TenSource aims to be a “CoStar in reverse”
Platform focuses on tenant needs, but gets mixed reviews from the industry
A commercial real estate technology startup is looking to turn the landlord-tenant matchmaking business on its head. TenSource, according to its founders Al Baumol and Sufyan Sigg, is the first online database for leasing brokers created to list and search for tenant requirements. While brokers described it as “a CoStar in reverse,” the fledgling firm faces a number of challenges.
Here’s how it works: A tenant representative can post their clients’ requirements on the site in the form of a tenant listing, and landlord representatives can scour such listings and connect with the tenant reps if they’ve got something that will fit.
Typically, tenant brokers email several dozen brokers each time they have a client that needs space, Sigg said. The program allows them to put the word out and have landlord representatives come to them, he added.
To protect their clients, many of whom aren’t willing to publicize the fact that they’re on the hunt, tenant brokers don’t share identifying details such as a tenant’s name or the exact space requirements. Rather, they will indicate the type of tenant — such as digital media or financial services — and provide a range for how much space is needed.
Tenant brokers said the service was a way to get the first crack at off-market space. “There’s a lot of shadow space out there that is kind of available, but may not be,” said JLL’s Paul Ferraro, whose client list includes tenants like watchmaker Bulova.
“There’s always that downtime in between getting hired to list space and actually being able to put on the market, he added. “This allows us [tenant brokers] to proactively go after spaces” that aren’t yet on CoStar or other major listing sites.
Baumol said a savvy landlord rep can also take advantage of the platform. “You can find tenants that work for your space, and reach out to their brokers one at a time, well before you have the ability to actually put out a space listing.”
It could also be a way for opportunistic landlord reps to win new business. “Sometimes people don’t have an exclusive, so they can’t post a listing,” said Winick Realty Group retail broker Zach Diamond. Through TenSource, a landlord rep can try to court tenant brokers and then go to landlords with a potential deal in hand.
Sigg and Baumol, both alums of commercial brokerage Sinvin Real Estate, estimate that 25 percent of office leasing and retail brokers in Manhattan have used their service. But it’s unclear how many of these are repeat users, and how many lease transactions have actually originated through TenSource. Diamond said that he has letters of intent out on potential deals that were sourced through the website.
And not all who’ve used the service are believers. Two tenant brokers who used TenSource told TRD that they got very little traction from the service, and gave it up shortly after trying it out.
Paul Amrich, a CBRE vice-chairman who represents many of the city’s top landlords, said that using a passive service such as TenSource is “not how deals are done in New York.”
At present, the five-employee, year-old startup is funded entirely by the founders and their friends and family. But they may look to tap into the fertile market for real estate tech investment down the road. One of the challenges it might face, heads of other real estate startups said, is TenSource’s niche focus is difficult to scale. Given that it costs nothing at the moment, many brokers have tried the site. But if the service begins to charge listing or subscription fees, it’s tough to say how many brokers will stick around.
“I don’t think I know what my threshold on is on paying for it,” Ferraro said. “I’m sure some amount is logical.”
A more promising source of revenue for the startup could be selling its detailed tenant data – broken down by location and industry – to developers, who can use it to select sites for future projects, as well as to government agencies, which can use the data in long-term planning.
“It shows you, in detail, where people are looking,” Baumol said, “so it has a predictive quality to it.”