How to Quickly “Visualize” Your Real Estate Comp Data : A New (Free) Tool For Your Business

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A common theme starts to arise when you spend enough time reading the BiggerPockets Forums and blog.

Do your due-diligence and know your numbers!

This sage advice is reiterated by many well-respected contributors in our community on BiggerPockets. It emphasizes the notion that real estate deals are driven by research and sound fundamentals. Where does this research and analysis typically begin? In most cases, it starts with the comps (comparables).

Our business is almost entirely driven by comps.

  • Want to estimate the value of a property? Start with the comps.
  • Want to gauge the vacancy trends in a specific market? Comps.
  • Want to get a handle on what rent increase is acceptable? Comps.
  • Want to decide on the appropriate finishes and amenities for a new property? You guessed it, comps!

Comparable properties are vital to understanding the pulse and strength of any market. Yet, with the wealth of information available today, analyzing comps can become increasingly overwhelming (if you let it)!

If you’re swamped in comps, here’s a very quick analysis tool that can help visualize and geo-code your data.

It’s called BatchGeo.

So what is BatchGeo? It’s an incredibly useful (and free) online tool that quickly geo-codes any address and visually groups property information using Google maps. The best part—you can produce a compelling, customized map in less than 60 seconds!

Let’s jump in.

Using BatchGeo

All you need to start is a list (edited in a spreadsheet) of the address, city, and state of the properties you wish to map.

For example, if you have comps that were pulled from the MLS or other comp sources, these can be arranged in your spreadsheet as a database (any list will work though). Once the address information is neatly arranged in separate columns, you can then organize any property data you wish to analyze.

  • If you want to map all of the properties in your market (or neighborhood, or even street) that sold for $125k-$150k between fall-2012 and today, map it!
  • If you want to locate new multifamily properties currently in the pipeline in your city, map it! (example below)
  • If you want to view where new-construction properties were built in that last ten years, map it!

The possibilities really are endless.  The trick is to organize your address, city, and state in your spreadsheet in separate columns and label each one accordingly. Then add your extra comp information in the columns after your address (ex: sale price, property size, date sold, etc.).  BatchGeo groups this information, geo-codes it, and takes care of the rest.

Check out the database below as an example. I pulled this data for free from a city website. The website was promoting new real estate residential developments in the pipeline and included detailed information on each project (my analysis goal: gauge how robust the pipeline is for new residential construction in the city).

Here’s how the formatted data looks in my spreadsheet.

Excel Batchgeo Database1

Once your data is organized like the above example, do a quick CTRL-C of the information you want analyzed and head over to BatchGeo.com. Once on the homepage, simply paste your data into the box, follow the steps to produce your map, and you’re finished.

Here’s a map of the property data I pasted in from my spreadsheet.

BeFunky_Jersey City Map 1

BeFunky_Jersey City Map 2

In this example, I wanted to visualize where all proposed residential development projects will be located in Jersey City, New Jersey (lovely place!). Interestingly, there appears to be a large amount of projects planned for the downtown area and along certain streets. I also wanted to categorize the years these projects would be finished and if they are condo, mixed-use, or multifamily.

This map helps visualize the density of new projects likely to be under construction over the next few years. But you can also apply this technique to single-family home sales, multifamily rental rates, retail lease comps…really anything!

If you’ve got a mountain of comp data, give this mapping technique a try. It may help make sense of it all.

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About Author

Kyle is the creator of realestate-java.com, a blog dedicated to commercial real estate development. Kyle is also a real estate development associate with Blu Homes, Inc. His company focuses on building sustainable homes throughout the country.

12 Comments

  1. Kyle

    Thanks for the share of a great tool. A similar tool that I was introduced to while analyzing data for equity sellers was Fusion Tables by Google Labs. What are your thoughts on that tool? Also I see your mapping Hudson MLS data. Nice to see a fellow Northern New Jersey blogger.

    -Ankit

    • Hey Ankit, I haven’t used Google Fusion yet. But it seems like a great tool for analyzing real estate projects. (will be adding it to the toolkit–thanks for the recommendation!)

      I’m actually based out of the Midwest in St. Louis. I worked on a project recently in Jersey City and thought it’d be a great example to showcase Batchgeo (especially given the city’s large database of new projects). Jersey City is getting a lot of attention from developers lately.

  2. How did you categorize the locations or flags by color in the map…did you use an Excel feature to do this?
    Did you map the locations using the BatchGeo app free version or are you using the upgrade?

    Thanks.

    • Hi Leo.

      BatchGeo automatically programmed and assigned the colors in the map. It used the “Development Type” column in my Excel file to label/color the flags because this column had repeated inputs (condo, multifamily, and mixed-use). When you click on individual flags, the rest of the information will pop up about that specific property (name, address, # of units, etc.).

      I used the free version for this example. I hope that helps!

  3. doh! the cat’s outta the bag… :) you’ll find (as you get more versed in mapping data) that today’s tech can really help w/data analyses! good stuff…. keep googling… google’s your friend esp when it comes to learning more about mapping tech and real estate data.

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