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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

AI's Image Problem: Who's the "Typical" Virtual Assistant User?

Posted by Chris Neal

Tue, Jan 09, 2018

siri2-1.png

Every nascent technology and every tech start-up faces the same marketing challenge of “crossing the chasm” into mainstream adoption.  Geoffrey Moore framed this very well in his 1991 classic, “Crossing the Chasm”:

adoption curve.pngWord of mouth can play a huge role in motivating certain segments to sip the Kool-Aid and make the leap.

With CES 2018—the world's largest gadget tradeshow—happening in Vegas this week, I can't help but wonder if mainstream consumers don’t relate to the early adopters of a new technology? What if they think it’s used by people who aren’t part of “their tribe”? Will it prevent them even considering the new tech? There are countless technology categories that have faced this challenge, for example:

  • certain gaming categories trying to expand beyond 15-24-year-old males
  • consumer robot products to this day
  • social media when it was first introduced
  • Second Life and other virtual worlds

I hypothesized that the virtual assistant (VA) category—and specific brands within it—faces this challenge. Yes, many people have tried and used Siri, but few mainstream consumers are truly using virtual assistants for anything beyond basic hands-free web-queries. To further complicate things, an increasing number of “smart home” products that connect to intelligent wireless speakers in the home (e.g., Amazon Alexa, Google Home, Apple’s forthcoming HomePod) are proving divisive. Some people love the experience or the idea of commanding a smart device while others categorically reject the concept. 

My team and I had the chance to test out a few hypothesis through our Consumer Pulse program and —voila!—we’ve got some tasty (and useful) morsels to share with you about how social identity is influencing consumer adoption in the virtual assistant space using our proprietary AffinIDSM solution.

Here’s what we found:

Social identity matters in the virtual assistant space. We studied US consumers (18+)—covering usage, adoption, and perceptions of the virtual assistant category and a deep-dive on four major brands within it: Apple’s Siri, Amazon Alexa, Google Assistant, and Cortana by Microsoft. We covered rational perceptions of the category, emotional reactions to experiences using virtual assistants, and perceptions of the “typical” user of Siri, Alexa, Google Assistant, and Cortana.

We then ran fancy math™ on our data to create a model to predict the likelihood of a virtual assistant “category rejecter” (i.e., someone who has never tried a VA before) to try any one of those assistants in the future. Our analysis indicates that how much a current VA category rejecter relates to their image of the type of person who uses a virtual assistant is the number one predictor of whether they are likely to try the technology in the future:

Blog_Chris.png

Unfortunately for the industry, category rejecters do not find the typical VA user very relatable. 
AffinID metric by brand.png

As the chart indicates, relatability (biggest predictor of likelihood to try as shown previously) scores the lowest of the three components of AffinID: relatability, clarity, and desirability. You may ask yourself: “are scores of 12 to 14 ‘good’ or ‘bad’?  They’re bad: trust me. We’ve now run AffinID on hundreds of brands across dozens of industries, so we have a formidable normative database against which to compare brands. The VA category does not fare well on “relatability,” and it matters.

Some brands’ VA ads, while amusing, are not very relatable to “normal” mainstream consumers. For example as my colleague Erica Carranza points out in her recent blog, Siri’s ad featuring Dwayne “The Rock” Johnson doing impossibly awesome things in one day (including taking a selfie from outer-space) with the help of Siri isn’t exactly a “normal” person’s day. A-grade for amusement on this one, but it is playing into an existing perception problem.

Stereotypes about users’ age and income are currently keeping “rejecters” away from the virtual assistant category.

The age gap between rejecters and “typical” virtual assistant users is a social identity construct keeping rejecters out of the category. Current rejecters, not surprisingly, skew older while current heavy VA users, also not surprisingly, skew young.

We uncovered this disconnect with a big predictive model using “match analysis” on a variety of demographic, personality, and interest attributes. For every attribute, we examined whether there was a “match” or a “disconnect” between how a rejecter described themselves vs. how they perceived the typical user of a virtual assistant brand.

The two specific perceptions that had the greatest ability to predict a rejecter’s likelihood to consider using a brand in the future was an age-range match and an income-range match. For example, if I’m over 35 years old (hypothetically!), and I perceive the “typical” user to be under 35 years old and higher-income than me…so what? Well, it does matter. For new technologies to achieve mainstream adoption, they must debunk the widespread perceptions that the early adopter is “young” and highly affluent, and that their product can be used by everyone (think: Facebook). SNL pokes fun at this generational discrepancy.

But in all seriousness, if a virtual assistant brand wants to achieve more mainstream adoption among older demographics, the brand gurus and creative teams working on campaigns need to tackle this head on.

And they must try to do this—ideally—without alienating the original early adopter group that made them their first million (think: Facebook, again…how many Gen Zers do you know who actually use it actively?). I—prototypical 45-year-old suburban dad—can’t imagine using Snapchat, for instance. If Snapchat wanted to get me and my tribe to buy in as avid users*, it needs to convince me that Snapchat isn’t just for teens and early twenty-somethings. Or it needs to launch a different brand/product targeted specifically at my tribe, and market it appropriately.

It’s worth noting there are other social identity constructs that help predict whether a non-user of a virtual assistant is likely to try a product in the future. For instance, the few VA category rejecters who perceive the typical (young, affluent) user as being as “responsible/reliable” as themselves are more open to trying a VA in future than those who do not perceive VA users this way. So, we’re seeing this stereotype that virtual assistant products are for young, affluent professionals living in a major coastal city with no kids to contend with yet, and this is turning some consumer segments off from trying out the category in earnest.  

Stay tuned to this channel for more on our study of the virtual assistant category. I’ll be covering some key insights we got by applying our emotional impact analysis—EMPACT℠to the same issue of what virtual assistant brands should be doing to achieve further adoption and more mainstream usage of their products. 

*I am more than 95% confident that the Snapchat brand gurus do not want me as an avid user…and my ‘tween daughter would definitely die of embarrassment if I ever joined that particular platform and tried to communicate with her that way.

 

Topics: technology research, EMPACT, Consumer Pulse, AffinID, Artificial Intelligence

Flying the Friendly Skies?

Posted by Chris Neal

Thu, May 18, 2017

pexels-photo (1).jpgI don’t envy the United Airlines (UAL) management team these days. Last month’s removal of passenger Dr. David Dao from an overcrowded plane in Chicago sparked a major PR nightmare for the airline carrier.  This debacle comes to a brand that was already struggling from image problems in an industry that has long been comedic fodder for bad customer experiences.

Overbooking, heightened security procedures, skyrocketing baggage fees, and shrinking legroom have made domestic air travel a very stressful experience. With emotions running high on the tarmac, in the air, and on Twitter, what’s an airline to do?

Emotions matter... and we've proved it.

Emotional analytics are a critical tool to help create a truly consumer-centric brand. Emotions are a key driver in consumer brand adoption/loyalty and will undoubtedly play a major role in how United performs going forward. In our self-funded study of the impact of emotions across 90 brands in 5 industries, CMB found that a brand’s overall emotional impact score can heavily influence future likelihood to purchase along with other key KPIs (advocacy, engagement, etc.).

We identified which specific emotions drive business outcomes in the airline industry, the top being “secure”, “efficient”, and “happy”. Of the negative emotions we tested, “anxious” proved to be the most damaging to a company:

drivers of airline use.jpg

We also found that of the five major airline brands tested, including United, UAL had the lowest Net Positive Emotion Score (NPES). NPES is the balance of positive emotions activated through experience with a company subtracted by the extent of negative emotions activated. It also accounts for overall emotional “activation” (high vs. low), and the general sentiment of that activation (positive or negative).

airline NPE net.png

Both United and American both share a special place at the bottom of the “Negative Emotion” spectrum (17 and 18, respectively), out-activating negativity by ~30% over the airline industry average of 13.

airline NPE neg.png

A Path Forward

Now let’s have a look-see at what specific emotions have the biggest impact on likelihood to consider flying United, specifically, and how that compares to the overall industry average of emotional drivers:

top emo drivers-airlines.png

The “Anxious” vs. “Relaxed” emotional spectrum is the biggest emotional driver of future United purchase intent. Lowering feelings of “Anxiety,” in particular, is much more important for United’s brand than it is for the industry average.

Unfortunately for United, their brand already generated 33% more “anxiety” than the industry average:

UAL anxiety.png

I can only imagine the anxiety Dr. Dao felt when he was removed from the seat he paid for to make room for a UAL employee. And I can also imagine the emotional connection felt by the millions of others who watched the video of him being dragged off the plane by airport security because they could relate to it in some way from their own travel experiences or common worries people have about flying:

  • “Will they arbitrarily change my flight times in a way that messes up the rest of my travel plans?”
  • “Will they cancel my flight altogether and put me on another (later) flight if it is under-booked?” (something that happens a lot on connector flights to smaller airports).
  • “Will I be forced to vacate my seat if they are over-booked?”
  • “Will there be delays that cause me to miss my connection, an important meeting, etc.?”
  • “Will I be sitting next to a 6’5” linebacker in a cramped coach class seat?”

No doubt this incident would have been a PR disaster for any airline, but the blowback was likely even more intense because it happened on a UAL flight—a brand that already activates more negative sentiments than most competing brands.

The bad news:

United Airlines was already in the hole before this incident, and now that hole is vastly deeper. Bad press and bad experiences linger longer in peoples’ memories than positive press or positive experiences, so it’s likely the image of Dao’s forced removal is here to stay (at least for a while).

Similarly, angry customers are much more likely to tell others about their bad experiences (typically with a bigger megaphone) than those with positive ones. Righteous indignation goes viral more readily than positivity. Furthermore, bad word-of-mouth has larger negative impact on a brand than good word-of-mouth has positive impact (by an order of magnitude). And some of the most prolific public haters will likely never be swayed otherwise, no matter what UAL does from this point forward.

The good news: 

In our analysis, we found that—across all industries tested—emotional reactions to the most recent experience have a much bigger impact on likelihood to buy in the future than the worst experience a customer has ever had with a brand (or the best). In other words, even brands that mess up big time can recover if they begin to deliver customer experiences and marketing communications strategies that foster the right emotions. With our “EMPACT” approach, we can identify very specific customer experiences, creative executions, and messaging that will deactivate the most damaging emotions like “anxiety” and activate key positive emotions like “relaxed.”

May the skies be friendlier.

If United wants to be a truly consumer-centric brand, they need to consider emotion measurements like NPES as a valid metric for tracking and analytics. United will need to profoundly understand which emotions matter, and how to proactively influence these emotions through specific customer experiences, promotional campaigns, and influencing what is (and isn’t) said about the brand on social media.

Emotional metrics deserve the same level of visibility and focus that traditional industry metrics like Revenue Per Available Seat Mile (RASM) and classic NPS receive. Until this happens, UAL may struggle to focus their customer experience strategies and creative campaigns in a way that helps them recover from this low point.

Chris Neal leads CMB’s Technology & Telecommunications practice. He gets emotional very easily. He is also a frequent flyer on United Airlines. While extremely angered and disgusted by the viral video of the UAL incident, he is curious to experience how UAL actually changes in future and will fly this airline again to find out.

Want to learn more about how we're revolutionizing  emotional measurement with our EMPACT solution? Watch our webinar:

 Learn More About EMPACT℠

Topics: EMPACT, emotional measurement, customer experience and loyalty

A Lesson in Brand Loyalty and Emotion from a Pure Barre Fanatic

Posted by Cara Lousararian

Wed, Mar 08, 2017

barre.jpg

Two and a half years ago, I fell in love with Pure Barre–a full-body workout inspired by ballet, yoga and Pilates. There are a bunch of barre studios with similar workouts to choose from, but I started with Pure Barre and am now fiercely loyal.

This loyalty didn’t develop overnight; the morning after my first class I could barely make it out of bed. I couldn’t understand why barre had such a big following. It felt like self-inflicted torture, and I definitely felt this guy’s pain.

I was never one to enjoy working out, so what’s so special about the Pure Barre brand that’s kept me addicted for years and kept me from heading to another barre brand? The physical pain is the same (intense) and the class prices are a little higher than other similar workouts. After giving it some thought, I realized that what I love so much about Pure Barre is how being part of the Pure Barre community makes me feel.

Pure Barre makes me feel confident, motivated, and strong. It evokes such positive emotions from me that I’ve found myself altering my behavior in order to incorporate Pure Barre into my life. For example, when I plan a vacation, I specifically look for hotels that are near Pure Barre studios, I get up extra early on holidays like Thanksgiving and Christmas so I can squeeze in a class, and I schedule my weekend social life around my classes. Not only that, while I'm normally a fairly frugal shopper, I’ll spend $17 on the special Pure Barre sticky socks used for class without batting an eye (I own 6 pairs!!!).

I’m also proud to be part of the Pure Barre community. We’re a network of loyal followers bound by our love of the Pure Barre experience who constantly support and encourage each other.  I’ve witnessed deep friendships begin at Pure Barre studios–maybe enduring the pain together is a strong bonding force? Either way, there’s a camaraderie among Pure Barre members unlike anything I’ve experienced at other gyms/studios.   

Pure Barre makes its members feel good and valued by doing little things, like celebrating attendance milestones. For example, you’ll get special recognition at your 100th, 250th, 500th, 750th, etc. class. You also get a free class on your birthday. Or, as Pure Barre calls it, your “barrety”.  Touchpoints like these makes me and my fellow Pure Barre addicts feel celebrated and drive attendance.

Pure Barre instructors also play a huge part in fostering positive emotions from the clients. Filled with upbeat energy and techniques for encouragement, they have a friendly way of ensuring that everyone works their hardest (for example, they won't call out the final 10 counts of the exercise until everyone has the right form). Instructors also learn the names of regular attendees and will call out your name if you are doing something particularly well during class. This “in the moment” recognition motivates me to push myself beyond my limits and get the most out of every class. 

I love talking about Pure Barre and am a huge promoter of the brand. I want others to have the same positive experience with Pure Barre, and so I regularly encourage friends to take classes with me.

Pure Barre is a great example of how successful a brand can be when it’s tuned into how its product/service makes their customers feel. When brands know what emotions they (and should) evoke from their customers, brands can more effectively create techniques to drive consideration and loyalty.  Pure Barre motivates, encourages, and supports its customers. The end result? A loyal following of barre fanatics willing to pay a premium to plié.  

Want to learn more about how we're revolutionizing  emotional measurement with our EMPACT solution? Watch our webinar:  

Learn More About EMPACT℠

Cara Lousararian is a Senior Research Manager at CMB and rarely passes up an opportunity to #LTB (that’s lift, tone, burn for those not familiar with the Pure Barre lingo).

Topics: EMPACT, emotional measurement, customer experience and loyalty, emotion

Using Emotion to Drive Brand Loyalty

Posted by Heather Magaw

Mon, Feb 13, 2017

Valentine's Day image.jpeg

Stores have been stocked with heart-shaped candies and cards since December, but now that it’s actually February, I think it’s okay to think about Valentine’s Day.  And because love is in the air (as well as on the shelves) it’s a perfect time to think about how brands can tap into this fundamental human experience to drive consideration, usage and loyalty.  

We already know that understanding and influencing consumers’ emotions is crucial for building a loyal customer base, but what do we really know about love that could help us achieve those lofty outcomes? Based on a quick Google search (and a few life experiences), here’s what I’ve learned so far:

Love is an emotion.

Love is an action.

Love is a biological motivation system.

Love is an attitude.

Love is a drive.

Love is a choice.

Love is patient.

Love is blind.

Love is a battlefield.

Love, as it turns out, is rather complex. So what does that mean for marketers trying to get people to fall in love with their brands? Where do you start?  

When studying emotion, traditionally researchers take a brand-centric approach and focus on how consumers feel about the brand. While there’s valuable insight there, it’s often more valuable to take a consumer-centric approach, one that asks consumers how the brand makes them feel. Consumers develop feelings about a brand because of how it makes them feel… understanding those feelings evoked by the brand is critical insight into how consumers develop strong, positive sentiments towards the brand.

That’s why EMPACTSM, our proprietary approach to measuring emotion, is based on decades of consumer psychology research, helping marketers understand how a brand or touchpoint should make consumers feel to most effectively drive their behaviors, and ultimately brand love.

For marketers trying to earn consumers’ love this Valentine’s Day (and the other 364 days of the year), it’s critical to explore which emotions your brand should evoke to make them love your brand. Do they want to feel respected? Proud? Efficient? Secure? Surprised?  Just like with the object of your romantic affections, you’ll be far more successful with your customers if you ask them how they want to feel and create experiences and messaging that inspire those emotions. [twitter.png Tweet this!]  

Heather Magaw is VP of Client Services at CMB. The brands she loves most this Valentine’s season are Apple, Amazon, Red Sox, IBM Watson, and CMB (of course!).  

Topics: EMPACT, emotional measurement, emotion