RealtyBizNews - Real Estate Marketing and Beyond
Real Estate Marketing & Beyond
Home » Housing » US Real Estate » Realtytrac partners with TKI to help Realtors & Real Estate Investors identify the most likely home sellers

Realtytrac partners with TKI to help Realtors & Real Estate Investors identify the most likely home sellers

By Press Release | November 8, 2021

REAL ESTATE INVESTORS IDENTIFY THE MOST LIKELY HOME SELLERS

RealtyTrac®, the largest online marketplace for foreclosure and distressed properties and TKI, a software development company with more than 20 years of real estate experience announced a partnership today to market nSkope, an AI-powered sales enablement platform that identifies properties likely to be listed for sale, to real estate investors and Realtors® across the country.

nSkope utilizes proprietary algorithms enhanced by artificial intelligence to identify patterns and correlations that fuel its predictions, analyzing over 300 data points in 95% of U.S. ZIP codes to identify the homes that are most likely to be listed for sale within the next 6-12 months. These predictions help real estate investors, brokers and agents identify potential prospects with insight that allows for more targeted marketing and greater conversion rates.

“The biggest challenge cited by both real estate investors and Realtors is the historically low number of homes available for sale today, which makes it difficult for investors to find properties to buy and equally hard for agents to find properties to list,” said Rick Sharga, executive vice president for RealtyTrac, an ATTOM company. “By partnering with TKI to identify properties with a high probability of being brought to market soon, we can help address that challenge, and provide our subscribers with a competitive advantage.”

While only a small percentage of homes in any market are sold each year, TKI’s nSkope platform identifies homes that it projects will come onto the market in the 180-240 days, while also providing contextual sales insights that provide real estate investors and agents the ability to potentially lower marketing costs by more effectively targeting prospects and increasing conversions. 

“Marketing to a wide swath at the ‘top of the funnel’ with the hopes of finding home selling clients is costly and inefficient,” said Tom Gamble, co-founder and CEO of TKI. “Our use of data has changed this approach as we have been extremely successful in predicting homes that will come on the market. We also utilize elements of storytelling to help investors and real estate professionals best understand the needs of these potential sellers so that their marketing messages truly resonate.”

Gamble pointed out that in its most successful markets, TKI has whittled down a potential seller’s base by as much as 75%, creating a return-on-investment of more than 500% in some markets when using nSkope.

About RealtyTrac
Founded in 1996, RealtyTrac publishes the largest database of foreclosure property information in the U.S. in addition to other real estate and mortgage data used by real estate investors and agents to find, analyze and invest in residential and commercial distressed properties. RealtyTrac is owned and operated by Attom Data Solutions, a leading provider of publicly recorded tax, deed, mortgage and foreclosure data as well as proprietary neighborhood and parcel-level risk data for more than 150 million U.S. properties. For more information, visit www.RealtyTrac.com.

About TKI

TKI was founded in 2002 and has worked with such clients as Comcast, QVC, Coldwell Banker Real Estate, Realogy, Cox, CTAM and the NFL. The software development company specializes in lead generation brand asset management and marketing automation. 

  • Sign up to Realty Biz Buzz
    Get Digital Marketing Training
    right to your inbox
    All Contents © Copyright RealtyBizNews · All Rights Reserved. 2016-2024
    Website Designed by Swaydesign.
    linkedin facebook pinterest youtube rss twitter instagram facebook-blank rss-blank linkedin-blank pinterest youtube twitter instagram