Many of those website owners, however, went on to discover just how tricky it is to analyze behavioral data. It might appear impressive that your company’s website traffic increased by 25% last month, but look a little closer and it may not be clear why. Did search rankings change, allowing people to find you more easily through search engines? Is it because a misleading paragraph on the home page is attracting customers who immediately click away when they realize they’re looking for an entirely different product? Or is it because an offline marketing campaign for your company’s website is has been surprisingly successful?

We recently completed a study on using web analytics in market research and uncovered some of the more challenging issues our members face:

• Challenge #1: Online segmentation is difficult without authentication information.
• Challenge #2: Web analytics efforts can collect an enormous amount of data, but determining what is useful and what is not is more ambiguous than one might think.
• Challenge #3: Web analytics is hard to explain to researchers and business partners alike.
• Challenge #4: Web analytics teams are not always well structured to integrate with market research.

Despite these challenges, web analytics can become a powerful tool for market research, whether to perform online segmentation or to increase sales conversions and lead generation. And, with the skyrocketing number of consumer transactions occurring online, it’s no longer an option to ignore how people are using your website.

MREB members, read our latest whitepaper An Introduction to Web Analytics to learn more about these challenges and how to overcome them.

Related Blogs:

• Segment Online, Even With Limited Data

Related Resources:

• Segment Online Consumers
• Integrating Analytics into Market Research
• Changing Role of Analytics for Market Research

As we’ve charted developments in the internal social media and collaboration space, we’ve seen many over-invest in the latest and greatest technology platforms. These efforts, such as implementing internal Facebook or Twitter-esque applications, met initial enthusiasm only then to see early adoption rates plummet and to struggle justifying value created for the business.

For the most part, these efforts failed because the platforms were non-intuitive and without an obvious purpose or benefit. Many companies wasted time and effort on employee sharing solutions that simply couldn’t compete with employees’ personal options. Before you begin experimenting with new social media options for employees, here’s what you need to beware of:

• With significant investment and application of the right principles, companies can create tremendous value from tools that allow employees to connect with and learn from one another. (see how one pharmaceutical company launched a wiki-style site to facilitate easy consumption of organizational knowledge)
• Companies should beware of efforts that require significant investment but feel unnatural for employees to use; these efforts will disappoint.
• Consider leveraging existing live and virtual employee interactions to redirect energy towards strategies that encourage peer learning. (for example, Research at Texas Instruments and Sabre Holdings have used this technology to identify expert opinions and tacit information)

The question for companies is not simply, How do we use internal social media to better communicate with our employees?, but also, How does my organization use social media as a collaboration and learning tool to drive employee performance and productivity?

The Four Fs of Social Media Collaboration

To answer this question, I turn to a framework in use by leading HR practitioners and developed by our sister program, CLC Human Resources. In their research, they simplify the 4 Keys to Effective Social Media-Enabled Collaboration into the easy-to-remember four Fs:

1. Focus: Aligning social media collaboration objectives with business objectives
2. InFrastructure: Selecting a platform that supports these objectives (admittedly a bit forced on the F here!)
3. Filter: connecting individuals with relevant, just-in-time information
4. Facilitate: Managing collaboration efficiently and effectively

And perhaps these points can go beyond just internal corporate collaboration.  Could the same framework be used to better engage respondents in research efforts?

Member resources:

• Texas Instruments and Sabre Holdings: Collecting information via social network technologies
• Wiki-style organization knowledge management
• Tools to build and share your company’s organizational knowledge
• General Motors’ informal intelligence network
• Passionate communities: Using engaged customer to get more from social media listening

Related blogs:

• “All of Us is Smarter than Any of Us”
• Knowledge Management: The Next Generation
• Greek to Me: Building a Strategic Relationship with IT

Like the function itself, we’re seeing many of our members evolve the name or brand that they use to describe their functions.  In fact, while our brand, the Market Research Executive Board®, has stayed consistent during our 10+ years of existence, many of our members no longer call themselves “Market Research.”  We did an informal poll late last year and estimate that about half of our members lead functions with the name “Market Research”.  Our membership now includes Insights, Intelligence, Analytics, and Customer Knowledge functions, and I’d invite you to leave a comment below to let us know what other names exist for Research within our membership.  While the names vary, the responsibilities and areas of focus tend to remain consistent, with a majority of our members working to position themselves as strategic partners. 

So what’s in a name anyway?

Some of our members rename their functions to more accurately describe the value they provide to the business.  Market Research, for example, can imply a focus on process and data instead of insights and decision making.  With most of our members aiming to be more than “data providers,” a rebranding often makes sense.

As part of our work on Embedding Customer Knowledge into the Business, we identified three different eras or phases for Research.  Fifteen to twenty years ago was the Era of Research as Methodology Expert.  The primary value that Research provided was around research innovation and project execution – and because information was scarce and Research was still perfecting methodologies, all customer information was new information.  Since then, the function has continued to evolve.  Approximately 10 years ago, we saw the advent of the second era – the Era of the Insight Consultant.  Sometimes I describe this as the “so what” era, where Research has transitioned from providing data and information to calling out the implications of that learning – and helping business partners plug that knowledge into business decisions. 

We don’t see the Era of the Insight Consultant disappearing anytime soon.  Having said that, becoming a trusted advisor requires most researchers to spend a lot of time with a limited number of decision makers.  As functions work to increase their impact and improve the company’s overall customer acumen, we’re seeing many functions focus on capabilities that include synthesis, socialization, and storytelling.  All of this is typically in an effort to share customer knowledge with a greater number of decision makers. It’s what we call the Knowledge Era, and it’s led a few of our members to brand themselves as Customer (or Consumer) Knowledge functions.

As you consider what the next-generation of Research looks like at your own company, here’s how we can help:

• Anatomy of a Business-Impact Focused Research Organization – prioritize those opportunities most likely to create value for your business partners
• Research Skills Diagnostic – evaluate your team’s current strengths and opportunities when it comes to developing Version 2.0 Researchers
• Planning for a Next Generation Research Function
• Embedding Knowledge into the Organization

In 2010, Design that Matters received widespread recognition for its innovative neonatal incubator. The innovation: the incubator ran off car parts.

Neonatal incubators are an effective tool against infant mortality, as about half of infant deaths worldwide (about 1.8 million infants total) can be attributed to a lack of a consistent heat until they have the body fat and metabolic rate to stay warm. The incubation challenge is extremely difficult in developing countries, where donated incubators fix the problem, until they break. Then they sit, unused, for lack of spare parts or repair know-how. But what did the design team see along with piles of broken, discarded medical devices? Countless old cars, trucks, and SUVs somehow coaxed into running smoothly. The lightbulb went off – if an incubator was built from car parts, mechanics could easily provide needed maintenance and repairs. The resulting incubator is pretty neat, with dashboard fans for circulation, signal lights and door chimes for alarms, a car battery to keep it running even in power outages, and headlights to provide heat.

This is a clever, and more importantly valuable, design. But again… market research? What’s the connection?

Design that Matters recognized a disconnect between the way incubators were built and the environment in which they were being used. MREB Research has shown a similar disconnect in the way that Research functions provide information to the business and the way that executives consume information.  The design team re-conceived the incubator to fit the constrains of its environment… how can Research re-conceive its information distribution processes to fit the new business environment?

We’ve seen companies doing just that – embedding customer knowledge in a way that fits executive decision-making processes:

1)      Focusing research scoping and execution for fast delivery to inform urgent decisions

2)      Using existing information flow to reach executives

3)      Engineering learning moments to correct over-confidence

MREB members, learn more about embedding customer knowledge into the business.

Related blogs:

• How to Teach a Know-It-All
• Don’t Try to Overpower Other Info Sources, Co-Opt Them
• 2 Ways to Get Executive the Information They Need, Fast

In the world of market research, however, good change can be hard to come by. How do we know which new methodologies are going to stick around and which innovations will instead share the fate of the Segway and Honegar?

In a perfect world, every new methodology would be faster, cheaper, and better at providing deep and relevant insight. In the real world, methodology innovation is more likely to succeed when:

• It is done purposefully, with a business need in mind. Teams can innovate selectively by identifying questions that cannot be answered with traditional methods, or by finding gaps in existing knowledge.
• There are structures and processes in place to support and encourage innovation.

Unilever was able to reduce new products’ time to market by 20% with their Standards-Based Methodology Innovation Cycle. A detailed set of best practices provides a benchmark against which new information sources can be evaluated, and helps to create clear innovation priorities. Ideas are solicited from a select group of suppliers and screened through a resource-efficient evaluation process.

Unilever created a great support structure around smart methodology innovation by tying change to business needs. Stay tuned to hear more ways new and better methodologies can be successfully integrated into your active portfolio, and in the mean time, check out our latest observations on methodology innovation.

Related resources:

• Unilever’s Standards-Based Methodology Innovation Cycle
• Illuminating the Unconscious: Using Neuroscience Techniques to Gain Deeper Insight
• Applying Neuroscience to Business Decisions

50 years later, we have computers, and algorithms which used to take days to run now only take seconds. While analysts of ages past were often slaves to Excel and had to build their own bridges, data analysis nowadays is easy and comes complete with nice intuitive graphic interfaces. This democratization of data has made marketers happy and market researchers somewhat weary.

Why? Because market researchers think it their prerogative to keep tabs on what’s going out to their business partners. When marketers brought home an analytics team, often conveniently embedded in their own function, market research sulked over their loss of control. When the analytics team started brandishing social media listening tools and data mining algorithms, some marketing functions started wondering if market research will go the way of dinosaurs with their surveys and focus groups. This premature tendency to ditch established methods is what one might call the Shiny Object Syndrome in analytics.

In reality however, this war of methods is much less a fight to the death than it is a simple redrawing of boundaries.  Some toes may be stepped on, but no one’s head should be rolling. In fact, on a higher level, it is driven by a common urgency to better understand the consumer and the ecosystem he/she lives in. When we polled our members earlier this year, marketers say they want to strive for agility partly through better use of data and market researchers say they’re aiming for more relevance through methodology innovation. It seems reasonable to conclude that the smart market researcher would work with, instead of around or against the analytics team, using the newer methods to sharpen and inform the traditional ones. At the same time, the smart marketer would know to take advantage of what both teams have to offer to get at a more holistic picture of the customer and the marketplace.

From my particular perch – where I do data analysis and also listen to our members talk about their data strategy, there seem to be at least two ways that traditional and new methods complement each other:

• New methods excel at getting the “what;” traditional methods excel at getting the “why.” Freaky as it may be, if a company can collect, buy, link and mine my transactional, browsing and social media data then their knowledge of me is 1000 times better than if I’d sat in a focus group for 3 hours. But to act on that knowledge, one has to know why I did the things I did or even why I did them in a particular order. Why did I for example, looked at one website but bought from another? Was it because of simpler checkout? Lower price? More selection? Detailed reviews? More product views? Or a combination of the above? Understanding my deeper motivation in its granular detail would require some conversation, which you could get through a focus group conversation or through a targeted survey. To drive the point home, this is a bit like digging for gold, your new method is the metal detector, your traditional method is the shovel. You need both to succeed.
• New methods are “data led,” traditional methods and “hypothesis led.” Whether it is writing a survey or conducting focus groups, one usually goes in with a list of things to prove or disprove – be it orange packaging improves perception or factor A drives customer loyalty. Hypotheses may be modified or scratched, but the process always starts with a story, however vague at first. With newer methods like data mining, the process is flipped on its head, you go in being open-minded about all possibilities, scanning the entire terrain to see which one data seem to support, then pressure test it for a credible story. To “think outside the box,” data mining adds unique value by allowing you to start without one. Whichever way you choose, where you start is much less important than finally coming full circle to the reasonable conclusion.

How has new data sources/new methodology worked for you? Success story? Headache? Leave me a comment or email me at ykang@executiveboard.com.

Related blogs:

• Don’t Try to Overpower Other Info Sources, Co-Opt Them
• Analytics as Competitive Advantage
• Will Social Networks Really Help Product Innovation?

Related resources:

• Integrating Analytics into Market Research
• Changing Role of Analytics for Market Research
• Microsoft’s Data Analytics Tool and Market Research Seal of Approval
• Applying Neuroscience to Business Decisions

According to some, the world is in a state of stagnation when it comes to innovation. Last year, in reaction to that, I asked if there weren’t still pieces of low-hanging fruit in management – are there things that innovation processes don’t consider? Places managers don’t look for innovative ideas?

We’ve noted that ideas and products that derive from customer-focused innovation processes are most likely to survive and succeed in the marketplace, so part of our recently-launched Marketer’s Playbook (which anyone at a company with an MLC membership can access using the same username and password you use for the MREB site) is a section on innovating with customers in mind . We think if you can convincingly cover all three of these bases, you’ll be well on your way to creating great, consumer-focused innovations:

Incorporate customer insight. There are limitations to using existing products as a point of reference for insight generation, but companies have seen great success by harnessing the creativity of lead users during the product development process. You can also use existing customers to surface underappreciated needs and market trends.  Surface unstated customer needs by focusing first on the task your customer is trying to accomplish with your product and then on how your customer measures success once they’ve completed the task.

Incorporate employee insight. Your customers aren’t the only ones that should be involved in the innovation process – employees are a great source of ideas about where to go next (as GM harnessed with their intelligence network) , but not in the ways you might think. You need to leverage employee insight and creativity across the organization in focused ways, and establish sensible guardrails to ensure employee-generated innovation stays relevant to the brand.

Build an effective team. Insights from customers and employees aren’t enough; an effective innovation process ends with a great team that turns insights into defensible products and services.

Related Blogs:

• Right People, Right Question is the Mantra of Open Innovation
• Need Innovation?  Look to the Humanities
• Lego’s Building Blocks of Innovation

Working with new (or even “new-to-me”) technology can be a hard transition to make. “How does it work?” “What is it good for?” “Is it worth it?” “This just feels… wrong!”

Nobody knows this challenge better than the Market Researcher faced with the array of new methods and data sources enabled by technology improvements over the past several years. Is Research keeping up with these changes, or are we still playing Atari?

There are increasingly more – and increasingly sophisticated – ways to collect information about customers and consumers. Advances in data collection methods, storage, and modeling make it possible to gain an understanding of customer behavior to a degree previously unattainable. On the other end of the spectrum are methodological advances like neuroscience and mobile research.

Is it worth it? Early indicators point to yes. More data certainly presents an opportunity to generate more holistic customer insights. From the opposite perspective, might the expanding sources of customer data present a potential threat to the unique value that Research has for the business?

The MREB is tackling this topic in its major research initiative for 2012, Rebalancing the Insight Portfolio. Members, read more about our latest observations pulled from interviews with your peers and take a look at some of our early hypotheses.

Much of the recent buzz around neuroscience in market research has centered on expensive brain scans, but if your research budget isn’t quite on par with that of a large university lab, there’s no need to be discouraged. Research functions with fewer resources can still harness the power of neuroscience in more budget-friendly ways. Here are some “neuro-lite” options that utilize what we know about how the brain works in order to access consumers’ subconscious reactions:

• The Implicit Association Test (IAT) relies on the theory that people can make quicker connections between concepts that are already closely tied in their minds.
•  The Zaltman Metaphor Elicitation Technique (ZMET®) is built on the idea that the metaphors that people frequently use in conversation can reveal hidden meaning.
•  The Facial Action Coding System (FACS) classifies 46 distinct facial movements to identify consumers’ true emotions. FACS also aids trained observers in catching “microexpressions” that are difficult to fake or conceal and flash across the face only momentarily.

Read about other low-tech neuroscience options, as well as how and when to use them, in the Market Research Executive Board’s new white paper: Using Neuroscience Techniques to Gain Deeper Insight.

Executives’ “gut” understanding of the customer/ marketplace, built through experience, is liable to all sorts of cognitive biases and has the danger of being outdated. But when an executive is making a customer-facing decision, they rely mostly on that gut – a phenomenon that threatens smart decision-making.  How can Research break through to people who are mistakenly confident in an outdated or biased view of the customer?

The answer lies in attacking the root cause – the confidence. Leading Researchers are shaking up executive confidence by demonstrating the wrongness or incompleteness of executive knowledge, provoking insecurity and curiosity. 

That’s not enough, though – Research then has to re-shape the gut correctly. Using highly authentic, realistic, and interactive teaching (mimicking the experience that had contributed to their original gut) re-builds executive knowledge, and re-builds their confidence in the new knowledge.

(A great aspect to these approaches? They work across the spectrum of decision-makers, from the resistant-to-learning type to the naturally curious.)

MREB Members, learn more about engineering learning moments.

Related blogs:

• Don’t Try to Overpower Other Info Sources, Co-Opt Them
• 2 Ways to Get Executive the Information They Need, Fast