Voices: the CMB Blog

A career in market research can make you pretty sensitive to advertising. An ineffective commercial can make me throw up my hands wondering how it got on air; a great one makes me appreciate all the work that went into making it. Recently, I got to see a behind the scenes example of what goes into a memorable ad campaign in CMB’s work with Aflac.

I expect you’re familiar with Aflac’s Duck, the be-feathered icon has appeared in the brand’s commercials since 1999 and his signature quack is instantly recognizable.  But Aflac faced a challenge, people knew The Duck, but they weren’t sure what he wanted them to do, or much about the company he represented.  To address this branding challenge Aflac needed to educate the market about their products, differentiate themselves from the competition, all while keeping The Duck in the picture.

CMB worked with Aflac, to conduct an innovative brand positioning study using discrete choice. The study allowed the team to:

• Identify the unique needs of  three target audiences: consumers, employers, and brokers

• Identify how specific changes to elements of brand positioning affected each group’s desire to learn more about Aflac, leading to the development of  a user friendly simulator for the brand and their agency

• Deliver optimized brand positioning specifying value statements, how to address audience goals, emotional and functional benefits, and the most compelling proof points.

The results helped guide Aflac and their agency to create ads that let customers get to know the company behind The Duck. Take a look at one of the ads that has gotten nearly 350,000 views on YouTube.

Want to learn more? Join us for a Webinar on March 7^th to hear CMB’s Rich Schreuer and Aflac’s Missy Wood share how CMB helped Aflac use the power of discrete choice to reposition their brand. Register here

Posted by Megan McManaman, Megan is the Content Marketing Manager at CMB. She enjoys watching and  parsing ads but draws the line at the ones with talking babies. Follow her on Twitter at @Megz79.

During a recent social media webinar, the question was raised “How do we convince clients that social media is statistically significant?”  After an involuntary groan, this question brought two things to mind:

• There are a lot of people working in social media research who do not understand the fundamentals of market research; and

• Why would anyone want to apply significance testing to social media data?

Apparently, there’s much debate in online research forums about whether significance testing should be applied to social media data.  Proponents argue that online panels are convenience samples and significance testing is routinely applied to those research results – so why not social media?  Admittedly that is true, but the ability to define the sample population and a structured data set should provide some test/retest reliability of the results.  It’s not a fair comparison.

I’m all for creative analysis and see potential value in sig testing applied to any data set as a way to wade through a lot of numbers to find meaningful patterns.  The analyst should understand that more things appear to be significant with big data sets so it might not be a useful exercise for social media.  Even if it can be applied, I would use it as a behind-the-scenes tool and not something to report on.

Anyone who has worked with social media data understands the challenging, ongoing process of disambiguation (removing irrelevant chatter). There are numerous uncontrollable external factors including the ever-changing set of sites the chatter is being pulled from.  Some are new sites where chatter is occurring but others are new sites being added to the listening tool’s database.   Given the nature of social media data, how can statistical comparisons over time be valid?  Social media analysis is a messy business.  Think of it as a valuable source of qualitative information.

There is value in tracking social media chatter over time to monitor for potential red flags.  Keep in mind that there is lot of noise in social media data and more often than not, an increase in chatter may not require any action. 

Applying sig testing to social media data is a slippery slope.  It implies a precision that is not there and puts focus on “significant” changes instead of meaning.  Social media analysis is already challenging – why needlessly complicate things?

Cathy is CMB’s social media research maven dedicated to an “eyes wide open” approach to social media research and its practical application and integration with other data sources. Follow her on Twitter at @VirtualMR 

Social media research is still behind social media marketing in terms of getting past the hype.  Clearly there’s some overselling going on and more education is needed about how and when to effectively use social media data.  Some sales folks even go as far as suggesting social media listening can replace market research as a way to save money – without having the background or unbiased perspective needed to make such a suggestion. 

It’s time for researchers to have an open dialogue about social media data – warts and all.  What biases exist?  What steps are necessary to put the data in a truly usable form?  What are the best applications for social media analysis?  How can we best integrate it with other data sources?  I’m not going to try and tackle all these questions in this blog, but hopefully I can help stimulate discussion over time.

To put things in perspective, one must consider that typically only a fraction of social media chatter is worthwhile and relevant to your specific objectives. Keep in mind that the topic of interest for your social media analysis has a huge impact on how many “sound bites” you have to work with.  As you are pulling data, it can be a challenge to “disambiguate” (i.e., remove irrelevant chatter) and, in some instances, almost impossible.  Another challenge is that social media data is largely unstructured. Automatic coding isn’t optimal – especially if you plan to integrate the results with other data sources. 

Despite these challenges, there is no denying that it’s a valuable data source.  Having the ability to learn from chatter that is occurring naturally online and applying state-of-the-art technology to aggregating and analyzing this data is powerful stuff.   Social media analytic tools and text analytics are always evolving.   But even with the best social media listening tools and analysts available, social media listening cannot and should not be applied across all situations.  NO analytic tool or technique is a one-size-fits-all solution.   

Let’s put social media analysis in perspective across all of the tools, techniques, and data sources we have to work with.   Exciting things are on the horizon, but for now, let’s not expect (or promise) more than social media data can deliver.

Cathy is CMB’s social media research maven dedicated to an “eyes wide open” approach to social media research and its practical application and integration with other data sources. Follow her on Twitter at @VirtualMR

Check out our webinar Understanding B2B Social Media: An AMD Case Study and learn more about how Social Media Research is making a difference for our clients. Click here.

Seems like everywhere I turn I see a QR code. From product packaging to billboards in the airport, those funny little black and white designs are popping up all over—even on T shirts.  So we set out to ask consumers what they think about the 2D bar codes known as Quick Response or QR codes in our latest Consumer Pulse: Scan Me-9 Things To Know about Consumer Behavior and QR codes.

There is no doubt it’s a very cool tool brands and companies can use to engage and share information with consumers, but even the coolest  tools and applications need to provide meaningful information to be successful.  Just like Twitter, Facebook and other social media marketing tools it always comes back to insightful content that consumers will value. The success of QR codes will depend on the content behind the scan.

What do consumers think?  CMB partnered with iModerate Research Technologies to see why consumers scan QR codes and what they expect from the little black and white squares.

As a marketer here are a few facts that stood out to me. Watch This:

Nearly 1 in 5 who scanned a QR code made a purchase after scanning (Tweet this)

81% say they’ve seen a QR code, but only 21% knew what they were called (Tweet this)

Half of smartphone users have scanned a QR code (Tweet this)

70% of those who scanned QR codes, said it was very easy (Tweet this)

Results are mixed on QR codes' usefulness, 41% say the information they got was useful (Tweet this)

Magazines and newspapers are the most common QR source for those who’ve scanned a code (Tweet this)

46% of those who’ve scanned a QR code did so because they were curious (Tweet this)

We found smartphone owners and non-smartphone owners alike are curious about QR codes for information and for discounts, free gifts and exclusive deals, and they find the process of scanning to be really easy. But as more and more consumers get smartphones and the ability to scan, marketers must go beyond the novelty of the application if they expect customers to scan again and make it a regular part of the purchase process.

I’d love to know, are QR codes part of your 2012 marketing plan? Will QR codes gain steam in 2012 or fizzle out?

Download the full report here.

Posted by Kristen Garvey. Kristen is CMB's VP of Marketing, a mom of two, and thinks QR codes  can be as useful as the content behind them, and that they will have their place in the marketing toolbox for 2012.

In this month’s “John’s Corner,” John discusses the limits of benchmarking and its alternatives with CMB's Megan McManaman.

MM: Today we’re discussing a topic that you feel strongly about, the misuse of benchmarking in marketing. Can you tell us what benchmarking is and how it’s used?

JM: Before we get too far along, I want to make it clear that benchmarking is a process aimed at enabling you to become the best through improvements.  It is not a score. Often benchmarking is used poorly in marketing, with too much emphasis on standardized “descriptive” scores. Yes, a comparative score is useful in raising a red flag, but then what should you do for success?  Unfortunately, there are third parties that don’t just offer comparative scores, but encourage you to meet or exceed this score using a diagnosis based on a “standard” set of externally generated criteria.  By focusing on the gaps between you and your competition you are assuming you can become the “best” by essentially copying competitors using criteria. In reality that will actually ensure you will not become distinctive. 

MM: I can see why a “best in class” company might not want to focus on standardized competitor scores, but what about the fifth ranked company, the tenth?

JM: For companies somewhere in the middle I also consider it unlikely they will gain a notable market advantage by closing the gap with higher score competitors.  In fact it could be quite detrimental. A focus on scores using standard measures will obscure what makes your company unique and distinctive.  It is your commitment to innovation that will better your performance and market standing, leading to improved financial performance. Apple does this well. They are a company committed to being distinctive: they would hardly be where they are today by copying others.

MM: It strikes me that this has been a fundamental problem with how benchmarking has been used in marketing from the beginning, is it particularly problematic now?

JM: Yes, it’s true. People are acquiring information differently and at faster rates, and it is not just because of the internet. The myopia that comes with focusing on standard benchmarking scores and gaps is particularly dangerous for companies in a marketplace saturated with a broader set of competitors. In part because people travel more widely, and information is not centralized, there are very few companies that are the “only game in town” and that number will grow fewer. So benchmarking as a process striving for distinctiveness will become even more important.

MM: Could you help me understand what a diagnostic approach aimed at distinctiveness looks like?

JM: Remembering that benchmarking is a process, the essential nature of a best practice is diagnostic: functionally and in what is produced.  In marketing we must aim at a holistic perspective due to the interconnectivity of all the strategic and tactical elements, and also the growing relationship to operations or value delivery.  So, the “diagnostic approach” recognizes the need to know what your competitors are doing, but rather than scoring yourself in comparison, you customize systems and methodologies directly relevant to your unique organization that focus on what will both help you stand out in the marketplace and improve your efficiency.

A process with a customized diagnostic approach allows both small and large companies to account for emerging challenges and opportunities, and be more nimble and distinctive in the face of these changes than companies that focus more on comparative standards.  Innovation and distinctiveness are more important than ever, and a custom diagnostic approach reveals these in a way that a competitive descriptive score based benchmarking cannot.

Download the full conference presentation here: The Perils of Benchmarking 10 things to consider when deciding how you should benchmark against the market.

So what do you think? Does benchmarking stifle innovation? does it encourage marketers to "keep up with the Joneses?"