Foresight 20/20

There is a good article in Strategy + Business about Consumer Choice Modeling.  Consumer Choice Modeling is a tool to project how well different product options and their attributes will do in the market.  Rather than being a simple preference test, it projects the consumer's likely behavior at the store shelf, given a specific set of choices.  As an example, they said that this tool accurately predicted that Apple's first iPhone was priced too high, which the market subsequently validated.

I think tools like this are great.  However, problems arise when they are used at the wrong point in the process.  These tools are best used after a new product is defined; the benefits, the details of how they will work, and what they will cost are all worked out.  These tools do not help you to develop a breakthrough innovation from scratch.  For that you need to figure out what would motivate a consumer to try a new solution in the first place; what problem really needs to be solved. 

The reason these tools are often misused is that they deliver an answer with a high degree of certainty.  This makes people comfortable.  But it does not take the place of the deep understanding required to figure out what a new offering should be.  What they do is confirm or disprove the decisions that have been made so far, but they will not give you information to come up with the idea in the first place - unless the idea is an improvement on what already exists. 

Once again, it all comes down to clearly understanding the scope of your innovation effort.  If you are already working with an existing offering, and want to improve it, then you can start with tools like Consumer Choice Modeling.  If, however, you want to develop something new, then save the Consumer Choice Modeling tool until you reach a point at which you have developed a set of choices for the consumer to make.

I've been thinking about trends lately.  Not in how I might identify them, but in observing how other people think about them.  Some want to be trend setters.  Others are fearful that they will miss an opportunity if they fail to recognize a trend.  What's common in these points of view is that trends are often seen as isolated occurrances that spring out of nowhere.  They see trendwatchers as people with a crystal ball who predict the future.  I don't agree that this is true, and for that reason I don't base my decisions on predictions by trend forecasting companies.  If I read them at all, it's to understand why they made the prediction. 

Then yesterday I was pleasantly surprised.  I was looking at trendwatching.com's top 15 trends for 2009.  In it they defined a trend as:  "A manifestation of something that has unlocked or newly serviced an existing (and hardly ever changing) consumer need,* desire, want, or value."

Bingo!  They went on to say that basic human values don't really change.  What does change are the social and economic contexts in which we live, which may surface issues that haven't concerned our society in a long time.  Technology is always evolving, giving us new ways to express or satisfy our current concerns.  On the surface, it may look like new trends are emerging that we have never encountered before.  And while it's true that we haven't encountered the specific expressions before, if we dig a little deeper we will find that the underlying drivers have not changed much at all.  Digging deeper is where we will find our answers.

And while we're speaking of trends, one trend I am seeing lately is the fact that more organizations are recognizing the importance of understanding consumer values and motivations as a way to succeed in the long term.  Their bigger issues are in translating these values into products and services that will satisfy consumer needs within today's social, economic and technological contexts.  When they get that translation right, they won't have to worry about trends, because they'll be transcending them. 

Now that's an underlying recipe for success that doesn't change.

For the last few months, I've been fortunate enough to be a participant in Seth Godin's online experiment - Triiibes.  This is a learning community, (currently, membership is by invitation only) and participants are actively exploring questions about the future of markets and marketing, and the forces that are changing the competitive landscape.  It has been a companion experiment to his latest book:  Tribes - We Need You To Lead Us.  I have learned enormously from the experiment, and offer thanks to Seth for starting it, and to the fellow community members for their participation and enlightened perspectives.

This week, Seth launches the book at an event in New York City.  It offers a new perspective that the future of successful marketing lies in the ability to create, connect and lead tribes.  Why is this important?  Because as innovators we need to learn to rally support from within our companies, our clients, and our peers.  Without the support we need from others we cannot succeed. Without strength in numbers, what we are doing is too scary for most people to support us.  We need to acknowledge their need to belong and believe in something greater than they can imagine today.  We do this for a living, and it's our responsibility to show the way.

In addition to the book, Triiibes - the online community, has collaborated on an ebook of tribal case studies.  Each one discusses elements that get to the heart of what makes tribes successful.  It's available to download for free, and I feel fortunate to have had two case studies selected for inclusion. Download, enjoy, and share!

updatedtribescasebook.pdf (2.97 mb)

I recently wrote about how good design embraces constraints.  In the comments, Kelly asked how we should go about focusing a client on the possible design constraints upfront in the process.  This is a good question, and the extent to which you can identify all the constraints upfront depends on the extent to which you are looking to improve the existing offering, or you are looking for a breakthrough.

In my experience, if you are looking to improve on an existing offering, the real constraints typically consist of tangible boundaries that are easy to identify.  These would be things like current manufacturing processes, distribution channels, category definition, and organizational structures.  If the new design needs to fit within these constraints, the designer should be made aware of them in the beginning.  It is then part of the designers job to creatively work within these constraints.  For example, if I am a company that manufactures padlocks, and I am improving my current product, the constraints should be easy to identify.

On the other hand, if you want to develop a breakthrough innovation, it is necessary to understand that one of the most important outcomes of the project will be to indentify the constraints.  In this case the real constraints tend to be less tangible, consisting of things like the consumers' culture, and macroeconomic regulations and conditions.  Any of the constraints listed above would be self-imposed.  Back to the padlock example, if I want to develop a breakthrough innovation, defining my company as a padlock company would be unnecessarily limiting.  I could redefine the company as a security company, and a whole world of options opens up.  The real constraints for how consumers perceive security would need to be indentified as part of the project, before potential solutions are explored.  Once potential solutions are explored and selected, the next set of constraints needs to be defined.  These would be things like where, how they will be made, new organizational processes that will be needed, which categories will now define the offering, etc.

The point is that regardless of the type of project you are undertaking, the constraints should be identified before the designer starts designing anything.  If we are trying to do something truly new, we should be aware that defining constraints is part of the process, and we should be prepared for the reality that current constraints may not need to be imposed on future offerings.

I was advising a client on how to collect some qualitative and quantitative research. He wanted to combine all the questions into one survey.  I cautioned him about collecting too many qualitative responses, and suggested that we may want to do two separate studies.

"Won't that take forever?" he asked? I responded that it wouldn't take that long, because we wouldn't need many responses in the qualitative part.  "But that's not statistically significant!" was his reply.  He had the understanding that no matter what type of research you're doing, statistical significance meant that you needed at least 500 respondents.  We then had a good conversation about what statistical significance means.

Statistical significance is a term used to describe the confidence level with which you can use the results of your study to project how the broader population will respond.  For example, if you are doing a quantitative study to find out how many people identify positively with your brand, you may collect 1000 responses recruited to represent proportions of the population.  If 800 of those people identify positively with your brand, you may say with a high degree of confidence that approximately 80% of the population identifies positively with your brand.  There are charts that can tell you exactly what that degree of confidence is, and that is your measure of statistical significance.

But let's say that you want to understand the associations with your brand more deeply.  You want to know how it makes people feel.  You can't ask this type of information in a quantitative survey without making some assumptions, so you decide to do some in-depth interviewing to find out how your brand makes consumers feel.  In each interview, you need to have time for a longer conversation about the consumer's values.  Even if you talk to a large group of people, if you don't go deeply enough to get an understanding of their values, your confidence level for understanding what those values are is pretty low.

In following this example through, suppose that in interviews with 10 people who love your brand, we find out that it gives them a greater sense of control than your competitors' brands.  These consumers may not have said this directly, but in 10 interviews, we were able to actively think about what we learned, and draw this conclusion with a high level of confidence. 

Would we project this conclusion onto the population at large?  No.  While we have a high level of confidence that we know the issue, we don't have a high level of confidence that this issue is true for the broader population.  For that we need a quantitative study with a large sample size.

What does the term "statistical significance" mean at your company?  Remember that it is a measure of your level of confidence that you have the right answer.  This will vary based on what you are trying to learn, the size of your total population, and how deep you need to dig for answers.  If you are doing very in-depth qualitative research, remember this:  A large sample size may be less statistically significant, because you won't be confident that you could find the right answer in the first place.

My current client owns some of the world's largest online consumer communities in niche enthusiast segments.  Here are a few things I've learned about doing consumer research within established online communities.  I hope you find them useful.

1)    Get introduced to the community by the founder.  Have a profile, and let everyone know who you are and what you'll be doing.  Be transparent about this.

2)    Remember that you're not really "one of them".  You may be welcome, but you are their guest.

3)    If you're working with a passionate community, you can actually disrupt some of the traditional in-depth research techniques, and learn some very deep information very quickly.

4)    Still, there are some things you need to be with people, in person, to learn.  This will vary with each community.

5)    Make surveys as much like an informal interview as possible.  Make the questions informal, and communicate as similarly to the way they communicate on the site as possible.

6)    When executing a survey, remember that consumers hate pop-ups.  Don't you?

7)    Long questionnaires feel smarmy.  You know, the ones with multiple matrix tables that expect consumers to know the name of every feature on the site?  Yeah, those.

8)    I'm sure no one reading this would ever do the previous two points, but let's say there's a prior agreement with a third party, and you have one on your site.  Make sure the community knows that it didn't come from you, and that you wouldn't do that to them.  Graciously collect all complaints about them.

9)    In global communities, be careful with how you use incentives.  Rules vary by country, and international members could feel left out.

10)  Remember that passionate communities LOVE their site.  If they honestly believe you are working to make it better, they will bend over backward to help you.  Authenticity and genuine interest will be your most valuable tools.