Case Study

How Invesco Uses TravelTime to Perform Geospatial Real Estate Analysis

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Invesco is a global independent investment management firm with almost $1.2 trillion assets under management. The firm manages assets on behalf of individual clients, pension funds and corporate institutions.

The Invesco Real Estate team’s primary role is to help investment professionals make the best decisions when it comes to property investment.

Since 2018, Invesco’s Real Estate team has been using TravelTime’s Alteryx macros to conduct geospatial analysis of real estate data.

With the tools, Invesco can run travel time catchment area analysis across thousands of properties in a just few clicks. All they need to do is select a property and enter a few parameters.

For instance, they may choose to show all reachable locations within a 20-minute bus journey from ‘53 Baker Street’. The travel time tool will create a shape, also known as an isochrone, showing all reachable locations within that time frame.

By taking into account transport times, travel time catchments give a real-life understanding of access compared to traditional distance catchments. This kind of data allows the team to accurately analyse how a property’s accessibility influences its value.

Using TravelTime’s Alteryx macros to analyse catchment areas

TravelTime geocoder
Using the TravelTime geocoder to process large volumes of addresses

First, using the TravelTime geocoder in Alteryx, Invesco can map out a huge quantity of addresses in a few clicks of a button. As Matt Hall, Director – Head of Data Analytics, Europe, explains:

“We can run a whole city with multiple nodes, processing thousands of locations in a single automated workflow. This is now very simple and easy, whereas the traditional system wasn’t capable of carrying out batch analysis.”

After using the geocoder, the team uses the travel time tool to carry out catchment area analysis and find out the accessibility of thousands of properties. The tool uses public transport timetable data to calculate accurate travel times. It can also use other standard modes like driving, cycling or walking, or even a combination of transport modes.

“The public transport side of the plugin was a real advantage over other systems as this is how most people who work in big cities travel,” says Hall. “We can now build catchments based on public transport which is incredibly valuable.”
60 minute travel time area
An example travel time catchment area showing how far can be reached within 60 minutes by public transport

Evaluating property value using travel time data

The TravelTime tool has become crucial for Invesco’s understanding of property accessibility, which is a key consideration when evaluating property value.

After pinpointing thousands of residential units across a major city, Invesco uses the travel time tool to calculate the travel time of each address to key locations. These might include key amenities such as schools, cafes, green spaces, and public transport locations.

30 minute public transport travel time visualisation

An example visualisation showing all schools within a 30-minute travel time

Invesco then plugs this data into specialist machine learning models to determine how the accessibility of the apartment, house or office space impacts its rent price. This granular analysis of proximity is crucial for a true understanding of a property’s value. As Hall explains, “when looking at investing in property, location is everything.”

Louis Wright, Senior Global Research Associate, adds:

“TravelTime has become integral to Invesco’s geospatial analysis of real estate data. This is particularly true for residential market analysis, where Invesco uses TravelTime’s tools to understand the complexities of Europe’s largest residential markets.”

“This kind of analysis helps our team answer questions such as: what is the rent price impact of being 5 minutes closer to green space? Or what is the rent price impact of a new train station on the surrounding properties?”

Using the TravelTime geocoder to create heat maps

The team at Invesco also uses the geocoder to conduct their own internal analysis.

Variation in rent prices heat map

For example, the heat map above, created using the TravelTime geocoder, shows how rent prices vary across Milan.

What are the benefits for Invesco?

Traditionally, this kind of analysis would be time-consuming. However, with the TravelTime macros, Invesco is able to run huge datasets in a few clicks. This saves the team a lot of time.

Additionally, the team can carry out mass level analysis with a high degree of granularity. By factoring in transportation and taking a human-centred view of accessibility, they can present investment professionals with unique and accurate real estate insights.

“Real estate data is increasingly granular and investment professionals are expected to be able to process large volumes of opportunities in multiple locations,” says Wright. “This ability to produce ‘first-cut’ market analysis, driven by large data sets, is invaluable when evaluating and underwriting investments.”

The team’s unique approach to real estate analysis gives Invesco a precise understanding of value. Whether carrying out financial modelling, underwriting or predicting, the team’s innovative approach helps to put Invesco at the cutting edge of real estate analysis.

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