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How Under Armour’s Social Currency Builds a Powerful Brand

Posted by Ed Loessi

Tue, Aug 23, 2016

 Last week, CMB and the Vivaldi Group released the results of our watershed study: Business Transformation through Greater Customer-Centricity: The Power of Social Currency.  In the report, we share insights from 18,000 consumers, about 90 brands, across 5 industries (beer, restaurants, auto, airlines, and fashion).

The genesis of this research was Vivaldi’s Social Currency concept. Introduced in 2012, Social Currency is a framework for understanding brands’ ability to fit into how consumers manage their social lives in today’s social, digital, and mobile context. This year, CMB partnered with Vivaldi to refine the concept and offer fresh insights into a changing marketplace.

One of the most powerful lessons from our research is that today’s customers don't see themselves as serving brands as the traditional “influencer”  or “brand ambassador” was thought to, but instead act in service of themselves. We see people looking for brands that help them represent who they are and what they believe. Today, the brand is in the hands of the customer and brands that facilitate experiences and behaviors that help consumers explore, develop, and express their identities are the brands that outperform their competitors. This level of performance difference includes high levels of Consideration, Loyalty, Price Elasticity, and Advocacy.

So, how does Social Currency come together? There are two parts; one is an overall score that is a weighted average of the 7 core factors or dimensions (shown below) that influence brand success. Topping that list of dimensions are two important forms of Identity—Personal and Social. Our research shows that identity is a key driver in people’s relationships to brands. The other piece of this framework is a Social Currency Assessment that helps brands develop truly customer-centric activities – messaging, advertising, content development, and digital media that align with customers' needs and wants. It’s important to note that we’re not just talking about brands being good at social media campaigns—it may be that customers express their needs and wants quite often in social media channels, but they also express themselves in many other social situations, and capturing that full spectrum is of vital importance.

SC_Pyramid.png


The Case of Under Armour

Let’s dig in! One of the stellar performers we uncovered was Under Armour. Founded in 1996, Under Armour is a relative newcomer in the sports apparel space, especially compared to well-known brands such as Nike (1964) and Adidas (1949). Without question, UA founder Kevin Plank had his work cut out for him when he began carting around his unique moisture-wicking T-shirts from the back of his car. It’s hard to imagine how a company with such humble beginnings has risen so quickly to take on many other well-established competitors.

As customer influence has grown, we can see patterns in the performance of those brands that create and nurture the activities that allow customers to identify and share their interaction with the brands. This concept was borne out very clearly in our study, which showed how Under Armour has eclipsed Adidas in its overall ability to deliver Social Currency, and edges closer to the top performer across all industries—Nike. Despite Under Armour’s size, it has done a masterful job understanding its customer and its customer’s needs, and through messaging, shareable content, and the linking of its customer’s Personal and Social Identities to the Under Armour brand, it has emerged as a force to be reckoned with in the sports apparel space. You can see in the diagram below “The Under Armour Success Story” that Under Armour scores particularly well in Personal Identity, Information, and Conversation dimensions.

UA_Success.png

How does Under Armour achieve these high marks of Social Currency and build its brand?

The Misty Copeland example:

From our report: “Like Nike’s “Just Do It” tagline, Under Armour’s “I Will” messaging, is empowering, inspiring, and inclusive. Under Armour’s messaging also celebrates the underdog with the competitive spirit embodied in its “I will what I want” campaign, featuring Misty Copeland, the first black woman to be promoted to principal dancer in the American Ballet Theatre’s 75-year history. The campaign produced $35 million in earned media and was particularly effective with women with a reported 28% increase in women’s sales. This success is supported by our research, while overall men’s Social and Personal Identity scores are higher across all sports apparel brands, Under Armour’s Social Identity scores among women (44.5) coming closer to those of men (48.1) than any of the others we tested in the category (Reebok, Adidas, Nike).”

The Michael Phelps Example:

You know we wouldn’t let this post go by without an Olympic reference, and neither would Under Armour. The Michael Phelps featured “Rule Yourself” campaign (part of the “I Will” strategy) and video has grown to become one of the most shared Olympic videos of all time. What’s so appealing? Why are so many people identifying with the message of “Rule Yourself” as put forth by Under Armour?

Katie Richards, writing for Adweek“For one, it's striking the right emotional chord with its target audience: millennial men between the ages of 18 and 34. The dramatic nature of the Phelps spot (with a killer track from The Kills) and its ability to take viewers through the swimmer's intense training process elicited a sense of inspiration among 47 percent of overall viewers, and 68 percent of millennial men.”

“Droga5 co-head of strategy Harry Roman echoed Prywes, adding that the Phelps ad is so shareable because it's able to convey the sacrifice that the swimmer makes each day to prepare for Rio.”

As someone who grew up playing every sport imaginable as a kid, and continued to do so through high school and beyond, I can relate to the “Rule Yourself” idea. I’ve now converted to low-impact sports to save my aging knees, but there is part of me that identifies with that idea of not letting go, of taking one more shot. It’s a natural bent of athletes, elite or otherwise. Under Armour has made it easy for me to identify personally, join the conversation through the videos created for the campaign, and express myself regarding the brand. A pale comparison it may be, but I can see that small bit of Michael Phelps in myself, the person who says “I will.”

One final note about the “Rule Yourself” campaign. According to Adweek, to date, 56 percent of the spots' shares are coming from Facebook, followed by Twitter at 28 percent. You’ll also notice, in the chart below, that across the social spectrum, people are expressing their personal and social identities in virtually every type of social environment.

 AA_UA.png

It’s clear, after studying the 90 brands, that those brands that facilitate digital, socially-driven experiences and behaviors that help consumers explore, develop and express their identities are clear winners. Under Armour, in particular, has done an exceptional job in this regard. They have built on the experiences of Misty Copeland and Michael Phelps and made them identifiable to their customers, and hence identifiable with their brand. Under Armour has then made it possible to share great content and express oneself as a function of that brand. Anyone, dominant athlete, former athlete, weekend (or weekday) warrior can see that underdog, and know that “I Will” also!

Ed is CMB's Director of Product Development and Innovation. He thinks there is a game-changing product or idea within everyone, and it’s his job to dig it out. You can share ideas with him @edloessi.

Download the full report, and let us show you how Social Currency can enable brand transformation:

Get the Full Report

And check out our interactive dashboard for a sneak peek of Social Currenct by industry:

Interactive Dashboard

 

 

Topics: Chadwick Martin Bailey, consumer insights, brand health and positioning, Social Currency

Swipe Right for Insights

Posted by Jared Huizenga

Wed, Aug 17, 2016

Data collection geeks like me can learn a ton at the CASRO Digital Research Conference. While the name of the event has changed many times over the years, the quality of the presentations and the opportunity to learn from experts in the industry are consistently good.

One topic that came up many years ago was conducting surveys via cellphones with SMS texts. This was at a time when most people had cellphones, but it was still a couple of years before the smartphone explosion. I remember listening to one presentation and looking down at my Samsung flip-phone thinking, “There’s no way respondents will take a CMB questionnaire this way.” For a few simple yes/no questions, this seemed like a fine methodology but it certainly wouldn’t fly for any of CMB’s studies.

For the next two or three years, less than half of the U.S. population owned smartphones (including yours truly). Even so, SMS texting was getting increasing coverage at the CASRO conference, and I was having a really hard time understanding why. Every year was billed as “the year of mobile!” I could see the potential of taking a survey while mobile, but the technology and user experience weren’t there yet. Then something happened that changed not only the market research industry but the way in which we live as human beings—smartphone adoption skyrocketed.
Girl_and_phone.jpg

Today in the U.S., smartphone ownership among adults is 72% according to the Pew Research Center. People are spending more time on their phones and less time sitting in front of a computer. Depending on the study and the population, anywhere from 20%-40% of survey takers are using their smartphones. And if it’s a study with people under 25 years old, that number would likely be even higher. We can approach mobile respondents in three ways:

  • Do nothing. This means surveys will be extremely cumbersome to take on smartphones, to the point where many will abandon during the painful process. This really isn’t an option at all. By doing nothing, you’re turning your back on the respondent experience and basically giving mobile users the middle finger.
  • Optimize questionnaires for mobile. All of CMB’s questionnaires are optimized for mobile. That is, our programming platforms identify the device type a respondent is using and renders the questionnaire to the appropriate screen size.  Even with this capability, long vertical grids and wide horizontal scales will still be painful for smartphone users since they will require some degree of scrolling. This option is better than nothing, but long questions are still going to be long questions.
  • Design questionnaires for mobile. This is the best option, and one that isn’t used often enough. This requires questions and answer options to be written with the idea that they will be viewed on smartphones. In other words, no lengthy grids, no sprawling scales, no drag and drop, minimal scrolling, or anything else that would cause the mobile user angst.  While this option sounds great, one of the criticisms has been that it’s difficult to do advanced exercises like max-diff or discrete choice on smartphones.

One cautionary note if you are thinking that a good option would be to simply disallow respondents from taking a survey on their smartphones.  Did your parents ever tell you not to do something when you were a child?  Did you listen to them or did you try it anyway? What’s going to happen when you tell someone not to take a survey on their mobile device?  Either by mistake or out of sheer defiance, some people will attempt to take it on their smartphone. This happened on a recent study for one of our clients.  These people tried to “stick it to the man,” but alas they were denied entry into the survey. If you want “representative” sample, the other argument against blocking mobile users is that you are blocking specific populations which could skew the results.

The respondent pool is getting shallow, and market research companies are facing increased challenges when it comes to getting enough “completes” for their studies.  It’s important for all of us to remember that behind every “complete” is a human being—one who’s trying to drag and drop a little image into the right bucket or one who’s scrolling and squinting to make sure they are choosing the right option on an 11-point scale in a twenty row grid.  Unless everyone is comfortable basing their quantitative findings off of N=50 in the future, we all need to take steps to embrace the mobile respondent. 

Jared is CMB’s Field Services Director, and has been in market research industry for eighteen years. When he isn’t enjoying the exciting world of data collection, he can be found competing at barbecue contests as the pitmaster of the team Insane Swine BBQ.

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Topics: mobile, research design, Market research

Passive Mobile Behavioral Data – Part Deux

Posted by Chris Neal

Wed, Aug 10, 2016

Over the past two years, we've  embarked on a quest to help the insights industry get better at harnessing passive mobile behavioral data. In 2015, we partnered with Research Now for an analysis37824990_thumbnail.jpg of mobile wallet usage, using unlinked passive and survey-based data. This year, we teamed up with Research Now once again for research-on-research directly linking actual mobile traffic and app data to consumers’ self-reported online shopper journey behavior.

We asked over 1,000 shoppers, across a variety of Black Friday/Cyber Monday categories, a standard set of purchase journey survey questions immediately after the event, then again after 30 days, 60 days, and 90 days. We then compared their self-reported online and mobile behavior to the actual mobile app and website usage data from their smartphones. 

The results deepened our understanding of how best to use (and not use) each respective data source, and how combining both can help our clients get closer to the truth than they could using any single source of information.

Here are a few things to consider if you find yourself tasked with a purchase journey project that uses one or both of these data sources as fuel for insights and recommendations:

  1. Most people use multiple devices for a major purchase journey, and here’s why you should care:
    • Any device tracking platform (even one claiming a 3600 view) is likely missing some relevant online behavior to a given shopper journey. In our study, we were getting behavior from their primary smartphone, but many of these consumers reported visiting websites we had no record of from our tracking data. Although they reported visiting these websites on their smartphones, it is likely that some of these visits happened on their personal computer, a tablet, a computer at their work, etc.
  2. Not all mobile usage is related to the purchase journey you care about:
    • We saw cases of consumers whose behavioral data showed they’d visited big retail websites and mobile apps during the purchase journey but who did not report using these sites/apps as part of the journey we asked them about. This is a bigger problem with larger, more generalist mobile websites and apps (like Amazon, for this particular project, or like PayPal when we did the earlier Mobile Wallet study with a similar methodological exercise).
  3. Human recall ain’t perfect. We all know this, but it’s important to understand when and where it’s less perfect, and where it’s actually sufficient for our purposes. Using survey sampling to analyze behaviors can be enormously valuable in a lot of different situations, but understand the limitations and when you are expecting too much detail from somebody to give you accurate data to work with.  Here are a few situations to consider:
    • Asking whether a given retailer, brand, or major web property figured into the purchase journey at all will give you pretty good survey data to work with. Smaller retailers, websites, and apps will get more misses/lack of recall, but accurate recall is a proxy for influence, and if you’re ultimately trying to figure out how best to influence a consumer’s purchase journey, self-reported recall of visits is a good proxy, whereas relying on behavioral data alone may inflate the apparent impact of smaller properties on the final purchase journey.
    • Asking people to remember whether they used the mobile app vs. the mobile website introduces more error in your data. Most websites are now mobile optimized and look/ feel like mobile apps, or will switch users to the native mobile app on their phone automatically if possible.
      • In this particular project, we saw evidence of a 35-50% improvement in survey-behavior match rates if we did not require respondents to differentiate the mobile website from the mobile app for the same retailer.
  4. Does time-lapse matter? It depends.
    • For certain activities (e.g., making minor purchases in grocery store, a TV viewing occasion), capturing in-the-moment feedback from consumers is critical for accuracy.
    • In other situations where the process is bigger, involves more research, or is more memorable in general (e.g., buying a car, having a wedding, or making a planned-for purchase based on a Black Friday or Cyber Monday deal): you can get away with asking people about it further out from the actual event.
      • In this particular project, we actually found no systematic evidence of recall deterioration when we ran the survey immediately after Black Friday/Cyber Monday vs. running it 30 days, 60 days, and 90 days after.

Working with passive mobile behavioral data (or any digital passive data) is challenging, no doubt.  Trying to make hay by combining these data with primary research survey sampling, customer databases, transactional data, etc., can be even more challenging.  But, like it or not, that’s where Insights is headed. We’ll continue to push the envelope in terms of best practices for navigating these types of engagements as Analytics teams, Insights departments, Financial Planning and Strategy groups work together more seamlessly to provide senior executives with a “single version of the truth”— one which is more accurate than any previously siloed version.

Chris Neal leads CMB’s Tech Practice. He knows full well that data scientists and programmatic ad buying bots are analyzing his every click on every computing device and is perfectly OK with that as long as they serve up relevant ads. Nothing to hide!

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Topics: advanced analytics, mobile, passive data, integrated data

Can Facial Recognition Revolutionize Qualitative?

Posted by Will Buxton

Wed, Aug 03, 2016

Full disclosure: I’m an Android and Google loyalist, but please don’t hold that against me or the rest of my fellow Android users, who, by the way, comprise 58% of the smartphone market share in the United States. As a result of my loyalty, I’m always intrigued by Google’s new hardware and software advancements, which are always positioned in a way that leads me to believe they will make my life easier. Some of the innovations over the years have in fact lived up to the hype, such as Google Now, Google Drive, and even Google Fusion, while others such as Google Buzz and Google Wave have not.

As a researcher, last year’s launch of Google Photos caught my eye. Essentially, Google
Photos now utilizes facial recognition software to group or bunch your photos based on people in them, scenery (i.e., beaches and Google_Photos_icon.svg-1.pngmountains) and even events (i.e., weddings and holidays). To activate the facial recognition feature, all you have to do is tag one photo with an individual’s name and all other photos with that person will be compiled into a searchable collection. Google uses visual cues within the photos and geotagging to create other searchable collections. While these features might not seem extraordinary—I can see who was the most frequent star of my photos (my enormous cat) or where I most commonly take photos (honeymoon sans enormous cat)—I began to imagine the possible impact these features could have on the market research industry.

Visual ethnographies are one of many qualitative research options we offer at CMB. This is a rich form of observation, and, for some companies, it can be cost prohibitive in nature, especially ones focused on a “cost-per-complete.” But, what if there was a way to remove some of the heavy lifting of a customer journey ethnography by quantifying some of the shopping experience using technology that could track date/time, location, shopping layout, products viewed, order in which products are viewed, and so on, all through recognition software? Would the reduction in hours, travel, and analysis be able to offset the technological costs of these improvements?

Market research, and, in particular, qualitative research have always been a combination of art and science, and to expect any technological advancement to adequately perform any cogent analyses is a bit premature and perhaps too reminiscent of The Minority Report. (I don’t think it worked out well). But the promise of these powerful tools makes it an exciting time to  be a qualitative researcher!

Will Buxton is a Project Manager on the Financial Services team. He enjoys finding humor in everyday tasks, being taken seriously, and his enormous cat.

Learn more about how our dedicated Qualitative practice helps brands Explore, Listen, & Engage.

 

 

 

Topics: methodology, qualitative research, mobile, storytelling, customer journey

Getting Virtual at IIR Omnishopper: The Future of Retail

Posted by Julie Kurd

Tue, Jul 26, 2016

cy.pngAt this month’s IIR Omnishopper conference, all anyone could talk about was Pokémon Go.  Several research suppliers told me they’d downloaded it and everyone was marveling at its stellar adoption and usage rates.  I had my 13 year old son’s account on my mobile device, so I began the conference naively thinking ‘I’ll go out before the sessions start and catch a few Pokemon for him.’  I couldn’t stop, and despite the fact that CMB works with leading gaming companies, and we’ve got more than a few die-hard gamers on staff, I don’t consider myself a gamer.

How had I morphed into Cheffen Yobs from the moment I began to play? The answers are a case study in consumer motivation:

  • Primary motivation/goal: My initial, primary motivation/goal for Pokémon Go, of course was getting more creatures and points because why not? It was a hot new marketing opportunity and I anticipated being able to talk about it over lunch at the conference (the game rates high on helping me build my social and personal identity)!
  • Secondary motivation/goal: I quickly learned that Pokémon Go has history embedded in each stop, so I started learning interesting things about the city of Chicago. This motivated me to alter my destinations, because I was curious about a particular building or statue. I was looking in the ‘corners’ of Chicago city center, and I was discovering new art, new monuments, and new bridges.  Over the course of the 3-day conference, I walked through several great sections of Chicago. I went to about 12 hours of conference material but I set my clock to wake up earlier to play that game.  Typically at a conference I fly in and then I sit.  And I sit. And I sit.   
  • Unintended benefit: Many of my colleagues share their gamified solution to fitness at our office, and they push each other to exercise more, but my life is hectic and I just don’t add fitness to my priority list. Imagine my surprise when one of the unintended benefits of my trip was that I actually walked 10 km in a level of heat that I can’t even describe, and I didn’t even know I had walked so much until I got home and my son told me!

Questions and excitement about Pokémon Go also found their way into the conference sessions.  The Mall of America’s Emily Shannon talked about the Mall’s digital strategy. There’s the mundane—assigning every bathroom a different text number so you can text that the bathrooms are dirty, and there’s the delicious—hungry shoppers can ask ‘where can I get a great ice cream?’ and because the Mall of America has 12 ice cream stores, the Mall staff ask further questions about the ice cream preference (via text) and deliver an exceptional experience.  Shannon said that the Pokémon Go was definitely delivering the excitement and enthusiasm that are central to the Mall of America’s value proposition, so they were meeting and selecting strategies to increase engagement and delight among mall goers.  In the week following the conference, the Mall of America has launched a Trainer Lounge and tips for playing Pokémon Go at the Mall. 

The conference was exactly about engaging consumers along the path of discovery through purchase and repurchase to loyalty and advocacy.  Each presenter had a different take, and each brought us through their approaches, from full body Virtual Reality to eyeglass technology, cash register data, landscape assessment, qualitative consumer diary, strategy platforms, ideation, and survey trends.  Many speakers, including Ron Wetklow of Treasury Wine Estates, to Scott Young of from PRS IN VIVO, and Laura-Lynn Freck, of Red Bull talked about digital engagement driving physical engagement. 

In the consumer insights industry, engagement, primary and secondary motivations and unintended consequences are central to our work.  In the weeks since the conference, I’ve logged in a few times, but I don’t feel motivated to play.  Why?  1) the history of my suburb just isn’t that exciting, 2) there are only a few stops near my house and it’s not that interesting to go to the same spot 10 times 3) thanks to in-group norms—I’m not going to stand outside the library with 10 kids under 18 years old to play a game on my mobile device because they’re ‘not my tribe’. But, combine the game with my frequent traveling and make me learn stuff on my timetable and maybe even talk to people and I’ll play every time.  It’s been 10 days since the conference and I see the game everywhere, my bet is on the brands who can “catch” the opportunities that come from these uber-engaging tech-enabled phenomena.

Julie blogs for GreenBook, ResearchAccess, and CMB. She’s an inspired participant, amplifier, socializer, and spotter in the twitter #mrx community, so talk research with her @julie1research.

Did you miss our recent webinar on the power of Social Currency measurement to help brands activate the 7 levers that encourage consumers to advocate, engage, and gain real value? You're not out of luck:

Watch Here

 

Topics: technology research, consumer insights, conference recap, customer experience and loyalty, retail research

5 Questions with CMB's Director of Product Development and Innovation

Posted by Lauren Sears

Wed, Jul 20, 2016

LEd_Loessi_web_final.pngast week, I had the opportunity to sit down with Ed Loessi, CMB’s Director of Product Development and Innovation. We talked about his role defining and developing products and solutions, why agency innovation is so important, and how our innovation efforts can lead to delivering better solutions for our clients.

Historically, early innovation has been around physical products. Personally, even when I think about innovation, my first thoughts are about technology, cars, phones, etc. So why do agencies, like CMB, need to invest in innovation?

Ed: To your first point about the perception around innovation being associated with products, Austrian economist Joseph Schumpeter wrote that innovation is achieved when companies craft inventions that constructively change their business models. For many decades, this was a very physical-product driven idea. However, for a service-based or information-intensive business that provides insights, the “product” is the insight itself.

This understanding makes it easy to see why companies that provide insights must be as focused on innovation as their physical-product counterparts. In order to succeed and continue to perform at a high-level, companies must constantly construct and deconstruct their business models in order to provide the best possible services to clients.

Makes sense. So, how do we get clients to value an organization that’s innovating services?

Ed: That’s actually pretty easy. If you went to anyone on the street and asked them if they want to buy this five-year-old smartphone, how many would say yes? Probably none. It’s the same with services and insights—nobody wants old insights or old ideas (unless they’re still valuable). Clients want to have all of their providers working to be the best at supplying materials, finished products, and services. What you have to do as a service provider is show that you’re constantly working to move the provision of your services forward—because that’s what moves the client’s business forward. This can be achieved by having POV’s on things that will impact your clients in the future, actively testing solutions to things that will impact them very soon, and actively engaging in solving problems that are impacting them right now. By covering the entire innovation spectrum, clients will begin to recognize you as an innovative organization.

Could you give some examples of innovation within CMB?

Ed: Sure—

  • First, CMB has been in business for more than 30 years, so there are many examples of innovation that have spanned those decades. We’ve embraced new ideas and technologies, and we have helped our clients through the peaks and valleys of changing economics.
  • The big change, and the reason for my role, has been to step up our speed of innovation. By having a person who focuses on innovation within the organization and works across all of the practice and service delivery areas, I can help things happen quicker. We’ve also matched that with a concept of virtual teams, in which people from the practice areas, service delivery, sales, marketing, analytics, and project management come together to focus on rapidly developing or upgrading an approach.
  • More specifically, we’re taking new ideas and existing approaches and applying agile methods (quick iterations, earlier customer feedback, and faster releases into the market) across all of the services that we provide. We’re working to make sure that all of our practice areas and market research services are constantly moving forward in quality and value.

You also just started an innovation group within CMB, and I’m excited to be one of its members! What was your thought process in establishing the group?

Ed: The main point of our innovation group is to have a way of training and helping more people in the company understand innovation. The company has always been innovative (hence its success over the years). The goal of the innovation group is to have as many people involved in innovation as possible and to keep people thinking about innovation as much as possible.

The innovation group contains several sub-groups, some of which focus on the innovations our clients are working on. Other subgroups look at the big challenges in market research and ask, “how do we tackle this?” All in all, we want to discover innovative ideas both internally and externally, and we want to be really good at getting those innovations to market.

What would be your advice to other agencies trying to be more innovative? 

Ed: Well, I don’t want to give away all of the secrets. However, it’s safe to say that you have to make a commitment to being innovative, and you have to do it quickly. Clients don’t want to wait around for new approaches, especially in a world that is changing as fast as the world that we live in today. You’ve got to be able to function as agilely as possible, and you have to be able to engage with your customers on those innovative ideas early and often. 

Lauren is a Senior Research Associate at CMB whose best innovative ideas form in the kitchen when she experiments with new recipes. 

Ed is the Director of Product Development and Innovation at CMB. He thinks there is a game-changing product or idea within everyone, and it’s his job to dig it out. You can share ideas with him @edloessi.

Topics: Chadwick Martin Bailey, growth and innovation

Do Consumers Really Know You? Why True Awareness Matters

Posted by Jonah Lundberg

Wed, Jul 13, 2016

From hotels to healthcare, brands are facing an unprecedented era of disruption. For brands to compete, consumers need to know and love your brand for what it really stands for. Critical questions for brands include: have folks even heard of you (Awareness), how well do they think they know you (Familiarity), and how well do they really know you (True Awareness)?

Folks probably won’t buy from you if they’ve never heard of you or don’t know much about you. To pinpoint areas to improve and track success, you need to include both Familiarity and True Awareness in your competitive brand tracking.

Familiarity

Familiarity can be a vague metric for stakeholders to interpret, especially alongside Awareness. A common question we hear is “What’s the difference between Awareness and Familiarity? Yes, I’m aware. Yes, I’m familiar. Isn’t it the same thing?”

Not quite.

Awareness is “yes” or “no”—have you heard of the brand name or not? Familiarity gauges how well you think you know the brand. Sure, you’ve heard of the brand, but how much would you say you know about it?

It’s summertime, so let’s use a baseball example–Comerica Park is home of the Detroit Tigers, and Target Field is the home of the Minnesota Twins:

  • I watch baseball a lot, so if you asked me if I was aware of Comerica and Target, I’d say yes to both.
  • If you asked me how familiar I was with Comerica, I would tell you that I have absolutely no idea what its products are. I just know its name because of where the Twins go when they visit Detroit to play the Tigers.
  • Target, on the other hand, I know very well: it’s headquartered in my home state of Minnesota, and I’ve been inside their stores hundreds of times.

In research-talk: I am not at all familiar with Comerica. I am very familiar with Target.

If you’re deciding whether or not to include Familiarity in your competitive brand tracking, you first need to determine whether you want your brand to be widely known and known well or just widely known. Do you want to be the popular guy at school who most people know by name but don’t know very well? Or do you want to be the prom king—the guy everyone knows the name of and knows well enough to vote for? 

Take a look at a real example below, showing Top 10 Brands Aware vs. the Top 10 Brands Highly Familiar in a recent competitive brand tracking study (brand names changed for confidentiality):

Jonah_blog.png

You’ll notice a pattern: a brand that many people have heard the name of (high Awareness) can be trumped by a brand that not-as-many people have heard the name of (low Awareness) when it comes to how well the brand is known (Familiarity) among those who have heard the name (among Aware). It is possible to be more successful in the market with a lower level of awareness if those folks know you well.                                            

This isn’t surprising, since Familiarity is only asked for brands that people are aware of.

However, Big Papi’s Burgers proves that you can be both widely known and known well. Again, though the brand name is a pseudonym, the data is real. So, if you think it’s worth measuring your brand relative to the Big Papi’s Burgers of your industry you need Familiarity to gauge your brand’s standing vs. the competition.

True Awareness

Just because folks say they know you doesn’t mean they actually do. Also, if you find yourself with a lower level of Familiarity, how do you fix that?

While Familiarity gauges how well you think you know a brand, True Awareness asks you to prove it. Familiarity serves as the comparison point vs. other brands, but True Awareness serves as the comparison point of your brand vs. itself: how well do people know you for selling X, and how well do people know you for selling Y and Z?

True Awareness is a question that asks people aware of your brand which specific products or services they think your brand offers. You show them a list of offerings that includes all the things your brand does offer and a few things your brand does not offer.

If people choose any of your brand’s offerings correctly (e.g., they select one of the four correct offerings listed) and don’t erroneously select any things your brand does not offer, then they are truly aware—they do, in fact, know you well. This also helps you identify sources of errors in perception. Folks failing to credit you for things you do, or falsely crediting you for things you don’t, helps you identify areas for improvement in your marketing communications. 

So what’s the point of asking True Awareness? It provides you with more good information to use when making decisions about your brand:

  • When you combine True Awareness with usage data (e.g., how much people use and/or would like to use X, Y and Z products/services in general) you are able to inject vibrant colors into what was previously a black and white outline—your brand understanding transforms from a rough sketch into a portrait.
  • As a result, not only do you understand what people want, you also understand what people know your brand for.
  • Therefore, you know whether or not people think your brand can give them what they want. If people like using Y and Z but aren’t aware that your brand offers Y and Z, then your brand is suffering.

So, True Awareness allows you to discern exactly what needs to be done (e.g., what needs to be amplified in messaging) to improve your brand’s metrics and conversion funnel.

Use both Familiarity and True Awareness in your competitive brand tracking to push your brand to be the prom king of your industry and to make sure people know and love your brand for what it really stands for.

Jonah is a Project Manager at CMB. He enjoys traveling with his family and friends, and he hopes the Red Sox can hang in there to reach the postseason this year.

Topics: methodology, research design, brand health and positioning

Strength-Based Leadership and Finding the #Boss Within

Posted by Blair Bailey

Wed, Jul 06, 2016

A few weeks ago, I relinquished my year-long membership to the "Broken Screen Club" and bought asgo-logo-home.png new phone. It was a good opportunity to clean up the apps I didn't need. I had two meditation apps, two fitness tracker apps, three nutrition apps, four dating apps, and two hydration-tracking apps. If there was a gap in my life, I had an app for it. 

I was an expert at pinpointing what I wanted to improve about myself and identifying the tools to do it...but was it working? Using these apps reminded me to drink water, but they also served as a constant reminder that I was bad at regularly drinking water.

Recently, I attended Strength-Based Leadership Workshop presented by She Geeks Out (SGO), a Boston-based community of women in the STEAM fields. The workshop was led by Katie Greenman, Founding Partner of HumanSide, a "human-centered consultancy" that works with individuals, teams, and organizations to build success from the inside out. Through activities and lively discussion, we discussed the concept of strength-based leadership and how to apply it in our personal and professional lives.

When it comes to introspection and self-improvement, it’s natural to focus on what’s wrong rather than what’s right. Strength-based leadership focuses on emphasizing an individual’s existing strengths and passions. The core belief is that there is higher growth potential in developing strengths rather than focusing on weaknesses.

At the workshop, everyone had a worksheet with about thirty traits listed and had to circle which traits we considered our strengths. For each of the traits listed, I wanted to brainstorm how I could improve on it rather than see if it was already a strength of mine. Next, we listed items from one aspect of our lives and discussed how our existing strengths would help or had helped us achieve our goals.

The last item was: "Something you're not doing so well with." It was easy for me to come up with something to improve upon...but how would my known strengths help? The takeaway is one of the central tenants of strength-based leadership—whether you're succeeding or not at a task, you should focus on your existing strengths to improve or to continue to excel.

Although the exercises focused on the individual, they can also be applied to teams. Focusing on strengths rather than weaknesses allows for diverse, passionate teams that can excel at the tasks at hand. It also creates a stronger relationship between a company's leadership and its employees. Acknowledging your employees' passions can build enthusiasm and promote evangelism. It's important to note that strength-based leaders don't ignore weaknesses altogether. However, they don't focus the majority of their time and efforts on filling the gaps.

Since attending the workshop, I’ve realized how much strength-based leadership plays a role at CMB. I’ve been assigned difficult projects and given unfamiliar roles that I was at first terrified to take on. But during one-on-one meetings, when I was internally panicking, my manager would tell me, “we thought of you for this.” Through challenges we reveal skills that are valuable to a project, a team, and the company as a whole.

Thanks to my "perfectionist" trait, it's still difficult for me not to focus on the negative, particularly my own. SGO's workshop provided me with a new perspective on how to approach my projects, my career, and myself. I still have more than one meditation app, but if that's the worst of it, I think I'll be okay.

Blair Bailey is a Senior Associate Business Analyst at CMB who still doesn’t drink enough water.

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Topics: Chadwick Martin Bailey, marketing science, marketing strategy, CMB Careers, Market research

Big Data Killed the Radio Star

Posted by Mark Doherty

Wed, Jun 29, 2016

It’s an amazing time to be a music fan (especially if you have all those Ticketmaster vouchers and a love of '90's music). While music production and distribution was once controlled by record label and radio station conglomerates, technology has “freed” it in almost every way. It’s 200542299-001_47.jpgnow easy to hear nearly any song ever recorded thanks to YouTube, iTunes, and a range of streaming sources. While these new options appear to be manna from heaven, for music lovers, they can  actually create more problems than you’d expect. The never-ending flow of music options can make it harder to decide what might be good or what to play next. In the old days (way back in 2010 :)), your music choices were limited by record companies and by radio station programmers. While these “corporate suits” may have prevented you from hearing that great underground indie band, they also “saved” you from thousands of options that you would probably hate. 

That same challenge is happening right now with marketers’ use of data. Back in the day (also around 2010), there was a limited number of data sets and sources to leverage in decisions relating to building/strengthening a brand. Now, that same marketer has access to a seemingly endless flow of data: from web analytics, third-party providers, primary research, and their own CRM systems. While most market information was previously collected and “curated” through the insights department, marketing managers are often now left to their own devices to sift through and determine how useful each set of data is to their business. And it’s not easy for a non-expert to do due diligence on each data source to establish its legitimacy and usefulness. As a result, many marketers are paralyzed by a firehose of data and/or end up trying to use lots of not-so-great data to make business decisions.

So, how do managers make use of all this data? It’s partly the same way streaming sources help music listeners decide what song to play next: predictive analytics. Predictive analytics is changing how companies use data to get, keep, and grow their most profitable customers. It helps managers “cut through the clutter” and analyze a wide range of data to make better decisions about the future of their business. It’s similarly being used in the music industry to help music lovers cut through the clutter of their myriad song choices to find their next favorite song. Pandora’s Musical Genome Project is doing just that by developing a recommendation algorithm that serves up choices based on the attributes of the music you have listened to in the past. Similarly, Spotify’s Discover Weekly playlist is a huge hit with music lovers, who appreciate Spotify’s assistance in identifying new songs they may love.

So, the next time you need to figure out how to best leverage the range of data you have—or find a new summer jam—consider predictive analytics.

Mark is a Vice President at CMB, he’s fully embracing his reputation around the office as the DJ of the Digital Age.

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Topics: advanced analytics, big data, data integration, predictive analytics

Dear Dr. Jay: Driver Modeling

Posted by Dr. Jay Weiner

Thu, Jun 23, 2016

Dear Dr. Jay,

We want to assess the importance of fixing some of our customer touchpoints, what would you recommend as a modeling tool?

 -Alicia


Hi Alicia,

DRJAY.pngThere are a variety of tools we use to determine the relative importance of key variables on an outcome (dependent variable). Here’s the first question we need to address: are we trying to predict the actual value of the dependent variable or just assess the importance of any given independent variable in the equation? Most of the time, the goal is the latter.

Once we know the primary objective, there are three key criteria we need to address. The first is the amount of multicollinearity in our data. The more independent variables we have, the bigger problem this presents. The second is the stability in the model over time. In tracking studies, we want to believe that the differences between waves are due to actual differences in the market and not artifacts of the algorithm used to compute the importance scores. Finally, we need to understand the impact of sample size on the models.

How big a sample do you need? Typically, in consumer research, we see results stabilize with n=200. Some tools will do a better job with smaller samples than others. You should also consider the number of parameters you are trying to model. A grad school rule of thumb is that you need 4 observations for each parameter in the model, so if you have 25 independent variables, you’d need at least 100 respondents in your sample.

There are several tools to consider using to estimate relative importance: Bivariate Correlations, OLS, Shapley Value Regression (or Kruskal’s Relative Importance), TreeNet, and Bayesian Networks are all options. All of these tools will let you understand the relative importance of the independent variables in predicting your key measure. One think to note is that none of the tools specifically model causation. You would need some sort of experimental design to address that issue. Let’s break down the advantages and disadvantages of each. 

Bivariate Correlations (measures the strength of the relationship between two variables)

  • Advantages: Works with small samples. Relatively stable wave to wave. Easy to execute. Ignores multicollinearity.
  • Disadvantages: Only estimates the impact of one attribute at a time. Ignores any possible interactions. Doesn’t provide an “importance” score, but a “strength of relationship” value.  Assumes a linear relationship among the attributes. 

Ordinary Least Squares regression (OLS) (method for estimating the unknown parameters in a linear regression model)

  • Advantages: Easy to execute. Provides an equation to predict the change in the dependent variable based on changes in the independent variable (predictive analytics).
  • Disadvantages: Highly susceptible to multicollinearity, causing changes in key drivers in tracking studies. If the goal is a predictive model, this isn’t a serious problem. If your goal is to prioritize areas of improvement, this is a challenge. Assumes a linear relationship among the attributes. 

Shapley Value Regression or Kruskal’s Relative Importance

These are a couple of approaches that consider all possible combinations of explanatory variables. Unlike traditional regression tools, these techniques are not used for forecasting. In OLS, we predict the change in overall satisfaction for any given change in the independent variables. These tools are used to determine how much better the model is if we include any specific independent variable versus models that do not include that measure. The conclusions we draw from these models refer to the usefulness of including any measure in the model and not its specific impact on improving measures like overall satisfaction. 

  • Advantages: Works with smaller samples. Does a better job of dealing with multicollinearity. Very stable in predicting the impact of attributes between waves.
  • Disadvantages: Ignores interactions. Assumes a linear relationship among the attributes.

TreeNet (a tree-based data mining tool)

  • Advantages: Does a better job of dealing with multicollinearity than most linear models. Very stable in predicting the impact of attributes between waves. Can identify interactions. Does not assume a linear relationship among the attributes.
  • Disadvantages: Requires a larger sample size—usually n=200 or more. 

Bayesian Networks (a graphical representation of the joint probabilities among key measures)

  • Advantages: Does a better job of dealing with multicollinearity than most linear models. Very stable in predicting the impact of attributes between waves. Can identify interactions. Does not assume a linear relationship among the attributes. Works with smaller samples. While a typical Bayes Net does not provide a system of equations, it is possible to simulate changes in the dependent variable based on changes to the independent variables.
  • Disadvantages: Can be more time-consuming and difficult to execute than the others listed here.

Got a burning research question? You can send your questions to DearDrJay@cmbinfo.com or submit anonymously here.

Dr. Jay Weiner is CMB’s senior methodologist and VP of Advanced Analytics. Jay earned his Ph.D. in Marketing/Research from the University of Texas at Arlington and regularly publishes and presents on topics, including conjoint, choice, and pricing.

Topics: advanced analytics, Dear Dr. Jay