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What’s The Best Geographic Search for Listings?

Oct 15, 2008 Michael Wurzer

During the CMLS conference a few weeks ago, the now perennial topics of raging regionalssyndication,  parcel based MLS systems, and consumer facing MLS sites were still hot.  I’ve covered these topics at length here on the FBS Blog for the last year or so but just started thinking about another, seemingly mundane issue that runs through all these issues, namely the best way to organize (and, therefore, search) MLS data geographically.

This issue impacts all the hot topics being faced by MLSs today: (1) regionalization and cross-MLS data sharing directly raise the questions of boundaries and geographies; (2) syndication of listings should be done in a consistent manner and the geographic data points are critical; (3) parcel maps are key to accurate geographic positioning; and (4) consumers want the easiest way to find properties in the areas in which they’re interested, and they want to see statistics and other data organized around those same areas, which requires solid and shared definitions.

Let me provide some examples to highlight the challenges.  First, many MLSs have created their own “ares” or “regions” to make organizing and searching data easier.  Here’s an example MLS area map from our customer in Santa Barbara.

MLS Defined Areas

MLS Defined Areas

The advantage of MLS defined areas is that they are easily learned by the agents and often represent the market fairly well.  One of the disadvantages of MLS defined areas is that markets change, and maintaining the areas and the consistency of the data has historically been difficult.  Also, as shown in the image below, the MLS defined areas raise the continual problem of the outer boundaries of the MLS.  Lastly, there is some concern that MLSs defining boundaries or areas is a potential fair housing issue.

Outer Boundaries of MLS

Outer Boundaries of MLS

Notice how when the map is zoomed out, the boundaries of the MLS become apparent and the issues of cross-MLS data sharing via the MLS defined areas raises all sorts of challenges.

To address some of these issues, many consumer facing web sites focus on city or zip code as the key geographic criteria, primarily because those are most familiar to consumers.  The challenge with city and zip code is that they are just too broad and often bear no relationship to the actual real estate markets within the city or zip code as shown above in the first image where the zip code actually is split across two different MLS defined areas.

Zip Codes Are Too Big and Not Market Defined

Zip Codes Are Too Big and Not Market Defined

To combat the problem of zip codes and cities being too big and the boundary limits and constantly changing nature of MLS defined areas, some MLSs have gone to a “grid” format that simply carves up the geography into squares or rectangles.

Map Grids Provide Consistency and Scalability But Not Relevance

Map Grids Provide Consistency and Scalability But Are Not Descriptive of the Actual Market

These grids are very useful because they can easily be extended to new areas with consistency, but the problem is they do not describe the actual market, which has twists and turns every which direction and those twists and turns often mean tens or hundreds of thousands of dollars in median home prices. Accordingly, market analysis is not useful based on a grid system and the grid system isn’t easily used by consumers.

New Mapping Technology Allows Custom Areas

New Mapping Technology Allows Custom Areas

To address some of the limitations above, some MLS systems and consumer web sites allow users to draw directly on the map to define exactly the area in which they are interested.  There are several limitations to this approach in most systems: (1) many agents and most consumers don’t want to or don’t know the detailed boundaries of the true market areas; (2) the areas that are drawn are not shared with others who may want to use them as well so users can learn from each other; and (3) they aren’t consistent enough to enable gathering of statistics and other data for agents and consumers.

Yet another approach has been to gather neighborhood boundaries.  Two companies working on collecting this type of data are Maponics and Urban Mapping.  In addition, Zillow has put forward some neighborhood files as open source files for contributions from many.

What I’ve been thinking about recently is how we might be able to create a massive win-win for MLSs, agents and consumers by enabling the real estate professionals to contribute neighborhood information directly into efforts like those linked above.  The result could be a nationwide set of neighborhood boundaries that accurately define the market areas and allow for easier organization and searching of MLS data and presentation of market statistics.

What do you think is the best approach to organizing listing data geographically?