Revester
Revester first reached national attention when Bill Lyons pitched it on Shark Tank in 2012. Originally asking for $500,000 for 10 percent, he lowered the ask to $50,000 for 10 percent after the producer suggested it. The pitch did not land, and the sharks' rejection made it harder to raise money afterward.
The original business grew to about 15,000 users but never passed 1,000 paid users. Its revenue came from realtors paying for ad space and from subscriptions for premium content and data. Bill redirected his energy into a mortgage company he started in 2013, which he said did $500,000 in revenue in 2014 and $1.7 million in 2015. He used that business to fund the relaunch.
Revester's current audience is an email list of about 30,000 names, of which Bill said roughly 14,500 were active. The list includes real estate investors and people looking to diversify from stocks and 401ks into property. Bill described the product as a pre-due-diligence tool meant to save investors hours of searching across Zillow, Redfin, the MLS and other sites.
The main lesson Bill drew was that the original product lacked traffic and leads for its realtor customers, which led him to cancel their subscriptions and refund their money in order to rebuild. The data costs are high: Bill said the ListHub feed costs about $6,000 a month, and foreclosure, vacancy and rental data add further expense. He also argued that many data companies have strong datasets but fail to make them useful, and that Revester's strength is turning the data into a usable tool.
As of the interview, Revester had zero revenue in September 2016 and was preparing its November 1 relaunch. The beta site runs nationwide with daily rent data for San Diego. Bill's stated goal is to reach a few million unique visitors per month and to sell advertising to realtors, with the company supported by a digital marketing firm and a PR firm.
- •Building the tool to solve Bill's own investing problem gave the product a clear and specific use case rather than a generic data feed.
- •Using a data product from an established source (MLS via ListHub) gives the product credibility that a bare analytics site would lack.
- •Cross-selling to the mortgage business gives the platform a built-in conversion path, so the data product does not have to monetize on its own right away.
- •Abandoning the failed realtor-subscription model and rebuilding around a sharper investor use case reflects a willingness to change direction after the first attempt stalled.
- 1.Start from a problem you have personally faced as a buyer, then build the first version around solving it for yourself and peers.
- 2.Layer computed investment metrics such as cap rate and cash flow onto a public listing dataset so users can screen properties before talking to an agent.
- 3.Keep the core tool free for sign-ups, and plan monetization through advertising to a professional audience such as realtors.
- 4.Pair the product with a related revenue business, like a mortgage company, to fund data costs during the early period.
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