Voices: the CMB Blog

This year has been rife with corporate scandals. For example, FIFA’s corruption case and Volkswagen’s emissions cheating admission may have irreparably damaged public trust for these organizations. These are just two of the major corporations caught this year, and if history tells us anything, we’re likely to see at least another giant fall in 2015. 

What can managers learn about their brands from watching the aftermath of corporate scandal? Let’s start with the importance of trust—something we can all revisit. We take it for granted when our companies or brands are in good standing, but when trust falters, it recovers slowly and impacts all parts of the organization. To prove the latter point, we used data from our recent self-funded Consumer Pulse research to understand the relationship between Likelihood to Recommend (LTR), a Key Performance Indicator, and Trustworthiness amongst a host of other brand attributes. 

Before we dive into the models, let’s talk a little bit about the data. We leveraged data we collected some months ago—not at the height of any corporate scandal. In a perfect world, we would have pre-scandal and post-scandal observations of trust to understand any erosion due to awareness of the deception. This data also doesn’t measure the auto industry or professional sports. It focuses on brands in the hotel, e-commerce, wireless, airline, and credit card industries. Given the breadth of the industries, the data should provide a good look at how trust impacts LTR across different types of organizations. Finally, we used Bayes Net (which we’ve blogged about quite a bit recently) to factor and map the relationships between LTR and brand attributes. After factoring, we used TreeNet to get a more direct measure of explanatory power for each of the factors.

First, let’s take a look at the TreeNet results. Overall, our 31 brand attributes explain about 71% of the variance in LTR—not too shabby. Below are each factors’ individual contribution to the model (summing to 71%). Each factor is labeled by the top loading attribute, although they are each comprised of 3-5 such variables. For a complete list of which attributes goes with which factor, see the Bayes Net map below. That said, this list (labeled by the top attributes) should give you an idea of what’s directly driving LTR:

Looking at these factor scores in isolation, they make inherent sense—love for a brand (which factors with “I am proud to use” and “I recommend, like, or share with friends”) is the top driver of LTR. In fact, this factor is responsible for a third of the variance we can explain. Other factors, including those with trust and “I am proud to wear/display the logo of Brand X” have more modest (and not all that dissimilar) explanatory power. 

You might be wondering: if Trustworthiness doesn’t register at the top of the list for TreeNet, then why is it so important? This is where Bayes Nets come in to play. TreeNet, like regression, looks to measure the direct relationships between independent and dependent variables, holding everything else constant. Bayes Nets, in contrast, looks for the relationships between all the attributes and helps map direct as well as indirect relationships.

Below is the Bayes Net map for this same data (and you can click on the map to see a larger image). You need three important pieces of information to interpret this data:

1. The size of the nodes (circles/orbs) represents how important a factor is to the model. The bigger the circle, the more important the factor.
2. Similarly, the thicker the lines, the stronger a relationship is between two factors/variables. The boldest lines have the strongest relationships.
3. Finally, we can’t talk about causality, but rather correlations. This means we can’t say Trustworthiness causes LTR to move in a certain direction, but rather that they’re related. And, as anyone who has sat through an introduction to statistics course knows, correlation does not equal causation.

Here, Factor 7 (“I love Brand X”) is no longer a hands-down winner in terms of explanatory power. Instead, you’ll see that Factors 3, 5, 7 and 9 each wield a great deal of influence in this map in pretty similar quantities. Factor 7, which was responsible for over a third of the explanatory power before, is well-connected in this map. Not surprising—you don’t just love a brand out of nowhere. You love a brand because they value you (Factor 5), they’re innovative (Factor 9), they’re trustworthy (Factor 3), etc. Factor 7’s explanatory power in the TreeNet model was inflated because many attributes interact to produce the feeling of love or pride around a brand.

Similarly, Factor 3 (Trustworthiness) was deflated. The TreeNet model picked up the direct relationship between Trustworthiness and LTR, but it didn’t measure its cumulative impact (a combination of direct and indirect relationships). Note how well-connected Factor 3 is. It’s strongly related (one of the strongest relationships in the map) to Factor 5, which includes “Brand X makes me feel valued,” “Brand X appreciates my business,” and “Brand X provides excellent customer service.” This means these two variables are fairly inseparable. You can’t be trustworthy/have a good reputation without the essentials like excellent customer service and making customers feel valued. Although to a lesser degree, Trustworthiness is also related to love. Business is like dating—you can’t love someone if you don’t trust them first.

The data shows that sometimes relationships aren’t as cut and dry as they appear in classic multivariate techniques. Some things that look important are inflated, while other relationships are masked by indirect pathways. The data also shows that trust can influence a host of other brand attributes and may even be a prerequisite for some. 

So what does this mean for Volkswagen? Clearly, trust is damaged and will need to be repaired.  True to crisis management 101, VW has jettisoned a CEO and will likely make amends to those owners who have been hurt by their indiscretions. But how long will VW feel the damage done by this scandal? For existing customers, the road might be easier. One of us, James, is a current VW owner, and he is smitten with the brand. His particular model (GTI) wasn’t impacted, and while the cheating may damage the value of his car, he’s not selling it anytime soon. For prospects, love has yet to develop and a lack of trust may eliminate the brand from their consideration set.

The takeaway for brands? Don’t take trust for granted. It’s great while you’re in good favor, but trust’s reach is long, varied, and has the potential to impact all of your KPIs. Take a look at your company through the lens of trust. How can you improve? Take steps to better your customer service and to make customers feel valued. It may pay dividends in improving trust, other KPIs, and, ultimately, love.

Dr. Jay Weiner is CMB’s senior methodologist and VP of Advanced Analytics. He keeps buying new cars to try to make the noise on the right side go away.

James Kelley splits his time at CMB as a Project Manager for the Technology/eCommerce team and as a member of the analytics team. He is a self-described data nerd, political junkie, and board game geek. Outside of work, James works on his dissertation in political science which he hopes to complete in 2016.

We’ve come a long way, baby. . .

In the past three decades, the exponential growth in technology’s capabilities have given us the power to integrate multiple sources, predict behaviors, and deliver insights at a speed we only dreamt of when I was starting out. CMB Chairman and co-founder, Dr. John Martin, was an early cheerleader of the value of using multiple methods and multiple sources, so the promise of bringing disparate data sources into a unified view of customers and the marketplace is this researcher’s dream come true. 

While integrating data to help make smarter decisions has always been a best practice, it is the advances in technology that have allowed for an even greater and easier integration. Below are some recent examples we’ve implemented at CMB:

• In segmentation studies, we include needs/attitude-based survey data, internal CRM behaviors, and third-party appended data into the modeling to create more useful segments. Our clients have found that our perceptual data is a necessary complement to their internal data because it helps explain the “why’s” to the “what’s” that the internal behavioral/demographic data tell them.
• For our brand tracking clients, we often combine web analytics (e.g., Google search data, social media sentiment analysis, client’s web traffic statistics) and internal data (e.g., inquiries, loyalty applications) with our tracking results to help tell a much more nuanced story of the brand’s progress. Additionally, we use dashboards to tie that data together in one place, providing a real-time view of the brand.
• Our customer experience clients now provide us with internal data from call center reports (detailing the types of complaints received) and internal performance metrics to complement our satisfaction tracking. 

. . .but we’ve got a ways to go.

While many organizations are leveraging technology to integrate data for specific decision areas, I see a number of stumbling blocks. Many companies are still failing to develop an enterprise-wide, unified view of the marketplace—and the barriers often have little to do with the data or tech themselves: 

• Organizational siloes make it very challenging for different functional areas to come together and create a common platform for this type of unified view. 
• Moreover, the politics of who owns what—and more importantly, who pays for what—oftentimes means efforts like this never get off the ground.  

So, while it seems like technology is helping make all sorts of different data “play together,” we as humans haven’t mastered the same challenge! 

How do organizations overcome these challenges to take advantage of this possibility? Like most challenges, the solution starts with senior leadership. If the C-suite makes it a priority for the organization to become customer-centric and stresses that data is a big part of getting there, that goes far to pave the way for the different personalities and siloes to come together. Starting small is another way to tackle this problem. Look for opportunities in which teams can collaborate, even if it’s something as simple as looking at subsequent purchase behaviors from customers six months after they complete a satisfaction questionnaire in order to develop/refine the predictive power of your customer experience tracking. Starting small can create a more positive beginning to the partnership, building the trust and communication necessary to attack the bigger challenges down the road.

Mark is a Vice President at CMB, and while he recognizes that technology has absolutely transformed all aspects of his professional and personal life, he sees meaning in the fact that he prefers his music playlists generated by humans, not algorithms. Long live the DJ!

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Every day there’s a new report about Millennials—they’re in debt/they’re saving for retirement, they’re mobile/they’re going off the grid, they’re hard workers/they’re too entitled to succeed—the list goes on. Brands are desperate to learn what makes this generation tick, but the current research lacks actionable insights for the marketers trying to serve them.

To dig deeper, we partnered with venture capital firm Foundation Capital to clear through the clutter and to learn what Millennials are doing and thinking about when it comes to their money. Through our Consumer Pulse research program, we surveyed 1,055 Millennials about their tech use and financial habits, and we included three “deep-dive” sections covering attitudes and preferences towards banking, investments, and insurance.

On October 26th, CMB’s Lori Vellucci will join Foundation Capital’s Charles Moldow at the Money 20/20 conference in Las Vegas to unveil new insights into the needs, perceptions, attitudes, and actions of Millennials. They’ll take a look at the very different needs within this most talked about generation, the coming disruption, and the wave of innovation required to address their financial needs.

If you can’t make it to the conference, don’t worry! We’ll be sharing takeaways from our research in November.

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The traditional military definition of a "wingman" is the second pilot who flies behind and off the right wing of the lead aircraft. The wingman protects the lead by watching his/her back. As I reflected on this year’s MRA Corporate Researchers Conference (CRC) in St. Louis, I thought about my experiences with the wingmen and wingwomen of Chief Marketing Officers at Fortune 500 companies. 

Here’s what separates wingmen and wingwomen from the rest of the pack:

• They test new stuff ALL THE TIME. Jeffrey Henning moderated a panel with Samsung’s Manvir Kalsi, Chico’s Ivy Boehm, and Lowe’s Celia Van Wickel, asking them to talk about techniques that have disappointed them. They primarily talked about emerging technologies, specifically about vendors who overpromised with facial coding in neuroscience and thematic roll ups that “create themselves” in text analytics. They discussed their “lead pilots” and their companies’ “formation” not having enough time for overly “mathy” insights. They also talked about how they’ve brought dynamic deliverables to their organizations in an attempt to reduce the PowerPoint clutter. Chico’s Ivy Boehm mentioned her quest to shift from 60 page “boring PowerPoints” (her words) to just 20 solid slides through combining information and drawing deeper conclusions. Manvir, Ivy, and Celia also discussed the challenges each of them faces as they make trade-offs in an effort to try new things—even though they know that sometimes all they need are some well-moderated traditional focus groups and a straight up, well-written quantitative survey. This panel proved that no matter the challenge, wingmen are always improving their game.  

• They play around with working at Mach speed and at a normal pace. Microsoft’s Barry Jennings talked about the company’s Rapid Deployment Programs, which elicit feedback from customers at the later stages of the product development cycle. Successful wingmen are able to adjust and change course quickly—they can’t just head for the horizon. This is the key challenge: knowing when and where to get insights quickly at a lesser cost. At Microsoft, the process is clearly defined: ideation, iteration, validation, repeat. This process helps some concepts fail faster and helps others go to market more quickly. While Microsoft does loads of very methodical research, it’s also pushing itself to be fast and impactful vs perfect. Their program integrates activities, social and independent, moving from ideation to quant to qual and back. They collect feedback across any device and operating system, and they launch research in a day, share results, integrate historic data, and iterate. 

• They begin with the end in mind and quantify their impact. Terrific researchers understand the business impacts of their research. Roxanne Gray, VP of Research for Wells Fargo, described the diverse household research that supports their “together, we’ll go far” promise. Customer insights played prominently for Wells Fargo as it launched its most recent campaign about the company’s commitment to helping diverse households talk about their finances. Grab a box of tissues, and see more about how Wells Fargo illustrated its 25-year commitment to people with diverse backgrounds. The impact? Roxanne’s research supported confident decision-making that quadrupled earned media. She was energized by the research itself, the executive decisions her stakeholders would make from the research, and the easy-to-digest delivery of insights that she presented as a story, and it showed. 

• They love what they do, and they stay curious. Wingmen and wingwomen venture out to conferences to present, network, and listen to others. This deep passion for research, learning, and sharing is what keeps us sharp and focused at our organizations. At the best conferences, such as MRA’s CRC, the sheer number of wingmen and the quality of presentations (not to mention the bacon at breakfast) is incredible. If your position as a wingman isn’t rewarded with an adequate budget for this type of travel, have no fear. . . you can check out your local MRA chapter, attend online webinars, talk and listen with your global research peers face-to-face, and connect on Twitter and LinkedIn. 

Let’s keep a line of sight on our lead pilots, the horizon, our formation, and let’s go!

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.

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The CarTrawler Yearbook of Ancillary Revenue reports that airlines generated $38 Billion in ancillary revenue in 2014, up 20% year over year. The report highlights the brands generating the most ancillary revenue–in terms of total revenue generated ($5.86 billion for United Airlines), the percent of revenue it represents (38.7% of Spirit Airline’s revenue) and discloses top revenue sources (e.g., frequent flier miles sold to partners, fees for checked bags, and commissions from car rentals).

Clearly, ancillary revenue is not confined solely to airlines; theme parks, cruises, car rentals, hotels all boost revenues from selling additional products, services and merchandise. And it’s easy to see why. In addition to driving incremental revenue, ancillary products and services enable a supplier to (1) offer a competitive base price - essential (particularly in some segments like cruising) to enter into a traveler’s consideration set; and (2) meet the needs of their guests by merchandising – and conveniently delivering – what customers crave and where they’re willing to spend extra.

But there are potential costs as well. A quick read of the Cruise Critic blog points to ‘high-pressure’ sales tactics employed by ship employees and the negative impact it has on the guest experience. Eavesdrop on airline rent-a-car counters and you’ll hear the ‘fear, uncertainty and doubt’ in the voice of infrequent car renters. And hop onto a Spirit airlines to get an earful of complaints (“$3 for a water bottle?!”). Suppliers—particularly in the Hospitality industry—need to think about their brand position and why their customers buy from them as they consider the revenue and cost of this incremental revenue stream.

Our recommendation: to develop a customer-centric ancillary revenue strategy you need to consider the ‘emotional impact’ it will have on your key customer segments and the emotional fingerprint your brand wants to leave on its customers. Is your brand in the business of making key customers feel delighted? Secure? Valued? If so, the Ancillary Revenue offers should avoid making customers feel angry and frustrated! First step is to identify the top emotional drivers of your brand and investigate whether the Ancillary Revenue products are aligned; consider whether the revenue strategy reinforces, or conflicts with, the desired emotional end-benefit. Watch our recent webinar to learn about our approach: EMPACT℠: Measuring Your Brand's Emotional Impact

There are plenty of positive examples of ancillary revenue opportunities aligned with the desired emotional impact. Here are a few:

Disney: There is no FastPass on rides for younger kids at Disney – and the wait time can easily surpass the patience of kids… and their parents. On a recent trip to Disneyworld, a colleague spent over $100 buying buzzing, spinning, bubble-blowing toys from push-carts surrounding the rides. The toys kept her son happy and occupied. She felt delighted; turning waiting in line into a fun instead of a frustrating experience.

Disney mastery in this area is evident. It successfully offers many products and services that drive ancillary revenue that reinforce the desired emotional outcomes – during and after the trip: the MemoryMaker photo package, the pins/guest books/signatures and stamped pennies, the character breakfasts.

Tigerair, serving Asia-Pacific destinations, offers a fee-based service to travelers waiting for a flight connection of at least eight hours where they can visit the city-center and go sightseeing. As a traveler, I’d feel productive, happy and secure (knowing that I’d be back in time for my flight!)

Hilton Worldwide: When traveling, for business and pleasure, most travelers describe Wi-Fi as an essential service. For years, most major full service hotel brands provided access for a daily fee. Slowly, but surely, major brands like Hilton Worldwide have moved to a position of providing basic access to all loyalty program members. Doing so removes a highly charged negative emotion and reinforces a feeling of ‘being valued.’ Ancillary revenue will be created through sales of the premium internet service with the negative emotional blowback of ‘nickel and diming’ for a basic requirement.

The key take-away: The quest for ancillary revenue will only heat up. Ensure your strategy aligns with – and supports – the reasons customers buy from you and the emotional benefit they’re looking to achieve.