5 Reasons Why Consumer Collaboration and Big Data Are a Perfect Match
In an article in the Harvard Business Review called "Collaborative Advantage: The Art of Alliances," my friend Rosabeth Moss Kanter observed: "Alliances that both partners ultimately deem successful involve collaboration (creating new value together) rather than mere exchange (getting something back for what you put in). Partners value the skills each brings to the alliance."
That principle has been a beacon for me ever since, and influences not just how I approach relationships with business partners, but drives my passion for consumer collaboration. It seems especially important now, because as Big Data generates Big Buzz and (occasionally) Big Results, there’s a temptation to think that we no longer need to bring the active, knowing, feeling human beings who are our customers into our product development and marketing efforts. But in fact, as valuable as Big Data analytics are, the opposite is true.
Here are five ways in which conscious, active consumer collaboration is an essential partner to Big Data as companies try to solve problems, deepen relationships, and invent the future.
1: Big Data is only effective at revealing what people are feeling.
It's not good at revealing why they're feeling it. One of our clients is a major airline with a small, private online community of elite frequent fliers. This airline recently introduced a new policy of charging infrequent fliers for checked bags, but waived the fee for people enrolled in their frequent flier program. To their surprise, the policy aroused the ire of the very people they were trying to serve--their most elite business customers--who felt it encouraged bad behavior among other passengers that would adversely affect everyone.
The Big Data technique of social media mining alerted our client to the existence of a problem. But once armed with that focus, it was much more efficient and actionable to just directly ask some community members why they objected to it, as opposed to weeding through reams of cranky comments in social media in search of the actionable insight.
2: Mining and analyzing Big Data is about collecting information.
More collaborative methods, on the other hand, allow you to generate insights.As the airline story illustrates, there is nothing wrong with intentionally soliciting the comments and feedback that you know will be the most actionable, as opposed to casting a broad net and hoping you’ll reel in something useful.
An hour spent on a live or remote shop-along with a retail consumer can teach you more about their needs and the retailer’s opportunities than a thousand mined comments.
3: Big Data analysis is great at finding and displaying patterns and correlations.
Collaboration helps you both forge and understand the deeper connections underlying them. Going deep into people’s psyches to understand their barely conscious emotional drivers and symbolic associations requires a trusting, reciprocal, and often private relationship between a brand and its consumers.
There are feelings, experiences, sights, sounds, and routines that provide invaluable insight to brands, which people do not want to share with, or in front of, their friends. But if you are transparent in your outreach and objectives, and if you are authentically interested in learning from and creating with your customers, you don’t have to guess at their motivations. You can explore and reflect with them.
4: Big Data has great predictive power, but is inherently backward-looking.
It makes the generative, creative potential of collaboration a great match. Although Big Data can be very useful in creating prediction models, its algorithms are, inevitably, based on what exists today.
So you may know that people who buy Book A also buy Book B, but how can you help authors write the books that will sell in the first place? Will this knowledge of correlations even help you develop an effective launch plan for Book C?
Innovation is an inherently creative act, not a purely reactive one. So how do brands innovate for what should exist in the future? Solutions take conscious, collaborative, concentrated effort--iterative work that you design and build on over time--and require only a relatively small group of people.
5: Changing goals, plans, and behavior requires measurement and empathy.
Marketers are in the business of changing perceptions and behaviors. But when was the last time you were moved to action by a histogram? How about a scatter plot? On the other hand, think of how often a single plaintive or inspiring comment, the expression on someone’s face, or the simple but sincere story you heard from a single customer, has moved you emotionally--and then moved you to act.
Ultimately, it’s not data that moves people. People move people.
If you’re interested in learning more--and I hope you are--click here for a more in-depth look at how you can use the synergies between Big Data and consumer collaboration to drive growth and innovation.
DIANE HESSAN is the Chairman of Communispace, a consumer collaboration agency she helped found in 1999. To date, it has launched more than 700 communities and in 2012 was rated the fastest-growing company in its industry. Diane is co-author of Customer-Centered Growth: Five Proven Strategies for Building Competitive Advantage.
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