Urban planning data, foot traffic, and ESG

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Foot traffic aka location data is often used with other urban planning data to help create more sustainable cities. This is important for future generations to meet their own long term objectives.

These objectives, increasingly driven by a focus on Environmental, Social, and Governance are met through impact investing driven by detailed trade area analysis with a strong ESG focus.

In addition to foot traffic, city planners and investors look at specific ESG criteria and ESG ratings when assessing urban planning opportunities. We'll discuss these in a bit more detail, below.

First, let's begin with a simple but important question:

Why does foot traffic matter in urban planning?

Urban planning is a complex thing. You need to understand where people are, what they want, and how they move around to get it. So, by understanding foot traffic and location data, you can get the big picture on human mobility and plan ESG smart growth from there.

How to assess foot traffic for urban planning and ESG

Our datasets can help you understand foot traffic to any defined urban area, Point of Interest, or venue. You can make more informed decisions for site selection or deselection, and learn how to boost your competitive advantage. To do these things, we help you follow three key steps:

urban planning data

Step 1: Gather raw data

Unacast uses GPS location data to measure foot traffic because it is the most reliable. It works by sending signals, or “pings,” from mobile devices to a constellation of satellites. GPS uses triangulation to determine where on the planet your device is, and describes that position using latitude and longitude. Each ping from a device also has a timestamp.‍

Step 2: Contextualize the data

The raw pings are clustered by our algorithms into events that indicate activity, such as dwelling at a location, or traveling and assigning retail venues and brands. An array of latitudes and longitudes are of no use. That's why Unacast's data engine translates the raw data feed into something understandable by adding context.

We make sure that private information, such as people’s exact home location, are obfuscated and not discernible to an address. We can add areas together to measure neighborhoods, cities, counties, states, and even an entire country.

Step 3: Create curated foot traffic datasets

We have datasets depending on your data maturity and needs: Foot Traffic Data, Dynamic Trade Areas Data, and Cross-Visitation Data. It’s tempting to think that once you add some context to the GPS pings on maps you’re done but there is more to it than data visualization. 

But there are literally an uncountable number of ways to make these location datasets say different things via catchment analysis, some of which are unhelpful.

This is where the team of data scientists and business strategists at Unacast helps you “ask” the data just the right questions.

How urban planning data influences ESG investing and mutual funds

ESG investing is largely driven by two core things: ESG criteria adherence and ESG ratings of an urban area. The higher the rating, the more likely an urban area is to draw impact investing from mutual funds and others.

The simplest way to think of it is that foot traffic drives use and density, which creates ESG needs for future generations, which dictates the portfolio investments that are made.

According to Bloomberg, Global ESG assets may surpass $41 trillion by 2022. Some of the best ESG funds out there today include Vanguard, iShares, Parnassus and 1919.

Retail stores and urban planning data

Data analytics is the cornerstone of modern retail stores. Data science not for science sake alone, but in order to understand more about customer journeys.

Modern retailers want to provide the ability to future generations to shop, dine and apply sustainable practices in their own lives as they choose. This is without compromising the ability to find what they want, when they want it.

Travel time - be it walk time or driving time - to a retail trade area or business district can not be a deterrent to use. All required amenities and services must be present without compromise.

Real time or near time data that tells an urban retailer where customers are coming from and where else they visit is very valuable. This intersection point with urban planning data and ESG is undeniable.

Urban planning data in public parks

It’s important for those responsible for delivering parks, public spaces, and other public services to integrate measurement and validation in their workflow. Otherwise, we risk perpetuating a cycle of ‘build it and they will come’ projects. Appropriate data allows us to refine both our ideas and the spaces we create, to better serve the public. 

These data can be computationally involved, and it takes time to get familiar with any new form of data. Further, some available tools and offerings that offer a nice initial impression mask warts in the incoming data streams, or limit the questions that you can ask. 

From a researcher’s perspective, no amount of lipstick will redeem the pig. So for many, the question becomes, ‘Can I even trust this? Is it worth the lift?’  The answer is yes. If you have the right questions and the right data streams informing your work.

Once the data is formatted and validated, it offers striking insights at extraordinary spatial precision. Working with fresh, clean data gives you both a global view, and lets you drill down to those individual corners, neighborhoods, streets and parks. It tells you where to focus.

Want to know more? Schedule a meeting with one of our data experts.


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