Marketing Your Products as Designed by Users: Benefit or Hindrance?

The Boston Globe reported this weekend on the fascinating new research of Vienna University Professor Martin Schreier.   He studied the marketing of crowdsourced products.  Schreier found that marketing an item as user-designed tended to increase sales more than marketing a product as created by a firm's own designers.  Why this positive effect?  Schreier discovered that, "People believe their peers understand their needs better, and therefore, come up with better solutions."   Moroever, Schreier found that people tend to react more positively if informed that the user-designers had something in common with them.   For instance, female consumers tended to prefer user-designers who were women similar to them.  

Is there a potential downside to marketing a product as "user-designed"?  Schreier found that the effect does not appear to be positive for luxury items or high tech goods.  Why?  For technologically sophisticated products, the consumer trusts experts with high levels of knowledge and expertise more so than fellow users.  As for luxury items, the explanation is quite different.  In those cases, consumers "want to set themselves apart."  Thus, they tend not to prefer something sourced from the crowd.  

Engaging Your Consumer to Create New Products

Leading companies have become much more adept lately at co-creating new products in close partnership with their customers.  They do so in a number of ways, including intensive ethnographic research, crowdsourcing projects, social media contests, customer advisory councils, etc.  One example of an interesting approach is the "Do Us a Flavor" campaign conducted by the Lays brand of potato chips (owned by Pepsico).  This Knowledge@Wharton article describes the effort.  This excerpt explains how the program worked:

Anyone who had a chip idea in mind could visit Lays’ Facebook page, enter some information about their flavor and be rewarded with a shareable image of “their” bag of chips. The company teamed up with Facebook to turn the “like” button into a vote of “I’d Eat That.” Lays’ Facebook cover photo became a rotating billboard, which featured a new submission every few minutes.  A panel of judges and campaign spokespeople — celebrity chef Michael Symon and actress Eva Longoria — helped narrow the contest to three finalist flavors: sriracha, cheesy garlic bread and chicken and waffles, and then opened the vote for a winner to the public.

14 million people voted in this campaign, and the bags of chips for the three finalists flew off the shelves in a matter of hours.  Of course, the campaign's true value extends well beyond the sales of these new flavors of potato chips.  In my view, the value lies in the learning that is taking place as the campaign unfolds.  The brand managers identify flavors that excite customers, as well as those that clearly do not.   They also learn about the type of people most likely to engage closely with the company via social media.  Perhaps these customers share other important needs and wants along the way.   Moreover, the company engages the customer in a way that may lead to more sales for the brand overall.  They drive traffic to important retail partners, and they give those retailers something new and exciting to merchandise.  Finally, they help the company reach millennials, an important group for whom the brand may otherwise become less relevant amidst many new choices.  

Who is More Biased? The Crowd or the Expert?

 Shane Greenstein and Feng Zhu have published a new working paper titled, "Do Experts or Collective Intelligence Write With More Bias:  Evidence from Encyclopedia Brittanica and Wikipedia."  Their results surprised me.  I would have expected more bias from experts.  I thought the work of the crowd would mitigate biases by any particular contributors.  However, they found that Wikipedia entries exhibited more political bias than encyclopedia entries.  Here's what they said in their paper:  "Using a matched sample of pairs of articles from Britannica and Wikipedia, we show that, overall, Wikipedia articles are more slanted towards Democrat than Britannica articles, as well as more biased."  Perhaps not surprisingly, they did find that the Wikipedia articles tend to become less biased as they receive more and more revisions.  However, the overall analysis does show more bias with Wikipedia.  The scholars conclude, "It is surprising because the average Wikipedia article receives over 1,900 revisions and that is still not enough for eliminating bias."  

Amazing Evidence for the Wisdom of Crowds

Check out the amazing results of something called the "Good Judgment Project," profiled here by NPR.   Three psychologists - Philip Tetlock, Barbara Mellers and Don Moore - have created this project in collaboration with members of the government intelligence community.   Over the past three years, the researchers recruited roughly 3,000 people to make probability estimates about geopolitical issues such as the threat of a North Korean missile attack.   The NPR article profiles one such person, who happens to be a pharmacist living in Maryland.  She does not have any special expertise in international affairs.  She received some basic training in probability estimation, and then set out to respond to various questions posed to her by the researchers.  Her responses are among the most accurate of all 3,000 average citizens participating in the study.   She credits Google searches as her most useful tool for learning about an issue before making a prediction.  The NPR story indicates that, "According to one report, the predictions made by the Good Judgment Project are often better even than intelligence analysts with access to classified information, and many of the people involved in the project have been astonished by its success at making accurate predictions."  

What's going on here?  First, it clearly demonstrates the concept of the wisdom of crowds.  If you pool the collective intellect of a large, diverse group of people, you can often get the right answers more frequently than you can by relying on a few experts.  Of course, the wisdom of crowds only works if you have members of that large diverse group making independent judgments.  If people are influenced by others, then the wisdom of the crowd breaks down.  Second, as the story indicates, "If you want people to get better at making predictions, you need to keep score of how accurate their predictions turn out to be, so they have concrete feedback."  The researchers have done that throughout the study.  Finally, why do the experts often stumble?  Well, they are subject to many biases.  For instance, they often fall into the confirmation bias trap.  They may have more data at their disposal, but they often rely on the information that confirms their pre-existing views.   Moreover, the experts perhaps are not making independent judgements.  They may be influenced to a large degree by others in their work group or agency.  In that way, they may be subject to conformity pressures.  

Innovation: Working at the Boundaries

For years, we have known that successful innovations often come from people working in other disciplines. They bring deep knowledge in a related field, and just enough outside perspective, to solve a tough problem that individuals with years of experience in a particular field could not solve. Harvard Professor Karim Lakhani has studied crowdsourcing efforts and confirmed this result. He found that, "successful solvers solved problems at the boundary or outside of their fields of expertise, indicating a transfer of knowledge."

What does that mean for people trying to drive innovation within firms? I think it means finding ways to expose tough issues to people in different functional areas and silos. It means finding people working at those crucial boundaries. It means giving problem solvers access to the social networks of people working in related fields, thus expanding their perspectives.

Separating Needs and Concepts: How to Develop Great New Products

Professor Laura Kornish of Leeds School of Business at CU Boulder has a great post about crowdsourcing over at Fast Company.   She reminds us that we have to be careful when identifying our objectives during consumer research or crowdsourcing initiatives.   We have to separate the determination of the customers' needs from the development of a new product concept.   Here's an excerpt:

In traditional product development practice, there is a separation between gathering data from customers about their needs--via interviews, observations, focus groups, and surveys--and proposing new product concepts. The classic example of this separation is, "People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!" (Theodore Levitt’s example from Harvard Business Review, 1960). In that view, managers guiding innovation should consult the users for what needs to happen, not rely on the users themselves to dream big about how it can happen. Crowdsourcing in innovation allows us rethink this separation. We can ask the crowd directly to provide the solutions, then work backward to infer what is on their minds.

What wonderful advice!  Don't ask the customer to design the new product.   Seek to understand what the unmet need of the customer is!   We don't want the customer actually having to come up with the innovation.  In fact, often they will just offer incremental modifications of the existing product.  They usually won't be able to "think outside the box" in the midst of a focus group or interview.  Seek instead to understand their frustrations and their pain.  What makes them unhappy at the moment?  Then, work on alleviating that pain with a new product concept.  

Why ESPN should embrace crowdsourcing

In the National Football League, statisticians have compiled a measure called "passer rating" to evaluate quarterbacks since 1973. Many people have criticized this statistic since it's inception. This year ESPN invested a great deal of time and effort to develop a better measure that they call "total QBR.". They unveiled the rankings of QBs based on this measure in a TV special recently. They argued that this rating includes a much better evaluation of how QBs perform in key situations.

Interestingly, ESPN did not disclose the actual formula and methodology for compiling the rating. I think this was a mistake. These days so many statistics experts love to dissect sports. They would love to sink their teeth into this rating. If ESPN embraced crowd sourcing, they could create a contest whereby many people could compete to refine and improve the measure. They could offer a special prize for the winner - think one day at the firm's Bristol headquarters complete with a lunch with a top ESPN personality. Such a contest wouls be very inexpensive to run, but it would have many benefits. It would engage many rabid sports fans, who are ESPN's core customers. The contest would specifically build connections with stats-obsessed fans. It could yield a better measure. Moreover, being open about the method could enhance the acceptance and use of this new rating by fans, media folks, and teams. Think of the hoopla that they could create and the attention it would draw.

Incentives for Crowdsourcing

The Boston Globe reported Sunday on an interesting new Chinese study about crowd sourcing. Professors Zhang and Zhu examined the behavior of non-Chinese after the Chinese government blocked it's citizens from seeing or using the Chinese version of Wikipedia. It turns out that non-Chinese reduced their contributions significantly. The scholars conclude that the size of a potential audience affects substantially individuals' incentives to contributeopening source projects.

Wisdom and Foolishness of Crowds

Jonah Lehrer had a nice column in the weekend Wall Street Journal about the "wisdom of crowds" - the notion that we can get the right answers to tough problems by marshaling the collective intellect from a large group of people through a mechanism such as a voting process. Lehrer points to a study by Swiss scholars that suggests that crowds may not always be so smart.   Lehrer writes:


The experiment was straightforward. The researchers gathered 144 Swiss college students, sat them in isolated cubicles, and then asked them to answer various questions, such as the number of new immigrants living in Zurich. In many instances, the crowd proved correct. When asked about those immigrants, for instance, the median guess of the students was 10,000. The answer was 10,067.
The scientists then gave their subjects access to the guesses of the other members of the group. As a result, they were able to adjust their subsequent estimates based on the feedback of the crowd. The results were depressing. All of a sudden, the range of guesses dramatically narrowed; people were mindlessly imitating each other. Instead of canceling out their errors, they ended up magnifying their biases, which is why each round led to worse guesses. Although these subjects were far more confident that they were right—it's reassuring to know what other people think—this confidence was misplaced.

The results do not surprise at all.  The key to the wisdom of crowds, as James Suroweicki explained in his great book on the phenomenon, is that individuals must make independent judgments.   In a voting process, where individuals do not interact prior to rendering their judgment, we have independence.  However, in group and organization settings, social influence often plays a powerful role.   People are affected and even swayed by the judgments of others, and that often has a negative effect on the "wisdom" of the crowd.  I've always highlighted this fact by asking people whether they think the audience's accuracy on the game show Who Wants to be a Millionaire would go up or down if people had time to sit in a conference room and deliberate about the particular trivia question.   Because of social influence, I have always argued that accuracy would likely fall.  This simple experiment reinforces that conclusion. 

Open Innovation and Creatives

Maxine Horn wrote an interesting column for Investors Digest titled "Here's What's Wrong with Open Innovation."  In that piece, she argued,

"There is a growing assertion that “ideas” are free and bountiful – with no value until they are commercialized. This devalues the very professionals in the creative industries that firms need. It devalues their talents, education, years of in-practice experience and their knowledge and know-how. We are increasingly leaning to a mistaken view that any one person’s idea is as good as any other person’s. Creatives are being asked to participate with the crowd for work."

Hank Chesbrough of Berkeley, a former colleague of mine from Harvard, wrote a very thoughtful response at Forbes.com.   Hank argues that, "Open innovation, properly understood, can actually boost the opportunities for creative people, rather than extinguish them."  He explains that open innovation enables creatives to build "deeper, more meaningful relationships with your audience."   As such, it can fuel new breakthroughs, broaden the market for creatives' work, and nurture a community of fans who will spread the good news about the creatives' products or services.  

I agree with Hank, but I do think that Maxine Horn raises some important points about the value of protecting intellectual property in an appropriate manner.  Moreover, she's right when she says we need more dialogue about the proper ethical guidelines when it comes to crowdsourcing practices employed by many companies.