Our mission involves recruiting large populations of internet users for research tasks, so we’re always interested in innovative crowdsourcing methods.  Crowdsourcing services allow many people to contribute to a project and be compensated in various ways.  We stumbled on 10 ways small businesses can harness big crowds by Ross Kimbarovsky, co-founder of CrowdSPRING, a sometimes controversial marketplace for design services.

The most interesting services highlighted are software testing (uTest), customer support (the always fantastic Get Satisfaction), domain-specific scientific, materials and technology research (InnoCentive), and prediction marketplaces (Inkling). The most successful crowdsourcing projects seem to be those that offer a win for both the business and the community members.  As a company developing tools to help both researchers and participants, this makes intuitive sense to us, and we’re happy to see this strategy succeeding elsewhere.

Dolores Labs is doing a bunch of cool work finding ways to distribute tasks to large numbers of people online.  As well as crowdsourcing tasks, they also check the results to make sure that you get higher quality results than using unmoderated tools like Amazon Mechanical Turk.

The Dolores Labs blog has an interesting post up about their recent partnership with Gambit (a payment tool used in online games and communities).  Together, they’re offering Facebook gamers the opportunity to earn in-game credit for doing real work through their platform.  This is a timely service, especially given TechCrunch’s recent indictment of offer platforms as scams. Now you can earn your in-game wage by completing simple tasks instead of signing up for credit cards and Netflix accounts!  We like this innovative way of reaching and rewarding large numbers of people via Facebook.

Dr. Markus Jakobsson of PARC has a great article sharing 5 tips on how to perform successful research using Amazon Mechanical Turk.  Jakobsson talks about some of the pros of Mechanical Turk for research (e.g., quick access to a large pool of participants and participant anonymity) and then delves into how to navigate the possible risks and difficulties (detecting cheaters, running multi-part studies, and avoiding biasing subjects, to name a few).  It’s a really nice look at how to best make use of the tools currently available; check it out!