms on the sidelines getting ready to play, in terms of expanding product lines and modifying how these products and services are distributed. Next year we’ll continue to monitor investors’ use of these automated investment services via our Cogent Beat Investor portal. We’ll also be taking a qualitative look at the impact of these services on both investors and advisors.” Continue reading

FreshMR 2014 Yearbook

2014 Word Cloud

It’s the tail end of December, and we’re taking a look back at all that we’ve mused about, waxed poetic on and dug into over the last 12 months. In 2014, we ran a total of 75,009 words across 124 posts, covering an increasingly broad scope in terms of research topics and the industries and research specialties on which we focus: Energy, Healthcare, Financial Services, Technology, Telecommunications, Consumer & Retail, Qualitative and Syndicated Research.

Looking back at this year’s body of work, we’ve increased our coverage in a few key areas that align with our 2014 research portfolio.

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Answers to the Four Most Popular Big Data Questions

2014-04-bigdataTwo thousand and thirteen was the year of Big Data, although not always in a good way. We saw some of the largest privacy breaches in history affect major brands like Target, Facebook and Adobe, as well as government-related snafus (Edward Snowden, the NSA and the Federal Reserve Bank) impact hundreds of millions of people. The public now understands that we are leaving a data trace with every cell phone call we make, website we browse, debit card we swipe and security camera we pass. No matter where you stand on whether our data are being used responsibly, one thing is absolutely clear…

Big Data is everywhere.

In addition to what we leave behind, we willingly offer our data in exchange for valuable benefits:

  • We pay up to $100 to give the government detailed personal information in exchange for faster access through TSA PreCheck lines at the nation’s airports.
  • We install connected thermostats that know when we are home, away and asleep, enabling companies to learn about our daily routines.
  • We wear devices like Google Glass and Fitbit to track and share our activity with friends.
  • And don’t even get me started on Facebook, Twitter, LinkedIn, Pinterest, Flickr, etc.

With this trend comes an insatiable demand for Big Data analytics. Marketing research used to focus on asking people how satisfied they are with a service or whether they prefer product A or product B. But businesses want to know more about their customers than what they are willing or able to reveal in a survey. Today, businesses want to predict the future, and they are turning to Big Data to feed a new breed of predictive analytics. Here are a few of the questions I hear most frequently from clients… Continue reading

Extend the Life Expectancy of Your Segmentation with Big Data

Editor’s Note: This is the final installment of a three-part series discussing how Big Data can be exploited to enrich market segmentations.

When clients request segmentation research, we often start the discussion by asking if segmentation is really what they need. Included in that discussion is consideration of how long the segmentation is expected to or should live in the organization. For some brands, the answer is short term (one to three years). For others, there is a desire for a solution to live on for five to 10 years, which feels like an eternity. How can this be accomplished, given the pace of change in the world today? As you may have guessed, Big Data has a role to play.

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How to Apply Meditation for Better Data Insight

Years ago I took up meditation as a practice. Once I even went to a retreat where I didn’t speak to another person for more than a week (astonishing for those who know me). Simply put, the practice is to become still enough so the mind stops jumping from one thought to the next and becomes quiet. In this quiet, one finds peace and insight.

One technique involves listening to, and being mindful of, the environment around you to try to notice the tiniest detail. Of course the tiniest detail will lie under the cacophony of the larger details—the traffic outside, the drone of the air conditioner, the clatter of the dishes in the kitchen. I believe the art of data sciences can also be tied to this philosophy. Often we are asked to find that hidden nugget of insight buried deep within the data. But time constraints, shifting objectives and scope creep make it easy to forget to step back, become still and look for the small things that might make all the difference. Don’t get me wrong, management of those larger aspects of a project is very important. However, without care, those things can become the project and then one can end up in a mad rush just to finish.

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The Fourth “V” of Big Data

A few weeks back I was invited to present at a meeting of the Council on Research Excellence. The topic was big data, and I was tasked with discussing the potential implications of the work done by the AAPOR Task Force on Non-Probability Sampling, a group that I co-chaired. There also were two presentations by folks from Nielsen, one on data integration, and another on their work at the intersection of big data, behavioral science and computer science. There was a presentation on the application of big data analytics and recent developments in text processing and machine learning.

It was a fascinating day, the overall theme of which seemed to be that while the integration of big data into market research is both promising and certain, it is not the panacea many make it out to be. There still is a lot of work to be done. The reconciliation of data science and even the most innovative of modern day market research methods is going to be extremely challenging.

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Blend Big Data and Survey Data to Drive Successful CX Programs

Editor’s Note: This is the second installment of a three-part series discussing how Big Data can be exploited to enrich market segmentations.

Special programs that motivate customer behaviors are a common component of customer experience management. Examples include loyalty rewards, medical adherence and low-income bill payment assistance programs. Big Data can be particularly helpful—as part of a larger plan—to identify target segments and define strategic actions to support special programs. The underlying idea is to use customer and/or third party data to help identify customers who are likely to benefit from and be responsive to your brand’s special program.

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Use Big Data To Sharpen Your Segmentation

Editor’s Note: This is the first installment of a three-part series on how Big Data can be exploited to enrich market segmentations.

French novelist Marcel Proust is particularly famous for saying, “The real act of discovery consists not in finding new lands but in seeing with new eyes.”  That sums up the way I see Big Data and its role in segmentation: It doesn’t necessarily point us toward undiscovered markets, but it can greatly enhance our ability to see our existing market in new ways.

How? I asked my colleague, Dr. Raymond Reno, to join me in creating some practical examples of how Big Data can sharpen your segmentation lens. In this first installment of our three-part series, we’ll show how Big Data can add value to creating market segments for a new product launch.

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