data visualization

QSR Consumer Spending Data for Delaware, 2020-2021

Anonymized, Location-Based Transaction Data Powered by SafeGraph Spend

Consumer spending data is obviously important for measuring a business’s financial health. But in addition to knowing how much money is spent, it can also be important for a business to know where and when customers are spending it. This can greatly influence a company’s decisions regarding where and when to expand their business, or to close underperforming locations.

That’s why we created our Spend dataset – to provide geospatial context to retail transaction data. As an example, the visualization here displays information from Spend regarding transactions at quick service restaurants (QSRs) in Delaware from the start of 2020 to the end of September 2021. It demonstrates the kinds of things Spend can tell a business about the customers spending money at particular stores, such as what demographics they belong to, where they’re coming from, how they’re paying, and when they’re most inclined to shop there.

About this transaction data example visualization

This dashboard visualizes statistics regarding aggregated and anonymized transactions at QSRs throughout the state of Delaware. This is real consumer spending data that ranges from the beginning of 2020 to the end of September 2021.

The dashboard includes a map that displays the locations of QSRs in Delaware where transactions took place. It also features a line chart showing average expenditures at selected QSRs over specific time periods (year, quarter, month, week, or day).

The dashboard includes three bar charts. One shows the number of transactions that took place through intermediary payment processors at selected QSRs. Another shows the top 10 cities in Delaware where the people who completed transactions at selected QSRs came from. The last one shows the average amount spent, per transaction, by customers from various income brackets at selected QSRs.

You can click on the magnifying glass on the map and type in a specific place you’re looking for. Or, click the “+”, “-”, or house buttons to increase, decrease, or reset the zoom on the map, respectively. Underneath those options, you can also set your cursor’s function to zoom in on a specific part of the map, or to move the map around.

By far the most useful of the additional options, though, are the ones that change your cursor’s function into a rectangular, radial, or lasso selector. You can click and drag with these tools to select groups of QSRs marked on the map; you can even hold down the CTRL/CMD key and click and drag again to select multiple groups. You can also click on a single QSR to select it. The charts surrounding the map will change to reflect the consumer spending historical data for the QSRs you select.

Finally, you can click the “+” or “-” buttons that appear underneath the line chart to increase or decrease the granularity of the dates being measured.

See more of what SafeGraph Spend can tell you about transactions at over 1 million stores nationwide. Read all about it here.

Enrich point of interest data with transaction and consumer spending data

Point of interest (POI) data, like that found in our Places dataset, can give fundamental information about many notable places on Earth: address, public accessibility, hours of operation, contact information, and so on. But not every POI is commercial in nature, and so not every set of POI data contains information about economic activity at the places it describes.

Conversely, not all financial data puts emphasis on where or when consumers spend their money. This can leave blind spots in a company’s business strategy. For example, some products may not sell well in a specific location because the geography doesn’t suit them, or because nearby competitors have already captured most of the market share. Other products may only sell well on certain days of the week, during a particular season, or close to a particular holiday/celebration.

We created Spend to remedy these issues by combining essential POI data with consumer expenditure data tied to places and times. This allows businesses to not only know where and when customers are spending money on their products, but also analyze how the market for their products and brands changes across time periods or geographic regions.

Analyze the success of locations and perform site selection and deselection

Retail transaction data analysis that takes location and time into account is critical for properly performing retail site selection and deselection. These are, respectively, when a company is looking for a new location to place a store and expand their business, or to shut down operations at a store because its operating costs are outweighing its profitability.

Both processes are significantly costly and risky; a poorly-informed decision in either of them can put a company far behind its competitors. That’s why when going through these operations, it’s important for a company to have not only a sufficient amount of data, but also a wide breadth of data for looking at the issue from multiple angles. This helps to minimize the risk involved and improve the chance for a positive outcome.

For example, a company may want to perform a full-scale trade area analysis to see if a market niche is (still) available for its business in a particular area. If so, it will need to consider a number of factors, including:

  • How many directly-competing businesses are in the area?
  • How many indirect competitors are in the area? Could we potentially partner with them?
  • Who are the area’s main demographics? What are their lifestyles? How much disposable income do they have?
  • Which locations in the area tend to get the most foot traffic (and why)?
  • When are locations with high foot traffic typically busiest (and why)?
  • Which locations in the area are the most accessible, given the current transportation infrastructure?

Datasets that take these kinds of variables into account – like SafeGraph Spend – are incredibly valuable tools for selecting and deselecting retail locations. They help companies understand what kinds of consumers are going where and when, and why. This lets companies make sound decisions on where to put new stores to attract more business, or which stores to close because business potential in the area has dried up.

How to get this data from SafeGraph

SafeGraph Spend, combines our flagship Places POI data with permissioned, anonymized, and aggregated credit/debit card transaction data. The result is a unique data product that lets you dive into the economic activity of over 1 million commercial locations across the US. Get information on the average amount customers spend per transaction, the rate at which visitors to a store actually make a purchase, how much is spent on a particular day, and how in-store spending for a brand compares to online spending for that same brand.

Find out more by downloading a free sample, or by visiting our site.

Related data visualizations

Foot traffic data – like that found in our Patterns family of products – can also be a good indicator of how popular certain businesses are, and how well they’re performing. Here are a few other visualizations that demonstrate this:

  • Foot Traffic to Gyms: 2020 vs. 2021 – A measure of the change in foot traffic to gyms in the US in 2021 versus 2020, both by state average and by month. It illustrates how gyms saw significant increases in foot traffic over this time period, as public health restrictions related to COVID-19 were lifted and people subsequently wanted to return to more active lifestyles.
  • Impact of COVID-19 on Foot Traffic – Graphs showing monthly US foot traffic values from 2019 and 2020 for various business categories, brands, and urban areas. Their purpose is to show how the COVID-19 pandemic (and the subsequent public health measures to combat it) affected visits to different types of places in different ways.
  • Spring Break Foot Traffic, 2018-2021 – A dashboard comparing changes in foot traffic for popular Spring Break destination cities in the US, as well as for bars in those cities, for the month of March from 2018 to 2021. There was a dramatic downturn in foot traffic for both vacation spots and bars during March of 2020, when the COVID-19 virus outbreak was declared a global pandemic. 2021 showed signs of recovery, though.
CONTENTS

Products we used to build this visualization:

Places Data

See how data leaders leverage Places as their source of truth for any location in the world.

Geometry Data

Incredibly accurate POI footprint data for a clear picture on the boundary of a place.

Patterns Data

Mobility and demographic aggregations that answer: how often people visit, where they come from, where else they go, and more.

Spend Data

See how and when people are spending their money at specific locations.

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