Voices: the CMB Blog

I recently came across an article focused on defunct exhibits at Disney parks. I’m a native Floridan so I flipped through the accompanying slide show with fond memories. And there it was...my all-time childhood favorite—Horizons at Epcot Center. From the robot butler to the holographic telephone, Horizons revealed a future full of promise, excitement, and funky monotone jumpsuits. 

It’s been 30 years, the future is now the present, and I don’t have a robot butler. Disappointing yes, but on the other hand, we do have the Roomba and I will argue Apple’s FaceTime is likely better than a hologram. So I think we can agree many companies have made serious innovations in the last few decades—they’ve understood that incremental change means incremental growth, and they’ve pushed the limits. Although product development is critical for companies to compete and grow, it also carries high risks, because it represents a big investment into new and unfamiliar territory—it’s crucial to get it right.

While we aren’t all Imagineers, there are strategies for new product and service development that have proven successful in a rapidly changing market—these strategies form the basis of our Best Practices in New Product Development. Two of these Best Practices are below:

1. Use advanced techniques that emulate real world trade-offs: In real life, people don’t evaluate the importance of individual features or attributes. They make choices between/among products. The more closely research emulates this process, the more accurate the findings will be. What people say they prefer, and what they actually choose, are often not the same thing. That’s why we use trade-off techniques (e.g., discrete choice) that let us derive the most important and relevant preferences as well as sophisticated data mining techniques that help us to create more accurate predictive models.

2. Build flexibility into the research: If you’re using trade-off techniques, channel Walt Disney himself (“if we can dream it, we can do it”) by including features that fall outside of current capabilities. This lets you mimic the current market and simulate a future market where these feature become available. So while you might not be ready to “do it,” if you’ve dreamed it, you can test it! That’s why, when appropriate, we build a user-friendly simulator. These simulators allow design decision-makers to run “what if” scenarios, providing additional insight when changes occur (e.g., a competitor responds with a new product, prices change, or when the technology to realize your stretch features catches up with your dreams).

We can’t promise your product development research will live as long as Horizons (16 magic filled years) but we can help ensure it’s useful for both the short and longer-term (at least until we all get our robot butlers). Check out the video below to learn how we help our make sure their new product development efforts are a success:

CMB New Product and Service Development from CMBinfo on Vimeo.

Athena is a Project Director at CMB, she looks awesome in a jumpsuit and is patiently waiting for her favorite Disney character, Donald Duck, to make a comeback.

A few weeks ago, I found myself seated at a trendy Mexican restaurant in Minneapolis, an eager participant at one of the more enjoyable business lunches I’ve encountered lately. As you might expect, the topic quickly turned from the vagaries of the marketing life to the weather, summer vacation stories, the gym, far-too-early holiday planning (I’m looking at you, Target), and then, unexpectedly, to dieting. It was there where I learned Jim Garrity, SVP and head of CMB’s Financial Services, Insurance & Healthcare Practice, was quite a fan of Weight Watchers, one of the few truly successfully long-term dieting options out there – it earned Consumer Report’s highest mark for nutrition analysis.Jim had become a devotee of the Weight Watchers PointsPlus® plan, which, for someone I’d fancied a meat-and-potatoes man like me, came as a bit of a surprise. But as Jim continued to discuss the program and what he enjoyed about it, I realized that PointsPlus® was nothing more than another example of CMB’s brand and product development bread-and-butter: the tradeoff exercise. 

For those not familiar with how it works, PointsPlus® assigns a numeric point-value to each meal/snack/dessert/shake/whatever you can buy through the program, based on protein, carbohydrates, fat and fiber content. The system will then give you a daily points target, taking into account your height, weight, age and gender; read more about it here. Simply stay at or under your target, and…well, that’s it. 

This, as you might expect, presents our would-be dieter with a daily flurry of choices.  Do you have the bagel with cream cheese or the fresh fruit for breakfast? Go with a savory salad or a slim sandwich for lunch? And how do these choices affect what you have “left” at dinner?  Sorry to burst your bubble, eager reader, but if you want that red velvet cake, you’re going to have to pass on the cream cheese.

Built on the economic principle of opportunity cost (the idea that to buy a product or undertake an activity, that product/activity must necessarily replace something else you might have bought or engaged in), these sorts of tradeoffs are exactly what we seek to model when researchers help develop brands, products, messaging campaigns, or basically anything else with a give-and-take.  You can’t be the industry leader and try harder. If you want to offer premium customer service, you’re going to have to charge a bit more. Anyone who’s ever made a budget, whether on a ledger or www.Mint.com, understands that if you go to the concert, you might have to skip the movies this week.

Our job, then, is to master the usage of methodological techniques which replicate these real-world tradeoffs within a research setting. Almost all of my clients take advantage of Maximum-Difference Scaling, an exercise where participants select which items/features/messages/etc. they like most and least, four options at a time. By forcing this tradeoff, we can accurately prioritize huge lists of information in short order, not only rank-ordering but also sizing the distance between items. Many also use allocations, which allow participants to assign different values to a set of given options, but knowing there are only so many points to go around (often 100). My brand and product development engagements often utilize Discrete Choice (or Conjoint) Modeling, an extremely powerful form of tradeoff exercise where participants must choose between holistic brand positionings or fully-configured products. We can then deconstruct their decisions, analyze the tradeoffs, and find those pesky drivers of decision-making that are the foundation of marketing as we know it.

Think about it this way: if you’re still with me, you’ve traded off the time you could’ve spent watching E!, playing Candy Crush, or checking Facebook in favor of a little lesson in economics and research. So what’ll it be, then–the pasta or the seafood?

Nick is a Project Manager within CMB’s Financial Services, Insurance & Healthcare Practice, as well as a poker-playing behavioral economics and game theory nerd. You can follow him on Twitter @NAPangallo. He would always choose the pasta.

In March of 2011 a movie was released in theaters, with all the hallmarks of box office success, it starred a handsome Hollywood newcomer and a seasoned Hollywood veteran, it had an intriguing plot, and it was released during the traditionally uncompetitive winter/spring movie season. So, when the movie, Limitless, debuted at #1, it was no surprise.

Now this sounds like a typical Hollywood hit, but there was something about this movie that made me (self-proclaimed movie buff since age 8) pay a bit more attention. The main plot device was a product: an experimental drug that allows the user to use 100 percent of his brain, and this product played a crucial role in character development and the overall plot. Could this movie increase demand for a similar type of drug in the real world, specifically for a segment of the US population that previously hadn’t been very demanding of that product? In short, could this movie make a target market aware of a need that they didn’t even know they had before?Fired-up about this epiphany like Peter Finch in Network, I boldly predicted to a friend that a certain company might actually run short of supply of the drug, because the movie would uncover previously unknown needs to a large segment of the US population, and that segment would consequently want to start buying like the floor traders at the end of Trading Places. (Yup: two movie references, one sentence.) After all, I had previously seen the effect that movies could have on product demand in the past:

• Top Gun = approximate 500% increase in the number of Naval aviator applications to the US Navy as well as a 40% increase in sales of Ray-Ban Aviator sunglasses (in a decade that had been decidedly keen on Ray-Ban Wayfarers, which themselves were allegedly given a sales boost after Tom wore them in 1983’s Risky Business)

• Lord of the Rings = 40% increase in New Zealand tourism from 2001 to 2006

• Field of Dreams = an isolated cornfield in the middle of Iowa that gets 60,000+(!) visitors per year

• 300 = sudden spike in GoogleTrends for Mark Twight and his CrossFit-like workouts that made the actors look like Spartan warriors

• And then of course there is the sad story of what Supersize Me did for the demand of ol’ McDonald’s Big Mac and its friends

So, I had seen this sort of thing before, and – wouldn’t you know it – about three months after opening night, this certain company publicly announced to its stockholders that it did not have enough supply to meet demand for the drug: they were plum out!

Coincidence? I think not! Well, at least I didn’t think so at the time. You see, I wasn’t a market researcher yet, so I didn’t really consider the hundreds of variables that could be involved in the outcome of something (in this case, that “something” being a company’s unexpected shortage of a certain type of product). Besides, it was a pretty bold and insightful prediction, it wouldn’t be the first time a movie drove up demand for something! So, the fact that my prediction actually came true gave credence and justification (at least in my own mind at the time) to the fact that the movie must have had the effect that I predicted it would!

Well, now that I have a few market research years under my belt, I see the situation a bit differently. In the article “Advertising Analytics 2.0” from the March 2013 issue of Harvard Business Review, I was happy to see that they DID talk about movies having an effect on product sales…but “cinema” is only one of hundreds of variables that are taken into account and run in a software analytics engine that determines the true weight and importance of each variable. So, the only way to determine whether or not the “movie variable” was actually significant in Limitless would be to get fancy and use some of those new Analytics 2.0 techniques, run an analysis of the effects of all the possible variables – and, after watching CMB’s analytics team in action, I can tell you that this means a lot of variables. Any of which could have played a part in either an increase in demand or a shortage in supply or both happening simultaneously. There are a few possible scenarios that led to a shortage in supply, and a lot of different variables that could’ve caused each of those scenarios to occur.

So, is it crazy to think that movies have the potential to dramatically increase demand for a product, when the right conditions are met within the movie? Well…maybe; for Supersize Me, the effect is obvious, but for Limitless, the effect of drivers is not perfectly clear and the conclusions are obtainable yet less certain. But, what’s important is the fact that sometimes, completely unbeknownst to anybody – there could be an unforeseen variable or set of variables out there, and they could ultimately have a profound effect on your product or industry. It could be a shift in consumer viewing habits, it could be a general economic shift, or maybe, just maybe, it could be a movie. Either way, you won’t know until you start asking the right questions and digging through all the possible variables.

Jonah is a Senior Associate Researcher, he’s been a movie buff since he saw India Jones: Raiders of the Lost Ark when he was 8 years old. (If you ever need a “movie guy” on your trivia team, he’s your man.)

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The New York Times article, The Extraordinary Science of Addictive Junk Food, caught my attention by linking the hot topic of “junk food” and the obesity epidemic to the market research that supports it.  This is where my inner geek gets really excited—it’s not often that two things I’m passionate about (nutrition and market research) are so perfectly linked. 

Ever wonder why it’s virtually impossible to eat just one Dorito? Or how they got the recipe for Dr. Pepper just right?  How do you think they engineered Cheetos into the perfect cheesy, crunchy, melt-in-your-mouth treat?  As any market researcher knows, it goes far beyond basic trial and error—this isn’t like asking a few people if they like your new brownie mix. But even for someone who lives and breathes market research, the article was incredibly illuminating. Companies put a lot of time and effort into developing foods that will both taste good and be profitable; they consider the basic principles of supply and demand, and couple that with food science and a lot of market research to fill our needs and desires.

Because I know very little about food science, I won’t talk about the “bliss point” (the levels of sugar, fat and salt in processed food that keep us craving more) though I find it fascinating.  Instead, here are some fascinating examples of how market research plays a role in determining what foods end up on the shelves of your local grocery store and in millions of pantries around the world.

Qualitative research identifies a need
In the article, we learn how Oscar Meyer conducted focus groups comprised of working moms to learn not what they were feeding their kids for lunch, but how they felt about the challenges and expectations they had in providing meals for their children. Oscar Meyer learned that these moms were strapped for time and felt pressured to provide a full lunch, while also getting themselves out the door, and to the office. The qualitative research revealed some of the tremendous sociological, psychological, and economic pressures faced by moms.  The company’s solution was Lunchables—a hugely successful product, with sales of $218 million in the first year.

Conjoint analysis configures a new product
Campbell’s Soup used a statistical method called conjoint analysis, to determine the optimal product configuration(s) for their soups.  We use conjoint analysis quite often ourselves because it lets us measure and evaluate the relative importance of individual characteristics and determine the right combinations of these characteristics. Campbell’s used conjoint the same way—to optimize the perfect combinations of ingredients, texture, taste, mouth feel, and so on, to (literally) engineer the ideal food.

Segmentation pinpoints a new target audience
Prego conducted segmentation research to find that there are three primary segments of spaghetti sauce consumers: those who like their sauce plain, those who prefer it to be spicy, and those who like it extra-chunky; the key here is that when the research was conducted, there was no extra-chunky tomato sauce on the market! Prego was able to identify a huge segment of the market whose needs (for extra-chunky tomato sauce) were not being met; the result was a new Prego “extra chunky” sauce that dominated the market.

Food is more than just fuel, especially for those of us lucky enough to have plenty to eat… it’s about things like family, comfort, convenience and love.  And whether you won’t touch a GMO or want Mayor Bloomberg to leave your giant sodas alone, it’s important to know when you grab that bag of chips—the first ingredient is most likely a ton of market research.

Dana is Research Director at CMB. Her husband’s recent conversion to a vegan diet has her thinking about food science even more than usual, though she continues to enjoy cheese.

Check out our latest webinar: The 6 Secrets of Succesful Segmentation, it's much healthier than Doritos we promise.

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.