Real Estate Customer Experience & Data Quality

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How real estate businesses use technology, and data in particular, is critical to providing value and differentiating themselves in a market that still relies heavily upon word-of-mouth referrals. Data is the basis for a number of initiatives that real estate businesses are embarking upon to improve their offerings, namely around providing more accurate location-based information about properties and more detailed analysis and recommendations. However, the reliance upon lower-quality, free data sources can prove a costly problem for businesses to fix.

A recent Forbes Insights report, “The ‘Ground Truth’: Improving Real Estate Customer Experience With Higher-Quality Data,” sponsored by Pitney Bowes, discusses some of these uses for data in real estate as well as the costs that can result from poor data.

Today it’s rare to see a site that doesn’t offer some kind of detailed neighborhood analysis on the nearest schools, fire stations and demographics. Real estate businesses are using this information to offer more in-depth analytics and comparisons, allowing sellers to set a more competitive price and providing buyers with better recommendations for comparable properties in similar neighborhoods and price points.

High-quality data can help brokers build a picture of relevant options. With this insight, they can make an evidential case to clients about listing prices, alternative properties to consider or where the greatest ROI potential on an investment property might lie. It is this capability to come to client conversations armed with data-backed recommendations that can set a brokerage apart and improve its customers’ experience.

 

On the other hand, poor-quality data can have real consequences for real estate companies. Data needs to be updated and kept current, regularly refreshing with new information. School zones change, boundaries are redrawn—and there could be huge reputational costs if customers have made purchasing decisions based on data that turns out to be incorrect.

There are two options for real estate companies when it comes to selecting data sources: free and premium data.
Free data typically comes from a variety of sources, including private companies, other real estate businesses, and state and local authorities. The main benefit of these sets is that there is no cash outlay required—although there is little consistency or guarantee of quality among the sets, which means the onus is on the user to validate them and ensure interoperability with other internally held data.

A few benefits of premium data:

Rights: Whereas rights to premium data can be negotiated in contracts to provide certainty, free data is often offered under inflexible boilerplate agreements or a Creative Commons license whose terms can change: This may result in legal gray areas when licensed and internal data are combined.

Professionally curated: Typically curated by GIS (geographic information systems) specialists with best practices in mind, so there is quality and consistency within and between data sets.

Standardized: Standardized formats, like tab, shape, WKT and GeoJSON, make data easier to integrate internally, whereas free data sets may be offered in non-standard formats requiring work up front before integration.

Updated: Refreshed on a regular monthly and quarterly schedule to ensure that information is current.

Support: If you’ve got an issue with your data, premium data sets come with customer support, whereas with free, you’re on your own.

Agencies can use data to deliver a better customer experience and deeper analysis for their clients, but they have to be able to rely on the quality of their data to do so. Bringing in outside data can enhance the quality of internal data, but it’s important to vet the sources carefully and understand the differences between free and premium data sets.

Source: https://www.forbes.com