Consumer Data | Aggregated Spend Patterns | Retail Transactions product image in hero

Consumer Data | Aggregated Spend Patterns | Retail Transactions

A dataset by SafeGraph
brands raw_total_spend raw_num_transactions raw_num_customers +19 more
["Target"] 76050.12 1521 435 ...
["Target"] 76050.12 1521 435 Sample
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Starts at
$250 / purchase
Consumer Data | Aggregated Spend Patterns | Retail Transactions 400K POI icon
400K POI
Consumer Data | Aggregated Spend Patterns | Retail Transactions 100% fill rates icon
100% fill rates
Consumer Data | Aggregated Spend Patterns | Retail Transactions USA covered icon
USA covered
Consumer Data | Aggregated Spend Patterns | Retail Transactions 2 years of historical data icon
2 years of historical data

Available Datasets for Purchase

Description

SafeGraph Spend is an aggregated transaction dataset of consumer data containing spending behavior at individual points of interest. This dataset includes transaction consumer data at individual POIs in the US based on aggregated debit card and credit card transactions.
Dataset contains more than 400K POI, focusing on consumer behavior data and transactions at major brands and chains. Samples/Tables Included POI information and consumer data: -Location name -Address -Category -Total spend -Number of transactions -Number of unique customers Additional Information: All SafeGraph POI-based datasets utilize Placekey (https://www.placekey.io/) as the primary key and are formatted as delimited CSVs. SafeGraph updates the Spend dataset every month with the past month's openings and closings and maintains a persistent Placekey across releases. Our detailed SafeGraph Spend Schema(1) is available online. Additionally please refer to Places Data Manual(2) for more detailed field definitions and methodologies. Our Places Summary Statistics(3) is updated with every monthly release to reflect data coverage. Data Dictionary Our documentation site includes detailed information for all of our products, but this product listing specifically only includes the Core Places data set and does not include Geometry or Patterns data. (1) Spend Schema: https://docs.safegraph.com/docs/spend (2) Places Data Manual: https://docs.safegraph.com/docs/places-manual (3) Places Summary Statistics: https://docs.safegraph.com/docs/places-summary-statistics Example Use Case: Correlations with Quarterly Revenue - When rolled up to the parent brand, SafeGraph Spend data can be compared against financial indicators of companies (eg. quarterly revenue). SafeGraph uses such tests as a benchmark even though the use cases of Spend are far more varied than aggregating by brand. Based on one such analysis, SafeGraph data track with quarterly revenue from major brands like McDonald's, Chipotle, and Target, including cases where companies report online sales separately than overall revenue (e.g., Chipotle).

Data Attributes

Attribute & Description Example
brands
If this POI is an instance of a larger brand that we have explicitly identified, this column will contain that brand name.business.
["Target"]
raw_total_spend
Total amount spent at this POI in transactions captured by our panel during the date range.
76050.12
raw_num_transactions
Number of transactions at this POI captured by our panel during the date range.
1521
raw_num_customers
Number of unique customers with at least one transaction at this POI captured by our panel during the date range. POI rows with fewer than 4 customers in the time period are excluded.
435
placekey
Unique and persistent ID tied to this POI. See the Placekey Concept for details on placekey design.
[email protected]
safegraph_brand_ids
Unique and consistent ID(s) that represents this specific brand.
["SG_BRAND_59dcabd7cd2395a2"]
median_spend_per_transaction
Median amount spent in each transaction at this POI.
50.00
median_spend_per_customer
Median amount spent by each customer at this POI.
174.83
spend_per_ transaction_percentiles
The 25th and 75th percentiles of spend_per_transaction at this POI.
{“25”: 23.11, “75”: 80.99}
spend_by_day
Total amount spent at this POI each day over the covered time period.
[2535.34, 5214.11, … ]
spend_per_transaction_by_day
Median transaction size at this POI each day over the covered time period. Values will be null for days with no transactions.
[20.33, 70.22, … ]
spend_by_day_of_week
Total amount spent at this POI on each day of the week over the covered time period. See Date Granularity.
{“Monday”: 10864.11, “Tuesday”: 15200.10, … }
spend_pct_change_ vs_prev_month
Percent difference between last month’s raw_total_spend and this month’s. Value will be null where reference month does not exist.
5
spend_pct_change_ vs_prev_year
Percent difference between last year’s same-month raw_total_spend and this month’s. Value will be null where reference month does not exist.
-10
online_transactions
The number of online transactions at this POI during the date range. The remaining transactions were in-person.
310
online_spend
The amount spent at this POI through online methods during the date range. The remaining spend was in-person.
7512.22
transaction_intermediary
The number of transactions at this POI based on the intermediary through which the transaction was made, if any. Transactions can have multiple intermediaries, in which case the number of transactions will be incremented for each intermediary.
{“No Intermediary”: 900, "Apple Pay": 215, "DoorDash": 155, "Square": 32}
spend_by_ transaction_intermediary
Total amount spent among transactions by intermediary, including no intermediary. For each POI, will have the same keys as transaction_intermediary.
{“No Intermediary”: 10400.12, "Apple Pay": 2015.00, "DoorDash": 1502.33, "Square": 320.00}
bucketed_customer_frequency
The distribution of customer repeat frequencies based on pre-specified buckets. Key is the number of transactions per customer and value is the number of customers that were within that range.
{ "1": 500, "2": 302, "3": 101, "4": 20, "5-10": 90, ">10": 5}
mean_spend_per_customer_ by_frequency
Mean amount spent per customer at this POI based on customer frequency. Key is the number of transactions per customer and value is mean spend by customers that were within that range.
{ "1": 10000.10, "2": 31000.32, "3": 999.01, "4": 200, "5-10": 805.00, ">10": 90.89}
bucketed_customer_incomes
The distribution of estimated customer incomes based on pre-specified buckets. Key is the range of customer income in dollars per year and value is number of customers that were within that range. Only includes keys where values are non-zero.
{“<25k”: 135, “25-45k”: 225, “45-60k”: 500, “60-75k”: 252, “75-100k”: 220, “100-150k”: 111, “>150k”: 12}
mean_spend_per_customer_ by_income
Mean amount spent per customer at this POI based on pre-specified customer income buckets. Key is the range of customer income in dollars per year and values represent the mean spend by customers in that income range. Only includes keys where values are non-zero.
{“<25k”: 1700.10, “25-45k”: 2221.51, “45-60k”: 5000.00, “60-75k”: 2593.12, “75-100k”: 124.00, “100-150k”: 999.19, “>150k”: 120.25}
customer_home_city
The number of customers to the POI based on the customer’s estimated home location. Homes are indicated by unique city and state pairs.
{“Palo Alto, CA”: 22, “Redwood City, CA”: 308, “Mountain View, CA”: 152, ...}

Geography

North America (1)
United States of America

History

2 years of historical data

Volume

400,000 POI
1,100 Brands

Pricing

Free sample available
License Starts at
One-off purchase Available
Monthly License Not available
Yearly License
$30,000 / year
Usage-based
$0.10 / API call

Suitable Company Sizes

Small Business
Medium-sized Business
Enterprise

Quality

Self-reported by the provider
100%
fill rates

Delivery

Methods
S3 Bucket
UI Export
REST API
Frequency
monthly
Format
.csv

Use Cases

Categories

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Frequently asked questions

What is Consumer Data Aggregated Spend Patterns Retail Transactions?

SafeGraph Spend is an aggregated transaction dataset of consumer data containing spending behavior at individual points of interest. This dataset includes transaction consumer data at individual POIs in the US based on aggregated debit card and credit card transactions.

What are the data attributes of Consumer Data Aggregated Spend Patterns Retail Transactions?

This product has 23 key data attributes. These include brands, raw_total_spend, raw_num_transactions , raw_num_customers , and placekey. Request a data sample from SafeGraph to see these attributes in more detail and see what information they can provide.

What is Consumer Data Aggregated Spend Patterns Retail Transactions used for?

This product has 5 key use cases. SafeGraph recommends using the data for Consumer Trend Analysis, Consumer Profiling, Retail Analytics, Consumer Intelligence, and Consumer Data Enrichment. Global businesses and organizations buy Demographic Data from SafeGraph to fuel their analytics and enrichment.

Who can use Consumer Data Aggregated Spend Patterns Retail Transactions?

This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Demographic Data. Get in touch with SafeGraph to see what their data can do for your business and find out which integrations they provide.

How far back does the data in Consumer Data Aggregated Spend Patterns Retail Transactions go?

This Dataset / Database / Data Feed / Data API has 2 years of historical coverage. It can be delivered on a monthly basis.

Which countries does Consumer Data Aggregated Spend Patterns Retail Transactions cover?

This product includes data covering 1 country like USA. SafeGraph is headquartered in United States of America.

How much does Consumer Data Aggregated Spend Patterns Retail Transactions cost?

Pricing for Consumer Data Aggregated Spend Patterns Retail Transactions starts at USD0.10 per API call. Connect with SafeGraph to get a quote and arrange custom pricing models based on your data requirements.

How can I get Consumer Data Aggregated Spend Patterns Retail Transactions?

Businesses can buy Demographic Data from SafeGraph and get the data via S3 Bucket, UI Export, and REST API. Depending on your data requirements and subscription budget, SafeGraph can deliver this product in .csv format.

What is the data quality of Consumer Data Aggregated Spend Patterns Retail Transactions?

SafeGraph has reported that this product has the following quality and accuracy assurances: 100% fill rates. You can compare and assess the data quality of SafeGraph using Datarade’s data marketplace. SafeGraph has received 17 reviews from clients. SafeGraph appears on selected Datarade top lists ranking the best data providers, including Best Data Providers For Location-Based Marketing and Top 10 POI Data Providers & APIs.

What are similar products to Consumer Data Aggregated Spend Patterns Retail Transactions?

This Dataset / Database / Data Feed / Data API has 3 related products. These alternatives include US Spending Data Aggregated Spend Patterns Credit Card/Debit Card Transactions, Yodlee’s Aggregate Panel (US Consumer Transaction Data Aggregated by Ticker/Merchant), and Fable Data Aggregated European Consumer Transaction Dataset. You can compare the best Demographic Data providers and products via Datarade’s data marketplace and get the right data for your use case.