Big data can be effectively utilized with digital marketing which is an emerging arena not really understood by many real estate professionals. For example, you can “geo-fence” your competition and serve ads to those people. Digital marketing can be used to stratify an audience into homogenous groups for a marketing campaign as well.

GlobeSt.com: How should companies ensure they have access to the right big data?

O'Connor: The first step for most companies is to combine data from multiple silos. We are working with one national real estate services firm that has nine separate databases: one for each division. While it is easy to suggest combining databases, there are logistical, technical and political issues that make implementation difficult. However, aggregating internal data sets is one of the best ways to gain insights on clients. For example, what portion of investment sales involves a loan generated by the same firm? Another example is the portion of investment purchase acquisitions generating a management or leasing contract for the company. Another option is to cross-index the percentage of cross selling between the departments in a company.

Procuring additional data sets is done after combining internal data sets. One excellent source of data is psychographics, used to understand the characteristics of existing clients. Another source of data is a client survey. Understanding the characteristics of clients and their objectives provides information for both refining services and marketing messages. Hence, the first step in obtaining data regarding existing clients to allow targeted marketing of prospects. There are many options for differentiating clients including age, income, location, family status, length of real estate ownership time, equity in the real estate and the interest rate of a loan.

GlobeSt.com: What does cost segregation entail?

O'Connor: Cost segregation typically involves federal income tax savings of five to 10 times the cost of the report in the first year. Cost segregation reduces and defers federal and state income taxes. For real estate investors who are paying income taxes, a cost segregation report is the safest investment with the highest return they will ever make. This is a bold statement but it is true: where else can you get at return of 2,500 to 5,000% over a five-year period with no risk? This is accomplished by using an IRS-directed method to properly calculate depreciation. Most investors simply classify commercial buildings as 39-year properties. However, a sizable portion of the improvements can be classified as five, seven or 15-year property. Correctly classifying the building components has the effect of increasing depreciation during the first 15 years and particularly during the first five years.

GlobeSt.com: Are there other benefits of big data?

O'Connor: Big data can be used for number of purposes, limited only by the imagination. Other than Enriched Data, there is currently no valid option to evaluate municipal utility district (MUD) bonds. MUD bonds often trade at a 200 basis point spread over treasuries. However, there is not readily available data regarding the underlying collateral. Enriched Data has developed a program that evaluates the taxable value of the collateral for a MUD bond for a series of years. In addition, it includes information such as the MUD tax rate, volume of foreclosures, volume of home sales, supply of homes for sale versus sales, trends in sales prices and days on market for homes during a period of time. This data is aggregated from multiple data sources and put into a five-page summary providing insight into the risk of a MUD bond. The same types of data can be compiled for municipal bonds and other tax entities.

GlobeSt.com: What does Enriched Data offer that is different from other big data companies?

O'Connor: Enriched Data focuses on providing useful, accurate data and analysis to clients. Types of data include ownership contact data for properties with mortgages about to mature and ownership contact data for recently purchased properties. The ownership contact data provided is at least 97% accurate and includes at least one verified phone number for the decision maker for each property (typically the person who signed the deed of trust). In most cases, two or three phone numbers are included. In addition, for 70 to 80% of the records, an email address, LinkedIn account and website address are provided. For 99% of the records, there is a physical mailing address.

Secondly, Enriched Data works on providing actionable intelligence regarding valuation of marketable securities. We are currently in the process of developing analytics for residential mortgage-backed securities (RMBS). To our knowledge, there is no tool to value RMBS bonds, one of the largest asset classes in the world.

HOUSTON—Big data is part of real estate in a big way. Just how big? Companies such as Enriched Data, employing more than 200 people, look at big data in order to generate insights not readily found in general statistics. The firm provides specialized data feeds to help companies increase revenue and reduce expenses, and maintains a national database for residential and commercial real estate. Patrick O'Connor is president of Enriched Data and recently shared his insights into big data and real estate in an exclusive with GlobeSt.com.

GlobeSt.com: How does big data benefit the real estate industry?

Patrick O'Connor: Big data is causing disruptive change both in the residential and commercial real estate markets yet its impact is obscure to many real estate professionals. It is analogous to the impact of the Internet in the early 1990s. The Internet was recognized but the impact was not understood until a decade later. People talk about the days when we did not have computers and cell phones. In 10 years, people will wonder how people functioned before big data was available.

Big data is defined as multiple, large data sets combined together which can be analyzed to generate insights not available from other sources. It can be used to narrow the universe of prospects for a service or product by 90% to allow highly targeted marketing. Big data can also provide insights into clients and what features and benefits they value. Companies can both increase revenue and reduce expenses by properly using big data.

Big data can be effectively utilized with digital marketing which is an emerging arena not really understood by many real estate professionals. For example, you can “geo-fence” your competition and serve ads to those people. Digital marketing can be used to stratify an audience into homogenous groups for a marketing campaign as well.

GlobeSt.com: How should companies ensure they have access to the right big data?

O'Connor: The first step for most companies is to combine data from multiple silos. We are working with one national real estate services firm that has nine separate databases: one for each division. While it is easy to suggest combining databases, there are logistical, technical and political issues that make implementation difficult. However, aggregating internal data sets is one of the best ways to gain insights on clients. For example, what portion of investment sales involves a loan generated by the same firm? Another example is the portion of investment purchase acquisitions generating a management or leasing contract for the company. Another option is to cross-index the percentage of cross selling between the departments in a company.

Procuring additional data sets is done after combining internal data sets. One excellent source of data is psychographics, used to understand the characteristics of existing clients. Another source of data is a client survey. Understanding the characteristics of clients and their objectives provides information for both refining services and marketing messages. Hence, the first step in obtaining data regarding existing clients to allow targeted marketing of prospects. There are many options for differentiating clients including age, income, location, family status, length of real estate ownership time, equity in the real estate and the interest rate of a loan.

GlobeSt.com: What does cost segregation entail?

O'Connor: Cost segregation typically involves federal income tax savings of five to 10 times the cost of the report in the first year. Cost segregation reduces and defers federal and state income taxes. For real estate investors who are paying income taxes, a cost segregation report is the safest investment with the highest return they will ever make. This is a bold statement but it is true: where else can you get at return of 2,500 to 5,000% over a five-year period with no risk? This is accomplished by using an IRS-directed method to properly calculate depreciation. Most investors simply classify commercial buildings as 39-year properties. However, a sizable portion of the improvements can be classified as five, seven or 15-year property. Correctly classifying the building components has the effect of increasing depreciation during the first 15 years and particularly during the first five years.

GlobeSt.com: Are there other benefits of big data?

O'Connor: Big data can be used for number of purposes, limited only by the imagination. Other than Enriched Data, there is currently no valid option to evaluate municipal utility district (MUD) bonds. MUD bonds often trade at a 200 basis point spread over treasuries. However, there is not readily available data regarding the underlying collateral. Enriched Data has developed a program that evaluates the taxable value of the collateral for a MUD bond for a series of years. In addition, it includes information such as the MUD tax rate, volume of foreclosures, volume of home sales, supply of homes for sale versus sales, trends in sales prices and days on market for homes during a period of time. This data is aggregated from multiple data sources and put into a five-page summary providing insight into the risk of a MUD bond. The same types of data can be compiled for municipal bonds and other tax entities.

GlobeSt.com: What does Enriched Data offer that is different from other big data companies?

O'Connor: Enriched Data focuses on providing useful, accurate data and analysis to clients. Types of data include ownership contact data for properties with mortgages about to mature and ownership contact data for recently purchased properties. The ownership contact data provided is at least 97% accurate and includes at least one verified phone number for the decision maker for each property (typically the person who signed the deed of trust). In most cases, two or three phone numbers are included. In addition, for 70 to 80% of the records, an email address, LinkedIn account and website address are provided. For 99% of the records, there is a physical mailing address.

Secondly, Enriched Data works on providing actionable intelligence regarding valuation of marketable securities. We are currently in the process of developing analytics for residential mortgage-backed securities (RMBS). To our knowledge, there is no tool to value RMBS bonds, one of the largest asset classes in the world.