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The Impact of Consumer Mobility on Urban Development and Transportation Planning

August 19, 2020
Ryan Fox Squire

SafeGraph’s Neighborhood Patterns dataset can help urban developers and transportation planners devise more effective transportation networks and smarter neighborhood development strategies

Last month, we announced the launch of the new SafeGraph Neighborhood Patterns dataset. To build this dataset, we took our knowledge and expertise about points of interest (POI) and applied the same methodology to Census Block Groups (CBG). Because CBGs can, more or less, be considered “physical places” in their own right, we saw an opportunity to shed light on population movement patterns in ways that we hadn’t yet explored in such granular detail.

Our Neighborhood Patterns dataset unlocks a new kind of knowledge that can help businesses, planners, researchers, and local governments to understand things like:

  • What days of the week different CBGs are the busiest 
  • How many people stop within CBGs during the morning, noon, and evening meal hours
  • Where do people travel to and from to get to these meal-time spots 
  • What is the difference in demographics and consumer movement patterns within and between CBGs on weekdays versus weekends

Our goal in building the Neighborhood Patterns dataset was simple: to demonstrate how a deeper understanding of consumer movement patterns can empower local businesses to make smarter decisions about how to drive long-term success. 

This has already proven its weight in gold for commercial real estate site selection (and de-selection) and retail trade area analysis. SafeGraph’s data has already given many businesses the knowledge and insights to identify where to build a new brick-and-mortar storefront (with the greatest chance of reaching its target consumers), to optimize businesses hours against retail operating costs, and to determine which other factors—directly tied to how consumers engage with and around their local communities—can help businesses run more efficient and profitable operations.

Huge benefits for transportation and neighborhood planning

Although our initial focus, when launching SafeGraph’s Neighborhood Patterns dataset, was on retail site selection and trade area analysis, we began to see a new opportunity emerging around transportation and neighborhood planning. 

In the same way that this data enables businesses to optimize for success within a local market, it also creates an entirely new way for urban developers to understand the load of transportation networks in relation to general movement patterns between different CBGs within a local area. Additionally, it allows you to see, with greater precision and granularity than ever before, how these patterns change at all hours of the day.

An example of SafeGraph’s Neighborhood Patterns data in action, showing the volume of consumer movement into downtown Seattle from various CBGs at different day-parts.

The value here for urban developers and transportation planners is quite unique. Whether you are looking to develop a new public rail network, a freeway expansion, an affordable housing community, or additional bike paths or park spaces, this data can help you make smarter, more informed decisions about what development strategies can best achieve your upfront goals. 

Additionally, it can also help you proactively identify problem spots or areas of opportunity within your local area. For example, has new suburban migration led to increased traffic on freeways during peak hours and, conversely, made “drive times” for getting to and from work longer and unbearable? Are certain metro rail lines operating with too little or too much frequency at different hours of the day in relation to actual consumer demand? Will local businesses be able to keep up with increased demand caused by building a new housing community—and, if not, will the development of new shopping malls and other commercial centers need to be considered in parallel? 

You get the point: by painting a clearer picture of how people move to and from their homes to various POIs and CBGs within their local area, SafeGraph Neighborhood Patterns data equips urban developers and transportation planners with actionable insights that lead to more effective transportation networks and smarter neighborhood development strategies.

Understanding consumer mobility leads to better urban planning 

Long story short, there are a lot of benefits that go hand-in-hand with understanding the general movement patterns of any given population. Whether your focus is purely on supporting the infrastructure needs of a local market or if you’re tasked with devising new strategies for efficient intra- and inter-state transportation networks—or pretty much anything that’s related to how people move to and from their homes—our data can unlock new knowledge and insights to help you make better planning decisions. 

Our team is ready to help you learn more about how SafeGraph Neighborhood Patterns data can take your urban development and transportation planning efforts to the next level. Schedule a demo with our team today to get started.

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