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In today's modern data-driven world, the ability to harness and synthesize property, demographic, and business consumer data has become a game-changer for businesses, government agencies, and researchers alike. In the ever-evolving realm of Geographic Information Systems (GIS), the Melissa Address Key emerges as a transformative tool, offering GIS experts a dynamic solution for unlocking location analytics across a spectrum of critical datasets. Address intelligence, property data, consumer information, and business details converge seamlessly through the Melissa Address Key, providing GIS professionals the ability to overlay or join (tabularly or spatially) diverse datasets to create a richer and more comprehensive understanding of the world around us.
As a geospatial professional, you use GIS in various applications. It can play an essential role in helping your organization understand the spatial relationships of data to make better-informed decisions. Here, we explore the possibilities and benefits of using Melissa's Geodata collection: Parcel, Business, Consumer, and Property data, and how they can provide a deeper understanding in suitability modeling, site selection and for property developers and real estate professionals.
Melissa Address Key (MAK) is the Key
Identifying optimal locations for new development (commercial, industrial, and residential) using property, business, and consumer data can play an integral role for property developers and real estate investors. The MAK is a persistent, unique 10-digit key assigned to each property address in the U.S. MAK application provides complete address coverage and makes it easy to link addresses in your database for analytics enrichment. Using the MAK, a user can integrate various datasets to obtain a more comprehensive understanding of demographic and socio-economic trends and analytics. The MAK resides in most of Melissa’s database, so joins on this unique key can associate a myriad of attributes. Creating spatial and table connections with Parcel, Address, Business, Consumer, and Property data can offer incredible insight about addresses and/or parcels. Here are some examples:
Identify preliminary development opportunities by finding properties that are uniquely zoned, such as multi-family housing or commercial use, to target potential opportunities. Each zoning category carries specific regulations regarding permitted uses, density, setbacks, and other development parameters. Identifying the zoning of properties ensures the chosen development aligns with these regulations, avoiding costly delays and potential legal troubles. Spatially join a zoning layer (publicly available) to the parcel database, then join the results to the Melissa Property database to identify a property’s zoning, address, ownership, structure characteristics, assessor’s valuation, mortgage details, and more.
GIS Procedural Steps:
- Add the parcel layer and zoning regulation layer to the GIS workspace.
- Use the "Spatial Join" tool (from Toolbox -> Analysis Tools -> Overlay -> Spatial Join) to select the parcel layer as the target layer and the zoning designation layer as the join layer.
- Specify the appropriate spatial relationship, such as "intersect" or “within”, to identify parcels overlapping with the various zoning types.
- Create a new layer containing the joined attributes, indicating the zoning designation for each vacant parcel.
- Table join the previously created layer to Property database, using MAK as the unique ID.
- Visualize by symbolizing the new layer by zoning type (e.g., multi-family residential) and query attributes from the property table to further understand potential development opportunities. Take it one step further by filtering certain parcels based on specific zoning criteria or property table attribution.
Figure 1: Using the MAK to link the Parcel record with the Address database
Figure 2: Finding the zoning classification (A1 – General Agriculture) for a given Parcel record
Assessing property market variables using a table joins on our consumer and property databases can reveal property characteristics of a given geographic area. Understanding potential market demand for real estate endeavors can be insightful in making data-driven decisions. Real estate professionals may want to find renter-occupied housing as a way to market potential real estate sales. Knowing the value of comparable properties in the area helps real estate agents price their clients' homes competitively and accurately. This maximizes the chances of a quick and successful sale. Understanding the rental landscape helps predict the availability and quality of potential tenants when selling an investment property. They can tailor their marketing towards investors seeking occupied properties with existing income streams.
GIS Procedural Steps:
- Add the parcel layer and demographic data table to the GIS workspace.
- Table join: Use the "Join" tool, selecting the parcel data layer and the demographic table as the join table.
- Match the fields containing the shared attribute (e.g., census block) in both layers. In this case, use the ‘MAK’ field.
- Export a new layer with the parcel geometry and the joined demographic data table.
- Visualize and analyze: Create thematic maps to visualize demographic patterns (e.g., renter occupied, assessor’s valuation). Additionally, use statistical tools to analyze potential market demand for different real estate types based on demographic characteristics.
Figure 3: Find renter-occupied housing
Figure 4: Classifying Property Valuation on local housing stock
Geospatial data can play a vital role in the real estate industry by providing valuable insights into property location, market trends, and marketing. It helps real estate professionals make data-driven decisions, optimize property development, and deliver enhanced client services. Melissa has the geospatial data that can help with your real estate needs and help your organization make more informed decisions.
Please get in touch with Melissa by visiting www.melissa.com for additional information.