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This Blog is Dark and Full of Emotional Turmoil

Posted by Dr. Erica Carranza

Thu, May 16, 2019

Includes spoilers through season 8/episode 5.

My love affair with Game of Thrones developed gradually and, by season four, I’d fallen head-over-heels. Like most fans, I enjoyed watching it buck narrative conventions, leaving them littered along the way like so many torched wights. But what really captured my heart was its subtle feminism.

Finally, here was a show where the women were just as varied, complex, and important to the story as the men. They had goals of their own, well-developed personalities, and together they represented an impressive range of attributes—vulnerability, compassion, strategic thinking, naivete, cynicism, resilience, physical strength, and more. They fought the patriarchy, but each in her own way. And, by the time Daenerys met her war council in Westeros, her strongest allies were women. That could have felt like a heavy-handed attempt by the writers to give women roles traditionally held by men. Instead, it felt like the natural result of all that had happened up to that point.

What’s more, even the men of Game of Thrones subverted expectations. My favorites among them were smart and funny—but also kind and compassionate. And few of them had the pretty face or chiseled physique worn by typical epic heroes. In its first season, Game of Thrones inspired the term “sexposition”—yet somehow it had delivered a smorgasbord of compelling male and female characters. And the world was watching.

With all these reasons to love the show, I was worried about how it might end. A happily-ever-after would betray what had made it great. But, truth be told, I didn’t want a villain to win. I was sympathetic to the conundrum the showrunners must be in, and pessimistic about their finding a good way out.

Turns out I wasn’t alone.

Right before “The Long Night” aired (season 8/episode 3), we ran a survey among friends and colleagues. We asked them their predictions for how the series would end, and how they expected to feel about it. While the survey was just for fun—and hardly a representative sample—the results were revealing:

  • Less than a third (30%) thought they’d feel mostly good about how the series ended.
  • A third (34%) thought they’d feel ambivalent (i.e., good and bad in equal measure).
  • Nearly a quarter (23%) thought they’d feel mostly bad.

In total, over half (57%) predicted having strong negative emotional reactions to whatever would unfold in the final episodes (i.e., the 23% expecting to feel bad, plus the 34% expecting to feel ambivalent). Only 13% of viewers—whose lack of emotional investment in the show I’ve come to envy—thought they would end up feeling neutral.

got pie chart

Furthermore, viewers thought they would feel highly activated, energetic emotions.

A bit of background… At CMB, we use a method of measuring emotion (EMPACT) that we developed to capture its two core dimensions: valence (i.e., intensity of the positive or negative feelings) and activation (i.e., their level of energy).

For example, sadness and anger can feel equally negative in terms of valence. But sadness is low in activation, while anger is high. Sadness is low energy and makes people want to withdraw. Anger is agitating—it makes people want to act. Not surprisingly, online content is particularly likely to go viral when it evokes high activation emotions.

When viewers predicted how they’d feel about the way the series ends:

  • Half (49%) predicted highly activated negative reactions. Specifics included feeling frustrated, annoyed, anxious, stressed, angry, and even disgusted.
  • About half (46%) predicted highly activated positive reactions. Specifics included feeling entertained, amused, amazed, happy, and excited.
  • Relatively few (27%) predicted low activation negative reactions (e.g., feeling drained, depressed, disappointed, and discouraged).
  • Even fewer (11%) predicted low activation positive reactions (e.g., feeling pleased, satisfied, and nostalgic).

So nearly everyone expects to feel highly activated—but viewers were split in terms of positive vs. negative valence. That’s a precarious situation for a show as it approaches its series finale.

got valenceLinking viewers’ expected emotion to their predictions for the show also uncovered some interesting trends. For example, those expecting to feel activated positive emotions (e.g., happiness and excitement) were particularly likely to think the “good guys” would survive—including Jon, Arya, Sansa, Tyrion, Samwell, and even little Sam. Other viewers were less optimistic. But, regardless of their predictions, most shared an intensely emotional relationship to the show.

I can relate. In fact, the anxiety I felt about whether Game of Thrones could stick the landing is nothing compared to how I feel now, having watched it ruin most of its best characters:

  • Sansa expressed gratitude (!) for her worst abusers and is now (according to showrunner Dan Benioff) stealing moves from Littlefinger’s playbook. Plus she continually snipes at Dany despite Dany’s essential help in saving the North.
  • Last we saw Brienne—the first and only female Knight of the Seven Kingdoms—she was pathetically bawling in her bathrobe as Jaime rode out of her life.
  • Then Cersei, having finally proven herself her father’s equal, died crying in Jaime’s arms.
  • Varys is burned alive thanks to Tyrion, who continues his two-season track-record of making inexplicably poor decisions. (He used to drink and know things. Now I guess he just drinks.)
  • Grey Worm led the remaining allied forces into a wave of war crimes.
  • And Dany, who locked-up her dragons when Drogon killed a single innocent child, has brutally murdered a whole city full of innocent children. Why? Because she feels threatened by a man, hurt by his rejection, frustrated by the skepticism she met in Westeros, and enraged at the beheading of a friend.

Yes, Dany losing her mind may have been in the cards from the start. But to have flipped in that moment—and for those reasons—didn’t fit with most of what we’d learned about her. Game of Thrones never made excuses for the ascent of powerful women. Now it’s making-up excuses to tear them down.

So it looks like the show that reveled in subverting narrative conventions will end by validating the oldest tropes in the book…

  • The hero where all our sympathies and hopes should lie is a white man. He’s a stoic warrior with a noble heart—and, lo and behold, he’s of noble blood.
  • Women, on the other hand, are weak, petty, manipulative, and overly emotional.
  • Women who seek power are particularly bad. Two women vying for the Iron Throne is apparently worse for Westeros than the Night King and his army of undead.

How does this turn of events make me feel? Discouraged, disappointed, angry, aggrieved… The last Game of Thrones episode has yet to arrive, but my love affair with the show is already over.

And, again, I bet I’m not alone.

__

Erica is VP of Consumer Psychology at Chadwick Martin Bailey. She has over ten years of experience leading market research for major brands across a range of categories—including clients such as Disney, Viacom, Mattel, Instagram, Prudential and American Express. A PhD social psychologist, Erica applies this expertise to give her clients a unique edge in understanding and engaging their target audiences.


Erica CarranzaErica has a B.A. from Wellesley College and a Ph.D. in psychology from Princeton University. Prior to CMB, she led insights research at American Express, where she was a recipient of the CMO Award for Achievement in Excellence.

For more insights, please follow us on LinkedIn, Facebook, and Twitter.

Topics: EMPACT, emotional measurement, emotion

The Road Ahead: Emotions and The Future of Self-Driving Cars

Posted by Chris Neal

Tue, Apr 16, 2019

We recently published self-funded research exploring the impact of consumer emotions on the emerging autonomous vehicle (AV) industry—the latest in our ongoing analysis of the relationship between emotion and disruptive technology.

As detailed in a previous post, this study revealed many consumers are skeptical of self-driving cars. Further, even the prospect of using this technology generates a negative emotional response.

We’ve measured the emotional activation of hundreds of brands in dozens of industries (learn more about our EMPACT approach here) and have found, by far, the autonomous vehicle category generates the most intense and widespread overall negative emotions—indicating a critical obstacle this industry must overcome.

The first two steps in charting a path forward are:

  1. Understand which specific negative emotions are the most important to deactivate
  2. Understand which specific positive emotions are most critical to activate

Better understanding these emotions can help guide the industry’s marketing efforts and actual customer experiences with this technology.

Overcoming the Right Negative Emotions

Unlike most industries we analyze, it’s more critical for the AV industry to deactivate negative emotions than it is to activate specific positive emotions, although doing both are obviously important.

Through our emotional gap analysis, we identified “Anxiety,” “Paranoia,” “Hesitancy,” and feeling “Overwhelmed” as the negative emotions where AVs fare worst when compared to how people feel about driving a car themselves:

Negative Emotions Activated by AV vs Car

Anxiety is no surprise here: people fear the prospect of truly letting AI take over and drive the vehicle with no human intervention.

People are also concerned self-driving car systems could be hacked, which explains the significant feeling of paranoia—an emotion common in a lot of emerging technology we study. Anything “smart” (i.e., connected to the internet) could be hacked, and there are always people who are more concerned about this than others.

Feeling “Hesitant” or “Unsure” also comes up a lot in new and disruptive technology categories. With anything truly new and different, people are unsure of whether it’s ready for primetime, or if they should try it.

The emotions around feeling “Hectic” or “Overwhelmed” are more unique to the AV category. It’s so new and potentially transformative that many people simply can’t process the idea of trusting the technology to get them from point A to point B. It’s overwhelming to really think on the complexity of AV systems, not to mention the myriad road scenarios an AI algorithm will need to be trained well enough to react to.

Positive Emotions Activated by Driving Your Own Car

Positive emotions are also important to driving mainstream adoption of a disruptive technology. This is a unique challenge for the AV industry because people already have many positive emotions activated when driving their own car.  

Not surprisingly, the biggest positive emotional gap between driving your own car and the prospect of getting in an autonomous vehicle is feeling in control.

Positive Emotions Activated by AV vs CarThe combination of anxiety, paranoia, and losing that feeling of control is a major emotional obstacle to for the autonomous vehicle industry’s path to widespread consumer acceptance. We see this in many AI-driven technology categories where life is increasingly automated and data-driven.

This fear of technology running our lives—and the possibility that it might not always do so benevolently—runs deep and has been prominent in popular culture long before the first self-driven test vehicle ever hit the road.

Open the Pod Bay Doors Hal

Source: GIPHY

There’s also a significant gap between feeling “Secure” and “Protected." As the chart above indicates, people feel a lot more secure and protected when driving their own car, but not so much about self-driving cars. The feeling of insecurity is influencing the high levels of anxiety we see from AVs.

The gap in feeling “Efficient/Productive” is also problematic for the AV industry. In most new technology adoption projects where we run this analysis, that emotion emerges as one of the key determinants of more mainstream consumer adoption. People expect disruptive technologies to make them feel more efficient and productive, but if they don’t truly get that feeling when using the technology, they are unlikely to change their existing habits.

Emotions That Predict Adoption

In addition to a straight gap analysis, we also ran a model to isolate which specific emotions (negative and positive) best predict (on a derived basis) peoples’ willingness to use autonomous vehicles in the future.

By far the biggest predictors, not surprisingly, are reducing anxiety and increasing feelings of relaxation.

emotional predictors

Another emotion that popped in our predictive modelling, which wasn’t evident from the initial data review, was activating emotions around pride. In other words, people who would feel “proud” using an autonomous vehicle are much more likely to actually use one, whereas people who might feel ashamed or embarrassed if their friends or family saw them inside an autonomous vehicle are highly unlikely to hop on board.

This “social identity” element is something we see in many new tech adoption studies through our proprietary consumer-centric approach to measuring the impact of identity on decision-making. Does someone identify as being one of those people who uses an autonomous vehicle, or is that for another tribe altogether? Turns out this tribal identity matters quite a bit for new technologies attempting to cross the chasm.

Feeling “Secure” and “Efficient” also help predict likelihood to adopt the technology, but as we saw earlier, not many people feel these emotions when they think about using an autonomous vehicle.

The Road Ahead*

In my next article, I will share some thoughts and findings from this study on potential paths forward for the industry to overcome these obstacles. You’ll get to see the results when I attempt to play an Ad Man and convince people to reconsider the category. Although it was a humbling experiment, it did reveal additional insights that can help actual creative teams with briefs that include different value propositions linked to specific emotions the industry needs to address.

In the meantime, if you’re interested in learning more about this research or our EMPACT approach, check out this recorded (quick) webinar:

Watch Now

*Sorry again! The puns are just too good to pass up in this blog series.

Topics: technology research, EMPACT, emotional measurement, Artificial Intelligence

How Advanced Analytics Saved My Commute

Posted by Laura Dulude

Wed, Aug 22, 2018

commuter

I don’t like commuting. Most people don’t. If you analyzed the emotions that commuting evokes, you’d probably hear commuters say it made them: frustrated, tired, and bored. To be fair, my commute experience isn’t as bad as it could be: I take a ~20-minute ride into Boston on the Orange Line, plus some walking before and after.

Still, wanting to minimize my discomfort during my time on the train and because I am who I am, I tracked my morning commute for about 10 months. I logged the number of other people waiting on the platform, number of minutes until the next train, time spent on the train, delays announced, the weather, and several other factors I thought might be related to a negative experience.

Ultimately, I decided the most frustrating part about my commute is how crowded the train is—the less crowded I am, the happier I feel. So, I decided to predict my subjective crowd rating for each day using other variables in my commuting dataset.

In this example, I’ve used a TreeNet analysis. TreeNet is the type of driver modeling we do most often at CMB because it’s flexible, allows you to include categorical predictors without creating dummy variables, handles missing data without much pre-processing, resists outliers, and does better with correlated independent variables than other techniques do.

TreeNet scores are shown in comparison to each other. The most important input will always be 100, and every other independent variable is scaled relative to that top variable. So, as you see in Figure 1, the time I board the train and the day of the week are about half as important as the number of people on the platform when I board. That means that as it turns out, I probably can’t do all that much to affect my commute, but I can at least know when it’ll be particularly unpleasant.

Importance to Crowding_commuter

What this importance chart doesn’t tell you is the relationship each item has to the dependent variable. For example, which weekdays have lower vs. higher crowding? Per-variable charts give us more information:

Weekday and Crowding_commuter

Figure 2 indicates that crowding lessens as the week goes on. Perhaps people are switching to ride-sharing services or working from home those days.

For continuous variables, like boarding time, we can explore the relationships through line charts:

Boarding Time and Crowding_commuter

Looks like I should get up on the earlier side if I want to have the best commuting experience! Need to tackle a thornier issue than your morning commute? Our Advanced Analytics team is the best in the business—contact us and let’s talk about how we can help!

 Laura Dulude is a data nerd and a grumpy commuter who just wants to get to work.

Topics: advanced analytics, EMPACT, emotional measurement, data visualization

Scoring with Emotion: A lesson for brands

Posted by Daniel Alderstad

Wed, Jun 27, 2018

soccer fans

If it’s Sunday morning in the Alderstad household, I’m engrossed in a football match on my tablet. I’m not talking about American football, I mean the real kind.

I’m from Sweden but live in the US, so I like to keep up with my home team—even if it’s an unimportant match against a non-threatening opponent. Following my team keeps me connected with fellow fans, especially when I’m watching alone from thousands of miles away.

I may be watching from my house, but I feel the same cocktail of nervousness and excitement as the other fans who are actually in the stadium. During a match, nothing else matters except for what’s happening on the screen.

Most matches take me on an emotional rollercoaster and leave me feeling high or low. I try to not let those feelings linger and dictate the rest of my mood for the day. 

I like to think that I can separate my feelings from the match, but I know that’s not entirely true. When it comes to my favorite team, eleven players chasing a ball can definitely impact how I’ll feel for the rest of the day.

Why is that?

Because I’m human and humans aren’t 100% rational.

And this is an important lesson for brands. Too often are we assuming a rational consumer—one who is motivated by the seemingly “obvious” and “rational” factors, like the functional features of a product. And yes, the functional benefits a brand or product provides is important. But, we can’t dismiss the power of emotion.

The link between emotions and decision-making has gained considerable attention in psychology, marketing, and even economics. But, I believe how emotions impact our decision-making process is still underestimated and underleveraged.  

At CMB, our solutions are grounded in consumer psychology and we know that consumers are motivated by three types of benefits, including emotional, functional, and identity. We’ve developed proprietary tools that measure how brands and touchpoints make people feel—understanding the emotional payoffs consumers experience, want, and expect from a brand.

Instead of focusing solely on what a product (or in my case, a team) can “do” for the consumer, brands must understand what emotions they should be evoking from target consumers, then create messaging and experiences that elicit such feelings. 

My emotional connection to my team may be a little mad, but isn't the duality of the human psyche—where our thoughts and decision-making are strongly driven by an unending conflict between logic vs. emotions and thinking vs. feeling—something to cherish?

I certainly think so.

Daniel Alderstad is a senior associate researcher who has tried (and failed) to get his peers to acknowledge that "football" is played with one’s feet and a round ball, while "American football" (which he very much appreciates) should be called "throwy-hand-ball-with infrequent-but- guaranteed-to-score-kicks-occasionally".

Topics: emotional measurement, emotion

How to Win Virtual Assistant Rejecters Over

Posted by Chris Neal

Wed, Jun 20, 2018

It seems like every week, tech giants are adding new features to their virtual assistant (VA) tech arsenal. See Google’s new Duplex technology—an AI system for accomplishing real-world tasks by phone. 

While companies are pouring millions into making their virtual assistants smarter and more integrated, most users don’t stray beyond its basic functions like asking for the weather.

Learn about the emotional and social identity dimensions keeping people from adopting and using this tech to its full potential, and what brands need to do to win the VA war.

CMB01_VA_Infographic_07_AW

Topics: technology research, Consumer Pulse, emotional measurement, AffinID, Artificial Intelligence