Hacking real estate to find the best off-market deals

Winning in real estate is about better information, with data sources like Redfin and MLS as table stakes. The most successful real estate players win by having an information edge. Kimono is a smart web-scraper – letting innovative real estate players like Michael Tomko find leads that others can’t. Here’s how Michael identifies high value properties and unlocks the best deals on the market.

Michael works part-time as a real estate entrepreneur in Franklin County, Ohio. His success is contingent upon being able to find and purchase valuable properties at a good price so that he can renovate and rent them out for profit. Like any savvy real estate player, Michael knows that unlisted properties in direct buyer-to-seller transactions offer the greatest value (these are unknown to other buyers and bypass a commission fee). To find these unlisted properties Michael has to reach out to many individual owners, leading to a few real transactions. The trick is generating the best leads.

Like many counties in the U.S., Franklin County, has a large repository of public documents available at the Auditor’s website. The website lists every land parcel in the county with its appraised value, address, owner, last transaction date and value, number of bedrooms and mortgage documents. With this information, Michael can reach out to property owners whose land matches his criteria (housing type, geography, appraised value and last turnover date).

The website has the data, but it is unstructured and difficult to access – users need to enter the land parcel ID number (a combination of the tax ID and a 6 digit number corresponding resident type) and then transcribe that data. Using kimono, Michael quickly scrapes and structures the data for all the parcels he’s interested in, generating qualified leads.

Now the wealth of previously hidden parcel data is easily accessible as columns in an excel spreadsheet. Michael then filters for parcels that match the ZIP codes he cares about and sends letters to the relevant owners. Using the previous transaction and audit information, he adds a well informed initial offer.

To date, Michael has reached out to ~5,000 properties and is closing deals for 12 units. He refreshes his data set weekly, helping him stay ahead of the market, see the best deals first and capture more value.



Michael Tomko is a third-year law student at Harvard Law School and real estate entrepreneur in Columbus, Ohio. Most of his work is concentrated on questions that arise at the intersection of real estate with law and finance, with particular attention to the ways in which internet technologies change these dynamics. You can visit his website at mtomko.com or find him on twitter @tomkomichael.

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4 thoughts on “Hacking real estate to find the best off-market deals

  1. While I’m not doing this to flip houses, I’m running a combination of 4-5 API’s into one API to filter a number of real Estate listing sites in Vancouver, BC and have written an Angular App to sort, filter and review the listings so that I can be ahead of the game to find my dream home.

  2. Will says:

    On a similar note to Colin, I’ve run a few APIs to monitor apartment rentals in the Bay Area to search to find my next apartment.

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