See how and when people are spending their money at specific locations. Combine POI, polygon, and spending data to understand how consumers behave by geography.
By layering aggregated transaction data over high-quality point of interest data, you can gain a clear understanding of consumer spending behavior. You can analyze spending trends over time at a set location, between locations, and even across entire regions.
Spend data provides detailed credit and debit transaction information like:
Coverage
Spend data is built with the largest source of credit and debit transactions available, plus a proprietary methodology to match transaction data to individual POIs for location-based insights.
Data Enrichment
Enriching points of interest (POIs) with transaction data enables you to see the whole picture, whether for competitive intelligence, site profiling, or audience building.
Ready to Use
Transaction data is messy, often requiring complex data engineering to be useful. Other providers do aggregation, but at too high a level to be insightful. Leveraging our expertise in the POI space, SafeGraph provides aggregated transaction data at the place-level for the most flexibility in analysis.
Explore aggregated transaction data tied to places.
Access Data Specs and Delivery Information
Access all documents related to our transaction attributes below.
See the schema for the Spend dataset so you understand how it pairs with Places and all relevant metadata.
We outline exactly how our data is curated, and explore how to quantify sampling bias.
See how comprehensive the Spend dataset is, detailing the attributes, brands, and regional coverage included.
Data can be accessed simply using any of the following 3 methods:
Access reliable, places-based transaction data at scale. Configure an S3 bucket for streamlined monthly data deliveries.
Query and download SafeGraph Spend directly through Snowflake to easily integrate transaction data into your workflows.
Reach out and try SafeGraph Spend for yourself. Explore the columns included and see the possibilities for enriching your current data.
Aggregated transaction data is data on individual transactions such as payments, purchases, loans, bookings, and more. Transaction data is aggregated when it comes from multiple sources and is compiled into a single usable collection of data. Personal information is removed from transaction data so that individuals cannot be tied directly to their purchases; this allows investors, retailers, financial institutions, and more to use spending data without compromising individual identities. Instead, spending data can be used to understand how groups of people near a specific POI or in a specific area (such as a neighborhood), interact with the places around them.
From raw transaction data, we use a proprietary algorithm to match anonymized transactions to POIs, leveraging the high quality information from our Places dataset to ensure high veracity matches. From there, we aggregate the matched transactions and apply rigorous QA methods to create the final Spend product. We source transactions from a well known financial data aggregator used by some of the largest financial institutions. We receive consumer-permissioned and de-identified credit and bank card spending data from accounts at thousands of financial institutions in the US, which we then aggregate to our POI dataset.
Spend data is aggregated monthly and delivered about two weeks after the final day of the prior month. This delay is to ensure that all transactions appropriately settle and to provide enough processing time.
Currently, we have transaction records going back to January of 2020.
Spend data is currently only available in the US. Interested in another geography? Let us know.
