Collaborative Discovery Engine
Hybrid Wisdom Labs

Hybrid Wisdom Labs Launches A Speedy, Scalable Engine For Visualizing Customer Insight

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Ken Goldberg, a professor of New Media, Robotics, and Industrial Engineering at UC Berkeley, launched an interesting new startup from the stage of The Web 2.0 Summit in San Francisco today, called Hybrid Wisdom Labs.

The startup, according to its founder, has emerged from “more than a decade of robotics and social media research at UC Berkeley”, resulting in today’s launch of its patented “Collaborative Discovery Engine”, a scalable way for companies to rapidly generate realtime insight from their customers and employees. To date, the technology has been used by General Motors, Unilever, Humana, and the US State Department, Goldberg said.

The idea for this new collaborative engine stems from the fact that most tools companies are using to gain intelligence from social media end up being list-based discussion interfaces that don’t scale well and quickly grow to unmanageable proportions, the founder said.

To combat this problem, the discovery engine combines thousands of ideas from brainstorming, social media, and robotics, runs them through a variety of analytic algorithms, before presenting them in a dynamic visualization format that allows companies to easily discover which ideas are important — and what they should be focusing their resources on.

The value proposition: Scale and speed. According to Goldberg, the engine can scale to support thousands of users without sacrificing the speed required to quickly find the best solutions to a company’s problems.

As one can see from the image above, each visualization is focused on a key topic, or question that a company has about its product or strategy, for example. Circles, or really, “blooms”, emerge in the visual rendering (i.e. graphical map), which represent a new idea or response proposed by participants. The positions of the blooms in relation to each other are based on the relevance of the opinion (or idea) to like-minded ones, and the color and size of the bloom represents the number of “likes” or positive responses the idea is generating.

Using sliders that represent two dimensions (how much they agree with AND how insightful they find the response), users then evaluate the responses, presumably resulting in a more robust analysis than the simple “thumbs-up” or “thumbs-down” pervasive to social media’s evaluation of preference.

As the reputation algorithm processes further responses, the least important ideas fade into the background, and the more popular (or commonly occurring) ones take visual precedence, leading to a deeper look into collective customer intelligence.

As to how beta testers have responded? According to a company statement, released via its website: “In January 2010, Hybrid Wisdom partnered with a leading Fortune 50 manufacturer to find insightful solutions into how they could improve their brand and reputation. The Collaborative Discovery Engine engaged 1,200 of their most valued customers. After a few weeks, the most valuable insights were reported back to the company, including users’ desires around extending warranties to convey confidence in quality and stability. Both the company and the participants were extremely pleased. In a follow up survey, 95% of users indicated that they would be “Extremely Likely” to participate again”.

For more, check out the company at home here. Let us know what you think.