Editor's Note: This Requester requested anonymity in order to protect the competitive advantage created by using Mechanical Turk.
As a leading group-buying site, this Requester publishes thousands of deals daily to millions of consumers around the globe. Users can purchase deals from merchants on a variety of products and services ranging from magazine subscriptions to all-inclusive cruise vacations.
In order to address increasing demand for great deals, this Requester must continually develop fresh and compelling deal inventory. To accomplish this, the Requester's sales team proposes campaigns by targeting merchants selling specific products and services based on user demand. However, to formulate these target campaign proposals, this Requester needs detailed information on the services that merchants in their database offer. For example, while beauty salons provide similar services, specific offerings can vary greatly—one salon may provide haircuts, highlights, and perms, while another may only provide manicures, pedicures, and facials.
Detailed information on products and services offered was not available for most of the prospects in their database. To collect this information, they initially assembled an internal team of fifteen researchers to categorize merchants based their offerings. But this team of researchers was not able to scale to meet the volume the business required. Additionally, the opportunity cost of staffing an internal team was expensive. As a result, this Requester turned to Mechanical Turk in search of a scalable, cost-effective staffing alternative.
Using Mechanical Turk, this Requester was able to cost-efficiently categorize hundreds of thousands of merchants in their database in a fraction of the time, without sacrificing quality. This enabled them to reallocate their internal team to other business-critical objectives while instituting a scalable, on-demand workforce solution for on-going categorization as demand for exciting, new deals continues to grow.