Venture Capital News: Reesio Lands $1.1M Financing
2013-10-02
SAN FRANCISCO, CA, Startup that provides real estate transaction management software to real estate agents, has just closed $1.096M in new funding.
Reesio, the San Francisco based startup that provides real estate transaction management software to real estate agents, has just closed $1.096M in new funding. Investors in this round include Digital Garage, MicroVentures, Hiten Shah, and several other angels. Reesio previously raised $205K and was part of 500 Startups Spring 2013 Accelerator.
The transaction management product that Reesio offers allows real estate agents, clients, and third parties to collaborate in real-time in the cloud for all aspects of a real estate deal. Buying and selling real estate through an agent has traditionally been a very manual and paper-driven process, and Reesio eliminates this pain point by offering electronic document/contract sharing and signatures, workflow management, alerts/activities, and messaging. The product allows everyone to easily manage and understand everything that's taking place in a transaction within a simple, centralized dashboard.
According to Co-Founder & CEO, Mark Thomas, when Reesio originally launched in April 2013, it was focused on selling its transaction management platform to real estate agents as a monthly SaaS subscription model. However, about halfway through the recent 500 Startups accelerator program, the Reesio team began to discover something more interesting that they believe will be the real game-changer. 'We started looking closely at the actual transactions themselves that were being created by agents in our system, and we realized that we were collecting this massive amount of listing and property data in real-time as it was progressing throughout the course of a transaction,' says Thomas. 'We then started comparing this transactional data to the big search portals like Zillow, Trulia, and Realtor.com, and we were blown away at how inaccurate those search portals were compared to what was actually happening in real-time within Reesio. There are some industry studies that state that 36% of the listings on the large search portals are inaccurate. We were finding it to be closer to 50% when we compared our transactions to those on the search portals.'
The specific types of data that Thomas cites as being inaccurate on large search portals include things like the correct status of a property (i.e. is it in contract, pending, sold, etc.), listing price data, and other property data like the number of beds, baths, square feet, etc. Displaying this inaccurate data leads to frustrations for all parties involved because no one knows what's really going on with a property. 'Buyers hate finding a property on Zillow and Trulia that they love, only to find out that it already went into contract 2 days earlier. Even worse is when the big search portals don't even have a property listed as for sale, when in reality, it really is for sale. Buyers end up completely missing out on such properties, which is a major problem.'
It's also estimated that 17% of listings are 'pocket listings', which never even make it to the search portals in the first place. And there are a significant additional percentage of properties which make it to the search portals as being for sale well after it's already gone into contract. All of which means that buyers end up completely missing out on being able to make offers on properties that they otherwise should have known about.
The core of this problem stems from how the search portals get their listing data. They use a combination of getting syndicated listings from the 900 nationwide MLS's, as well as pulling from public records and other sources. The MLS's get their listings directly from Listing Agents, who enter their listings manually into their local MLS system. Because this process requires the Listing Agent to manually create the listing in their local MLS system and manually update it every time there is a change in the transaction, a lot of the data is significantly delayed in terms of when it's actually updated in the MLS. Or worse, the data is never updated in the MLS at all. Which means that when the MLS's syndicate the data to the large portals, it ends up being wrong there on the portals also.
Reesio is removing this friction by automatically updating the listing in real-time as things are happening during the course of a transaction in its system. For example, Reesio knows the moment a property gets listed for sale because the Listing Agreement gets signed by the Listing Agent and the Seller right in their system. Same thing for knowing when a property goes into contract or when a price changes. From there, Reesio is able to automatically update the listing on behalf of the Listing Agent, without the Listing Agent having to do any work. 'The beauty of our system is that agents just need to do their job as they already are doing it in our system, and we update everything automatically for them. No more having to go and manually update the MLS or any other search portal,' says Thomas. 'This means that the listing data in Reesio's system is more accurate than even what's currently in the MLS, because it's being updated in real-time as things progress throughout a transaction.'
Reesio plans on using the new funding to scale the number of agents and transactions that it has in its system, and to ultimately grow into the largest, most accurate listing database in the country. Instead of charging $15/agent/month, Reesio will begin giving the product away for free to agents starting later this month. Agents will be able to create as many transactions and have unlimited use of the system at no charge. Additional features will also be launched at the same time that will allow agents to market their property from these real-time listing pages, as well as handle the offer-making process. 'It's all about giving agents the tools they love in order to do their job, and becoming a one-stop shop where they can transact and market their properties within a beautiful product,' says Thomas.
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