Bizly turned to CloudFactory when it needed to significantly expand its database of event spaces. The CloudFactory team verified existing data and enriched location profiles with additional data like capacity and ambiance.
Gus Goldsack had a dilemma.
As the product manager for Bizly, an event planning and management platform, he needed to add thousands of vetted venues to Bizly’s database so they could launch their new app.
Goldsack found the prospect of hiring contractors or part-time staff to fill out the database daunting. Then a colleague told him about CloudFactory. Eight months after learning about the managed workforce option for the first time, Goldsack is sold based on results, quality, and price.
Bizly’s platform is designed to help teams find the perfect venue for their events with a minimum number of phone calls. The company also provides resources for managing events, building and managing guest lists, and measuring event impact. The challenge that brought them to CloudFactory was the need to dramatically expand the database—going quickly from 2,000 venues to 18,000.
Bizly had tried to expand its venue list through third-party data providers. “But it’s hard to keep the information fresh. We realized early on that we needed to have human eyes on these venues,’’ Goldsack says.
The company also wants to make sure venues aren’t getting requests from Bizly users that aren’t valid. “If you send an inquiry for a 100-person event to a venue that can only accommodate 20 people, that is a waste of time for everyone,’’ Goldsack added. “We wanted to make sure that by the time a Bizly client speaks to a venue, they already know the venue can accommodate them.’’
Goldsack thought he would need to hire people on site at Bizly to do the work, but that raised a host of issues. “We’re a small team without a dedicated HR resource. We weren’t sure about contract work vs. hiring part-time or full-time. We didn’t want to do anything wrong.’’
Goldsack had never heard of a managed workforce before a colleague told him about CloudFactory. “She highly recommended that we look into CloudFactory.’’
The CloudFactory team quickly caught on to what we were doing. They understood the eccentricities of the work and asked the right questions and acted very quickly on any feedback we had. Now it’s running like a well-oiled machine.
CloudFactory selected a project manager who would train the data analysts assigned to Bizly, taking their detailed instructions and applying training best practices to ensure the workers understood how to complete the job. Goldsack described the onboarding process as smooth.
As the first batch of entries was added, a Bizly staff member spot checked the work for quality and provided feedback to improve quality going forward.
“Right away I was wowed by the CloudFactory solution,’’ Goldsack says. “We had this preconceived notion that our needs were bespoke and I thought a managed workforce could only handle very specific kinds of tasks and not some of what we needed which included people who could do research.’’ He added: “I was also surprised at how affordable it was.’’
Goldsack says he’s been thrilled with the results. “It's really been a set-it-and-forget-it experience,’’ he says. After initially spot-checking 50% of CloudFactory’s work, Bizly has cut back to checking about 20% of the entries and even less in some weeks. “A key has been the Train the Trainer approach. It’s so much easier to have just one person to communicate with.”
Another huge win for Bizly was how fast the Kenya-based CloudFactory managed workforce came to understand the business model and what each entry needed. “The team quickly caught on to what we were doing. They understood the eccentricities of the work and asked the right questions and acted very quickly on any feedback we had,’’ Goldsack said. “Now it’s running like a well-oiled machine.’’
CloudFactory added more than 12,000 venues in less than six months with a 96% accuracy rating. “We thought that (enriching our database) was going to be something that required a lot more money, a lot more time, and involved a lot more incorrect data combing. I have been truly surprised by just how easy everything has been.’’
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