Voices: the CMB Blog

You know you’ve been to a great conference when the ideas and insights are still percolating and expanding weeks later; the Insights Innovation Exchange Conference in Philadelphia definitely fit that bill.  In part one of my take on the conference I talked about the change we’re seeing in the market research industry.  In this post, I’ll discuss the implications and manifestations for the change.Technology is driving the change, but people will lead it 

Technological changes are a primary piece of the “revolution,” but does this mean we will do more with less? The short answer is no. Technology will not reduce our need for people.  In fact, the big changes introduced by technology and new tools & techniques will require most market research firms to aggressively hire more people, not fewer. The challenge, however, is defining and finding the new talent and skills that will apply to the market research of the future.  Data management skills will be critical, as will business systems knowledge. Most importantly, strong logic and an understanding of decision theory will be big differentiators for the professionals of tomorrow. 

A wider view of consumer behavior
Besides the change in how we conduct our work, technology is changing the way we view behavior.  IIeX focused an entire track on neuroscience and emotional measurement, with a variety of emotional measurement techniques like fMRI, EEG, eye tracking, and facial recognition becoming more mainstream (see Mediapost’s: The State Of Neuroscience In Market Research)

If some in our industry see these new technologies as just measurement techniques, they’re not seeing the forest for the trees.  In fact, the trends and changes in the industry reflect new consumer behavioral models that reflect multiple aspects of decision making processes. During the conference, I even noted the fact that we seem to have reached “critical mass” with regard to behavioral economics.

Gone are the days of the rational economic decision maker.  Instead, advances in neuroscience and behavioral economics reveal the strong emotional components of all decisions.  If you don’t have an understanding of the core value and applications of behavioral economics and the new research in neuroscience, you may as well go back to using MS Office ’98, collecting data on 80-column punch cards, and worrying about how to conduct interviews via that new-fangled Internet.  Cognitive models developed within the past couple decades have gained acceptance and are frequently being applied in market research. The growing regard for intrinsic measurement gives me hope that we will achieve a more cohesive framework for addressing the emotional and subconscious layers of behavior. 

New innovators, new partners, new collaborators
The conference’s final day wrapped up with two presentations around a common theme: collaboration.  Gayle Fuguitt, CEO/President at Advertising Research Foundation (and former Vice President Global Consumer Insights at General Mills), presented “A Call For A New Collaborative Model,” highlighting ARF’s efforts to bring clients and competitors together to address the promises and challenges of biometric and neurological research methods .

Gayle’s central argument is built on well-regarded themes—organizations need to find new ideas and innovations by fostering the diversity of thought and value a broad team can provide.  Her advice:  “work with people who don’t laugh at your jokes” and “seek partners who are frenemies,” highlighting the fact that true collaboration doesn’t occur among the like-minded.  In a similar vein, Kyle Nel, head of International Consumer Research for Lowe’s Home Improvement, presented “Data Philanthropy: Unlocking The Power Of Adjacency Across Sectors.”  For Kyle, the focus for the future will be on “uncommon partnerships” to help companies gain a competitive advantage.    

These new relationships will take market researchers out of their comfort-zone, working with partners who might not bring the same rigor and methodological requirements. The hard work arises from more than accepting compromises; instead, the greatest effort (and reward) comes from working with new partners to find an optimal solution aligning the strengths of each participant with the desired objective.  When working with technology partners, market researchers must be aware of tradeoffs when using the technology; no technology solves all problems. (BTW, technology partners, you’re not off the hook either. You must be aware that you can't solve all problems and will need to partner with market researchers to create optimal solutions for the business objectives). The effort of collaboration is a matter of compromise and acknowledging that “perfection is often the enemy of progress.” 

A great opportunity
In spite of all of the posturing about the end of market research as we know it—the irrelevance of the “long-form survey” and the un-engaging nature of many online interview formats, I came away from the conference with a positive outlook on the industry.  We‘re in a unique position, intimately involved in the largest trends that are shaping business and the economy: mobile, social and big data. The Information Economy is fully upon us, and market research has the opportunity to seize the value that new technologies are bringing to businesses and the economy.  It’s a matter of hard work, collaboration, and courage to accept new ideas and change that will allow us to take advantage of these opportunities.  

Jeff is VP of Market Science Solutions at CMB. This marks the first, and probably last, post accompanied by a picture of Vanilla Ice. Find Jeff tweeting @McKennaJeff.

CMB is proud to be named to the Honomichl list of the Top 50 U.S. Market Research Organizations. Check out our case studies to learn more about our business decision focused approach.

Welcome to Part One of my coverage of the Insights Innovation Exchange Conference (#IIEX) that recently wrapped up in Philadelphia. The event was three solid days of presentations and panel discussion on the changes and innovations that are shaping the future of market research and the business insights industry. The event targeted insights practitioners and anyone who wants to deliver evidence-based business insights to their clients. The event focused on the future of the industry, and the usual suspects were there: mobile, social, gamification, Big Data, neuro-measurement tools (like eye tracking and facial coding), and communities. The vendor space was filled with companies offering technological solutions, and the lion-share of presentations focused on at least one of these tech aspects. I was surprised, and pleased, to discover that this collection of innovation agents focused less on the tools and technology (partly because speakers were limited to just 20 minutes) and more on fundamental elements of change in our industry. In Part One, I’ll briefly summarize our current state. In Part Two, I’ll describe the manifestation of that change for future growth.

The Shift from Old to New Research: 

“We no longer live in a world where information is rare.  In contrast, we are overwhelmed with data, Big, Medium and Little. This represents the most fundamental challenge to the business model of market research since its inception.”

That’s Dr. Larry Friedman, Chief Research Officer at TNS, who packed a comprehensive synopsis of the market shift into his 20 minutes. The key points are nicely summarized here.

It’s true that because we are an industry that has established its value through collecting and managing data, market research faces a difficult future; its fundamental activity has become less valuable. For a hundred years, businesses and managers have turned to market researchers to design studies, collect data, and translate the data back to them. Some market researchers might find additional value in providing insights and recommendations, but it’s rare to be rewarded with full “consulting rates” for this work. 

Given that data can be collected at low cost, the management tasks of sample design are not as important today, and the science behind collecting the “right” data can be glossed over with more (and cheaper) data. Even the translation and application of research data to business decisions are becoming more common with easier-to-use software and training. Tableau, Good Data and (even) MS Excel are some of the analytical tools that now put data directly into the hands of business decision-makers. Heck, even kindergartners are learning the “basics” of market research.

But market researchers still have a head start. As the professionals who have experience with managing and translating data, we should be able to fill a vast need for curating the wide variety of data files and warehouses to support business analyses. Additionally, our knowledge of data types (e.g., categorical vs. scale, just to name one of the many ways we look at the multidimensionality of data) and structure is critical for laying the foundation for information users to access and translate data most efficiently and effectively.

We might not be able to design the right sampling methods, but who among us has not fixed a study where the sampling was done incorrectly? We might not be able to design the questions to get the best data for analysis, but who hasn't needed to come up with a method to fix data that had been coded incorrectly or had incorrect skip patterns applied? (Just to name a few of the complications that can occur). All of these new data streams bring many more opportunities to fix, translate, and apply the results to support the decisions our clients need to make.

The takeaway: there are major challenges but Market Research isn’t dying, and it’s not on life-support. It’s a reasonably secure business that has attracted other companies to its space because companies find great value in evidence-based decision making. Let’s be honest, Google wouldn’t be making a big investment in Google Consumer Surveys if it didn’t see an opportunity to make a lot of money.

But when Google enters your space, you better believe you need to put your helmet on, and get ready…

Jeff is VP, Market Science Solutions at CMB. He is just as comfortable explaining advanced analytical models as he is parsing the cultural significance of "Tommy Boy." Find him tweeting @McKennaJeff.

If you're over the age of 25, are childless, and have any idea of what Snapchat is, kudos on your tech hipster status. For those with tweens or teens, you may have been allowed to see a brief glimpse of this world, and maybe some of you have even heard it called a “sexting” app.Don’t we love our flow of both successful and flash-in-the-pan communication tools!  YouTube, Facebook, Twitter, Instagram…and now there’s Snapchat. Will it have the longevity of these household names?  It’s hard to say. But there’s been phenomenal adoption for this app that allows instant communication gratification. One of the key selling points of Snapchat appears to be its “self-destruct” feature.  That is, when you take a picture and send it via Snapchat the recipient has, say, 10 seconds to view it once opened before it, poof, vanishes. The idea is that the communication happens but there’s no record—incriminating or otherwise.

Now, a recipient can take a screen shot of the image (the sender is notified in this case), or if they were so inclined could use another device to take a picture of the image showing on the phone… Whew, that’s a lot of work with 50 million snaps a day already flying around as of last December (for reference, 300 million images are uploaded to Facebook a day).  

So with Snapchat, users take pictures or videos of themselves or their surroundings and send them (with a message if desired) to a contact. Once viewed, the recipient’s device in theory no longer retains the image.  This purports to alleviate concerns over the public trail left on Twitter or Facebook, and it has already been used for branding. 

A frozen yogurt shop in NYC, 16 Handles, was reportedly the first to use it for an instant couponing program—if a customer was in the right store and the right time they could get an instant coupon to flash to the salesperson for a discount. It was essentially gamification of the mobile social local aspect of the app – adding something fun and interactive. Early this month, Taco Bell joined the action, urging their fans to add them on Snapchat and reintroducing the Beefy Crunch Taco via the app.

How can other brands use this app to help manage and measure customer experiences? Much like Google Surveys says you can ask a whole survey worth of questions, pieced together one question per respondent at a time, to make the whole picture, instant messaging apps could be used to piece together a more holistic picture of how customers experience and interact with a brand.

Or, shh, what about Whisper—another app phenomenon that recently got $3m in start-up funding. This one allows anonymous posting of secrets. It’s not the first idea of its kind, but it is apparently heavily moderated—good. And here’s where the generation gap really kicks in. Whisper users need this app on a psychosocial level because they have pressure to live such curated lives on Facebook. Living up to the self-brand they create is too much. Whisper is supposedly an outlet for being “real.”

That sounds even more like something that could be a source plumbed for customer experience insights, although their terms and conditions currently say clearly that you may not use the site to mine data. What about a Whisper business account that asked consumers what they secretly do, or wish they could do, with their next vacation, car rental, computer purchase, etc.?

It’s conceivable that the future could be mapped through compiling many blips of information into a coherent story. It is big data of a whole different kind. Yet, a word to the wise: there will always be newer and cleverer platforms, apps, or gadgets to let you connect with customers, but you still need to know your audience’s wants and needs—that’s been the same for centuries!

Kate is a Project Director, working with clients across many industries at CMB. She has been known to perform in local musical theater here and there, speaks three languages well and a few others passably, and loves coincidence.

Click here to read our 2013 Consumer Pulse-The Mobile Moment: Barriers and Opportunities for Mobile Wallet

Originally published on Loyalty 360

I love New Year’s Resolutions!  Every December, I enjoy reflecting on what I’ve learned in the last 12 months, and set goals to grow professionally and personally.  On my list again this year, is studying opportunities to drive customer engagement—understanding how companies in the travel and hospitality industries can use new techniques and technologies to drive loyalty and ultimately profits.Every two years, Marketing Science Institute (MSI), a think-tank bridging academic theory and business practice, reaches out to thought leaders to set its priorities for upcoming research and conferences.  MSI’s “Priority Topic” list reflects marketing’s key challenges and opportunities (see the full list here). Topics include: Big Data; insight into people as consumers; rethinking the journey to purchase (and beyond); and mobile’s impact on how people live their lives. 

If you were to improve your organization’s effectiveness in any of these areas, chances are good you will increase your customer’s engagement and loyalty.  My “2013 professional resolution” is to share learnings about each of these Priority Topics.

Today, let’s tackle Big Data:  leveraging the customer and market information available to drive business results.  Although the topic of Big Data is just that— “Big,” the reality is when you break it down into small steps you can begin to drive customer engagement with data you already have on hand.

Big Data: The promise and the pitfalls

As computers and cell phones play an increasingly important role in consumers’ daily activities, mountains of data are collected and stored by travel and hospitality companies.  From customer transactional (e.g., bookings, loyalty program redemptions, web site visits, call center logs) to interactional data (e.g., posts on Facebook) and observational data (e.g., networked sensors in cellphones or cars), the amount of data available for analysis is immense and expanding daily.    

When it comes down to it, Big Data is useful only as we are able to glean useful business intelligence from all this data.  The true value of Big Data (or any data for that matter) is not in the bits and bytes but in using the knowledge gained to help you make better decisions—to reduce the chances of making a bad decision and to help you “sleep better at night.”  Companies can leverage big data in a number of ways including product and service development, process improvements, and revenue management.

Some companies who’ve found success with Big Data engagements (outside of travel and hospitality) include:

• Amazon.com, eBay, and Google continuously test factors—from where to place buttons on a Web page to the sequence of content displayed—to determine what will increase sales and user engagement. 

• Capital One continues to refine its methods for segmenting credit card customers and for tailoring products to individual risk profiles. According to Nigel Morris, one of Capital One’s cofounders, the company’s multifunctional teams of financial analysts, IT specialists, and marketers conduct more than 65,000 tests each year, experimenting with combinations of market segments and new products.

• The online grocer Fresh Direct adjusts prices and promotions daily (or even more frequently) based on data feeds from online transactions, visits by consumers to its website, and customer service interactions. 

The pitfalls: 

Quantum physics might be easier to explain than Big Data and brain surgery might be easier to do!  Not only do you need to conceptualize the plan, structure the data, acquire the software and/or analysis tools but then you need to do the analysis.  This is hard to get your head around! 

Big Data exercises to predict customer behavior have been met with limited success.  Netflix offered a $1 Million prize to the firm that could improve its movie selection algorithm by just 10%.  Three years later, a group managed to create a model using available data however the formula was too complicated for Netflix to implement.   If you haven’t read it yet take a few minutes to check out this HBR post that talks about the challenge of modeling consumer behavior: Big Data Hype (and reality).

Big Data: Baby steps

Here are some practical ideas for you to begin to look to incorporate some ‘Big Data’ activities into your 2013 plans:

• Link financial data to your customer satisfaction.  Understand the monetary value (in the short and long-term) of a satisfied guest to make informed decisions on investments and initiatives. 

• Build bridges between different data sources.  First, use the same categories to code responses in your customer satisfaction study, social media analytics and your call center. Second, ensure a person is tagged with the same identifier in all data sources so you can look at a customer’s responses across the silos of your organization. 

• What? So What? Now what?  Start your quest for decision-support with the end in mind.  Get agreement on the “Essential Question” you are looking to address, and identify the supporting information (from all relevant sources) you need to support your recommendations.  Make sure your recommendations answer the question:  Now what action should I take? 

We see a bright future for travel clients in using Big Data for building engagement and loyalty.  Develop a plan to answer your Essential Questions and, then you will be in a better position to practically analyze the right data from the right data sources – applying a laser-like focus on the problem you are trying to solve. 

How will you use Big Data (or any data for that matter) to drive customer engagement and loyalty in 2013?

Judy is VP of CMB's Travel & Entertainment practice and loves collaborating with clients on driving customer loyalty.  She's the mom of two teens and the wife of an oyster farmer. Follow Judy on Twitter at @Judy_LC

You may have heard the latest from Disney—they’re about to introduce a new “MagicBand” wristband letting wearers take advantage of perks like skipping to the front of the line for rides, as well as pay for meals, and purchase gifts.  It offers guests the ability to leave the wallet and paper tickets at home and focus on having fun.  The benefits to Disney can be huge, and a lot of people are seeing it that way; as one headline proclaimed: “Disney creates the happiest data mine on earth.”  Pretty clever, but of course there are those who aren’t quite as happy about the innovation; besides the thought of Big Brother entering our lives, won’t somebody think of the tan lines?But let's focus on the business aspect, the ability to track all activities and purchases on-park creates an immense opportunity for marketing, and much of the chatter concerns how Disney can use the data for direct marketing.  Did the guest ride all of the roller coasters?  Target promotional offers touting the latest thrill rides.  Did the guest get a picture with one of the cast members?  Send a doll to the guest’s suite to increase engagement.  Did the guest make a purchase at any of the retail stores?  Give them a coupon for a Disney store near their home.

Nearly everyone is coming up with ideas for how this might help Disney directly sell more of what it offers.  I’d like to think about how Disney can learn from this data in order to innovate and improve the experience.  In the direct marketing examples, the data remains data— it’s used solely to trigger marketing offers.  For market researchers, the data isn't useful until we find relationships that are relevant to decisions.

So, here is my challenge for you: what type of analysis do you think needs to be done?  What potential relationships might Disney find to innovate and change the experience?

I’ll get it started:

Disney could run on-property communication tests to improve messaging and information delivery.  By placing unique signs throughout the park, Disney can track all guests who pass each sign and capture behaviors after passing the sign.  Instead of waiting many weeks or months to gather feedback, Disney can get an “immediate” understanding of which signs work best – and potentially why.

Tell me your ideas in the comments:

Jeff is VP, Market Science Solutions at CMB. He'll have a pair of shiny new mouse ears for the most interesting idea. If he's not wearing his wristband you can still find him tweeting @McKennaJeff.