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I, for one, welcome our new robot...partners

Posted by Laura Dulude

Tue, Oct 17, 2017

 

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Ask a market researcher why they chose their career, and you won't hear them talk about prepping sample files, cleaning data, creating tables, and transferring those tables into a report. These tasks are all important parts of creating accurate and compelling deliverables, but the real value and fun is deriving insights, finding the story, and connecting that story to meaningful decisions.

So, what’s a researcher with a ton of data and not a lot of time to do? Hello, automation!

Automation is awesome.

There are a ton of examples of automation in market research, but for these purposes I'll keep it simple. As a data manager at CMB, part of my job is to proofread banner tables and reports, ensuring that the custom deliverables we provide to clients are 100% correct and consistent. I love digging through data, but let’s be honest, proofing isn’t the most exciting part of my role. Worse than a little monotony is that proofing done by a human is prone to human error.

To save time and avoid error, I use Excel formulas to compare two data lists and automatically flag any inaccuracies. This is much more accurate and quicker than checking lists against one another manually—it also means less eye strain.

As I said, this is a really simple example of automation, but even this use case is an incredible way to increase efficiency so I have more time to focus on finding meaning in the data.

Other examples include:

  • Reformatting tables for easier report population using Excel formulas
  • Creating Excel macros using VBA
  • SPSS loops and macros

I’m a huge proponent of automation, whether in the examples above or in myriad more complex scenarios. Automation helps us cut out inefficiencies and gives us time to focus on the cool stuff

Automation without human oversight? Not awesome.

Okay, so my proofreading example is quite basic because it doesn’t account for:

  • Correctness of labels
  • Ensuring all response options in a question are being reported on
  • Noting any reporting thresholds (e.g. only show items above 5%, only show items where this segment is significantly higher than 3+ other segments, etc.)
  • Visual consistency of the tables or report
  • Other details that come together to create a truly beautiful, accurate, and informative deliverable.

Some of the bullet points above can also be automated (e.g. thresholds for reporting and correctness of labels), but others can’t. On top of that, automation is also prone to human error—we can automate incorrectly by misaligning the data points or filtering and/or weighting the data incorrectly. Therefore, it’s imperative that, even after I automate, I review to catch any errors—flawless proofing requires a human touch.

When harnessed correctly, automation maximizes efficiency, alleviates tediousness, and reduces error to free up more time for insights. Before you start arming yourself against a robot takeover, remember: insights are an art and a science, and machines haven’t taken over the world just yet.

Topics: quantitative research, Artificial Intelligence, Market research Automation,

We're excited to join the ITA Group Family!

Posted by Savannah House

Fri, Oct 06, 2017

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We’re excited to announce that we are now part of the ITA Group family—a worldwide leader in corporate engagement solutions.

“An increasingly complex and data-driven world requires an innovative and strategic approach to helping companies and their people succeed,” said Jim Garrity, CMB's CEO. “While ITA Group and CMB bring unique expertise and talents to this partnership, we are committed to the same goal: delivering best-in-class data-driven solutions to our clients.” CMB Chair Anne Bailey Berman adds, “I am confident combining our complementary expertise will strengthen our current offerings and carve out new opportunities in our respective industries.”

“Organizations are demanding to know the future,” said Tom Mahoney, ITA Group Chairman and CEO. “They want predictive analytics that allow them to capitalize on their existing assets and create new opportunities for growth. This acquisition will give our clients and prospective clients the data-driven insights that can further drive their business.”

 To learn more about this exciting new chapter, read our full press release here.

Does your metric have a home(plate)?

Posted by Youme Yai

Thu, Sep 28, 2017

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Last month I attended a Red Sox/Yankees matchup at Fenway Park. By the seventh inning, the Sox had already cycled through seven pitchers. Fans were starting to lose patience and one guy even jumped on the field for entertainment. While others were losing interest, I stayed engaged in the game—not because of the action that was (not) unfolding, but because of the game statistics.

Statistics have been at the heart of baseball for as long as the sport’s been around. Few other sports track individual and team stats with such precision and detail (I suggest reading Michael Lewis’ Moneyball if you haven’t already). As a spectator, you know exactly what’s happening at all times, and this is one of my favorite things about baseball. As much as I enjoy watching the hits, runs, steals, strikes, etc., unfold on the field, it’s equally fun to watch those plays translate into statistics—witnessing the rise and fall of individual players and teams.

Traditionally batting average (# of hits divided by number of at bats) and earned run average (# of earned runs allowed by a pitcher per nine innings) have dominated the statistical world of baseball, but there are SO many others recorded. There’s RBI (runs batted in), OPS (on-base plus slugging), ISO (isolated power: raw power of a hitter by counting only extra-base hits and type of hit), FIP (fielding independent pitching: similar to ERA but focuses solely on pitching, and removes results on balls hit into field of play), and even xFIP (expected fielding independent pitching; or in layman’s term: how a pitcher performs independent of how his teammates perform once the ball is in play, but also accounting for home runs given up vs. home run average in league). And that's just the tip of the iceberg. 

With all this data, sabermetrics can yield some unwieldy metrics that have little applicability or predictive power. And sometimes we see this happen in market research. There are times when we are asked to collect hard-to-justify variables in our studies. While it seems sensible to gather as much information as possible, there’s such a thing as “too much” where it starts to dilute the goal and clarity of the project.  

So, I’ll take off my baseball cap and put on my researcher’s hat for this: as you develop your questionnaire, evaluate whether a metric is a “nice to have” or a “need to have.” Here are some things to keep in mind as you evaluate your metrics:

  1. Determine the overall business objective: What is the business question I am looking to answer based on this research? Keep reminding yourself of this objective.
  2. Identify the hypothesis (or hypotheses) that make up the objective: What are the preconceived notions that will lead to an informed business decision?
  3. Establish the pieces of information to prove or disprove the hypothesis: What data do I need to verify the assumption, or invalidate it?
  4. Assess if your metrics align to the information necessary to prove or disprove one or more of your identified hypotheses.

If your metric doesn’t have a home (plate) in one of the hypotheses, then discard it or turn it into one that does. Following this list can make the difference in accumulating a lot of data that produces no actionable results, or one that meets your initial business goal.

Combing through unnecessary data points is cumbersome and costly, so be judicious with your red pen in striking out useless questions. Don’t get bogged down with information if it isn’t directly helping achieve your business goal. Here at CMB, we partner with clients to minimize this effect and help meet study objectives starting well before the data collection stage.

Youme Yai is a Project Manager at CMB who believes a summer evening at the ballpark is second to none.

 

Topics: advanced analytics, data collection, predictive analytics

Hulu's Emmy Win Marks a New Age for Content Creators

Posted by Savannah House

Thu, Sep 21, 2017

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Hulu made Emmy and television history on Sunday night when “The Handmaid’s Tale” took home the award for Outstanding Drama Series. Hulu’s dystopian drama beat out heavy hitters like Netflix, NBC and HBO to become the first streaming service to win the coveted award.

We’ve seen the rapid maturation of streaming services ever since Netflix released “House of Cards” in 2013. It was the first time a streaming service delivered Emmy-nominated original content that could compete and win against powerhouses like HBO and Showtime. And while “House of Cards” put Netflix on a path to become an award-winning and prolific content provider, a best series award eluded them.

That’s not to say that Sunday wasn’t a big night for other networks—HBO snagged the highest number of awards with 29 wins and NBC’s “Saturday Night Live” was the top winning program with 9. But Hulu’s big win is a game changer—securing a seat at the table and putting networks on notice.

The sheer volume of award-winning content means there are literally thousands of quality programs available on every device imaginable. With that sort of competition, how do content creators ensure their programs will get visibility and retain viewers?

Gone are the days of linear viewing—people can access what they want, when they want, and how they want. Empowered consumers are more decisive and critical than ever before. For that reason, it’s important to understand what’s motivating people to discover, watch, and stick with shows.

Next month at TMRE, CMB’s Judy Melanson and ABC’s Lyndsey Albertson will share findings from a comprehensive content discovery initiative that gets to the heart of a viewer’s path to engagement, loyalty, and advocacy. While this is a case study on the disruption within the media and entertainment space, the challenges and solutions will resonate with any brand looking to gain traction with new products while navigating a market in flux.

The shift towards consumer-centricity transcends the entertainment space, but Hulu’s shining moment at the Emmy’s underscores the rise of streaming services as legitimate content providers and the need for all entertainment players to start considering what is motivating their customers if they are to be content kings.

Are you going to TMRE next month? If so, let us know! We’d love to connect you with one of our lead researchers to brainstorm upcoming projects. If you’re not going, tell us know anyway and we’ll send you the ABC presentation!  

Savannah House is a Marketing Manager at CMB whose list of shows to watch is longer than Game of Thrones season 7.

Topics: digital media and entertainment research

Are We There Yet? How TURF Can Save Your Family Trip

Posted by Victoria Young

Tue, Sep 05, 2017

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As the summer comes to a close, I’m reminiscing about the annual end-of-summer trip to New Hampshire my family used to take. There’s a lot to do and see in New Hampshire, and only having a week, we had to pick and choose how to spend our time wisely. Ultimately that decision was up to my mom, but that didn’t prevent me and my brother sharing our various opinions.

We all loved Story Land (that was a given) and it was always included on our NH itinerary… but that’s where unanimous agreement ended. My brother pined for Six Gun City–a Wild West themed park–but I preferred Santa’s Village. I thought Santa’s Village was cute while my brother thought it was tacky. Meanwhile, both my brother and I moaned and groaned when our mom insisted we hang out on the side of the road for an hour to look at The Old Man in the Mountain (RIP).

During the week, we managed to hit all desired attractions (and more), but tensions ran high some days. My brother complained at Santa’s Village while I couldn’t be bothered at Six Gun City—looking back, I can’t imagine the stress we caused our mom with our eye-rolling and sighs.

The researcher in me wonders if there could’ve been a way to satisfy everyone’s desires without upsetting some? Then I realized that this scenario isn’t totally unlike what we run TURF analyses for. If there had been a TURF analysis for our family vacations, perhaps it would’ve saved a lot of headaches.  

But what is “TURF”?

TURF is an acronym for “Total Unduplicated Reach and Frequency.” TURF Analysis is a statistical analysis that was traditionally used to help media buyers determine where to place ads to reach the widest possible audience. But the use of TURF has since expanded to help answer product development questions like “What is the smallest number of features, services or products that could be offered to appeal to the largest number of potential consumers?”  

TURF determines the maximum number of people reached by looking for unduplicated reach. For example, if Person A likes Channel X and Channel Y, and both channels are included in the analysis, the model will get no additional reach from Person A than it would’ve had only Channel X or Channel Y been included.

This type of analysis could’ve helped us determine which attractions would appeal to the largest audience on our family trips. TURF is ideal when the number of choice combinations is high and the number of combinations are restricted—in my family’s case, we were restricted by time, money, and patience.

TURF tests each combination of options (e.g., Story Land, Clark’s Trading Post, Santa’s Village, etc.), and reports both reach and frequency for each combination. As you add items (in this case, attractions), the reach increases for a while and then tapers off. This is called the law of diminishing returns. The key is finding that sweet spot where you get the highest reach with the fewest items, and where anything above that is only incremental.

To make this more digestible, consider the example below. We’re planning a family vacation with our extended family, all of whom have varying preferences:

Story Land table.png

Of our 8 family members, 4 like Story Land (50% reach). Two other attractions–Attitash Bear Peak and Santa’s Village–appeal to 3 family members, but because all 3 who like Santa’s Village also like Story Land, only Attitash Bear Peak adds to the model’s reach. 

If we add Attitash Bear Peak, we come up with a total of 6 family members (75%) who get something they want.  Both Six Gun City and Clark’s Trading Post reach 2 family members, but only Six Gun City reaches Cousin Blair, one of two family members not reached by the first two attractions, bringing us to 87.5% reach.  We’re unable to please everyone, especially Long Lost Uncle Mark who appears to not enjoy anything. 

As the chart below suggests, we could please almost everyone in three stops: Story Land, Attitash Bear Peak, and Six Gun City.  Instead of going everywhere, we can maximize everyone’s happiness (reach) and stay within our restrictions (budget, time, patience) by going to those three stops.

Story Land chart_2.png

 

Ok, so TURF might not be the most logical answer to family vacation logistics, but it can help companies make important business decisions, especially when they are faced with multiple options and a limited budget.

So for now, my mom, brother, and I will continue to ask ourselves, who’s up for Story Land?

Victoria is a Senior Associate Researcher at CMB who still loves Story Land and traveling with her family.

Topics: business decisions, quantitative research

Why the Market Research Industry Must Stand up for the Census

Posted by Athena Rodriguez

Wed, Aug 23, 2017

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You might be forgiven if the future of the U.S. Census didn’t make your “list of things to worry about this week”. But a lack of funding coupled with the recent resignation of Census Bureau director John Thompson has put the 2020 census in danger—and the ramifications are deeply concerning.

The U.S. Census Bureau might not get the media coverage of other government entities, but it plays a critical role in our democracy, federal spending, and in the market research industry. As we prepare for the 2020 census, it’s time to start paying attention.

The U.S. Census

As a reminder, the U.S. Census, mandated by the Constitution, is a decennial survey that counts every resident in United States. The data is used to allocate Electoral College votes and congressional seats by state.  In addition, it helps the government determine how to allocate roughly $4 billion in federal funds to local communities that help pay for infrastructure like schools, hospitals, roads, public works, and other vital programs. The U.S. Census Bureau also administers the monthly American Community Survey—comprised of the long form census questions—sent to about 295k households a month. You can read more about the work of the Bureau and how the data are used here.

A New Collection Methodology Puts the Census in Danger

Replicating the 2020 census using the 2010 methodology would cost $17.8 billion, but Congress has mandated that the Census Bureau limit spending to meet the 2010 census budget ($13 billion over ten years).   

To comply, the bureau hoped to implement a new system, adding online and phone data collection, in addition to mail and in-person visits, that will ultimately keep costs in line. However, any change in methodology requires rigorous planning and testing to ensure results are accurate and replicable. For example, when moving a brand tracker from the phone to web, you typically run tandem data collections (both via phone and online) for the first wave and then compare the results. This testing requires extra work, and initially may cost more, but it’s critical to ensure the results from the new methodology are comparable and will save money in the long run. 

The scope and costs of the census far exceed my brand tracker example, and given the uncertainty of the census budget, it’s unclear whether the census will be able to properly test their new methodology before implementation. If funding isn’t there for testing, the Census Bureau runs the risk of missing the mark.

The end-to-end of the census test is still slated for 2018 but the prerequisite field tests that were to run this year have been cancelled.  The Bureau hopes to include the areas from the cancelled field tests, but that’s still up in the air.

The US Census and Market Research

The US Census serves as the backbone for all consumer market research. I don’t think it’s an exaggeration to say that here at CMB, we use the census on a weekly basis, if not more often, for designing sampling plans, weighting data, sizing audiences, and recommending who to target. You’d be hard pressed to find a research firm that doesn’t use census information to inform its work.

To that end, if the census is flawed by undercount (resulting from a poorly-tested methodology), these errors will be reproduced in most consumer market research studies. As researchers, we’d begin to question the foundation upon which much of our research is built—as would the many businesses that use our services

The Larger Picture

If the census is underfunded, the undercount would most likely impact areas where residents are harder to reach (think lower socio-economic groups less likely to have internet access, rural populations, transient populations like seasonal workers, etc.). These areas—the very communities that need funding the most—could be deprived of vital federal funds due to disproportionate allocations.

In addition to faulty fund allocation, an underfunded, undercounted census could produce a misrepresentation of seats in our House of Representatives. In this charged political environment where everyone’s vying to be heard, it’s more important than ever to ensure we are properly represented.

What’s Next?

2020 may seem far off, but if Congress doesn’t properly fund the census now, while there’s still time for testing, we run the risk of executing a bad census, one that misrepresents the population, unfairly allocates resources, and undermines the quality and credibility of market research. I strongly encourage the market research community to stand up and make their voices heard to preserve this important institution.

 Athena is a Project Director at CMB who wants to see her daughter grow up in a world where the US Census is accurate. 

Topics: big data, B2B research, Market research

Namesake: The Next KPI?

Posted by Laura Blazej

Wed, Aug 16, 2017

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When my fiancé and I adopted our first dog a few months ago, we wanted to name her something meaningful… something that we wouldn’t grow tired of saying over and over. We landed on “Pharah,” after the rocket-launcher-wielding, jetpack-flying, altogether-badass character from one our favorite video games, Overwatch. As a market researcher charged with measuring brand health and loyalty, I started to wonder what naming my new pup “Pharah” says about my relationship with Overwatch?

This is the kind of question we ask when we’re measuring brand health. To gauge the strength of the relationship between consumers and a particular brand, we look at metrics—called Key Performance Indicators (KPIs)—to help indicate how a brand is doing. While namesake might not be a legitimate KPI (yet!), there are loads of others we measure in order to help our clients understand their brand health:

Unaided Awareness

  • Definition: The ability to recall a brand without help (This is different from Aided Awareness, which is the ability to recognize a listed brand)
  • Common question to gauge this metric: “Thinking about [industry], what brands come to mind?” (Respondent provides open ended answers)
  • Goal: Unaided awareness determines whether there is an existing relationship between the consumer and brand
  • Fit: Unaided awareness is a useful metric for smaller, newer, or regional brands who are working on improving their brand recognition. For example, the regional brand, University of Pittsburg Medical Center, would focus on unaided awareness, whereas the universal brand, Google, wouldn’t

Top of Mind Awareness

  • Definition: The first brand recalled without help in an open-end response
  • Common question wording: “Thinking about [industry], what brand first comes to mind?”
  • Goal: Top of mind awareness gauges either the most loved, the most hated, or the most prevalent brand to each consumer in any given industry
  • Fit: Useful for established brands who want to be first in consumers’ consideration set

Net Promoter Score (NPS)

  • Definition: The willingness of customers to recommend a company’s products or services to others. To calculate NPS score, we subtract the percentage of those unlikely to recommend the brand from the percentage of those likely to promote it
  • Common question wording: “How likely are you to recommend this brand to a friend or family member?”
  • Goal: This metric determines the magnitude and valence of the relationship between consumer and brand—that is, how strong or weak the relationship is (farther or closer to 0), and whether the relationship is positive or negative
  • Fit: NPS is useful to measure holistic loyalty since it accounts for both the high and low end of the scale in a single metric

Funnel/Pyramid Metrics

  • Definition: Often comprised of awareness, familiarity, favorability, preference, likelihood to purchase, and/or likelihood to recommend shown as descending or ascending bar lengths, forming a funnel or pyramid shape
  • Common question wording: Surveyed as a series of questions that touch on the aforementioned metrics
  • Goal: This metric focuses on the whole picture by following the entire journey to purchase/loyalty and the conversion ratios between each step
  • Fit: Useful as a big-picture approach to pinpoint where along the journey to focus marketing efforts

Preference

  • Definition: Likelihood to choose a brand over its competitors
  • Common question wording: “Which brand is the one you prefer?” among a list of brands
  • Goal: Preference is like NPS in that it measures loyalty, however it does so by comparing the brand against the competitive market
  • Fit: This metric is useful for brands that are already well-known and working on improving loyalty in a competitive market
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And very often we create a unique secret-sauce combination of some or all of these metrics, called Brand Strength Scores, for some clients. These special scores use several metrics at varying weights determined specifically for the clients’ goals, industry, and competitive market to calculate a single score to compare against competitors and evaluate change over time.

The point is, there’s no prescribed “right” set of KPIs to track when measuring brand health. These metrics are used to answer different questions, and what KPI a brand like Bank of America might use is probably a lot different than what makes sense for a regional credit union.

However, and this MAY be a stretch, I’d argue namesake would be a great way to gauge ultimate commitment and loyalty to a brand—regardless of size. When I was thinking about what to name Pharah, I thought about the things I love and wouldn't mind repeating (shouting?) for the next decade. To name a pet, or even a person, after a character or brand indicates a level of commitment to that brand that isn’t measured by the conventional KPIs described above.

Who knows, maybe “How likely are you to name a pet after this brand?” will start to show up in our brand health questionnaires.

Laura Blazej is a Senior Associate Researcher at CMB who enjoys playing video games with her new pup.

Topics: brand health and positioning, customer experience and loyalty

Words from a Veteran Telecommuter

Posted by Betsy Herrick

Wed, Aug 09, 2017

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I have the coveted corner office with a magnificent view. But it’s not the typical “corner office” you might be thinking of, the one perched thirty stories up, with floor-to-ceiling windows offering unobstructed views of the bustling city street below. Nope, my corner office looks out over the quiet, rural landscape of my backyard in Maine.

Even though my company’s headquarters are in Downtown Boston, for the past 11 years, I’ve been a full-time remote employee.

When I first started working from home in 2006, it wasn’t nearly as popular as it is today. The concept of working from home, or “telecommuting", as it’s come to be known as, seemed to be a perk that only startups offered employees, not "regular" businesses. To those who weren't familiar with the concept, they probably pictured remote employees as sitting at home with their feet up at their desk eating bonbons. But fortunately, even in the early days, CMB embraced the idea with optimism.

Over the last decade, telecommuting has gained tremendous popularity with the number of full-time remote employees in the US increasing by 115% between 2005 and 2015. I was the first CMBer to work remote full-time, and now we have more than five employees telecommuting with another group doing so part-time.

Both the employer and employee have much to gain from this arrangement, for example, higher productivity, fewer sick or weather-related absences, more flexibility, a generally happier workforce, etc. While telecommuting can be mutually beneficial, there are a couple key things that must happen in order for it to be a productive and successful arrangement.

In my eleven years as a remote employee, I’ve learned communication is integral to a successful telecommuting arrangement. And fortunately, today’s technology makes it really easy for communication to flow seamlessly between colleagues—ensuring I am connected and engaged, even when I’m hundreds of miles away in Maine. In addition to traditional email and good, old-fashioned phone calls (never underestimate the power of the spoken word!), we regularly use virtual meeting software equipped with screen sharing and video chat capabilities. These technologies enhance productivity and enable real-time responses.

A successful telecommuter must be able to prioritize tasks without much guidance and regular physical check ins. It’s their responsibility to keep up with important deadlines, and know which projects take precedence over others when priorities shift. In my case, as a graphic designer, it helps that I have a deadline-oriented job—I’ve been trained to work autonomously towards daily goals, but know when I need to rearrange my schedule if something unexpected pops up.

Working from home offers distractions that a traditional office setting might not—whether it’s the beautiful weather outside or a pile of laundry inside. To combat these distractions, it’s important for a telecommuter to have a designated work space away from their “home life”.  I treat my office space as exactly that, a place “away” from home where I go to work each day. It is a separate space with a desk, good lighting, and all the technology I need to do my job. I do not answer my home phone or go pull weeds in my garden during business hours, just as if I was at my company’s physical location… although I do enjoy having a cat on my lap occasionally while I work.

As telecommuting grows in popularity, companies are discovering other, less obvious benefits from this practice: better staff health, lower operating costs, greater loyalty (with less turnover) for the company, and fewer weather-related business interruptions, to name a few. But despite the pros, telecommuting is not for everyone. When you work remotely, you sacrifice the social aspect of going into a physical office—there’s no water cooler at my house and I regularly miss out on weekly company events.

But ultimately, my commute rocks, my productivity is high, my colleagues keep me “in the loop”, and I love my corner office with a view. I wouldn’t change my work situation if you paid me, and ironically, I already get paid to stay home.

Betsy is CMB’s Corporate Design Specialist, and does enjoy bonbons…just not during working hours.

Topics: Chadwick Martin Bailey

Qualitative Research: Thinking Outside the Box(ing) Ring

Posted by Kelsey Segaloff

Wed, Aug 02, 2017

My friends and family greeted the news that I was joining a boxing gym with more than a little disbelief. Granted I am an imposing 5 feet tall and have a reputation for tripping over my own feet, so maybe they had a point. But four months and two pairs of gloves later, I’m not only fitter and stronger, I’ve learned some essential truths about boxing that I can apply to my professional life as a qualitative researcher. 

 kelsey boxing.jpg

Don’t forget the “Why”

Boxing is a commitment—physically, financially, and mentally—and it’s tempting to hit the snooze button when I don’t want to get out of bed for an early morning class. Oftentimes, I must remind myself why I keep up with it. To help motivate members, there’s a large chalkboard titled, “Why I Fight” filled with trainers’ and members’ “whys” in the front of the gym.  It’s the first thing you see when you walk in and serves as motivation to both me and fellow boxers.

Focusing on the decisions or the “why” is critical for researchers. Before kicking off a project, we work hard to fully understand our clients’ business needs and the decisions they need to make—this focus keeps us on track for everything from designing a study and choosing a methodology, all the way to the final deliverables and implementation. It’s also important to consider our participants’ “why”—that’s the reason we often use tools like projective techniques in qualitative research to dive deep into participants’ thoughts and uncover their beliefs, motivations, feelings, etc.—the old one-two punch, as some might say.

#FightFam

One of my favorite things about my gym is the sense of community it provides. My #fightfam challenges me to put my all into every class, whether it be Gennifer reassuring me I’m “crushing it,” or Roscoe in the bags room reminding the class we are winners (“And what do winners do? THEY WIN!”). While I feel a personal sense of accomplishment after every class I finish, I also feel a shared sense of pride with my fellow classmates and trainers—and that’s important.

A knockout team is also the foundation for greatness in qualitative research. At CMB, our all-star roster, VP of Qualitative Strategy + Innovation, Kathy Ofsthun, Qualitative Research Director, Anne Hooper, Qualitative Project Manager, Erin Stilphen, and I work together and encourage one another to perform at our highest capacity. We bring inventive and innovative qualitative methodologies like co-creation, and over 40 years of combined qualitative experience to the ring. We’re also adept to thinking on our toes—ask me about the time I recruited for a study in a Canadian train station! And when we need to tap other teammates, we’ve got specialized qualitative research consultants in our corner.

Master Technique, Prepare to Improvise

Boxing is known as the sweet science (the nickname is an appreciation of the technical skills required—strength, endurance, conditioning, core, and flexibility), but it’s just as much an art, requiring improvisation and creativity.

The same goes for qualitative research. We’re masters of improv, but good technique is integral. Recently, I was thrown through a loop while moderating an in-home ethnography for our self-funded research on Millennial and Gen Z use of virtual assistants (think Siri, Cortana, etc.).  Shortly into one of the interviews, it turned out the participant belonged in a different segment than what my guide had indicated. Instead of stopping the interview, I used my improvisation skills and reframed the questions without interrupting the flow of the conversation. Going a little off script helped us gather the insights we needed.

I love that I’ve discovered a sport and gym I am passionate about, and I’m even more thrilled I can draw meaningful parallels between boxing and my profession. Of course, there are times when my muscles ache, my wrists hurt, and I’m tired, but then I remind myself why I keep going. I box because it makes me stronger, faster, and confident—and that these attributes help me be a better qualitative researcher is a bonus!

kelsey boxing 2.jpg

Kelsey Segaloff is CMB’s Qualitative Associate Researcher, and can be found working on her jab-cross at EverybodyFights Boston.

 

Topics: our people, qualitative research, Consumer Pulse, co-creation

Flying High on Predictive Analytics

Posted by Amy Maret

Thu, Jul 27, 2017

pexels-photo-297755_resized-1.jpgBuying a plane ticket can be a gamble. Right now, it might be a good price, but who’s to say it won’t drop in a day—a week? Not only that, it may be cheaper to take that Sunday night flight instead of Monday morning. And oh—should you fly into Long Beach or LAX? As a frequent traveler (for leisure and work!) and deal seeker, I face dilemmas like these a lot.

The good news is that there are loads of apps and websites to help passengers make informed travel decisions. But how? How can an app—say, Hopper—know exactly when a ticket price will hit its lowest point? Is it magic? Is there a psychic in the backroom predicting airline prices with her crystal ball?

Not quite.

While it seems like magic (especially when you do land that great deal), forecasting flight prices all comes down to predictive analytics—identifying patterns and trends in a vast amount of data. And for the travel industry in particular, there’s incredible opportunity to use data in this way. So, let’s put away the crystal ball (it won’t fit in your carry on) and look at how travel companies and data scientists are using the tremendous amount of travel data to make predictions like when airfare will hit its lowest point.

In order to predict what will happen in the future (in this case, how airfare may rise and fall), you need a lot of data on past behaviors. According to the Federal Aviation Administration (FAA), there are nearly 24,000 commercial flights carrying over two million passengers around the world every day. And for every single one of those travelers, there’s a record of when they purchased their ticket, how much they paid, what airline they’re flying, where they’re flying to/from, and when they’re traveling. That’s a ton of data to work with!

As a researcher, I get excited about the endless potential for how that amount of historical data can be used. And I’m not the only one. Companies like Kayak, Hopper, Skyscanner, and Hipmunk are finding ways to harness travel data to empower consumers to make informed travel decisions. To quote Hopper’s website: their data scientists have compiled data on trillions of flight prices over the years to help them make “insightful predictions that consistently perform with 95% accuracy”.

 While the details of Hopper are intentionally vague, we can assume that their team is using data mining and predictive analytics techniques to identify patterns in flights prices. Then, based on what they’ve learned from these patterns, they build algorithms that let customers know when the best time to purchase a ticket is—whether they should buy now or wait as prices continue to drop leading up to their travel date. They may not even realize it, but in a way those customers are making data-driven decisions, just like the ones we help our clients make every day.

As a Market Researcher, I’m all about leveraging data to make people’s lives easier. The travel industry’s use of predictive modeling is mutually beneficial—consumers find great deals while airlines enjoy steady sales. My inner globetrotter is constantly looking for ways to travel more often and more affordably, so as I continue to discover new tools that utilize the power of data analytics to find me the best deals, I’m realizing I might need some more vacation days to fit it all in!

So the next time you’re stressed out about booking your next vacation, just remember: sit back, relax, and enjoy the analytics.

Amy M. is a Project Manager at CMB who will continue to channel her inner predictive analyst to plan her next adventure.

Topics: big data, travel and hospitality research, predictive analytics