Marketing Insights magazine: Jan/Feb 2015

January/February 2015 ama.org

Driving informed decisions and business value through analytics.

Generation Youth

A m e r i c a n m a r k e t i n g a s s o c i at i o n January/February 2015 ama.org

Driving informed decisions and business value through analytics.

Jan/Feb 2015 Volume 27 Number 1

Generation Youth

Driving informed decisions and business value through analytics.

AMA.org/MarketingInsights

contents

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features

30

The Metrics Map Using analytics to navigate metrics of substances versus metrics of convenience

24 cover story

36

Generation Youth MTV’s senior vice president of research and insights weighs in on the brand’s youth-focused insights strategy

departments

How social media insights inform—and improve—product development

03

By the numbers

Case in Point The State of Spam

04

Fast Track Nathaniel Lin

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THE ART OF CONVERSION A Panel for Every Purchase

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INSIGHTS MACHINE Lost in the B-to-B Time Warp

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The Big Picture Digital Footprints Abound

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IN CONTEXT The Social Game

18

Social Cues Creating Community

20

The Innovator Strategic Insights

22

Split Screen Cultural Collaboration

48

The New Innovation

42

k n ow l e dge b as e

Alan Gould from Instantly Inc. discusses panel management best practices

A m e r i c a n m a r k e t i n g a s s o c i at i o n

Jan/Feb 2015 | Vol. 27 | No. 1

Phone (800) AMA-1150 • Fax (312) 542-9001

American Marketing Association Ric Sweeney Chairperson of the AMA Board 2015-2015 Russ Klein AMA Chief Executive Officer | rklein@ama.org Dennis Dunlap AMA Chief Executive Officer Emeritus | ddunlap@ama.org Editorial Staff Mary M. Flory Editor | mflory@ama.org Melody Udell Managing Editor | mudell@ama.org Julie Davis Staff Writer | jdavis@ama.org art Kristina Zapata Art Director | kzapata@ama.org Vince Cerasani Graphic Designer | vcerasani@ama.org Advertising Staff Richard Ballschmiede Advertising Sales Director | rballschmiede@ama.org Catherine Eck Advertising Account Representative | ceck@ama.org Sally Schmitz Production Manager | sschmitz@ama.org Editorial board Greg Allenby, The Ohio State University’s Fisher College of Business Lynd Bacon, Loma Buena Associates and Northwestern University Chris Chapman, Google Inc. Jeffrey Hunter, Market Framework Inc. Michele Kessler, thinkThin

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marketing insights January/February 2015

A note from the editor Welcome Back to Marketing Insights.

Marketers and researchers alike cannot seem to escape the need to speak “millennial,” and few brands do it as successfully as MTV, which is winning over digital natives with the help of its growing research department. In our cover story Q&A on page 24, Jane Gould, MTV’s senior vice president of research and insights, explains why the network values “letting the data breathe,” how to achieve symmetry in research, and the advantages of being the disruptor versus being disrupted.

We address another ubiquitous challenge starting on page 30, where Christian Kugel, AOL’s vice president of consumer analytics and research, discusses success metrics, and how to distinguish between metrics of substance and metrics of convenience. And on page 36, Richard Shaw, a vice president at Brainjuicer Group, posits that social media insights can inform and improve product development, if business doesn’t get in the way.

Continuing this issue’s expert-level thought leadership, Justin De Graaf, global media insights director at The Coca-Cola Co., shares his top five social analytics fundamentals (page 18). Further, Nathaniel Lin retraces his data career from research scientist for the U.S. Air Force to chief customer insight officer at Attract China (page 6), where he helps U.S. brands leverage analytics to attract Chinese travelers.

All the best in 2015,

Mary M. F lory, e ditor mflory@ama.org

Bits and bytes

bn

Edited by Julie Davis

by the numbers

6 While mapping connections between Twitter users commenting on the same topic, researchers at Pew Research Center noticed that users conformed one of to six types of conversation structures.

25% By 2018, CIOs who have strong relationships with their company’s CMOs will drive a 25% improvement on ROI for marketing technology.

find out more at

85% According to research consultancy Vision Critical, 85% of social media updates come from enthusiasts— users who post five or more times per week—but those users only reflect 29% of a company’s social media audience.

$ 2.1 billion The global market for marketing analytics is expected to grow from $1.2 billion in 2014 to $2.10 billion by 2019, according to market research firm Research and Markets.

91.3% Among Americans age 12 and older, 91.3% listen to the radio each week, according to Nielsen’s 2014 State of the Media report.

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marketing insights January/February 2015

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CP Case in point

The State of Spam

Experts weigh in on how Canada’s recent anti-spam legislation is affecting e-mail marketing metrics and list management

By Julie Davis, staff writer  jdavis@ama.org

O

n July 1, 2014, e-mail marketing got a little more complicated. Canada rolled out the first stage of requirements for the Canadian Anti-Spam Legislation (CASL), marking the country as one of the last G20 nations to pass federal

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anti-spam legislation. But CASL, which experts deem as some of the strictest e-mail marketing legislation in the world, is not just an issue for Canadian marketers. Any marketer who sends promotional e-mails to Canadian consumers

needs to understand the legislation— and its effect on their digital marketing efforts, e-mail data sets and campaigngenerated insights.

The major difference between CASL and the U.S. anti-spam legislation, CANSPAM, which stands for Controlling the Assault of Non-Solicited Pornography and Marketing, is subscriber consent.

Under CASL, marketers can only send promotional e-mails to individuals who have expressed consent from their recipients. Under CAN-SPAM, however, marketers can send e-mails to any individual as long as they provide consumers the option to opt-out of the communications.

Case in Point

“What CASL doesn’t have—in the definition of a transactional message— versus what CAN SPAM does have is the 80/20 rule, or the primary purpose,” says Matt Vernhout, chief privacy officer and deliverability manager at Guelph, Ontario-based e-marketing agency Inbox Marketer Corp. and blogger at EmailKarma.net. CANSPAM allows 20% of a transactional electronic message to contain marketing messages, so long as it isn’t at the top of the message, but CASL does not. “Anything that has commercial content becomes a commercial message,” he says.

CASL has a staggered roll-out to allow marketers time to be in compliance.

As of July 1st, companies had to have at least obtained implied consent from consumers, which means that there must be an existing business or personal relationship between the sender and receiver. Actions such as downloading a webinar or purchasing a product are viable as implied consent. By 2017, marketers must show expressed consent from those contacts, typically obtained by sending those contacts an e-mail requesting that they opt in to the specific communications they would like to receive from the sender.

Even before CASL was enacted, obtaining implied consent from an e-mail marketing recipient was considered a best practice, Vernhout says. Yet many marketers who follow this practice don’t have the electronic paper trail to demonstrate where a contact came from and what kind of consent they’ve given.

Vernhout adds that those hardest hit by the new changes are companies that purchase third-party e-mail lists.

Studies show that as few as 14% of them have detailed records necessary to be

CASL compliant, and those working to gain compliance face an uphill battle to convince consumers to agree to receive promotional e-mails from unknown third parties, Vernhout says.

Many smaller businesses may need to invest in new technology in order to keep track of their electronic records, which requires that marketers be more stringent when using third-party lists, says Nathan Yerian, owner of Houstonbased inbound marketing agency Adhere Creative. Marketers must now make sure those third parties have good records and can demonstrate consent from their Canadian customers.

Cambridge, Mass.-based HubSpot is leveraging value-added content, such as free white papers or webinars, in exchange for receiving expressed consent. “We want to use this time to capture as many people as possible with express consent, and also be able to test different ways to be able to get that expressed consent,” says Ellie Mirman, HubSpot’s director of inbound marketing.

U.S.-based marketers also must decide whether or not to create separate communication processes for their Canadian customers. For HubSpot, it’s been worthwhile to segment out their customers based on the structure of their e-mail address (whether it’s .ca, .org, .com, etc.) or the location of their IP address. However, Yerian finds that, for most of his clients, it is better simply to make all of their electronic communications CASL compliant. “Sit down with [your] legal [department] to review past marketing activities and identify where you may have been in violation to make sure it’s not repeated,” Yerian says. For his clients, becoming compliant has drastically reduced the size of their subscriber lists but increased their quality, he says. “Just

because you have a 10,000-person list doesn’t mean you have 10,000 actively engaged e-mail recipients. Cleaning up and re-engaging has been the No. 1 most effective thing that we’ve done.”

So far, CASL hasn’t been a drastic change for most marketers already following industry best practices, Vernhout says. “There were a lot of companies, and it actually surprised me even after I found out about it, that had that ambiguous ‘I don’t know where I got the data from’ [answer], and they used the opportunity to actually clean up their lists prior to July 1st by sending an upgrade campaign,” he says. “On average, they saw anywhere from 3 to 20% reconfirmation on those names—pretty small, but what they ended up with was a pretty engaged list of people who had given them express consent.” Plus, CASL-compliant companies have fewer bounced e-mails, according to Vernhout.

According to Inbox Marketer Corp.’s 2014 e-mail marketing benchmarks, Canadian marketers now have a 0.6% bounce rate. “They’re becoming extremely clean in regards to who they are communicating with and who they’re selecting for communications,” he says.

Complying with the law will be a significant business expense for marketers and mean more stringent documentation practices, but it will enforce practices that follow industry trends toward a greater reliance on content marketing and more tightly targeted communication practices. “I don’t know if CASL is forcing any new insights, but I do think that it’s forcing cleaner lists and better list-management practices,” Vernhout says. “Therefore, you’ll end up with more engaged subscribers, which leads to that cycle of better deliverability, better ROI and better revenues.” mI marketing insights January/February 2015

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FT

Career highlights in 60 seconds

by Melody Udell

Fast Track

1982

2006-2007

Ph.D., environmental engineering

Partner, Director of Analytics

The University of Birmingham

“My experience taught me that at the end of the day, if it’s too complicated, you haven’t found the optimal solution yet.

It should be easily explainable and actionable.”

OgilvyOne

1983-1999 Research Scientist U.S. Air Force Research Laboratory, Hanscom Air Force Base

2009-2011

After 17 years researching advanced radar technologies and quantum qubit computing, Lin decided to apply his datamining and research skills to the business world, and enroll in an MBA program.

President of Advanced Analytics Aspen Marketing Services

Present 2000

President Analytics Consult

MBA MIT Sloan School of Management

2001-2005 Senior Manager of Marketing Intelligence and Head of Marketing Analytics IBM Asia Pacific

“I had spent many years already working in analyzing data and teasing out insights to make [a problem] simpler, solvable and actionable, which was useful when I became the head of analytics for IBM.”

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Nathaniel Lin Chief Customer Insight Officer, Attract China Nathaniel Lin started his career as a research scientist but took his skills to the business side just when Big Data and analytics were gaining traction. Now, the chief customer insight officer at Boston-based international marketing consultancy Attract China and author of Applied Business Analytics leverages his research background and analytics leadership to help U.S. brands engage Chinese consumers.

Present Chief Customer Insight Officer Attract China

Lin draws upon his data research background to help U.S. brands leverage analytics to attract Chinese travelers.

“We’re going out there with Big Data analytics and engaging them before they travel. …

We’re the matchmaker, the B-to-B-to-C sitting between the businesses and the consumers to hopefully form a lifelong loyal relationship between them.” mI

THE ART OF CONVERSION

SA M PLE RESEA RCH

A Panel for Every Purchase But which one to choose?

David Krajicek  david.krajicek@gfk.com

F

or years, marketing research focused on driving quality through quantity. We were all taught that in survey-based MR, increased sample sizes equal increased precision—assuming that we have developed and polled a representative sample of individuals.

When we talk about panels and research today, no topic could be more pertinent. The marketplace has been focused for a while on the efficient use of large amounts of sample research, driving business decisions with speed and efficiency. By now we should all recognize that we are living in a “realtime” world of consumer marketing, where the sheer variety of digital touch points demands nimbleness. This need for quickness, in the interest of avoiding costly errors, is top of mind for ROIminded marketers.

As I have observed in the past, rapidity for its own sake, in the absence of context and strategic focus, can lead you astray just as quickly as any slow-to-market approach to consumer understanding. A marketer can consult his or her dashboard dutifully every day, and take actions when the metrics shift, but if the calibration behind

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the dashboard is off-kilter, or the information feeding the dials has not been vetted, this marketer could be driving his brand into the ground. What roles do panels play in enabling rapid but accurate information to ensure sound decision-making?

Today, research panels come in all colors and shapes—small or huge, selective or broad, loosely knit or tightly managed. Working with an existing panel, instead of an ad hoc sample, should allow us to know more about our respondents (through profile surveys), achieve higher response rates and even save on incentives.

And different panels may be appropriate for different marketing goals. If my target audience is frequent business flyers who log 1 million travel miles a year, I may become very

focused and narrow in my sample search. Even if my target is slightly broader, such as households making $250,000 a year, issues of sample quality will likely give way to concerns about achieving participation among such a rarefied audience.

The most important context for any discussion of panel and research quality is to determine your goal. We hear a lot of talk these days about “fit for purpose”— seeking out the research approach that makes sense for a given set of priorities.

Where are your richest opportunities in the marketplace? Who should your target audience be? What is the information that you need about them to make critical decisions? Answer these questions first, and discussions of panel source and quality will follow naturally.

Of course, one of the priorities shaping many research approaches today is a shrinking consumer insights budget. In how many conference rooms, at any given moment, is a marketer saying, “And we need to find all of that out for under $50,000”?

In the most recent GreenBook Research Industry Trends (GRIT) report, research suppliers and buyers cited cost as the most important perceived concern driving the choice of data collection methods. But when asked what they, themselves, considered a top priority for choosing a methodology, researchers and buyers put data quality first among all considerations.

Marketers have a great deal of skin in the panel- and research-quality game, whether they know it or not, and they need to take more aggressive action to get the quality that they need.

What this says to me is that quality should still be a top concern, but it has to be in the context of the value provided to a research buyer and the business issue at hand. If no one cared anymore about claiming the mantle of quality, earned or otherwise, then our nagging worry about accuracy should turn to outright alarm. However, the GRIT figures show that while quality may be a concern, folks on both sides of the marketing and research table think that the other guy is pressuring them to do more with less.

Let’s be real: There is no business decision that is made without cost or potential ROI being a factor. Research quality in the corporate world has to

live within the inevitable context of what it costs and what it will gain. The question is: Are we perceiving the cost/ benefit tradeoffs correctly?

The disappointing fact is that within certain extreme bounds of believability, correct and incorrect numbers look the same on PowerPoint charts. It is rare, indeed, that a failed product can be directly traced to a given number on slide 37 of the marketer’s presentation deck from six months before. This may seem to give the industry a lot of breathing room when it comes to research approaches, but that would be a very dangerous conclusion.

It’s often said of marketers that we worry about the 80/20 rule. If I get 80%

of my objectives, I call myself happy, although I may not know whether I’ve accurately answered 80% of my questions.

But I think we need to focus on another ratio: the cost of research measured against the magnitude of the decisions it will be used to support, as well as the relative price of quality information.

I can tell you right now, with 99% certainty, that a $10,000 research investment should not be guiding a $50 million marketing decision. Call me a big spender, but it just should not be. This doesn’t necessarily mean that you need to drop $500,000—solid information can be available for much less. But cut-rate insights informing bigticket decisions are never a good idea. marketing insights January/February 2015

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Regardless of whether anyone revisits slide 37 of the marketer’s deck, it will still be he or she who is called to account when a product fails.

Marketers have a great deal of skin in the panel- and research-quality game, whether they know it or not, and they need to take more aggressive action to get the quality that they need. Where can they start?

Exceptional tools are already at hand.

For years, ESOMAR has been publishing its “28 Questions to Help Buyers of Online Samples” guide. Marketers should ask all of their major research suppliers to answer these questions as a prerequisite of doing business.

Marketers also have to claim some responsibility for the quality issues plaguing the industry today. In the

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GRIT report, buyers and sellers complained about a dearth of engaged respondents and a rising tide of exhausting surveys. Getting more from less is wearing out panelists quicker than ever before, and marketers should see this as a major business concern, not just a wonky research conundrum.

While we have seen some progress in addressing fatigue through streamlined mobile designs, gamification and shorter surveys, we also need to be careful that we are not bombarding potential respondents with a multitude of small queries. In the age of sample routers, this could work against our efforts on engagement.

When marketers have the quality information that they need, they should advertise that to their internal

clients. Do not dive into the first data points until you have explained to your audience why this information is solid enough to support the important decisions at hand.

Of course, even a bulletproof sample does not guarantee that you will receive your answers on a platter, fully baked.

Accuracy does not translate into insight absolutism. Good research provides guidance and direction, but developing specific insights and action steps is still the marketer’s purview, and should be. Those actions, coupled with a foundation in truly accurate research, will ensure that you never have to worry about slide 37 again. mI ✒ David Krajicek is CEO of GfK Consumer Experiences North America.

INSIGHTS MACHINE

B -TO- B M A RKETING

Lost in the B-to-B Time Warp Calling all superheroes: A plea to redefine B-to-B marketing and communication for the 21st century Don E. Schultz  dschultz@northwestern.edu

O

ver the past few months, my attention has been increasingly drawn to B-to-B marketing and communication. It’s not that I had been ignoring the topic—I am still a member, in somewhat good standing, of several B-to-B organizations. It’s just that so much has been occurring in the whirling, swirling world of new media and new marketing that my research and learning has drifted away from the topic.

A few recent events have reminded me, though, how the community of businesses selling to other businesses is still such a major part of the world’s economy. But let’s face it: The traditional world of B-to-B communication—that is, sales brochures, retailer sell-in sheets, sales force support materials and an occasional trade ad focused on a listing of benefits—is not what B-to-B is all about these days. I think what has happened is that too many marketing organizations and marketers, like me, have become so enamored with Twitter feeds about the adventures of

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Justin Bieber or the most thrilling new gadgets that they’ve lost sight of what is happening in B-to-B. Yet in the world of B-to-B commerce, technology is likely infinitely more important than it is in the marketing of consumer products.

The challenge seems to be that B-to-B just doesn’t get the publicity or attention that it deserves, and most discussions have not evolved beyond the challenges marketers were facing in the 1980s.

In short, B-to-B marketing and communication seems to be caught in a time warp that prevents the field from progressing. Much of that I attribute to the almost stultifying concepts and approaches of a bygone manufacturing arena, in which both academics and practitioners keep twisting and turning but not moving forward. Many of our traditional concepts are clearly obsolete, but we keep hanging onto them like some sort of safety net. In my view, unless and until we face some of those issues head-on, I suspect little progress will be made in B-to-B marketing and communication.

As a start, here are just three of the B-to-B issues that I believe need to be examined in the cold, hard light of the 21st-century marketplace.

1

For most organizations, the field sales force is becoming irrelevant. They can’t gather

prospects today simply because buyers now are more sophisticated than they are. Buyers know their needs much better than any sales person ever can, and thus, the field people spend most of their time trying to catch up with customers and prospects, not leading and directing them. Recent industry figures suggest that somewhere between 60 to 70% of many B-to-B buying decisions have already been made before the sales force ever becomes involved. So much for the aggressive sales person turning up a prospect that no one knew existed.

Other figures show that when the sales person does get in the door, they have less than a minute to present their wares. There’s no longer a structured, solution-selling, flip-chart-based approach that so many organizations still seem to believe exists. Today, the sales force is a “closer,” not a “sales developer.”

2

Brands and branding are becoming increasingly important. Where once the field sales

force represented the organization, or, more accurately, was the face and future of the organization, now there are so many other ways the firm and its products are evaluated. The idea that any B-to-B organization doesn’t need to employ various forms of proven brand development is simply wrong. When reputation, trust, recommendations, consortia and transparency are the critical factors that drive organizational

buying, or at least they enable the firm to make the “first cut” in an electronic search, a strong brand is critical. Yet too many B-to-B organizations are caught in the time warp of branding and communication, being managed by a couple of “blue-haired” matrons, a few failed field sales people or, worse yet, a couple of executives serving out their time to retirement. In the 21st century, branding is not just logo colors and typeface decisions. Brand planning and execution needs to be as cutting edge as the latest robotics assembly systems.

3

B-to-B marketing and communication is no longer just about “buying centers,” structured sales presentations and CRM feeds. Every B-to-B manager can

cite chapter and verse on why and how B-to-B marketing and communication is different from B-to-C—or at least it once was—but they keep applying all the same old, hoary concepts they have always used. Today, B-to-B is not only hard to define, it is even harder to put a string around and bundle up into a nice

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package. Take the simple, basic concept of work. Where once work was a noun, where a person went to accomplish tasks, today it’s a verb. We “work,” everywhere, 24/7. Similarly, a B-to-B organization was defined by operating smokestacks, number of employees, sales volume or other factors such as SIC codes. Today, it is hard to tell a B-to-B firm from any other type of business operation, although we keep trying.

To me, the major difference between B-to-B and B-to-C firms is where the output is consumed. Thus, small- and medium-sized businesses, which are where much of the B-to-B growth is, are no different from consumer companies, yet we’re caught in the time warp of classification, resulting in calcification.

The differentiation made sense when most of the enterprise value was in manufacturing or making something, unlike today, in which enterprise output is based on skills, services and IP. Clearly, we need to re-think how we identify and articulate what B-to-B marketing and communication is and

what managers need to know to lead such radically different structures both inside and out. We need to toss out many of the concepts and approaches that currently hamstring B-to-B marketing and communication. Who is going to do that? Most likely, it won’t be B-to-B sales management since they have the most to lose and seem to be much of the problem. It can’t be B-to-B marketing and communication folk.

Typically, they are buried too deep in the bowels of the organization to surface anytime in the near future. Will it be the agencies and communication groups?

Not as long as they are beholden to the existing structures and formats.

Today, it seems time for a new B-to-B “superhero”—someone who can get out of the time warp and start to re-think what B-to-B is really all about. There are some lights in the distance, including GE, Intel, Cisco, Emerson and the like, but they are few and far between, and most of them are still simply trying to escape the doldrums of the time warp.

So if you see, hear or have employed a B-to-B superhero who has escaped the time warp, treasure him or her.

Encourage them. Nurture them. Give them breathing space. But most of all, don’t expose them to your current managers, where they will likely be contaminated by the traditional B-to-B apprentice system. They are likely the future of your organization, and showing them the past, telling them “war stories” and providing them with “best practices” is likely the worst thing that you can do.

Simply put, it’s time to move forward, not just keep reinventing and refining the past. mI Don E. Schultz is a professor (emeritusin-service) of integrated marketing communications at Northwestern University in Evanston, Ill.

✒

THE BIG PICTURE

CONSUMER TRACKING

Digital Footprints Abound Will consumers’ digital footprints change marketing research?

Gordon Wyner  gordon.wyner@gmail.com

D

igital footprints are growing in numbers as more and more consumers are using the Internet to search for product information, purchase products and express themselves via social media.

Through these actions, consumers are leaving behind lots of information that has potential value for marketers.

At the same time, companies are investing more into harnessing the data from these footprints and packaging it in various ways to generate insights about consumers and markets. Will this wave of increasing digital information become a major source of insights? Will it supersede and/or replace other forms of information-gathering, particularly consumer surveys?

The answer will depend on whether digital footprints become solely another entry in the marketing insights data analysis toolkit, or whether they become an entirely different platform for marketing insights. Do the data and analyses complement other ways of generating insights, and are they mostly additive? Or do they make traditional methods obsolete? Will multiple methods become integrated (online and

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offline data, for example), or will the new methods drive out the old?

There are good reasons to expect substantial alterations to the insights landscape, and disruptions of traditional ways of conducting and using market research. The definition, creation and delivery of insights require new technologies and may involve new players, roles and responsibilities, and a different view of what makes insights important to a business.

Footprint Appeal

Digital footprints have several benefits that could lead to continued adoption, at least for some marketing research applications. With data, marketers have potential to generate insights on what the market as a whole is saying through social media expression about a brand or marketing campaign.

The challenge is to summarize all the comments made on social media (and other media, like blogs) in ways that are consistent and reliable over time. For example, the volume of comments and the direction of opinions (positive or negative) are candidates for creation of index

numbers that can be charted by day, month or year, thus enabling measurement of differences between brands and changes from period to period.

No sampling of individual consumers and collection of data via structured interviews is required. This suggests that costs would be lower than for survey data, assuming that any costs to access the stream of digital data are minimal, such as from Google, Twitter or Facebook. In general, the individual consumers’ footprints would not be accessible to marketing analysts due to privacy concerns and other issues.

The amount of data on the leading digital platforms is huge, so sample size may not be an issue in the way it is for survey-based tracking studies. The number of searches, comments, likes and dislikes is often extremely large and it may capture all the expressions of consumers on the chosen channel.

Another appealing feature of footprint data is its potential to become embedded into an ongoing business process that enables real-time marketing decisionmaking without requiring lots of customized analysis and interpretation.

For example, the trajectory of positive mentions of a brand or a new product could provide early indications of in-market success and guidance for continued marketing support. Early indications of problems, dislikes and negative opinions could be used to pull back an introduction and consider revisions to strategies and tactics.

Ideally, data streams would be continuously captured in dashboards that have been programmed to generate pre-formed analyses in executive-oriented formats, such as infographics. These would show the time path of consumers’ sentiments in small intervals and to be reported

quickly, and also can be quickly absorbed by management, resulting in shorter turn-around for traditional tracking surveys. Importantly, the structure for listening to the market would be open-ended so that it captures whatever issues are registering through consumers’ digital activities, without the need to tailor the design or data collection to each new campaign.

Footprint Challenges

What would have to happen to enable this ideal scenario to play out in the market for this tracking application?

First, there ought to be a reproducible index of the aggregated amount of opinion expressed. While the starting point might be based on simple sums of the number of comments made, it’s possible that extraneous factors, unrelated to brand content, might influence the results. For example, external news events, like elections, public policy issues and economic changes, could generate spikes in social media and effectively suppress the usual personal commentary. To be useful, the index ought to be stable enough that decision makers would have confidence that they mean the same thing time after time, and could be interpreted as trends, rather than as disjointed spikes caused by irrelevant events that confound comparisons.

One possible way to establish consistent meaning to the results is to demonstrate empirically that the footprint measures correlate to other meaningful measures of brand activity.

This could be done by comparing footprint measures to survey-based brand equity, purchase intentions and satisfaction scores, and by comparing them to behavioral measures of product usage and purchase. Tying footprints to business outcomes can establish practical relevance as well as statistical validity.

Research by Wendy Moe and David Schweidel, authors of Social Media Intelligence, uses multiple channels of social media data streams and anchors results against survey-based brand metrics to create a brand index. This model-based approach supports the notion that social media data can, under some conditions, serve as a proxy for brand measures.

In practice, analyses have to be preplanned in order to be user-friendly for decision makers who have no time or resources to verify methodologies and calculations. In some instances, the footprints represent marketing input data, such as exposure to websites, advertisements and promotions. To ensure acceptance by management, these measures must accurately reflect agreed-upon media plans, product changes and introductions, and other tactical marketing decisions.

Some thought must be given to how the reported footprint data will be used to trigger intervention into the market.

For example, in marketing effectiveness analyses, what would be the decision criteria? How much change in consumer sentiment is important enough to warrant follow-up action? What changes could be made in marketing tactics, and what might the likely consequences be of shifts in messages and resources?

As important as digital footprints are, and are likely to become, it’s worth acknowledging that a lot of marketing behavior continues to happen offline.

The vast majority of retail sales are still offline—more than 90%, according to eMarketer. While Internet ad spending continues to grow rapidly and may eventually overtake TV as the leading media by 2018, according to eMarketer, TV is expected to continue to have a very strong position. Digital footprints need to be considered alongside offline behavior to gain a complete picture of the market.

The evolution of the insights market toward more usage of digital footprint data coincides with shifts toward more technology applications in marketing.

New solutions to the marketing executive’s decision-making problems may come from the technology sphere, as well. The role of digital footprints will likely vary by application, such as from mind-set-tracking, concept evaluation or segmentation. Providers of traditional market research and consulting solutions should anticipate new types of competition for the solutions that best meet the marketer’s needs in a form that they can easily use—and at a price they are willing to pay. mI ✒ Gordon Wyner is vice president of client solutions at Millward Brown and contributing editor of the Marketing Management section of Marketing News.

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IN CONTEXT

SOCIAL MEDI A

The Social Game From basketball to social media analytics, a firm grasp on fundamentals makes all the difference Justin De Graaf  jdg@coca-cola.com

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f you have ever played basketball, you know that a flawlessly executed pump fake almost always guarantees a scoring opportunity. What’s better is that a pump fake doesn’t require the athleticism of an Olympian. Anyone who picks up a basketball can use a pump fake to his or her advantage, and that is what makes it a basketball fundamental.

Thinking about fundamentals, what would they be for social analytics?

Reflecting on the last 18 months as the lead of social analytics at Coca-Cola, I’ve come up with the following five must haves:

1

Listen more than you speak.

For years, marketers have built fantastic skills speaking to consumers using all types of media, but when it comes to social media, these one-way communication skills need to come second. The strongest social media marketers listen first in order to discover the context of a situation. Who is talking?

What are they talking about? Which words do consumers use that differ from the ones that we use inside corporate headquarters? Listening can be done for free—using tools like TweetDeck or Hootsuite—or can be done through a paid subscription to a social listening

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service. When listening, be sure to listen for your brand, your competitors and, most importantly, your entire category.

2

Understand that metrics and analytics are different.

Metrics are fantastic at telling you what happened, but you need analytics to understand why, what else and what if.

Think of reporting as a clock. While a clock can tell you what time it is right now, analytics will tell you that you’re 27 minutes away from your destination and that you will be 7 minutes late due to traffic on the freeway. Both are fundamental, and successful social teams need both analytics and metrics.

3

Use benchmarks to provide relativity and context. If a

4

Use simple visuals to communicate data. Members

report shows you the number seven for a given metric, how will you know if that’s good or bad, expected or unexpected? Social data changes rapidly, and understanding the normal range for KPIs will help craft appropriate recommendations. Go beyond comparisons to other brands or prior campaigns within your company. Instead, create median-based benchmark ranges for the past seven, 30 and 90 days to provide relativity to the current data.

of social analytics teams usually come from a wide variety of backgrounds, and output from the team travels widely throughout the company. Presenting complicated visuals with too many graphs, tables or time series charts will not help the business make decisions.

Use the data to create visuals that answer questions, such as: How big is the conversation? Is it evolving? Is the conversation important to us? If creating simple visuals is a skill missing from your team, make the investment for a graphic designer or use self-service sites like Visual.ly or Piktochart.com.

Metrics are fantastic at telling you what happened, but you need analytics to understand why, what else and what if. ... While a clock can tell you what time it is right now, analytics will tell you that you’re 27 minutes away from your destination and that you will be 7 minutes late due to traffic on the freeway.

your company or brands, then trend that using your benchmarks. If your brand involvement in a negative conversation is increasing, start considering the action plan. As your teams help make datadriven decisions a normal behavior, they will begin looking to set measurement objectives before campaigns launch.

5

Make decisions based on the data. Once the data is gathered,

analyzed and visualized, help train your social analytics team to encourage decisions based on the data. Do you want to measure if your campaign was a success? Compare it to your

brand specific 90-day benchmark. Are you within normal range or has your campaign generated conversation that exceeds the norm? Are you trying to assess the potential threat of a topic? Run an analysis that shows what percent of the total conversation includes mention of

Like the pump fake, these are fundamentals that any team can learn to do. Create consistent scoring opportunities by focusing on the basics. mI ✒ Justin De Graaf is global media insights director at The Coca-Cola Co. and a member of the AMA’s Marketing Insights Council. You can find him on Twitter at @justindegraaf.

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SOCIAL CUES

THIRD- PA RTY DEPENDENCY

Creating Community Why social media marketers should start looking inward Joan Mancuso & Karen Stuth  jmancuso@5squareresearch.com  kstuth@5squareresearch.com

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his past year, many businesspage owners have felt daunted by changes to Facebook’s algorithms, which now selectively decide which people from your list of Facebook “friends” will see your posts, rather than showing posts to your entire list. Facebook has altered its “rules of engagement” so that only very high-traffic posts—those that obtain a very high rate of engagement (“likes,” clicks, comments and shares) compared to Facebook engagement rates overall—will be seen by a lot of people, regardless of whether those people are fans or friends. A recent study by Ogilvy & Mather found that companies’ Facebook posts went from reaching 12% of their followers in October 2013 to just 6% in February 2014.

Social media experts agree that the reason for the change was obvious.

The new algorithm pushes many users, particularly brand or business-page owners, to promote their posts—that is, paying Facebook to show what was, in the past, shown as a matter of course and what many users perceived as the core of Facebook’s brand promise. As an individual, this means that if you want all your Facebook friends to see photos of your cat in her Halloween

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costume, you will need to spend $10 or so to make it happen. That’s just for individuals. For brand or businesspage managers, it means an allocation of marketing budget and additional resources to ensure that their Facebook friends see their content in the first place. They are the true casualties of Facebook’s change of direction.

While this change is well-known and has been in place for a while, one question remains: Does it change the value of Facebook as a social media outlet for businesses or brands that were viewing it as a source of marketing and “soft” marketing research? The inability to reach all of their customers through posting, as they could before, and to view Facebook comments and feedback as a “finger on the pulse” information source has forced some companies to revise their social media focus, especially where Facebook is concerned, while others have left Facebook entirely.

Some companies have merely accepted the policy change and continue to attempt to engage with their Facebook “family” as before, while others have shifted their focus to other social media channels such as Google+, Tumblr, Path and, depending on their target markets, Snapchat and Instagram.

Reddit, LinkedIn and Pinterest are making concerted efforts to draw in small- and medium-sized businesses with ad prices that are attractive compared to the ever-increasing cost of Facebook ads.

Investment in Facebook time and resources may have been more costly to brands than they had realized, magnetizing customers to social media channels, including Facebook, at the expense of direct interaction with the brand itself. There is only so much attention a consumer can pay to a brand. Marketers were caught in a bind. They followed customers onto social media because that’s where the customers were, but the platform that gained attention was not their own, and brands may have paid the price.

In response, some are employing a different strategy—now building communities of customers either locally or using a platform such as Ning in an effort to create relationships with their products that will replace the void created by Facebook’s algorithmic change.

Either way, many companies are beginning to balk. Some are beginning to reclaim their brand in the face of the ever-changing sands of destiny that characterize Facebook today, and perhaps other social media venues in the future, looking for ways instead to socialize their brand and create customer relationships and intimacy without the dependency on third-party platforms. Perhaps the very best way to do this is through the product itself.

An excellent example of this phenomenon is the immensely popular Fitbit. Owners of a Fitbit device use an online dashboard to track their daily progress but also have the opportunity to create their own community of people with Fitbit

devices—friends, family and even virtual strangers—who encourage each other in their daily progress and health goals and share their own Fitbit progress. These self-made communities of product users are deeply connected to the brand and product through a private social community that they create.

Another example is Cisco’s Customer Connection Program, which invites customers to connect with more than 14,000 other Cisco customers in a global user group, where they can receive and share expertise, access exclusive product programs and stay up-to-date on product development. In addition, members can participate in

private online communities to interact with their peers, participate in monthly think tank groups and also receive special benefits for Cisco conferences.

All of these private community activities help to sew their members deeply into the brand and brand experience, and to feel a kinship with Cisco and other community members.

As many companies learned the hard way when developing their initial social media presence, it pays to have someone who understands the brand and company, articulates a clear brand message and stays on that message—a person who knows how to funnel customer questions to appropriate parties within the

organization and repackage the answers back to customers. Similar to an excellent focus group moderator, this takes considerable skill and sophisticated experience—this is usually not a project for a recent college grad. Grasping the ins and outs of the software is never as challenging as keeping the community on track, engaged and happily participating in a way that continues to meet the organization’s needs. Delivering an ongoing stream of insight and inspiration to internal stakeholders is paramount, as is ensuring that the brand always presents a consistent voice to customers or other community members.

Are we saying that companies should forsake all social media and try to build their own communities or platforms?

We don’t recommend one strategy over another, but rather, as with any robust marketing strategy, companies should avoid relying heavily or exclusively on third-party media. Instead, use them as a complementary path to customer engagement, brand involvement and the development of a consistently loyal customer base. Additionally, social media should be used to constantly drive followers in any channel back to the company Web page or product community, where customers in decent numbers can again become a source of marketing feedback, product development information and market research “cues.” mI ✒ Joan Mancuso and Karen Stuth are founding partners of South Pasadena, Fla.-based 5 Square Research. Mancuso has more than 25 years of research experience with a background in sociology, psychology, econometrics and clinical research.

Stuth has more than 25 years of experience in marketing, business development and marketing research management.

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THE INNOVATOR

DIGITA L STRATEGY

Strategic Insights Are digital efforts at the center of your brand’s strategy?

Joy Armitage  joy.armitage@dunnhumby.com

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nce upon a time, not too long ago, approaches to reach customers and glean actionoriented insights were developed in isolation. The marketing department would develop its annual strategy, sometimes with input from other departments. The customer service strategy often was developed in isolation. The sales strategy boiled down to “sell more stuff to more people.” And the digital strategy? Well, no one knew where to put that. It touched many areas, so sometimes it would be part of each department’s strategy and sometimes it wouldn’t be part of anyone’s strategy.

Those days are gone.

Today, the digital strategy—and the wealth of data and customer insights that result—must be the cornerstone of any successful company’s go-to-market strategy. It must be pervasive throughout the entire buying cycle. Customers are no longer limiting interactions with a brand or company solely through the traditional forms of media. The “onesize-fits-all” approach is gone.

Today’s consumers want what they want, when they want it. Consequently, the need for a digital strategy as the centerpiece of customer interaction, marketing and sales programs is vital for survival and growth.

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With today’s consumers spending so much time glued to a mobile device, your customers are likely to interact with your brand outside of the “real world.” In fact, if you relegate your digital strategy to the digital department without integrating it into your go-to-market strategy, you could be missing a huge opportunity.

But, more importantly, it needs to be the right digital strategy, which includes recognizing that consumers are spending increasing amounts of time on smartphones, using created content to engage your audience, and making digital advertising techniques work for you.

First, from a pure interaction standpoint, smartphone ownership continues to grow, and users are spending more of their digital time on mobile, especially with apps.

Accordingly, if your digital strategy consists solely of a mobile-enhanced website, you could be missing opportunities to interact with your customers.

As apps (and app usage) grow in popularity, more competition exists.

To ensure that your brand’s app has the most loyal and repeat visitors, create functionality that would lend itself to increased customer interaction. Apps that have more relevant content and are easier to use will result in people using them more frequently.

But smartphones and apps are just one way of interacting digitally.

Some of the most important campaigns and impressions happen when consumers merge the digital world with the “real” world.

Brands that design communications strategies for life in the digital world are more likely to succeed than brands that design just a digital strategy. What’s the difference? Digital strategies are usually focused solely on devices and channels (for example, mobile, online and/or social media). Digital communications strategies put the person at the center and create strategies to reach them based on their habits, preferences and behaviors.

One great example of this approach is a campaign by Mooresville, N.C.-based Lowe’s Companies Inc. Knowing that the Lowe’s audience can be diverse— contractors, repairmen, do-it-yourselfers and first-time homeowners—the brand honed in on a shared characteristic among its target market, which, according to the campaign, was the desire for quick-fix solutions to improve their living environment.

To reach this group and appeal to that shared desire, Lowe’s created a video campaign called #LowesFixInSix. Some of the current six-second fix-it videos include how to get a wine stain out of carpet, using a magnet inside of a cabinet to hold bobby pins, and installing a speaker that can double as a shelf. This content is intermingled with timely product and sales promotions, such as deals on fire pits and miter saws.

When planning a digital communications strategy, smart marketers are thinking beyond created content to digital advertising. According to our research, there’s been an increase in digital media ad spend, but we haven’t seen a corresponding increase

in consumption and change in behavior.

However, digital advertising has a huge potential to break through the clutter.

The ability to target potential buyers with brand messages most relevant to them should not be undervalued.

There’s no golden formula for creating a digital communications strategy as the centerpiece for reaching consumers and, most importantly, it won’t happen overnight. But by shifting your focus to digital, your marketing efforts—and your brand—won’t be left behind. mI ✒ Joy Armitage is the social media and innovation director at London-based dunnhumby, where she is responsible for the development and strategy of word-of-mouth propositions.

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ration

YoUth If ‘Video Killed the Radio Star,’ then MTV’s consumer insights authority, Jane Gould, is helping ensure that video—and the network—won’t meet the same fate. Here she discusses being the disruptor versus being disrupted, why a brand should co-create with its audience and symmetry in research.

By Julie Davis

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T

here’s no shortage of online content directed at millennials these days, from silly cat videos to TV show GIFs to pop culture quizzes. But if any brand has maintained its hold on the youth market since before the dawn of the ‘listicle,’ it’s MTV. The youth-oriented TV network has created a business out of understanding the teen and young adult markets since it began as a music video channel in 1981, nearly the same year that the first of today’s millennials were born. Soon after, the network began expanding its programming to include scripted TV shows, game shows and reality television with programs like The Real World, Total Request Live and Jersey Shore.

As so-called “digital natives” became the dominant youth market, MTV—and its marketing efforts—evolved alongside them: In 2010, the network had the fastest growing branded page on Facebook and has remained among the top 10 branded pages with the largest following each year since, according to Ignite, a social media agency based in Cary, N.C. That same year, MTV’s growing research department conducted its study, “The Millennial Edge,” which has been widely referenced by the consumer insights community. The study showed that millennials highly value self-expression and look for brands to give them opportunities for co-creation.

That’s where Jane Gould comes in. A longtime TV market researcher, she joined the MTV team as the vice president of research and insights following a 15-year run at Nickelodeon as the senior vice president of global brand and consumer insights. Gould oversees all consumer studies and manages a team of 50 who provide qualitative and quantitative analyses to inform MTV’s brand positioning, and forecast trends that influence development, programming and marketing for the company across its media channels.

Marketing Insights caught up with Gould to learn how MTV uses research to engage millennials and provide valuable programming insights to keep the network’s offerings fresh for a constantly evolving youth market.

Q: You’ve spoken before about how millennials are a “generation of innovators.”

Tell me how understanding this mentality helps MTV engage with this hard-to-reach audience.

A: First, if you look at all generations, it’s not to say that any other generation didn’t have some of the traits that millennials have. I just need to put that in perspective. I think there’s a lot of overlap in terms of the traits. It truly is about how they manifest for each generation and the cultural context of the pot.

So if you compare the Gen Xers’ to the millennials’ childhoods and coming-of-age stories, they’re vastly different.

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That said, if you subscribe to the [William] Strauss–[Neil] Howe theory on generations—that these millennials are special and confident, and up for team work—what has been interesting for me in the past few years has been to pull apart the older and the younger millennials because their cultural stories are different. They have grown up in vastly different times, [with] vastly different concerns and, by some stretch, morals.

Q:

Can you explain some of those differences?

A: If you look at those older millennials, which are the ones I’m most envious of and wish I was—just to fully out myself—they were born in a time when

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anything was possible. It was absolutely fantastic, and they felt it. They were educated that way and they were parented that way and it was a wonderful thing.

And these younger millennials have really been coming of age at a time when it doesn’t feel like anything is possible. It does feel like you really have to try and stand out to be heard, but it doesn’t feel like there’s a real natural path for you to follow. So there’s a real difference between the two of them in terms of how I think they’re approaching [life]. … Their ability to be self-aware is something that absolutely connects them and is different from other generations.

Q: What does this mean for your department and its research work? How do you tailor your research methods and tools in order to reach millennials?

A: To think like a millennial is key. We need to speak their language and be one of them and feel their world the way they feel their world. That’s, I think, what’s really important about what we bring back to the team here at MTV. … That’s something that is important to us: to be able to understand their perspective but to also see and feel their perspective. Not look at them from a distance and point fingers, but to truly come in and say that this is what it feels like to be them right now.

Q: When it comes to mining customer insights from millennials, how do you assess the value of soft, behavioral data against hard, quantifiable data? How do you leverage both within your overall insights strategy?

A: I really do think there is such value in both sides. If you were only steeped in one, you don’t have the whole story. They do work seamlessly together when everything is working well. For instance, there’s been many an occasion when we’ve seen something come out in a piece of data that we couldn’t explain, but we then have to go the other way around and start talking to millennials to really understand what is going on. Likewise, we’ve heard the very hint of a theme from a couple of conversations—and it really could be a couple of conversations—but it has hit such a very important note for us that we’ve then believed in the story enough to go out and quantify it and follow it up. So I really do believe in the symmetry between the two of them. … I think one of the most important things that we can do here is listen. It’s so easy to have a very firm question in your mind, and you can miss so much in the data when you only

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have that one question. I much prefer to look at the data set and let it tell its story because like anyone, when you’re having a conversation face-to-face and you’re not listening, you’re only listening for what you’ve asked for, then you’re not getting the whole story that the person has told you. I feel the same way about data as I do about conversation.

Really, you need to open your mind and let the data breathe and tell its story to you. It always reveals secrets that are really fascinating when you can step back like that.

Q: How does your view about ‘letting the data breathe’ come through in your research?

A: When I’m in that mode, it is always about, ‘What is their story that they’re trying to tell us?’ It may not be something that they’re aware of, but there are clues in everything that they do: what songs they choose, what clothes they wear. … It’s all telling us a story and it’s giving us clues. What I really focus on is putting them at the center of everything we do, and then we translate it for the business needs later on, rather than trying to make them a mini executive of MTV. I’m not that interested in, ‘If you were in change of MTV.’ They’re in charge of themselves, and they’re really good at it, so I want to focus on what they’re really, really good at.

Q: How does your department incorporate predictive analytics into your overall marketing strategy? Do you expect the accuracy of predictive analytics to improve in time?

A: We can predict some things when everything stays the same, but there are so many things that can happen that could stop that moment from happening as it’s meant to be. What’s really important about predictive analytics is that we utilize them, we dive deep so that we get the things that really matter in this space. What it helps us do is understand the behavior that’s happening right now and how predictable we believe that behavior [will be] in the future. The next layer I want to add to that is: What things do we think could come along to disrupt this behavior?

I think my passion for predictive analytics is clear: It’s important, and we need to try and layer that out for ourselves and our own futures, but it’s equally important that we layer in what we think could disrupt this behavior moving forward. Then, I think, we have a whole story: Here are the things that we’re going to monitor to see if they continue down that path, and here are the things we’re going to keep a close eye on because we think they could disrupt this behavior. … I feel very strongly that you

should never just look at a predictive analytics piece and think you know the whole story. It’s a part of it and it’s a possible future, but there are many things that could come along and disrupt that.

Also, we might decide we want to be the disruption, right? That’s the [question]: How do we want to pivot? Do we want to stay in that path, or do we want to be part of that disruption and make a big statement and try to shift things, as well? Or do we know that someone else will?

Q: Marketers are charged with communicating consumer insights to the C-suite, yet oftentimes, even executive-level stakeholders misunderstand the crucial differences between metrics and analytics. How can marketers help educate and manage data-driven brand perceptions at the stakeholder level? How can they communicate those results effectively throughout the rest of the organization?

A: There is a lot of stuff for people to absorb, so we really like to try and come up with innovative and exciting ways to share information. Sometimes it’s just a matter of getting people what they need as quickly as possible. … When we want to share big pieces of information, we have a quarterly get-together. Every department from the company is represented. We take them out of the building for the day

and we just celebrate millennials. Sometimes that means having millennials come in. Sometimes it means that we present their stories or a big piece of research that’s come in. … And then, it filters throughout the rest of the [company] for the rest of the quarter. It allows us to set a tone that everyone knows what we know now.

Q: Brand perceptions are changing all of the time, especially in the eyes of constantly connected millennials. How do you measure— and manage—MTV’s established brand metrics in such an uncontrolled environment, where anyone can access a variety of non-MTVsanctioned content, from customer complaints to editorials?

A: It’s as complicated and as simple as being everywhere they are. It sounds so easy. That’s certainly been MTV’s brand philosophy, and therefore, it’s been our brand measurement philosophy: to be everywhere they are.

[We need to] not just measure what’s important to us, but also measure what’s important to them, which goes to my [point that] you can predict the future but you better be measuring where you think those disruptions are going to happen at the same time. Something that’s very important to us is to understand where MTV is, and whether we got closer or further away. mI

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The The

Metrics Map Using analytics to navigate metrics of substance versus metrics of convenience

By Christian Kugel

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H

ow do you know that you are measuring the right things?

I ask this question a lot, and to a wide variety of people—clients, partners, suppliers and internal managers. After all, in the digital marketing space, there’s no shortage of metrics. The daily deluge of data in dashboards and reports can easily overwhelm anyone tasked with making marketing decisions. The challenge often revolves around which metrics are worthy of attention and which ones ought to be downplayed.

All too frequently, I see managers falling into the trap of using metrics of convenience as opposed to metrics of substance. And when this happens, it creates a vicious cycle: An (inadvertently) inconsequential metric is chosen, the machine revs up to support it, marketing managers optimize efforts and resources to drive that metric, and then, in the end, the real resulting impact to the business objective is unclear.

Here’s a common example I’ve come across related to the consumer’s journey with products. My team works with a lot of automotive advertisers and their agencies.

Quite frequently, they tend to value metrics with a singular focus, centered on driving traffic to their brands’ websites. At its most basic, it is a metric such as “cost per visit.” Slightly more advanced metrics focus on the volume and efficiency of high-value tasks on the brand’s site, such as “build a vehicle” or “compare models.” Either way, the metric defining success, in this case, is digital media’s ability to drive some type of traffic to their sites.

The fly in the ointment is this: According to our automotive path-to-purchase research, where we passively observed auto shopping behaviors across the Internet, 37% of new vehicle buyers never visit any brand website in the six months leading up to their purchase.

Not just for the make that they purchased, but for any make of vehicle. Think about the implications of that for a moment: Auto brands prioritize website-traffic-driving metrics over all others, yet four in 10 buyers never exhibit that behavior leading up to the moment where they spend tens of thousands of dollars purchasing a vehicle.

The reality is that the nature of car-buying has evolved. When we asked the 37% why they never visited

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a brand.com site, their reasons were obvious: They know the information will be biased, so they value the third-party sites more. They find that they can get more comprehensive information elsewhere; the brand.com sites don’t offer them anything that they can’t get on other independent sites. And, somewhat surprising to me, it sometimes just doesn’t occur to them.

In this case, traffic-driving metrics are metrics of convenience, not metrics of substance, for the simple reason that they fail to include the 37% of buyers for whom that action has no value. And when those metrics lead to optimization decisions, to purposefully exclude such a large proportion of buyers, you can see how the vicious cycle rears its ugly head. Is traffic easy to measure? Sure, but at what ultimate cost? I would argue that marketing efforts misaligned to natural consumer behavior are destined to flounder, at best. They will probably fail.

Metrics of substance, on the other hand, are grounded in the realities and complexities of the marketplace. And to get there, it takes a disciplined approach that combines research and analytics. In addition to the 37% fact, our path-to-purchase work revealed several other key insights, illuminating the true nature of how people shop for cars.

First, the active shopping window is incredibly short.

People only spend 28 days actively shopping for a new vehicle online. Conventional wisdom has always said that it takes more like six months. And while that might have been true 10 years ago, the way people shop has changed.

Now, they don’t need to spend that much time shopping.

And in addition to that, when people first start the shopping process, the very first action they take, most frequently, is “browse dealer inventory.” By following a

typical purchase funnel model, most marketers assume that the first action is at the top of the funnel—an action such as “compare models” or “read reviews.”

The data, however, is quite clear. By the time the active shopping window starts, people have already established their make and model preferences. Now this is not to say that buyers never change their mind during the active shopping period—they do. But counter to accepted wisdom, they actually start at the bottom of the funnel and cycle up and down it throughout their shopping process.

Now consider the implications of all of that and how it affects the totality of the consumer shopping journey. The holistic conclusion, given the human truths detailed above, is that it should be even less about the traffic-driving KPIs. In addition, the insights compel a strategy that targets potential buyers well ahead of in-market signals. If an auto brand waits until the 28-day active shopping period begins, it is probably too late to convince a consumer to change his mind and consider that brand.

There simply isn’t enough time.

But again, if the KPIs in this case are focused on driving in-market consumers to brand.com sites, the tactical decisions and optimization mechanisms will exacerbate a flawed strategy. Reliance on metrics of convenience will magnify the bad decision.

Armed with these insights from the research, the nature of the analytics and metrics challenge takes on an entirely new form. In the face of this information, you can see how it would be completely insufficient to rely only on traffic-driving marketing metrics. Instead of simply measuring and optimizing to the volume and cost of traffic to the brand.com site, an entirely different—and more complex—analytics package needs to be created. In this new consumer shopping environment, establishing brand preference prior to the active shopping window is critical. Therefore, metrics should evolve accordingly and focus on quantifying the shift of preference among the appropriate target groups. Operationalizing that

is no easy task. It requires a full understanding of the dimensions of the problem. What are the most relevant target groups? Which type of messaging motivates them?

What is the right level of frequency, taking into account wear-out and depth of interaction with the content? How does their mindset affect messaging? How do we best quantify preference, one that is predictive of purchase?

This, I think, speaks to a core issue presently facing the marketing discipline. What the industry needs is a rigorous harmonization of research, analytics and metrics.

All too often, managers skip the work in the beginning and middle, and jump right to the metrics. Creating metrics of substance forces the research-analytics-metrics continuum. Research, when done properly, reveals the human truths, the nature of the marketplace and the triggers for purchase. Analytics, when done properly, finds predictive proxies that measure these elements: proxies that can be continually monitored. These proxies, of course, are themselves metrics, but they are now metrics of substance. When aligned with the reality of consumer behavior, they are better positioned to be operationalized and used for optimization. marketing insights January/February 2015

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Research, when done properly, reveals the human truths, the nature of the marketplace and the triggers for purchase.

Analytics, when done properly, finds predictive proxies that measure these elements: proxies that can be continually monitored.

Again, I ask the question, “How do you actually know that you are measuring the right things?” Unless any marketer can describe how they arrived at the metrics they use, via analytics and research (or some other type of validation), I’m willing to bet that they’re making the mistake of relying on metrics of convenience.

Here’s a very straightforward example of how we deploy this process for our owned and operated properties at AOL. It’s somewhat well-known (but not that well-internalized) that website traffic follows a Pareto distribution. Roughly 80% of the time spent on websites or apps is consumed by 20% of the audience. Two numbers that drive revenue for digital publishers are monthly unique visitors and page views. You would be quite right in imagining that the disparity in page views between heavy users and casual users is huge. However, due to the nature of digital reporting (meaning the metrics systems and tools that are widely used), the distribution tends to be reduced into a single, averaged metric for each of those two concepts.

Marketers, therefore, tend not to get a sense of even the view of a distribution in the reporting dashboards. They know it exists, but when the metrics conceal the true nature of the distribution, it obviously tends not to be top of mind.

A very simple analytic exercise will reveal the actual distribution, and whether it follows a classic 80-20 split, 90-10, or some other proportion. It also reveals the raw number of pages and time spent among the heavy, medium and light groups. And it doesn’t take much modeling to understand the total potential impact on the property if the casual users increase their consumption even slightly.

After this analysis, we implemented a research initiative to understand the drivers of use for each of those groups.

It was designed to address questions such as: What causes a person to visit the site more frequently? Which utilities/ features/functionality are associated with incremental use?

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Which other properties are a part of their competitive mix?

Once we understand that, the entire orientation of the continuous A/B testing process changes. Rather than looking at basic, average-use metrics among test cells, it’s better to dimensionalize the metrics by the heavy/medium/ light usage segments. This gives a better indication if the changes to the sites are resonating against casual users relative to their identified needs and triggers.

The point is that neither metrics nor analytics, either alone or combined, are sufficient. It also requires a step of understanding the human truths regarding how people actually use the properties, what motivates that use, where the white space exists and which levers we can pull. It also reframes the ideation and design process to be more sensitive to the nuances of site visitors, rather than treating them as a monolithic block. Research informs the analytics framework, which then generates better metrics.

In Lewis Carroll’s novel Alice’s Adventures in Wonderland, there’s a great exchange between Alice and the Cheshire Cat that perfectly captures the contrast between these two types of metrics. After meeting the Cat, Alice asks, “Would you tell me, please, which way I ought to go from here?”

“That depends a good deal on where you want to get to,” said the Cat. “I don’t much care where—” said Alice.

“Then it doesn’t matter which way you go,” said the Cat. “—so long as I get somewhere,” Alice added as an explanation.

“Oh, you’re sure to do that,” said the Cat, “if you only walk long enough.”

It seems that Alice was dealing in metrics of convenience, while the Cheshire Cat understood the value of metrics of substance. Let’s ensure that we know where we want to get to before we jump on the easy metrics.

The best way to do that is to ground metrics in research and analytics. Creating them takes different skills—crossfunctional skills, in fact. It takes time. It takes discipline.

But without all three, we’re left with either a compass or a map. We need both. mI ✒ Christian Kugel is the vice president of consumer analytics and research at New York-based AOL Inc. and is a keynote speaker at the AMA’s 2015 Analytics With Purpose conference March 1-3 in San Diego. For more information on his presentation at the event, visit AMA.org/AnalyticsWithPurpose. Kugel can be reached at christian.kugel@teamaol.com.

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How social media insights inform— and improve—product development

B y R i c h a r d Sh a w

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it g in ” . o g d n e o r ’ r u o w Y “ The voice wasn’t my golf coach, my

young nephew or even my partner. It was that voice in my head. The one

with the Texas drawl that always perks up when my brain realizes that the thing I’ve been slaving over for days, even weeks, isn’t working.

It was 2010 and I was going through the text from a new product development discussion from an online community. We’d asked consumers all the usual questions: “Tell us about the problems you have when preparing food” and “How do you get around those problems?” The answers read like a Martha Stewart Living article— one that had already been written.

The responses we received were not the insights we were looking for, and I wasn’t the only one who realized this. We had fallen into the trap of asking unreliable witnesses to comment on their own behavior. Why didn’t we tap into the insights that consumers were already creating for us every day on social media?

A small but growing number of practitioners like Annie Pettit, author of the paper “I Will Tell You What They Want, What They Really Really Want,” companies like Precise and startups like Niice have started using naturally occurring online content to inspire, inform and innovate. The work that is being conducted in this space is not social media monitoring. It’s not about counting the number of online mentions, seeing who has the most followers or forcing sentiment analysis.

These are approaches that use online content to understand the world rather than measure it. This understanding can then be taken to inspire new product development.

If the Internet is such a great tool for innovation and insight practitioners, why is it so underutilized?

Businesses have tended to focus on using social media simply for reputation monitoring, or for marketing, with a mixture of success and failure. But using social media research as a foundation for new product and communications work has suffered from a number of problems: The analysis is time-consuming, the data is noisy and the sampling is misunderstood.

Insights and analysis based on findings A n afrom l y s i s the Businesses have steered away from using social media for AMA’s 2015 Marketing Analytics Survey innovation research because there’s so much of it. Relying 38

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solely on counts and word clouds leads you to the most common and usually most obvious product ideas. At its

best, this counting is useful for incremental innovation. The alternative high-touch approach, where a researcher reads through thousands of pieces of content, is an expensive and time-consuming, if not impossible, task.

Machine classifiers and sentiment analysis, in particular, have a bad reputation in marketing, often because they have been used as naïve metrics. However, when properly applied, machine classifiers can offer a third way between very broad counts and very expensive human sifting. In new product development work, it’s better to use the categories created by the classifiers as filters rather than metrics. We think of it as a way to add initial structure to the data and not a meaningless number.

Network analysis is another area that is growing.

While the technique can be used for things such as the

segmentation of Twitter followers, it can also be used to study how topics and ideas relate to one another. This is especially useful in innovation work. The best ideas come from joining existing ideas together in novel ways. By treating all the information you collect as a network, you can see which concepts are most commonly associated with a topic, how these concepts relate to each other and, most importantly for innovation, which concepts are emerging at the edge of a network. When investigating home theater systems, we discovered that most of the problems people had were technical, but at the edge of the network, there was a small but consistent number of issues around using surround sound in open-plan homes. This led us to develop concepts around the home theater systems with directional sound rather than surround sound. marketing insights January/February 2015

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One of the key t h i n g s t h at h a s h e l d social media back in marketing is our F r e u d i a n f i x at i o n on demographic sampling, even when d e m o g r a p h i c s h av e n o b e a r i n g o n w h at w e ’ r e trying to achieve.

Easy-to-use tools like Gephi and NodeXL, along with accessible education like the social network analysis course from the University of Michigan, are putting these analytical techniques within reach of every marketer. In a project we conducted with a car manufacturer to develop new ideas for the launch of a new vehicle, we segmented the car owners of a social network based on their connections and then analyzed their public posts to see what interested them. We then researched those interests in more detail and used the findings as a basis for a variety of campaigns.

D ata Unless you have a very distinctive brand or category, “and/ or” online search queries lead to the return of a lot of unwanted content. Traditionally, this has been dealt with by using negative keywords that exclude content containing certain words or more complex “near/if ” queries.

Instead of filtering out the noise, a better solution is to send it to the bottom of the pile. While we want technology to aid analysis and discovery of insights, it is not yet at the stage where it’s able to do the analysis for us. Promising projects in artificial intelligence allow users to teach a system what is good content and what isn’t as good, which enables them to see the most useful content first and work down from there. In our own work on a social-mediabased innovation approach, called DigiViduals—a kind of “research bot” we’ve been experimenting with—algorithms that automatically generate short written summaries are based on thousands of pieces of content.

Sa m p l i n g One of the key things that has held social media back in marketing is our Freudian fixation on demographic sampling, even when demographics have no bearing on

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what we’re trying to achieve. Finding people of a certain demographic who are posting online is difficult to do at any sort of scale, even if you limit your research to a particular platform like Twitter.

When conducting social media research, marketers often worry that the majority of people consume content but don’t post content. This is true, but the number and variety of people posting and consuming content online far outweighs the amount of people on survey panels or participating in focus groups. While online content sampling is far from perfect, it can be more reliable than the next-best alternative.

Rather than worrying about who is posting content online, it can be more useful to think about how behavior manifests itself. Context drives behavior. This is why it can be more useful to sample and study the culture consumed by a demographic rather than just content produced by a demographic.

We know from tools like Compete or Wakoopa which demographic categories visit which websites and, in some cases, when they visit them. We then weight the websites from which we sample content based on this data. This improves sampling accuracy and sheds more light on what is driving the behavior of a particular segment. This weighting can work wonders in innovation work. When developing a line of new pet treats, we found that useful ideas were few and far between on large social media platforms like Twitter and Facebook. Valuable ideas really started to emerge when we focused our sampling on pet care and pet fan forums.

Hopefully others in marketing will start taking advantage of the innovation opportunities offered by online content. Social media research is just one tool in a shed of techniques, but it’s powerful and has been underutilized for too long. Online content can kick-start innovation projects with a wider variety of ideas than you get from other research methods. It can help pick out the useful outliers from common banter and focus in on the geeks and fans in a particular area who are often the most exciting people to listen to because, in many ways, they are already living the future we are looking to create.

The Internet is the greatest collection of human knowledge ever assembled, all of it searchable and linked together. Surely it makes sense for marketers to use this as the starting point for innovation. mI ✒ Richard Shaw is vice president and DigiVisionary, and a member of BrainJuicer Labs, at London-based Brainjuicer Group PLC. He can be reached at richard.shaw@brainjuicer.com.

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10 Minutes With Alan Gould By melody udell, managing editor  mudell@ama.org

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n today’s marketing research landscape, the state of the survey gets lost amid a swirl of industry chatter: discussions about redesigned survey frameworks and algorithms, the efficacy of mobileempowered consumer engagement and seemingly endless technology-enabled research opportunities. Yet in a realm that frequently welcomes new tool sets and methods for yielding data-rich

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insights, the survey is still an industry stalwart. Alan Gould, CEO of Encino, Calif.-based market research software provider Instantly Inc., formerly known as uSamp, aims to keep surveys a key element of a broader marketing research program, and he’s starting with panel management.

Marketing Insights caught up with Gould to learn more about the trends in online survey software, what matters most when putting together a qualified research panel, and how to glean high-quality data— and insights—from survey respondents.

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Q: USamp just announced its rebrand as Instantly Inc. What led to the rebranding, and how will it affect the company’s core offerings for marketing researchers?

A: We decided to rebrand as

Instantly because we felt it was time to bring all of our products and solutions under the same umbrella. … In order to stay ahead of consumer trends, our industry is seeking greater precision about when, where, how and in what form it sources insights from consumers, and by unifying our offerings, we give clients immediate access to everything from sample audiences for projects to insights tools. Our rebrand is about establishing Instantly as the company you go to when you want data and insights now.

Q: Instantly’s panel management platform has a database with millions of survey participants, allowing clients to find and leverage an audience of qualified survey respondents. How do you source this panel traffic to ensure that you’re engaging relevant participants?

A: [Our] ‘adaptive profiling’

technique creates efficiencies in the recruiting process. …

Essentially, what we’re doing is using a kind of algorithm and

A

machine-learning about our panelists to ask them a single question to determine their eligibility, if you will, to take any one of the hundreds of surveys that are potentially coming through our system. … We’re trying to figure out the exact match that a panelist might have with a particular research firm.

We’ve completely reconstituted our own data base understanding of our panelists, and so we’ve written and created software that does this, and the more that we do it, the smarter we get at doing it. ...

We’ve built a panel [with millions] of folks worldwide who, at different times, have been active [survey participants]. It’s largely a panel that we’ve built and maintained—some online and, increasingly, some on mobile.

Q: Founders Matt Dusig and Gregg Lavin left the company in December 2013.

How has Instantly evolved since it was first launched in 2008 under the name United Sample? How has its role as a technology provider for the market research industry—not a market research company, itself—helped carve its niche in a crowded panelmanagement marketplace?

A: One of the things I did when I came in was essentially rebuild our core technology so that our business could be at scale. The

knowledge base

company had grown very fast off of a basic startup foundation, if you will. I’m a huge believer in quality—both quality in the datagathering process and quality in delivering [results], and I’m also a very big believer in data science as a process. These are big changes in the panel side that I’ve brought to [Instantly]. Secondarily, I’ve launched the Instantly [re]brand, where we are taking our own panel and turning it into insights and data to marketers directly, in addition to providing some sophisticated research tools. The goal of Instantly is simple: To become the Bloomberg terminal for marketers, so to speak: A place for a brand manager to go to get 50 to 70% of the answers to any question that [he] might have on demand. The goal is big and its broad.

[Our goal] is to allow marketing researchers to get the answers that they need, and technology is our competitive advantage in this space. If you were to visit our headquarters in LA, we have about 23,000 square feet, and three-quarters of it is taken up by engineers. We are far more an engineering and technology firm than we are a market research firm. … Our core proposition will remain that we’re primarily a tech firm that services the market research space.

Q: Survey research is a divisive issue among researchers today.

Instantly focuses its panel

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management software on mobile survey technology, but many still advocate for more traditional survey techniques. Where does mobile fit within a wellrounded survey research program? How will the role of mobile survey research continue to evolve or alter traditional market research?

A: Increasingly, in terms of

traditional survey work, the tension in the research industry

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right now is that you have a lot of folks who have operated off of very large brand trackers. By ‘large,’ I mean asking consumers a lot of questions. Typically, that’s been done in more recent years in an online, Web-based environment.

Once you move into a mobile world, your survey design has to change, so the products now that are being developed on the survey side are different: The way they look is different, and they’re much shorter form. We’re beginning to see changes driven by brand

marketers who want a certain percentage of their insights coming from folks who can be attached to specific location. If you’re going to do that, you can’t ask people 50 to 60 questions from devices that are four to five inches long. … We think that location-based research is going to be huge, period.

I see [mobile and traditional surveys] being used in combination. You’re going to want to know the location of a panelist, and potentially, depending on the research you’re doing, you may

want to do to passive tracking or passive tracking in combination with some Q&A. They’re going to work together over time.

Q: Thanks to the sheer amounts of data available today, there’s been an industry-wide surge of concern with data quality over data quantity. How can researchers weed out the white noise to ensure highquality data and, as a result, high-quality insights?

A: I wrote a letter to our

employees a couple months back that I released publicly. I stated that we’re essentially going to change our business model to focus only on working with clients who require the highest quality input, and therefore, reliable output and insight. Simply stated, if you’re doing research for a brand, and that brand appeals to a particular group of consumers, doing quality research means talking to their actual consumers— those who actually fit the profile of folks who are buying or considering buying their products.

The closer that you can actually get to that, the higher quality the data will be—assuming, of course, that your research methodology is correct. But before you even get to research methodology, you’re talking about people: Who are you talking to? How do you obtain them? There’s a real difference between actual consumers and a fanatic group of people who

just like to take surveys. The fanatics who like to take surveys may be willing to exchange their information for very little, but the data that they produce may or may not be helpful for a brand manager. One of the trends that we’re seeing is—increasingly over the last 40 years—brands that are more traditional, incumbent, are more at-risk today of losing out to a challenger than they’ve ever been because it’s easier to create, launch and distribute a new product than ever before. The insights that most brands are using today have to be measured against a [potential] challenger, and are you willing to test your ability to change, adapt and win the kinds of panelists that have been powering your insights?

Take the example in Chicago of [Oak Brook, Ill.-based] McDonald’s. My guess is that the new team at McDonald’s, especially inside the marketing team, are looking hard at all the research inputs that have been flowing into Mcdonald’s over the past 10 years. That’s a brand that

has a problem, in particular, with millennials. They’ve had declines in same-store sales and problems with the product mix, and so the research that they’re relying on to regain their footing against all kinds of other fast-and-casualstyle restaurants that have popped up in recent years. The research is becoming crucial. My guess is that [McDonald’s] is redoing all of those research relationships now because they don’t like the results that have been producing over the last 10 years for them.

You can go brand by brand of who’s having issues, and what we’re seeing is that those brand managers are starting to question the data sources that they’re plugged into, and they’re starting to question the amount of money that they’re spending on insights that they may not be willing to bet the company on. … The good news is that from our perspective, it’s possible to gather real consumers together, understand their digital consumer behavior, verify their actual physical behavior, and, in

“You can go brand by brand of who’s having issues, and what we’re seeing is that those brand managers are starting to question the data sources that they’re plugged into, and they’re starting to question the amount of money that they’re spending on insights that they may not be willing to bet the company on.” marketing insights January/February 2015

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an engaging way, make surveys an important part of answering a lot of the ‘why’ questions that researchers and brands ultimately have. But there is no other way to do this kind of verification without investing heavily in technology.

Q: Everyday consumers are flooded with survey requests on a daily basis. What steps should researchers take to avoid consumer survey fatigue or burnout?

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A: One of the ways that burnout

has traditionally occurred is, under the old system, you may have gotten past five, 10, 15 questions before the system figured out that you weren’t eligible to participate.

You do that a couple times and it causes a burnout. You might not be willing to come back to the panel even if you’re exactly the kind of person that a lot of other brands would want to talk to. We basically figured out how to do most qualifications [with a] single question. It also comes down to the general environment that

panels are operating in. You want [participants] to be engaged. We’re doing a lot of experimentation right now in terms of how we build community within panels, which hasn’t been done before.

Essentially, it’s about offering interactive opportunities and the ability for folks on particular panels to communicate with each other, creating more of a shared environment.

Q: But does that interaction within research panels enable a piggybacking

mentality among survey participants? How do you know that you’re getting unique, individual responses if participants are communicating with each other during the survey process?

A: Quality insights come from highly engaged panelists. …

People are not just supply. They need to be part of a community.

One way to create a community, for example, is to build consumer-facing experiences

that people want to participate in and, as an added benefit, also involve them in survey opportunities. In such a world, the activities of the community would not affect research integrity but would still yield valuable data that brands could gain insights from.

Q: For marketers, collecting data and culling action-oriented insights is only half the battle. Now that there’s an increasing pressure for marketers

and researchers to prove ROI, how can they best communicate datadriven results to company stakeholders?

A: It’s not easy to do, but clarity

is key and, in particular, clarity around the relationship between the problem and the data set being used to solve it. The issue for stockholders is trust: Can they trust you have correctly identified the problem, and can they trust that you are using the right data to solve it? mI

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SS Split screen

Marketers Raise your awareness. According to Henderson, every marketer needs a solid understanding of the importance of diversity within the marketplace in order to apply it within their brand’s overall marketing strategy. “If you’re using [non-cultural] methods to market to consumers, you’re missing out not only on the present, but certainly on the future,” she says.

Cultural Collaboration

Consumers today are bridging

by Melody Udell | Managing Editor connections  mudell@ama.org across the globe, resulting in an increasingly diverse international marketplace. As a result, global marketers are no longer stymied by emerging markets, and the opportunity to expand a brand’s global reach has never been more accessible. Yet despite fewer barriers to multiculturalism, the research community is still catching up: Fewer than 3% of all subjects in major research studies represent participants with diverse backgrounds, according to Geraldine Rosa Henderson, associate professor of marketing at Chicago-based Loyola University, and Jerome D. Williams, distinguished professor and Prudential Chair in Business at New Brunswick, N.J.-based Rutgers University.

In the latest issue of the AMA Journal Reader, Henderson and Williams summarize a collection of global diversity studies from the Journal of Public Policy & Marketing, and analyze how each contributes insight toward a broader framework for intercultural competency. “It’s interesting that most Fortune 500 companies are trying to build up their presence in the U.S. and abroad, and when you look at the largest countries, India and China account for a huge percentage of the global population,” Henderson says. “[We need to] incorporate novel approaches that will help move the ball forward with our understanding of what’s happening in the multicultural marketplace.” mi To the right, Henderson shares the key points from her essay to help marketers and researchers implement recent diversity-related research and take steps toward cultural inclusion within the research community.

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Have a diverse workforce to deliver against a diverse marketplace. “You need to have people who’ve been steeped in different methods and approaches [on your team]. Hire people who have an awareness, sensitivity and openness to diverse marketplaces so that they can spot opportunities as they arrive.”

Researchers Understand diversity within data collection. “Make sure your sample is representative of the population you truly are interested in studying … and that people who are reading the data can interpret it in a way that makes sense, so that means they need to have some awareness and sensitivity, too.”

Work together. “Multicultural data is hard to get, so market researchers need to come together and move the ball forward by sharing their data and research.”

•org To read the essay in full—or for more thought leadership from leading marketing scholars—visit AMA.org/jreader.