Data Points

Data is at the heart of every real estate decision, whether you're an investor or seller. What makes a property unique is everything from the type of flooring to the township it sits in. According to a 2019 National Association of Realtors report, school quality is the fifth most important factor in the home buying process, following neighborhood quality, convenience to jobs, affordability, and convenience to friends or family.¹ Research suggests this is not isolated to American consumers; a 2016 research study in Australia found that the four types of data profiles most relevant to prospective homebuyers were related to the property, region, educational system, and local transportation.²  Visualizing this data is key - another study found that visitors spend 40% more time on a real estate listing page when it contains a dynamic visualization of not only the property itself but also the area around it.³

What makes visualizations so important in real estate is the ability to layer relevant information onto a map to get a comprehensive view of a property. What's important to one person is irrelevant to another, so users require the ability to toggle on or off different datasets. This differs for each and every transaction, necessitating a wide variety of data and flexibility in deployment.

For example, a business searching for a new office location may only be interested in the property details and parcel size, which can help them anticipate future costs. 
They may also want to know what the environmental hazard risk associated to that property is, helping them determine insurance and upkeep costs.

A residential property search would look quite different. Of course, the physical and financial property information is just as essential as it was for the business example.

[1] 2019 Home Buyers and Sellers Generational Trends Report, (National Association of Realtors Research Group, April 2019) 36.
[2] Mingzhao Li, Zhifeng Bao, Timos Sellis, and Shi Yan, Visualization-Aided Exploration of the Real Estate Data, (Springer International Publishing, 2016).
[3] Case Study: Data Visualization Company, (Pitney Bowes, n.d.).

------------------------------
Briana Brown
Pitney Bowes
------------------------------

Great post Briana, thanks for sharing. What's really interesting is the additional detail that can be learned about a neighborhood when you begin incorporating individual and household level data. Generally, individual consumer data is not appropriate for many visual demos do to the sensitivity of personal information that can be exposed. But, for specific use cases the recency and precision of consumer data provides additional value to support real estate decisions. By anonymizing consumer data we can visualize observed trends (without sharing personally identifiable information) and answer questions like; what type of people have moved into this neighborhood in the last year, what's their average age, do they have children, where do they work? It would be cool to see this additional level of detail built into this real estate demo!


------------------------------
Dylan Conrad
Product Manager
------------------------------

Original Message:
Sent: 10-22-2019 10:58
From: Briana Brown
Subject: Data for real estate home search

Data is at the heart of every real estate decision, whether you're an investor or seller. What makes a property unique is everything from the type of flooring to the township it sits in. According to a 2019 National Association of Realtors report, school quality is the fifth most important factor in the home buying process, following neighborhood quality, convenience to jobs, affordability, and convenience to friends or family.¹ Research suggests this is not isolated to American consumers; a 2016 research study in Australia found that the four types of data profiles most relevant to prospective homebuyers were related to the property, region, educational system, and local transportation.²  Visualizing this data is key - another study found that visitors spend 40% more time on a real estate listing page when it contains a dynamic visualization of not only the property itself but also the area around it.³

What makes visualizations so important in real estate is the ability to layer relevant information onto a map to get a comprehensive view of a property. What's important to one person is irrelevant to another, so users require the ability to toggle on or off different datasets. This differs for each and every transaction, necessitating a wide variety of data and flexibility in deployment.

For example, a business searching for a new office location may only be interested in the property details and parcel size, which can help them anticipate future costs. 

They may also want to know what the environmental hazard risk associated to that property is, helping them determine insurance and upkeep costs.

The business would also be interested to understand the area it is potentially moving to, particularly its crime profile. Will workers and the property be safe?

A residential property search would look quite different. Of course, the physical and financial property information is just as essential as it was for the business example.

But understanding the community, such as the neighborhood and school districts, becomes much more important.

Potential buyers may also be interested in understanding what's closeby, especially for vital amenities like grocery stores that they plan to frequent.

Whether investing in or selling a property, layering data is the best way to get a comprehensive view of a property. Check it out  for yourself with the Home Search Real Estate Demo,which layers 18 datasets for enhanced real estate insights. Knowledge Community members already have access!

[1] 2019 Home Buyers and Sellers Generational Trends Report, (National Association of Realtors Research Group, April 2019) 36.
[2] Mingzhao Li, Zhifeng Bao, Timos Sellis, and Shi Yan, Visualization-Aided Exploration of the Real Estate Data, (Springer International Publishing, 2016).
[3] Case Study: Data Visualization Company, (Pitney Bowes, n.d.).

------------------------------
Briana Brown
Pitney Bowes
------------------------------

Nice article Briana.
The power location information provides in these situations is incredible. We are seeing some trends in Australia that may change the way we search for properties. At the moment it is all about price, number of bedrooms, type of property etc etc. The trend is moving toward asking questions to understand what is important to the potential purchaser - Do they like eating out, what services are important to them, what sort of environments to do enjoy, what are their favorite activities, where do they work ............... From this the emerging systems are hoping to provide matches that are far more suitable to a purchasers preferred lifestyle.
I think this type of use is so easy to relate to, I see it as a computational approach of that used in the UK show Escape to the Country. Often the properties liked the most are in areas the purchaser had never thought about.
I get excited when customer centered approaches are paired with the power of location.

------------------------------
Gerry Stanley
Pitney Bowes Australia Pty Ltd
Macquarie Park
------------------------------

Original Message:
Sent: 10-22-2019 10:58
From: Briana Brown
Subject: Data for real estate home search

Data is at the heart of every real estate decision, whether you're an investor or seller. What makes a property unique is everything from the type of flooring to the township it sits in. According to a 2019 National Association of Realtors report, school quality is the fifth most important factor in the home buying process, following neighborhood quality, convenience to jobs, affordability, and convenience to friends or family.¹ Research suggests this is not isolated to American consumers; a 2016 research study in Australia found that the four types of data profiles most relevant to prospective homebuyers were related to the property, region, educational system, and local transportation.²  Visualizing this data is key - another study found that visitors spend 40% more time on a real estate listing page when it contains a dynamic visualization of not only the property itself but also the area around it.³

What makes visualizations so important in real estate is the ability to layer relevant information onto a map to get a comprehensive view of a property. What's important to one person is irrelevant to another, so users require the ability to toggle on or off different datasets. This differs for each and every transaction, necessitating a wide variety of data and flexibility in deployment.

For example, a business searching for a new office location may only be interested in the property details and parcel size, which can help them anticipate future costs. 

They may also want to know what the environmental hazard risk associated to that property is, helping them determine insurance and upkeep costs.

The business would also be interested to understand the area it is potentially moving to, particularly its crime profile. Will workers and the property be safe?

A residential property search would look quite different. Of course, the physical and financial property information is just as essential as it was for the business example.

But understanding the community, such as the neighborhood and school districts, becomes much more important.

Potential buyers may also be interested in understanding what's closeby, especially for vital amenities like grocery stores that they plan to frequent.

Whether investing in or selling a property, layering data is the best way to get a comprehensive view of a property. Check it out  for yourself with the Home Search Real Estate Demo,which layers 18 datasets for enhanced real estate insights. Knowledge Community members already have access!

[1] 2019 Home Buyers and Sellers Generational Trends Report, (National Association of Realtors Research Group, April 2019) 36.
[2] Mingzhao Li, Zhifeng Bao, Timos Sellis, and Shi Yan, Visualization-Aided Exploration of the Real Estate Data, (Springer International Publishing, 2016).
[3] Case Study: Data Visualization Company, (Pitney Bowes, n.d.).

------------------------------
Briana Brown
Pitney Bowes
------------------------------