Where things get tricky is fully understanding what quantitative research can do for you in your innovation process.

Put simply, quantitative research is a measurement tool. It does not measure behaviors; it only quantifies the prevalence of things in your study population. And these things are limited to the following:  perceptions, beliefs, attitudes, opinions, memory, and choices.

While we still ask about purchase intent frequently in quantitative surveys, debate exists about the question’s predictive ability. If you think about it, purchase intent is nothing more than an opinion or attitude at a point in time.

Purchase intent is often used to mitigate product launch risk. If enough of the right people give a “thumbs up,” an investment decision is recommended. The downside:  as Americans, we love choice. There is evidence that, in surveys, too many people “raise their hand” and a lot fewer follow through and buy.

We think that you should measure different things at each step in your innovation process. For example, what is the exact proportion of your target population who shares the motivating need or insight? Aside from purchase intent, how do we determine which idea or concept does the best job of addressing the identified need? What is the optimal combination of benefits and features that will drive the greatest customer utility? And, most importantly, what is the pricing expectation?

In the past few years, there have some significant advancements in our tools: Max Diff, Discrete Choice, Adaptive Choice Based Conjoint Analysis, and more. (All great terms to impress your friends and associates.) Each tool works best at different points in a Stage-Gate® process.

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There are, however, numerous ways to compensate for the inherent weaknesses of traditional concept testing.

Make the end-user first and ideas second.

Most organizations are “too good” at generating ideas. The result is that we see a lot of ideas in search of a need. We advocate flipping the process. Invest your research dollars on validating the human side of things:  needs, motivations, beliefs, behaviors, and pain points. Align your ideas to these opportunity areas. The end result is fewer, but higher-quality ideas.

Co-develop with end-users.

Organizations are getting much better at understanding and validating needs. From there, it is the job of R&D, product development, or marketing to translate needs into ideas and concepts. Without immediate end-user feedback, you may be forced to go back and validate your ideas. There is mounting evidence that co-creating with your end-users yields much better (and faster) results.

There is “good enough” research.

The key to innovation success is to listen and observe end-users. More focus groups, site visits, and survey responses are always better, but time and money is limited. In many cases, the goal is to do enough to inspire and strengthen your intuition. The quality of responses is far better than the number of responses.

Focus more on behaviors vs. opinion.

Focus groups and surveys only gauge perceptions, opinions, beliefs, and attitudes. Observational research allows you to pinpoint behaviors. Past purchase data and Internet use is purely behavioral. So, instead of spending money on a concept test, why not put product ideas on an e-commerce site? If someone attempts to buy, you could always tell them it is out of stock. In a few days, you’ll get a better read on end-user demand than through a survey.

In the food industry, some manufacturers are eschewing concept tests altogether. They are investing in small batches of real product and setting up “lemonade stands” in stores to see if consumers are willing to buy. In this approach, researchers are getting consumer feedback and a behavioral response at the same time.

Quantitative concept testing can be an important tool. It has obvious limitations, and is not a substitute for building empathy for end-users. Before embarking on the next survey, ask yourself:  do I need to measure or do I need to understand?  If the answer is “to understand,” you really need a more human approach.

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While the company has a product development and marketing function, they’ve never invested in formal consumer research. Up to this point, they never saw the need.  Like many firms that get to this stage and size, growth can stall and as this CEO put it, “our decision makers are disconnected from the consumer.” He now thinks one part of the solution is to build an “ongoing program of consumer inquiry and evidence gathering.”

I challenged him on the word choice and accused him of sounding like an engineer. (Apologies to my engineer friends.) My response to him: “Did you build this company on inquiry and evidence?” After shifting in his seat for a few seconds, he answered “no.”   I continued: “What then was it that made you see a solution that no-one else saw?”  We went around a few times and he finally reached the answer I was pressing for: the company’s initial success was based on an insight, or a deep intuitive understanding of the consumer. This CEO could put himself in their shoes, better known as empathy.

That conversation helped him understand the importance of fostering the right balance of empathy and evidence when making decisions. As organizations grow, some become more risk intolerant. As such, hard evidence supports decision making and can trump the fuzzier concepts of intuition, insight, and instinct.

As our conversations progressed, this CEO quizzed me on what best performers do as it relates to their insights functions.  My first reaction was predictable: “You need to hire a person with this background and with these skills.”  He turned the tables on me: “Kip, you sound like a researcher.”  Touché.  “I want to know about the culture. How do the best performers behave?”  This caught me off guard.  I’ve never been asked this question before.  After a few days of reflection, I came up with this 5-point list.

1. Best performers are masters of empathy. They spend a lot of time with their consumers in a variety of settings:  at their homes, where they use the products, in stores, and in traditional research settings.
2. In their innovation process, they pull learning forward and push the decisions as late as possible.
3. Decision makers rely on objective facts and data but never discount the subjective. Numbers are important but so are the reasons behind a particular measurement.
4. They are a little paranoid about what they don’t know, and never feel like they know enough. At the same time, they are comfortable with ambiguity and rarely suffer from analysis paralysis.
5. Research is used to inspire and align teams, and rarely used to settle internal disputes or “prove a point.”

Looking back, this dialogue was a gift.  I’ve never thought about an insights culture.  The more I reflect on this list and the organizations we have worked with, I’m convinced that being a great insights organization is finding the right balance of empathy and evidence.  As innovators, we should never forget that we are making goods and services for real people.

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To date, our industry has focused on technological solutions to measure emotional response.  That is, hook people to machines for brain scans and to measure other biomarkers. These work, but they are expensive and inaccessible to many clients.

We think a more human approach is the answer.

If the foundation is trust, traditional qualitative research can be modified to ensure study participants have trust with the facilitator and others in the group.  More trust equals a deeper exchange than what is achieved with typical approaches.

So, you may be asking, what’s different?

The first and most obvious modification is the elimination of the one-way mirror.

We work closely with a behavioral scientist in tweaking our methodologies. She had never been to a focus group in the market research industry and was horrified by the mirror. Oops.

The role of the moderator is different

From our knowledge of behavioral sciences, building trust requires that the receiver of feedback be perceived as an equal and not an authority figure. This requires a thoughtful process in how the study itself and “moderator” are positioned to study participants. As an equal in the group, the “moderator” should also be prepared to fully participate.

The expression of emotions may require non-verbal tools.

Some people are not comfortable expressing emotions verbally. For example, we’ve had success in using emoticon cards. For some, it’s much easier to hold up a picture of what is going on inside versus stating it. For others, a simple anonymous writing exercise could help. In this technique, thoughts are written down and placed in a hat. The session leader reads the notes out loud and then fosters group discussion.

Advance relationship building is critical.

A function of trust-building is one-on-one time with the leader and participants in advance of a face-to-face meeting. With today’s technologies, this is very easy to do. Try a low-key mix-n-mingle before a session; too many study participants are stressed out from traffic when they arrive. We find it a little weird that in traditional focus groups, participants and the moderator don’t usually meet one another until they walk into the conference room.

There are still limits to what people will express in a group

Even if all of these changes are implemented, some will still be reluctant to fully open up. The group leader must still rely on body language and facial expressions for insight.  We’ve experimented with “Truth Booths” where participants record their reactions and thoughts privately for the moderator to review later. Think of it as a recorded confession without the priest.

There is indeed a middle ground between brain scans and the traditional focus group. With effort toward building trust, it is much easier to “peel back the onion” and understand emotional filters. One word of caution, though.  Be prepared for the group hug at the end of each session.

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It struck me that there was a common theme among all of these authors. For many innovations, it is very difficult for end-users to even recognize that they even have a need for something.

Early concept testing for the microwave oven and the mobile phone was not positive. At that point in time, consumers could not imagine the need for a large metal box that cooks with radiation. Similarly, one of the articles described how consumers struggled with understanding the usefulness of a briefcase-sized phone used in the car. A more recent example is Google Glass. With the ubiquitous smartphone, what exactly is the relative advantage of Internet access via a pair of glasses?

As researchers, a common postmortem conclusion is that we didn’t ask the right questions, or that we didn’t “nail the insight.” I’ve conducted and observed hundreds of focus groups over the past twenty years and for the most we do a good job of asking questions. More often than not, I find that study participants are terrible at giving answers.

The more we learn about how the brain works, it reveals several shortcomings with traditional qualitative research in the evaluation of new-to-world product concepts.

We Rely on the Wrong People

Deeply articulating the benefits of a never-seen-before innovation requires a highly-imaginative person—someone who can see beyond the hear-and-now. According to the Myers Briggs Type Indicator®, we know that three-quarters of U.S. adults are not optimal for this task. It is possible to screen for the right characteristics, and focus on the quality of the participant vs. the quantity.

Think Time

We also need to rethink the research process. The traditional approach to qualitative research is not optimal. Whether you are highly-imaginative or not, adults need think time. Hitting someone cold with a conceptual topic and expecting sparkling insights in 30 minutes is tremendously difficult.

Make it Tangible

The cognitive demands required to give feedback on something intangible are enormous. Most people find it difficult to visualize how a two-dimensional rendering can benefit them or incorporate into their life. Reaction to something tangible is much preferred—even if the early idea is made from construction paper and rubber bands.

A favorite sport among study observers is rating participants on their effectiveness. Yes, some participants are better than others. But, we need to put ourselves in the participants’ shoes and realize that what we ask them to do is not easy. No, participants are not brain dead. The problem is ours: we often fail to pick the right brains for the assignment and often do not set up the right environment so their brains can flourish. The science certainly continues to bear this out.

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Why Max?

A big challenge in new product development is prioritizing the features most important to end users.  A typical outcome of qualitative research and ideation is a long list of potential features and benefits.  Including all possible features in a first-generation product may not be technically feasible, or worse—cost prohibitive.  Furthermore, marketing needs to know which benefits to communicate.  There is only so much “marketing real estate” to emphasize the top benefits and features.  Max can sort this out.

The typical approach is a survey to determine importance of each feature and benefit and relationships to purchase intent.  The issue:  we often find that everything is important.

Alternatively, end-users can rank-order features and benefits.  There are two issues with this approach.  First, any list greater than five items is a mental puzzle; surveys are mind-numbing enough.  The second issue with rank-order is scale.  That is, you’ll end up with a first place, a second place, and so on, but you won’t know the relative difference between each position.

Max to the Rescue.

Max allows you to determine the relative importance for each item in a large list, including features or benefits.  The model presents 4-6 items at a time and asks customers to select their most and least preferred in the set.  A different combination of items is presented over several iterations; the model learns and begins to understand where customers are willing to make trade-offs.

Also, the output is easy to interpret.  The best way to think about it is a 100-point allocation across all items tested.  The more important the item, the more points it gets.  A key strength of Max is that the top items driving choice are very easy to isolate, giving product developers and marketers much clearer direction.

Max at Work.

Max is extremely versatile as demonstrated by these recent case studies.

• An early childhood learning center was trying to determine which features were most important to its target consumer. The list was 20-items long and included curriculum, abundant computers, foreign language classes, and music instruction.  Marketing was struggling on how to differentiate the business.  Turns out “quality of care” trumped all factors, but every center claimed this.  It was decided to focus on the second most important attribute:  the center’s unique curriculum.
• A manufacturer of lawn and garden products offered its specialty retail partners a variety of value-add services. It hypothesized that a small subset of these services was directly related to loyalty and repeat purchases. Max supported a narrowing of its value-add services down to three.  The subsequent cost savings allowed the client to shift additional resources to those programs that mattered.

We are strong proponents of Max in the innovation process, especially when the goal is to narrow down the specific features and benefits most likely to drive purchase.  Because of his strength and simplicity, Max is indeed our new BFF.

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I really hesitated in writing an article about Insights. I could imagine the groans because this is the most overused word in my profession, but bear with me, as I would like to give you a different look.

Let’s start off with defining what an insight is not. It is NOT a fact or data point. Rarely will an insight emerge from a single data point. In quantitative research, you can string together several data points from one or multiple studies to create an insight.

Sometimes insights emerge from completely unrelated topics. For example, a colleague of mine used to run innovation for a large hotelier. She happened to be reading a book about homelessness and it dawned on her that in many respects business travelers are homeless. This merging of concepts gave her organization a fresh perspective on how they can better meet the needs of their customers.

“Insight moments” also emerge during qualitative research. Through listening and observing we develop this deep understanding of the consumer and situation.

I think there are two predictors of creating great insights: One is Grey Hair and the other is Grey Matter.

I think life experience (aka grey hair) is essential to creating great insights. I recall some focus groups a few years ago where a young marketer was struggling to embrace the feedback he was getting from home improvement consumers. I asked him if he had ever renovated a home, and I quickly learned that he never even owned a home. He completely lacked the experience – and hence, the empathy – for the people he was charged to persuade. The older you get, the easier it becomes to start recognizing patterns in human behavior and beliefs that can lead to great insights.

The other predictor is grey matter. I’ve been “doing research” for a long time now, and some people have the gift and some don’t. It is a learned skill, but some folks struggle mightily. There’s a very human reason for this: some brains aren’t wired that way.

As many of you know, I am a student of Jungian psychology and the Myers-Briggs Type Indicator. The most successful insightful researchers I’ve encountered are those who are highly intuitive. That is, their brains are great at assembling disparate pieces of information and also seeing the big picture. Insights come to this person in a flash; They could never recite a step-by-step process for creating one.

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For example, do these sound familiar?

• You’re leading a workshop to align a team on an important initiative. Half of the participants dominate the conversation and the other half don’t say a word.
• You’re running an ideation session, and it’s falling flat.
• You’re watching focus group participants struggle to articulate what they think of your new product concept.

The problem is not motivation or personality. The problem is you don’t have the “right brains” in the room, or you lack the skills to make the most of each person’s thinking style. Mastering the concept of cognitive style is essential if you want to maximize the skills and abilities of the people in the innovation process, whether an internal team or study participants.

Cognitive style refers to how people absorb information, how they process and express it, and how they solve problems. As Richard Scholl of the University of Rhode Island puts it, “cognitive style is less about the decisions that individuals actually make and more about the process used to make them.”

We’re all different. Some of us are extroverted, and others are introverted. Some people can clearly express feelings about an idea, while other brains find this tremendously difficult. A lot of us are grounded by facts; and others more intuitive. These differences are rarely reflected in job titles or demographics, although that is usually where we start in pulling together innovation teams or research participants.

For innovation managers, the key to putting the right brains in the room is to match the cognitive style of team members to the tasks at hand. And that goes double for researchers looking for the right research participants.

For example, we recently completed a client ideation session to generate new product ideas. Prior to the session, we profiled all 12 people on the team: all but two were highly-sensing. That means that 10 of the people had a cognitive style that is especially sensitive to deficiencies in process. We warned our client and the results were predictable. Instead of generating breakthrough ideas, we spent four hours discussing issues about the current customer journey. A clear mismatch between the task and the people needed to complete the task.

Here’s another example. Last year, we coordinated focus groups on home furnace maintenance with the same goal—generate new product ideas. Our concern was that the insights would be dull and uninspiring. Therefore, we loaded the group with consumers hard-wired to tell stories. We gave them permission to think broadly about furnace maintenance, indoor air quality, and overall health and well-being. The results were, well, magical.

The bottom line: there is a human side to innovation. Understanding cognitive styles helps you make the most of the people in your innovation process.

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In spite of being notoriously unreliable, asking whether your target customer intends to purchase your new-to-world product is fairly standard in research to support product development decisions.  And, it can be completely useless information.

Purchase intent has some value in fast-moving consumer goods where the metric is captured during concept testing, and then married with eventual sales.  After numerous product launches, these ratios can help winnow down concepts that are more likely to do better in the marketplace.  However, if you have a new-to-world concept, are a B2B marketer, or in a niche space, there are few (if any) comparisons.  Knowing that 40% of those surveyed are “likely to purchase” something never seen before is, well, academic.

Think of it this way:  as human beings, many of us tend not to recognize problems that have no immediate solutions.  A review of past “new-to-world” product launches explains the conundrum.  When the cellular telephone was introduced, the intent-to-purchase numbers were very low—people simply could not imagine why they would need to be in touch 24/7.  The microwave oven was another example that would never have been launched if marketers had relied on intent-to-purchase numbers.

So, what should you do?

Learn to rely more on the voice of the customer, and not be bogged down by making a go/no-go decision only on quantitative metrics like purchase intent.  Throughout your innovation process, incorporate these proven techniques:

• Learn the secret of insight-based innovation.  Research indicates that many successful product launches are based on meeting an unarticulated need.  That is, designing solutions based on a deep understanding or belief of the target customer.  It’s not easy, and this is never accomplished via a survey.
• Tap into people’s imagination.  When getting feedback on new-to-world concepts, you often have to ask participants to imagine how they might use the product, or to describe a person who would benefit from the idea.  This relies on sophisticated projective techniques.  Done properly, it can shed tremendous insight on the concept’s value proposition.
• Ask the right people for feedback.  Not all of us have the innate ability and imagination to project how we might use a new concept.  Studies estimate that the proportion of these highly-intuitive types is less than 20% of the population.  You may need to conduct additional screening to find those that can give you feedback beyond the here-and-now, but it’s worth the effort.
• Listen for the intensity of feedback.  In every new product launch, there will be early adopters.  While they may be small in number, it is their intensity that matters.  Find those people who raise their hand and say, “I’ve got to have this, right now.”  Understand the reasons for their enthusiasm, and use your intuition to determine if these reasons can eventually apply to the masses.
• Follow Your Gut. The role of vision and courage in new product development cannot be underestimated. While marketing research has an important role in all of the phases of bringing new products and services to market, at the end of the day, you may just have to take that leap. However, by developing a deep understanding of consumers’ needs, and the problem you are solving for them, you can increase your chances of a safe landing.

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So what is it about these more successful product introductions?  They tend to come from companies with a well-defined product development process with strict criteria for go/no-go decisions.  This leads  to more new product successes and fewer post-launch failures in the marketplace, which can be expensive and embarrassing.

Stage-Gate International explains, “top performing organizations also have a higher percentage of product cancellations before launch when compared to bottom performers.  The percentage of pre-launch kills is greater than commercial failures for top performers, while bottom performers have a higher percentage of failures than kills.”

Why Stuff Fails

Joan Schneider and Julie Hall, writing in the Harvard Business Review, identified “40 Ways to Crash a Product Launch.” Aligned with each product development phase, the reasons ranged from a faulty product development process to misguided sales and marketing.

Among the 40 launch-crashers cited by Schneider and Hall, there are nine that can be directly addressed by better understanding the customer:

• No marketing research on the product or the market has been done, at all. (This is painful to read.)
• The product is interesting but lacks a precise market.
• The product is untested by consumers; only the company can assert its benefits.
• The launch is aimed at the wrong target audience.
• The ad campaign is untested and ineffective.
• Line extensions aren’t test-marketed as thoroughly as the original product, so they fail.
• Consumers don’t understand how the product works.
• The product is priced to high.
• Consumers are unclear about who the product is geared.

Get Better at Killing Concepts

“Kill early and kill often” should be your mantra.  But, how do you make your new product development process a ruthless concept-killing machine?  Do your homework.

Customer input and rigorous analysis gives you the weapons to identify and eliminate weak concepts before you invest too many resources.  Indeed, the more you know about customers and their needs, the less likely you will be to have to kill a product before or after launch.  So “kill early and kill often” by supporting the new product development process with the information and research necessary to improve the odds of market success.

Marketing research can provide information for both new products and revitalizing existing products. Given the costs involved in innovation, research and development, commercialization and market launch, investing in marketing research in the new product development process is simply good business.

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