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 series A 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: Strategic 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, Mobile, Retail, 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

Star Wars Marketing: Full Light Speed Ahead

Posted by Julia Powell

Thu, Dec 10, 2015

Star_Wars_The_Force_Awakens-1.jpgUnless you have been living in exile on the swampy planet Dagobah, you may have noticed that December 18th marks the release of Star Wars: The Force Awakens. There are reminders in every corner of the consumer landscape from Chewbacca Spiced Latte Coffeemate peering out of the dairy freezer to Limited Edition Star Wars lipsticks from Covergirl (including silver and gold but not Chewbacca). Star Wars-licensed clothing abounds from discount retailer Primark to The Gap and more. There are Star Wars shoes available ranging from Crocs (complete with Yoda-sound emitting add-ons) to customizable Superstar 80s from Adidas.

Of course, there are toys, too, featuring characters from the previous films and The Force Awakens. These were launched in grand fashion with “Force Friday,” which took place on September 4th 2015 (falling conveniently ahead of the back-to-school and holiday shopping seasons). There have been three months of merchandise build up, with more character items set to be released after the full plot of the film is revealed. While witnessing the amazing treasure trove of merchandise and brand tie-ins, I couldn’t help but wonder, how did LucasFilm’s promotion of the first film compare to Disney’s current efforts with The Force Awakens?

A long time ago (38 years) in a galaxy far, far away, the first Star Wars installment opened on May 25th in just 32 theatres. Initially marketed only to a small science fiction fanbase, momentum grew as the film received positive reviews and word of mouth spread. By August 1977, the movie was on over 1,000 screens. The film itself appealed to children and adults, and it featured ground-breaking 4 channel Dolby sound, adding to the overall cinematic impact (and audiences’ desire to repeatedly return to the theater). It dominated the box office in 1977, grossing over $461 million dollars domestically (over $300 million ahead of another sci-fi classic: Close Encounters of the Third Kind). To put this in perspective: that’s over 1.85 billion when adjusted for ticket price inflation.

 By Christmas 1977, Kenner Products, which held the original licensing rights to Star Wars action figures, was underprepared to meet the production demand the surprise sensation. What was a toy retailer to do when faced with the inability to deliver the characters every kid (and some adults) wanted? Easy: sell empty boxes. Ahead of the holiday shopping season, Kenner cleverly sold “Early Bird Certificate Packages,” including a certificate for action figures (available in February 1978), a diorama stand, and a Star Wars fan club membership card. Waiting to redeem those certificates must have been agony.

When Star Wars was first released, there was nothing else quite like it, and there was no way to anticipate the film’s success nor the audience’s desire for merchandise. With The Force Awakens, Disney knows its audience and has guaranteed there are enough items available to drive interest ahead of the film. There’s also enough stock on the shelves as families head to the theaters (in sharp contrast to Disney’s 2014 Frozen toy shortages). On top of the items available ahead of the release, there are several characters yet to be revealed, including Andy Serkais’ Supreme Leader Snoke, which means that there’s even more to come.

Have you ever waited in line for a pre or post-release movie toy? Will you be headed out to see The Force Awakens sporting any character socks?

An Associate Researcher and owner of a now vintage, non-mint condition Ewok village Julia Powell is. 

Topics: Marketing Strategy, Media & Entertainment Research, Retail

Say Goodbye to Your Mother’s Market Research

Posted by Matt Skobe

Wed, Dec 02, 2015

evolving market researchIs it time for the “traditional” market researcher to join the ranks of the milkman and switchboard operator? The pressure to provide more actionable insights, more quickly, has never been so high. Add new competitors into the mix, and you have an industry feeling the pinch. At the same time, primary data collection has become substantially more difficult:

  • Response rates are decreasing as people become more and more inundated with email requests
  • Many among the younger crowd don’t check their email frequently, favoring social media and texting
  • Spam filters have become more effective, so potential respondents may not receive email invitations
  • The cell-phone-only population is becoming the norm—calls are easily avoided using voicemail, caller ID, call-blocking, and privacy managers
  • Traditional questionnaire methodologies don’t translate well to the mobile platform—it’s time to ditch large batteries of questions

It’s just harder to contact people and collect their opinions. The good news? There’s no shortage of researchable data. Quite the contrary, there’s more than ever. It’s just that market researchers are no longer the exclusive collectors—there’s a wealth of data collected internally by companies as well as an increase in new secondary passive data generated by mobile use and social media. We’ll also soon be awash in the Internet of Things, which means that everything with an on/off switch will increasingly be connected to one another (e.g., a wearable device can unlock your door and turn on the lights as you enter). The possibilities are endless, and all this activity will generate enormous amounts of behavioral data.

Yet, as tantalizing as these new forms of data are, they’re not without their own challenges. One such challenge? Barriers to access. Businesses may share data they collect with researchers, and social media is generally public domain, but what about data generated by mobile use and the Internet of Things? How can researchers get their hands on this aggregated information? And once acquired, how do you align dissimilar data for analysis? You can read about some of our cutting-edge research on mobile passive behavioral data here.

We also face challenges in striking the proper balance between sharing information and protecting personal privacy. However, people routinely trade personal information online when seeking product discounts and for the benefit of personalizing applications. So, how and what’s shared, in part, depends on what consumers gain. It’s reasonable to give up some privacy for meaningful rewards, right? There are now health insurance discounts based on shopping habits and information collected by health monitoring wearables. Auto insurance companies are already doing something similar in offering discounts based on devices that monitor driving behavior.

We are entering an era of real-time analysis capabilities. The kicker is that with real-time analysis comes the potential for real-time actionable insights to better serve our clients’ needs.

So, what’s today’s market researcher to do? Evolve. To avoid marginalization, market researchers need to continue to understand client issues and cultivate insights in regard to consumer behavior. To do so effectively in this new world, they need to embrace new and emerging analytical tools and effectively mine data from multiple disparate sources, bringing together the best of data science and knowledge curation to consult and partner with clients.

So, we can say goodbye to “traditional” market research? Yes, indeed. The market research landscape is constantly evolving, and the insights industry needs to evolve with it.

Matt Skobe is a Data Manager at CMB with keen interests in marketing research and mobile technology. When Matt reaches his screen time quota for the day he heads to Lynn Woods for gnarcore mountain biking.    

Topics: Data Collection, Mobile, Consumer Insights, Marketing Science, Internet of Things (IoT), Data Integration, Passive Data