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Dear Dr. Jay—Brands Ask: Let's Stay Together?

Posted by Dr. Jay Weiner

Thu, Feb 11, 2016

 Dear Dr. Jay,

 What’s love got to do with it?

 -Tina T. 


DrJay_Thinking_about_love.pngHi Tina,

How timely.

The path to brand loyalty is often like the path to wedded bliss. You begin by evaluating tangible attributes to determine if the brand is the best fit for you. After repeated purchase occasions, you form an emotional bond to the brand that goes beyond those tangible attributes. As researchers, when we ask folks why they purchase a brand, they often reflect on performance attributes and mention those as drivers of purchase. But, to really understand the emotional bond, we need to ask how you feel when you interact with the brand.

We recently developed a way to measure this emotional bond (Net Positive Emotion Score - NPES). By asking folks how they felt on their most recent interaction, we’re able to determine respondents’ emotional bond with products. Typical regression tools indicate that the emotional attributes are about as predictive of future behavior as the functional benefits of the product. This leads us to believe that at some point in your pattern of consumption, you become bonded to the product and begin to act on emotion—rather than rational thoughts. Of course, that doesn’t mean you can’t rate the performance dimensions of the products you buy.

Loyalty is a behavior, and behaviors are often driven by underlying attitudinal measures. You might continue to purchase the same product over and over for a variety of reasons. In a perfect world, you not only create a behavioral commitment, but also an emotional bond with the brand and, ultimately, the company. Typically, we measure this path by looking at the various stages you go through when purchasing products. This path begins with awareness, evolves through familiarity and consideration, and ultimately ends with purchase. Once you’ve purchased a product, you begin to evaluate how well it delivers on the brand promise. At some point, the hope is that you become an advocate for the brand since advocacy is the pinnacle of the brand purchase hierarchy. 

As part of our Consumer Pulse program, we used our EMPACT℠: Emotional Impact Analysis tool to measure consumers’ emotional bond (NPES) with 30 brands across 6 categories. How well does this measure impact other key metrics? On average, Net Promoters score almost 70 points higher on the NPES scale versus Net Detractors. We see similar increases in likelihood to continue (or try), proud to use, willingness to pay more, and “I love this brand.”

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What does this mean? It means that measuring the emotional bond your customers have with your brand can provide key insights into the strength of that brand. Not only do you need to win on the performance attributes, but you also need to forge a deep bond with your buyers. That is a better way to brand loyalty, and it should positively influence your bottom line. You have to win their hearts—not just their minds.

Dr. Jay Weiner is CMB’s senior methodologist and VP of Advanced Analytics. He has a strong emotional bond with his wife of 25 years and several furry critters who let him sleep in their bed.

Learn More About EMPACT℠

Topics: NPS, path to purchase, Dear Dr. Jay, EMPACT, emotional measurement, brand health and positioning

Move Over Cupid: A Qualitative Researcher’s Guide to Valentine’s Day

Posted by Eliza Novick

Tue, Feb 09, 2016

eliza_blog_image.pngAs Valentine’s Day ticks closer, I’m reminded of my best and worst dates over the years. At best, I’ve enjoyed rosé, cheese, and interesting conversations; at worst, I had a beer spilled on me and endured lots of awkward pauses. Through all the ups and downs, I’ve perfected a few tricks that can help make a date a great success and avoid your typical first date pitfalls. Best of all, these are tricks that I can apply to my work as a qualitative researcher!

Moderating a focus group is kind of like going on a blind date with eight people at once while your boss watches. Yes, it can be awkward, but it’s critical that respondents really connect with the moderator to ensure that our clients get reliable findings. With that in mind, here are my top three tips for making it through a first date and for wow-ing clients by getting the most out of your qualitative research:

  1. Ask open-ended questions: Nobody likes stilted conversation, but sometimes it can feel hard to avoid. Rather than asking close-ended questions that end in one-word answers, try asking people to describe an experience. “What kind of things have you been cooking recently?” tends to get a lot more traction than, “Do you like to cook?” Likewise, “Tell me about a time you paid for an unanticipated medical expense” can take you (and your clients) much further than “Have you ever had an unanticipated medical expense?” Putting the emphasis on sharing a story encourages people to give detailed responses and speak genuinely about their interests and experiences.
  2. Don’t try to cover too much ground: Meeting new people can be overwhelming—there’s a lot to digest. So, I’ve found that it’s best to keep the conversation simple. Unlike the unfortunate fellow who asked me rapid-fire questions for two hours over drinks, try asking follow-up questions on one topic. This lets you get to know someone better and discover interesting details that you wouldn’t uncover if you were speeding through topics. It also works in qualitative since your respondents are coming into the conversation with virtually no context. They weren’t privy to the hours of client calls, discussion guide revisions, and marketing materials like the research team was. While it’s tempting to cram as much content as possible into the discussion guide, nine times out of ten, clients find more value in clear, detailed findings than high-level, scattered anecdotes. Besides, speeding through different topics makes it difficult to identify patterns. So, do everyone a favor—slow down, and see where the conversation takes you.
  3. Trust your gut: If something doesn’t seem right, trust yourself. If you’re on a date and things aren’t going well, it’s ok to leave early. Likewise, if your carefully laid research plans are not panning out as you had planned, it’s ok to take a different route. Try phrasing a question a different way. Or, if you have a sense that someone in the group disagrees with a point but is too shy to say so, ask them if they’ve got anything they’d like to share. Not only will this show your respondents that you’re listening and care about what they have to say, it will also elicit more honest responses that lead to better findings (and happy clients).

Qualitative research, like dating, is really about connecting with people—we get the best results when respondents feel they can relate to us researchers on a personal level. So, don’t be afraid to put yourself out there! Take your time, listen to the data you’re getting, and trust yourself. Easy!

Eliza is a qualitative researcher at CMB. In addition to applying her dating life to her work, she likes to be outside, read books, and cook. 

For the latest Consumer Pulse reports, case studies, and conference news, subscribe to our monthly eZine.

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Topics: qualitative research, research design

Will the Sun Set on British Brands?

Posted by Josh Fortey

Thu, Feb 04, 2016

British-brands.pngAdele, One Direction, Burberry, Downton Abbey, Kate Middleton, the Royal Family, and, of course, myself… the British are once again invading the shores of the U.S.

Young British musicians continue to take the American music industry by storm—in 2012, four out of five of the top five selling albums in the U.S. were from British artists. Just last December, approximately 10 million fans fought over 750,000 tickets for Adele’s upcoming 2016 tour. The entertainment industry is not the only one seeing dollar signs with this British Invasion. Coffee shop and fast food chain, Pret a Manger, plans further U.S. expansion after successful stints in Boston, New York, Washington DC, and Chicago, building on its brand of fresh, prepared products.

It’s clear that Britain as a brand has been riding a positive wave in the U.S. in recent years with the London Olympics and the birth of the Royal Prince and Princess acting as potential catalysts. The allure of international expansion into the American market, therefore, seems the most logical step for British brands looking for the next stage of growth. According to a Barclays study in 2013, the U.S. was considered the top current market for sales growth for British retailers, but it was also considered the toughest overseas market to break. British supermarket chain Tesco found out firsthand the difficulty of attempting to break the American market. Pre-packaged, fast-food meals have been a staple product on the shelves of British grocery chains for years, and the research, Tesco believed, seemed to suggest this could work among U.S. consumers. However, a lack of familiarity with this style of eating, the onset of the 2007 depression when Tesco’s “Fresh & Easy” chain launched, and the higher associated costs in comparison to buying fresh produce ultimately resulted in a failed $1.8 billion gamble when Tesco withdrew from the market in 2013.

The notable failure of Tesco is a stark reminder of the potential pitfalls for British retailers looking to expand into the U.S. market. While there is clear admiration for the quality and culture of British brands, any decision a British business makes in deciding to jump over the Atlantic should be highly researched and strategized. Any brand looking to break into a new international market should build their decision on a solid foundation of research, with some key research criteria identified below:

  • Identify a target market: The world is a big place. With over 200 possible markets, identifying the correct target market is critical. How have previous brands fared when venturing into new potential markets? How do exports fair? What are the current economic conditions, and do these favor new entries into the market?
  • Market conditions: GDP growth, birth rate, employment rate, and inflation rate—all of these are among a variety of macro-level economic indicators that can help gauge market condition.
  • Opportunity: Is there identifiable demand for your product in the market, and do consumers have a familiarity with your offering? Is the market existing and mature, or is it in its infancy?
  • Consumer preferences: While consumers can appear to share certain elements of cultural identity, this does not necessarily mean that they share the same purchase and consumption culture. Pret a Manger has understood this, adapting its style of service and menu for the U.S., where its coffee is self-serve, unlike the Barista approach taken in Britain.  
  • Competitive situation and positioning: Understanding the competitive situation and brand positioning of competitors can help you gauge how to uniquely position your brand to acquire market share. British brands seeking to enter the U.S., for example, can leverage perceptions of heritage and quality to command a greater price premium, but must emphasize its position and point of difference in ways that meet consumer needs.
  • Market sizing and growth potential: Have we identified our target market? Are we confident there is an opportunity? Do we have an idea of the kind of consumer we could attract and where our brand sits? Do we understand the current competitive landscape and current levels of competitor usage? Knowing the answers to these questions when entering a new market requires a market sizing task to understand the financial opportunity or return on investment. 

There has been a lot of buzz in the CMB office recently around the Boston debut of low-priced fashion retailer Primark (which is only about a half mile walk from the office). This is a hugely successful and cult brand in the U.K., but time will tell if the Irish retailer has effectively researched and gauged its ability to seduce the American consumer with its own brand of discount fashion, or whether, like many before it, they have underestimated the difficulty of breaking the U.S. market.

Josh is a Project Manager at CMB. Having recently entered the U.S. market himself, he is hoping his own brand of British fares better than Tesco’s.

We recently did a webinar on research we conducted with venture capital firm Foundation Capital on Millennials and investing. Insights include a Millennial segmentation, specific financial habits, and a look into the attitudinal drivers behind Millennials' investing preferences. 

Watch Here!

Topics: international research, brand health and positioning, market strategy and segmentation, retail research, growth and innovation

Millennial Women and Planning for the Future

Posted by Lori Vellucci

Wed, Jan 27, 2016

Millennials_investing.jpgMy first real job came with an important-sounding title (Project Director) and all the things grown-ups look for in a position, such as health insurance and a 401K. I was 22 and didn’t know anything about retirement plans; retirement itself seemed to be in the infinite distance. My dad told me, “It’s free money. You can’t turn it down,” so I dutifully enrolled in the company’s program. When I left that job for a bigger title and a better salary, I promptly liquidated my 401K and took the cash. Retirement still seemed really far away and besides, even with my important sounding title, the salary hadn’t been nearly as impressive. Receiving a paycheck just once a month had left me with a lot of credit card debt, and I thought paying that down might be a better use for the money I had painfully put into a 401K each month over the previous several years. 

Since that first step on the career ladder, I’ve enrolled in other retirement plans with other employers, opened a SEP when I worked for myself, and acquired other investment vehicles over the years. Even so, based on many articles I have read, I will likely never make up for not contributing and staying invested in those first early years. 

CMB recently conducted a thought-provoking, nationally representative study on Millennials and money, and I wondered what young women today are doing and if they’re smarter about retirement and investing than I was at 22.

According to our study, overall, women ages 21-30 are driven, idealistic, and interested in furthering their education—more so than their male counterparts.

table1.jpg

Many are confident that if they budget and plan well enough, they will be shielded from financial setback. Further, a plurality feel they will reach their long-term financial goals and the majority plan to have more than just their employer-sponsored retirement plan when it comes time to retire. Most of these young women feel confident that they are saving enough for their future! So far, so good.

Millennials_Investing2.jpg

But wait—nearly twice as many young women don’t feel confident making their own investing decisions compared to men, and more than four in ten feel they would invest more if they understood it better.

table3.jpg

While young men and women participate in an employee sponsored retirement plan at about the same rate, women are significantly less likely to own mutual funds, individual stocks, and to have their own brokerage account.

table4.jpg

Certainly, there has been a great deal of reporting on women’s reluctance to discuss financing and investing. Women often indicate feeling less confident in their knowledge, even as they tend to have lower risk portfolios, which perform just as well as those of male investors.

Traditional financial services investment firms have made efforts to tailor content and offerings to younger women, and websites like GoGirlFinance have also sprung up to fill a real void. But are these new sites reaching young women in a compelling and meaningful way? 

As co-author of our Millennials and Money study and partner at Foundation Capital, Rodolfo Gonzalez notes: “The financial services industry is at a critical juncture. We are seeing a lot of companies emerge to address the financial needs and expectations of the Millennial audience. The Millennial consumer expects a mobile, on-demand, simple, and useful user experience as they are the first digital natives. In the future, we can expect to see start-ups emerge to focus specifically on women and financial services.”

Even so, are they reaching young women in a compelling and meaningful way? A very good question.  Not wanting to rely just on our statistically meaningful, nationally representative study, I conducted an office poll...

They feel unprepared to invest on their own:

 “Not confident in my knowledge about investments; seems like a risk.”

“I have thought about trying it, but I feel uneducated on what would be a good investment. I would like to try to dive into investing on my own and experimenting with a small amount of money in the next few years.”

 “I am not at all confident in investing on my own. It is very foreign to me, so (although I feel like I probably should be) I just don’t do it.”

Further, closer-in priorities tended to over-shadow investing and saving for retirement:

“I am most focused on saving for my wedding and a house down the line.”

 “College debt is a huge one, I graduated with over $80,000 in debt, so that’s a huge hindrance to reaching some of my financial goals.”

“In addition to college debt, there’s my car payments, saving to buy a house/condo, and getting married in the next few years.”

 “My college debt is a concern, but mostly I just focus on my day to day expenses (rent, activities, and food). In my mind, any savings I have are designated for travel.”

Many of the young women in the office combine traditional banks with online tools like Mint or Personal Capital to manage their finances:

 “Currently I mainly manage my finances on a pen and paper ledger #oldchool but I check my accounts daily – Bank of America, Citizens, Capital One—and I log on to all loan platforms multiple times a month. I have used Mint before.”

“I use the app Mint to keep track of my finances. I also use apps for each savings/checking account I have (Bank of America, Charles Schwab, USAA) that I monitor.”

“Mint.com is great for monitoring all my accounts at once since it all pipes in, but not for budgeting. I just use Excel to actually manage my finances.”

While these women certainly have dreams of retirement in the abstract, for many it still feels very far away:

“Retirement is so far away for me right now—I just let my contributions go into my account automatically and hope that what I’m doing now will be enough and will be worth it when retirement time comes.”

 “What I’m contributing right now feels like it should be enough, but how can I know what will happen in the next ~50 years?”

“I wish I was more involved with my retirement and could a higher percentage of my paycheck, but I know I’ll have that chance down the line, so I’m not worried right now.”

It’s clear financial service providers, both traditional banks and start-ups, have a lot of work to do to educate, motivate, and inspire young women investors. 

Want to learn more about Millennials’ financial needs and expectations as well as what that means for your industry?

Watch our webinar!

Lori Vellucci is an Account Director at CMB.  She spends her free time purchasing ill-fated penny stocks and learning about mobile payment solutions from her Gen Z daughters.

Topics: financial services research, millennials, Consumer Pulse, webinar

A Data Dominator’s Guide to Research Design…and Dating

Posted by Talia Fein

Wed, Jan 20, 2016

people_on_date.jpgI recently went on a first date with a musician. We spent the first hour or so talking about our careers: the types of music he plays, the bands he’s been in, how music led him to the job he has now, and, of course, my unwavering passion for data. Later, when there was a pause in the conversation, he said: “so, do you like music?”

Um. . .how was I supposed to answer that? There was clearly only one right answer (“yes”) unless I really didn’t want this to go anywhere. I told him that, and we had a nice laugh. . .and then I used it as a teaching opportunity to explain one of my favorite market research concepts: Leading Questions.

According to Tull and Hawkins’ Marketing Research: Measurement and Method, a Leading Question is “a question that suggests what the answer should be, or that reflects the researcher’s point of view. Example: “Do you agree, as most people do, that TV advertising serves no useful purpose?”

In writing good survey questions, we need to give enough information for the respondent to fully answer the question, but not too much information that we give away either our own opinions or the responses we expect to hear. This is especially important in opinion research and political polling when slight changes in word choice can create bias and impact the results. For example, in their 1937 poll, Gallup asked, “Would you vote for a woman for President if she were qualified in every other aspect?” This implies that simply being a woman is a disqualification for President. (Just so you know: 33% answered “Yes.”) Gallup has since changed the wording—“If your party nominated a generally well-qualified person for President who happened to be a woman, would you vote for that person?”—and the question is included in a series of questions in which “woman” is replaced with other descriptors, such as Catholic, Black, Muslim, gay, etc. Of course, times have changed, and we can’t know exactly how much of the bias was due to the leading nature of the question, but 92% answered “Yes” as recently as June 2015.

The ordering of questions is just as important as the words we choose in specific questions. John Martin (Cofounder and Chairman of CMB, 1984-2014) taught us the importance—and danger—of sequential bias. In writing a good questionnaire, we’re not only spitting out a bunch of questions and receiving responses—we’re taking the respondent through a 15 (or 20 or 30) minute journey, trying to get his/her most unbiased, real, opinions and preferences. For example, if we start a questionnaire by showing a list of brands and asking which ones are fun and exciting, and then ask unaided which brands respondents know of, we’re not going to get very good data. Just like if we ask a person whether he/she likes music after talking for an hour about the importance of music in our own lives, we might get skewed results.

One common rule when it comes to questionnaire ordering is to ask unaided questions before aided questions. Otherwise, the aided questions would remind respondents of possible options—and inflate their unaided answers. A couple more rules I like to keep in mind:

  1. Start broad, then go narrow: talk about the category before the specific brand or product.

Remember that the respondent is in the middle of a busy day at work or has just put the kids to bed and has other things on his/her mind. The introductory sections of a questionnaire are as much about screening respondents and gathering data as they are about getting the respondent thinking about the category (rather than what to make for the kids’ lunch tomorrow).

  1. Think about what you have already told the respondent: like a good date, the questionnaire should build.

In one of my recent projects, after determining awareness of a product, we measured “concept awareness” by showing a short description of the product to those who had said they were NOT aware of it and then asking them if they had heard of the concept. Later on in the questionnaire, we asked respondents what product features they were familiar with. For respondents who had seen the concept awareness question (i.e., those who hadn’t been fully aware), we removed the product features that had been mentioned in the description (of course, the respondent would know those).

  1. When asking unaided awareness questions, think about how you’re defining the category.

“What Boston-based market research companies founded in 1984 come to mind?” might be a little too specific. A better way of wording this would simply be: “What market research companies come to mind?” Usually thinking about the client’s competitive set will help you figure out how to explain the category.

So, remember: in research, just as in dating, what we put out (good survey questions and positive vibes) influences what we get back.

Talia is a Project Manager on CMB’s Technology and eCommerce team. She was recently named one of Survey Magazine’s 2015 Data Dominators and enjoys long walks on the beach.

We recently did a webinar on research we conducted in partnership with venture capital firm Foundation Capital. This webinar will help you think about Millennials and their investing, including specific financial habits and the attitudinal drivers of their investing preferences.

Watch Here!

Topics: methodology, research design, quantitative research

My Data Quality Obsession

Posted by Laurie McCarthy

Tue, Jan 12, 2016

3d_people_in_a_row.jpgYesterday I got at least 50 emails, and that doesn’t include what went to my spam folder—at least half of those went straight in the trash. So, I know what a challenge it is to get a potential respondent to even open an email that contains a questionnaire link. We’re always striving to discover and implement new ways to reach respondents and to keep them engaged: mobile optimization is key, but we also consider incentive levels and types, subject lines, and, of course, better ways to ask questions like highlighter exercises, sliding scales, interactive web simulations, and heat maps. This project customization also provides us with the flexibility needed to communicate with respondents in hard-to-reach groups.

Once we’ve got those precious respondents, the question remains: are we reaching the RIGHT respondents and keeping them engaged? How can we evaluate the data efficiently prior to any analysis?

Even with the increased methods in place to protect against “bad”/professional respondents, the data quality control process remains an important aspect of each project. We have set standards in place, starting in the programming phase—as well as during the final review of the data—to identify and eliminate “bad” respondents from the data prior to conducting any analysis.

We start from a conservative standpoint during programming, flagging respondents who fail any of the criteria in the list below. These respondents are not permanently removed from the data at this point, but they are categorized as an incomplete and are reviewable if we feel that they provide value to the study:

  • “Speedsters”Respondents who completed the questionnaire in 1/5 of the overall median time or less. This is applied to evaluate the data collected after approximately the first 20% or 100 completes, whichever is first.
  • “Grid Speedsters”:When applicable, respondents who, for two or more grids of ten or more items, has a grid speed less than 2 standard deviations from the mean for the grid. Again, this is applied after approximately the first 20% or 100 completes, whichever is first.
  • “Red-Herring”We incorporate a standard scale question (0-10), which is programmed at or around the estimated 10-minute mark in the questionnaire, asking the respondent to select a number on the scale. Respondents who do not select the appropriate number are flagged.

This process allows us to begin the data quality review during fielding, so that the blatantly “bad” respondents are removed prior to close of data collection.

However, our process extends to the final data as well.  After the fielding is complete, we review the data for the following:

  • Duplicate respondents: Even with unique links and passwords (for online), we review the data based on the email/phone number provided and the IP Address to remove respondents who do not appear to be unique.
  • Additional speedsters: Respondents who completed the questionnaire in a short amount of time. We take into consideration any brand/product rotation as well (evaluating one brand/product would take less time than evaluating several brands/products). 
  • Straight-liners: Similar to the grid speeders above, we review respondents who have selected only one value for each attribute in a grid. We flag respondents who have straight-lined each grid to create a sum of “straight-liners.” We review this metric on its own as well as in conjunction with overall completion time. The rationale being that if respondents are only selecting one value throughout the questionnaire and appear in the straight-lining flag, these individuals will also have sped through the questionnaire.
  • Inconsistent response patterns: In grids, we can sometimes have attributes that would use the reverse scale, and we review those to determine if there are contradictory responses. Another example might be a respondent who indicates he/she uses a specific brand, and, later in the study, the respondent indicates that he/she is not aware of that brand.

While we may not eliminate respondents, we do examine other factors for “common sense”:

  • Gibberish verbatims: Random letters/symbols or references that do not pertain to the study across each open ended response
  • Demographic review: Review of the demographic information to ensure that they are reasonable and in line with the specifications of the study

As part of our continuing partnership with panel sample providers, we provide them with the panel ID and information of those respondents who have failed our quality control process. In some instances, in which the client or the analysis require that certain sample sizes are collected, this may also necessitate replacing bad respondents. Our collaboration allows us to stand behind the quality of the respondents we provide for analysis and reporting, while also meeting the needs of our clients in a challenging environment.

Our clients rely on us to manage all aspects of data collection when we partner with them to develop a questionnaire, and our stringent data quality control process ensures that we can do that plus provide data that will support their business decisions. 

Laurie McCarthy is a Senior Data Manager at CMB. Though an avid fan of Excel formulas and solving data problems, she has never seen Star Wars. Live long and prosper.

We recently did a webinar on research we conducted in partnership with venture capital firm Foundation Capital This webinar will help you think about Millennials and their investing, including specific financial habits and the attitudinal drivers of their investing preferences.

Watch Here!

 

Topics: Chadwick Martin Bailey, methodology, data collection, quantitative research

Making Your Brand a Habit: Why Small Patterns of Behavior Make a Huge Difference

Posted by Hannah Russell

Wed, Jan 06, 2016

Decision.jpgMost of us have heard the phrase “humans are creatures of habit,” but have you really ever sat down and thought about how habits dictate your life? From the moment you get up in the morning, habits are playing a role in how you interact with others, complete everyday tasks, and function within your environment.

In a lot of ways, habits are a necessary part of human life. Our brains naturally seek out and latch on to routines and scripts—it’s how we’re able to work so efficiently. Unfortunately, habits can also be unhealthy or unproductive. Oftentimes, we even have habits that are completely invisible to us until we take the time to truly examine our patterns of behavior.

I recently starting thinking a lot about this after picking up The Power of Habit by Charles Duhigg. His book details the formation of habits and neurological systems at play, colored by examples from scientists, academics, and businesses. Duhigg explains that by breaking down a habit loop into the cue, routine, and reward components, we are able to experiment and focus in on how a particular habit functions. He cautions that his book isn’t necessarily a secret formula for immediately dropping your afternoon cookie habit, but it does provide you with the necessary knowledge to start identifying which levers to adjust.

The notion that we can take our patterns of behavior and use that information to improve our personal life or business is one that really stuck with me as a market researcher. After all, as a researcher, I am constantly keeping an eye out for patterns. Patterns within and across datasets, patterns in response styles, and patterns within an industry. Patterns (or lack thereof) are often drawn upon for insight, as they tend to be a good indication if something is going right (or wrong), expected (or unexpected), or reflecting larger changes within the economy, company, or brand. This is often why businesses invest in tracking studies—a small shift in NPS or brand awareness may not seem overly interesting quarter to quarter, but it’s often part of a larger trend happening in the data. Patterns tell us a story and direct our attention to areas that we may need to investigate further.

At CMB, we spend a lot of time looking at these larger patterns and studying consumer habit loops that can impact a business. Companies looking to increase loyalty want to make their brand part of a customer’s routine—automatic and hard to disrupt.

For example, let’s imagine you’re going to pay for your groceries. Which credit card do you choose? Is it the one you always use for groceries? Do you even think about reaching for another payment method? Here’s the breakdown:

  • Cue: You’re at the register, and it’s time to pay.
  • Routine: You grab the card you always use since it earns you extra points for groceries.
  • Reward: You have your groceries, and you have earned bonus points.

By understanding these habit loops, we can begin to experiment with ways to make the cue stronger, the routine easier, or the reward more rewarding. We can also begin to understand what doesn’t work well when building brand loyalty and how these habits can be disrupted. At CMB, we’ve developed a method of segmenting on these habit loops, and each loop is linked to important outcomes such as NPS or database spend. We answer:

  • What are our client’s consumers’ habits?
  • If/how do these habits differ by consumer segments?
  • How well does each habit help drive business results?

These answers help our clients develop new strategies for reinforcing positive habits and disrupting ones that work against business goals. The takeaway: habits matter. Whether you’re looking in from an organizational or an individual perspective, these small patterns of behavior can play a huge role in both our successes and failures. 

Hannah is an Associate Researcher for CMB and is still working on transforming her coffee habit.

For the latest Consumer Pulse reports, case studies, and conference news, subscribe to our monthly eZine.

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Topics: strategy consulting, business decisions, consumer insights, brand health and positioning, customer experience and loyalty

The CMB Blog 2015: 6 of Our Favorites

Posted by Kirsten Clark

Wed, Dec 30, 2015

chaos_vs_clarity_light_bulb.jpgWe run this blog a little differently than other corporate blogs—instead of relying on a few resident bloggers—each of our employees writes at least one post a year. This means you get a variety of perspectives, experiences, and opinions on all aspects of market research, analytics, and strategy consulting from insights professionals doing some pretty cool work.

Before we blast into 2016, we wanted to reflect on our blog this past year by taking a second look at some of our favorite posts:

  1. This year, we launched a market research advice column—Dear Dr. Jay. Each month, our VP of Advanced Analytics, Jay Weiner, answers reader-submitted questions on everything from Predictive Analytics to Connected Cows. In the post that started it all, Dr. Jay discusses one of the hottest topics in consumer insights: mining big data.
  2. Research design and techniques are two of our favorite blog topics. A member of our Advanced Analytics team, Liz White, wrote a great piece this year about conjoint analysis. In her post, she shares the 3 most common pitfalls of using this technique and ways to get around them. Read it here.
  3. In June we launched EMPACTSM— our emotional impact analysis tool. In our introductory blog post to this new tool, CMB’s Erica Carranza discuss the best way to understand how your brand our product makes consumers feel and the role those feelings play in shaping consumers’ choices. Bonus: Superman makes a cameo. Check it out.
  4. Isn’t it great when you can take a topic like loyalty and apply it to your favorite television show? Heidi Hitchen did just that in her blog post this year. She broke down the 7 types of loyalty archetypes by applying each archetype to a character from popular book seriesA Song of Ice and Fire and hit HBO TV series Game of Thrones. Who’s a “True Loyal”? A “Captive Loyal”? Read to find out!
  5. Our Researcher in Residence series is one of our favorite blog features. A few times a year, we sit down with a client to talk about their work and the ideas about customer insights. Earlier this year, our own Judy Melanson sat down with Avis Budget Group’s Eric Smuda to talk about the customer experience, working with suppliers, and consumer insights. Check it out.
  6. We released a Consumer Pulse report earlier this year on mobile wallet use in the U.S. To deepen our insights, we analyzed unlinked passive mobile behavioral data alongside survey-based data. In this post, our VP of Technology and Telecom, Chris Neal, and Jay Weiner, teamed up to share some of the typical challenges you may face when working with passive mobile behavioral data, and some best practices for dealing with those challenges. Read it here.

What do you want us to cover in 2016? Tell us in the comments, and we look forward to talking with you next year!

Kirsten Clark is CMB’s Marketing Coordinator. She’ll be ringing in the New Year by winning her family’s annual game of Pictionary.

Topics: strategy consulting, advanced analytics, consumer insights

Black Friday Is Dead…Long Live Black Friday

Posted by Megan McManaman

Tue, Dec 22, 2015

retail2.pngIf you noticed the annual coverage of Black Friday shoppers seemed somewhat muted this year, you weren’t imagining things. While Cyber Monday sales were the highest since its debut in 2005, Black Friday sales were at their lowest since 2011. We all know how many elves flew (or didn’t) off the shelves, but to learn more about consumer holiday shopping behaviors, we partnered with Research Now for a quick survey of smartphone owners, ages 18 and up. 

Does 2015 mark the end of Black Friday—retail’s highest and holiest holiday? One retailer, REI, even opted out of this year’s Black Friday altogether, though their website did allow shoppers to make purchases online. The 87% of respondents who reported shopping on Black Friday might suggest that its imminent death is exaggerated. But the 81% of those Black Friday shoppers who did at least some of their shopping online suggest the explosion of ecommerce may have circumscribed the usual Black Friday frenzy.   

And then we have mobile—2015 marked the introduction of app-only deals from retail giants Amazon, Walmart, and Target. Of respondents who did shop from their smartphone or tablet, on either Black Friday or Cyber Monday, a full 27% purchased through an app. Still, a Cyber Monday dominated by in-app sales may be a few years away—61% of the Black Friday and Cyber Monday online shoppers used a PC to make their purchases. 

Need further evidence that online shopping and mobile technology are disrupting the traditional holiday shopper customer journey? “Just” 67% of Black Friday deal-seekers said they actually braved a brick and mortar store—this on a day once defined by the in-store experience. Is nothing sacred? 

Megan is CMB’s Senior Product Marketing Manager. She can’t stand Christmas music and was once visited by 3 ghosts. 

Topics: technology research, mobile, retail research, customer journey

Dear Dr. Jay: Can One Metric Rule Them All?

Posted by Dr. Jay Weiner

Wed, Dec 16, 2015

Hi Dr. Jay –

The city of Boston is trying develop one key measure to help officials track and report how well the city is doing. We’d like to do that in house. How would we go about it?

-Olivia


DrJay_desk-withGoatee.pngHi Olivia,

This is the perfect tie in for big data and the key performance index (KPI). Senior management doesn’t really have time to pour through tables of numbers to see how things are going. What they want is a nice barometer that can be used to summarize overall performance. So, how might one take data from each business unit and aggregate them into a composite score?

We begin the process by understanding all the measures we have. Once we have assembled all of the potential inputs to our key measure, we need to develop a weighting system to aggregate them into one measure. This is often the challenge when working with internal data. We need some key business metric to use as the dependent variable, and these data are often missing in the database.

For example, I might have sales by product by customer and maybe even total revenue. Companies often assume that the top revenue clients are the bread and butter for the company. But what if your number one account uses way more corporate resources than any other account? If you’re one of the lucky service companies, you probably charge hours to specific accounts and can easily determine the total cost of servicing each client. If you sell a tangible product, that may be more challenging. Instead of sales by product or total revenue, your business decision metric should be the total cost of doing business with the client or the net profit for each client. It’s unlikely that you capture this data, so let’s figure out how to compute it. Gross profit is easy (net sales – cost of goods sold), but what about other costs like sales calls, customer service calls, and product returns? Look at other internal databases and pull information on how many times your sales reps visited in person or called over the phone, and get an average cost for each of these activities. Then, you can subtract those costs from the gross profit number. Okay, that was an easy one.

Let’s look at the city of Boston case for a little more challenging exercise. What types of information is the city using? According to the article you referenced, the city hopes to “corral their data on issues like crime, housing for veterans and Wi-Fi availability and turn them into a single numerical score intended to reflect the city’s overall performance.” So, how do you do that? Let’s consider that some of these things have both income and expense implications. For example, as crime rates go up, the attractiveness of the city drops and it loses residents (income and property tax revenues drop). Adding to the lost revenue, the city has the added cost of providing public safety services. If you add up the net gains/losses from each measure, you would have a possible weighting matrix to aggregate all of the measures into a single score. This allows the mayor to quickly assess changes in how well the city is doing on an ongoing basis. The weights can be used by the resource planners to assess where future investments will offer the greatest pay back.

 Dr. Jay is fascinated by all things data. Your data, our data, he doesn’t care what the source. The more data, the happier he is.

Topics: advanced analytics, Boston, big data, Dear Dr. Jay