Trada Challenges Crowdsourcing Status Quo with new “Optimizer Matching” and "Expertsourcing" Model

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Innovative model integrates crowd-powered results with technology

Trada is challenging the concept that a larger crowd is necessary to get optimal results.

Trada, the only performance-based paid search marketplace, announced today a significant enhancement to their crowdsourced approach. After 4 years building and expanding their crowd of certified experts who work to optimize search campaigns across the Google, Yahoo and Bing networks, Trada will roll out a new version of their marketplace, which challenges some of the traditional notions of crowdsourcing.

Crowdsourcing, the practice of assigning work traditionally performed by an individual to a group of people, typically relies on large communities and rules rooted in game mechanics to incentivize the right behaviors and ensure quality work.

But Trada is challenging the concept that a larger crowd is necessary to get optimal results.

“There is an emerging class of crowdsourcing companies that employ expert workforces,” said Niel Robertson, founder and CEO of Trada. “Our data shows that, on a given campaign, we can specifically curate a smaller expert team based on experience and skillset, and that dramatically boosts performance.”

Trada’s success in designating fewer, more specifically qualified experts to a campaign defies the conventional wisdom that implies that, for a crowd, more is necessarily better.

Trada’s new “Optimizer matching” technology collects information about the experts’ unique skillsets and their historical performance in the Trada system, and assigns them to campaigns whose objectives they can best serve. In paid search, the strategies used to achieve different goals are highly variant, so subject matter expertise in an advertiser’s vertical, size, and conversion type are critical to success.

Game mechanics continues to play an important role. A paid search campaign whose work is performed by a smaller team of qualified experts allows each individual expert more data to drive decisions, more influence over the results in the campaign, and ultimately greater earnings – which naturally leads to each expert being more invested in the campaign's success.

“This move to highly data-enabled matching technology ensures that each advertiser has experts specifically trained and vetted to drive results on that campaign,” said Robertson. “With the right experts aligned to a campaign, a crowd still gets better results than an individual, but your crowd can be smaller and more engaged.”

Trada's paid search marketplace allows mid-market advertisers - those companies who are in the influential space between small businesses and enterprise companies - access to a community of search experts who perform the tasks of building out PPC campaigns, as well as constant research and optimization throughout the lifetime of the campaign.

Trada's model is particularly suited to the unique requirements of a mid-market advertiser, who needs to scale paid search in a sophisticated way but often does not have the time or in-house expertise to do so.

"We believe that our discoveries and execution will be relevant to other crowdsourcing companies, especially those with expert workforces whose tasks are data-driven,” said Robertson. “Trada benefits from the collective wisdom of the crowd to deliver excellent performance for customers, which should be the common goal in our industry."


Trada, the only performance-based paid search marketplace, allows mid-market advertisers access to a community of paid search experts, who do the daily work of campaign setup, buildout, research and optimization. Advertisers benefit from the collective broad strategies the community affords, time savings, and a focus on improving ROI. Paid search experts make money based on their performance, without having to find or manage clients.

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