Audiences
Provided By: Mastercard
Audiences
Provided By: Mastercard
Mastercard Audiences analyzes aggregated and anonymized consumer spending patterns to create standard or custom audience segments at the micro-geographic (i.e., Zip+4) level. Customers can apply Audiences insights to their data sets to make those insights actionable.
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Public offer
Payment schedule: Upfront payment | Offer auto-renewal: Not supported
$0 for 3 months
Overview
Mastercard Audiences
Data Product Overview
Mastercard Audiences analyzes aggregated and anonymized consumer spending patterns to create standard or custom audience segments at the micro-geographic (i.e., Zip+4) level. Our customers can apply Audiences insights to their data sets to make those insights actionable. There are two types of Mastercard Audiences:
- Mastercard Standard Audiences – Hundreds of off-the-shelf audiences based on aggregated and anonymized transaction data in different industries and seasonal shopping behavior. a. Some examples include:
- ZIP+4 - Online Food & Meal Delivery – Frequent Buyers
- ZIP+4 - Online Shoppers – High Spenders
- ZIP+4 - Likely to Be a Small Business – In Market
- ZIP+4 - Luxury Retailers – High Spenders
- ZIP+4 - Fast Fashion Apparel Buyers – High Spenders
- ZIP+4 - Big Ticket Shoppers (Online) – Frequent Buyers
- ZIP+4 - Affluent Shoppers
- ZIP+4 - Brick and Mortar Shoppers
- ZIP+4 - Luxury Travelers & Tourists
- Mastercard Custom Audiences – Built-to-order audiences designed to a client’s specifications to align directly with their advertising strategy and based on layering the following attributes:
- Transactions (e.g., amount, frequency, offline vs. online)
- Date and Time (e.g., date range, time of day, weekend vs. weekday)
- Geography (e.g., country, state/province, DMA, city, region)
- Industry / Merchants (e.g., Merchant Category Codes (MCCs), custom aggregate set of industry merchants)
Use Cases
Audiences customers can leverage aggregated and anonymized Audiences for:
- Customer Segmentation: Identify customer segments with a high statistical probability of making a purchase within their industries
- Tailored Marketing & Promotions: Customize creative messaging based on an understanding customer segment spend across categories and channels
- Ad Research/Ad Sales: Build look-alike models to extend campaign reach
- Analytics & Insights: Enhance their existing models by applying cross-category spend behavior
- Location-Based Automation: Personalize using geographic-based spend insights
Metadata
| Description | Value |
|---|---|
| Update Frequency | Monthly for standard audiences, custom segment refreshes are available upon request |
| KPI(s) | Audiences makes metrics such as Demi-decile, Propensity and Binary available for each ZIP+4. Note: Some scores may be omitted at Mastercard’s discretion if data cannot be sufficiently aggregated or anonymized |
| Demi-decile | Ranking of 1-20 based on spend, where #1 stands for top 1-5% of spenders, #2 stands for top 6-10% of spenders,…,#20 stands for bottom 95-100% of spenders |
| Propensity Models (forecast data) | A probability to spend 0-100 generated by predictive model score |
| Binary | A value of 0 or 1, where 1 indicates the top 20% of spenders or propensity scores and 0 the bottom 80% |
| Geographic coverage | Total USA, Zip, Zip+4 level reporting in the US |
| Time period coverage | Actuals: Standard Audiences are based on the past year, however three years of data is readily available for building custom audiences. Propensity model forecasts apply to the next 1 - 3 months |
| Data Source(s) | Mastercard Audiences are built by creating segments based on spending insights from anonymized and aggregated transaction data |
| Original Publisher of data | Mastercard |
| Data Set(s) Format(s) | CSV, Excel |
| Raw or scraped data | Aggregated and anonymized transaction data |
| Key Fields | Geography (Zip5), Micro-Geography (Zip+4), Audience Segment Score(s) aggregated to the Zip+4 level (e.g. Zip 10001-0001 scores high for High Spenders in Video/TV Streaming Services, Zip 10001-0002 scores low for Frequent Spenders of Online Food & Meal Delivery Services) |
| Key Words | Audiences, Segments, Shoppers, Consumer Insights, Online Shoppers, In-store Shoppers, Propensity Models, Consumer Behaviors, Seasonal Shoppers, Travel and Tourism Insights, Personas, Transaction, Spend, Credit Card, Marketing, Advertising, Digital Advertising, Customer Segmentation, Customer Targeting |
| Number of companies/brands covered | Mastercard Audiences covers aggregated and anonymized spend data in 19 Industries and 88 Sub-Industries |
| Data Channels | Aggregated and anonymized POS Transaction data, including both online and brick-and-mortar sales |
Tables
The three tables below illustrate various data file layouts. The first shows Demi-Decile Audiences (Actuals), the second shows Propensity Audiences (Forecast), and the third shows Audiences presented in a Binary Threshold format (applying to Demi-Decile or Propensity outputs for simplification).
Demi-Decile Audiences (Actuals)
| Geography (Zip5) | Micro-Geography (Zip+4) | Standard Audience 1 | … | Standard Audience n |
|---|---|---|---|---|
| 10001 | 0001 | 19 | … | 2 |
| 10001 | 0002 | 7 | … | 14 |
| 10001 | 0003 | 5 | … | 3 |
Propensity (Forecast)
| Geography (Zip5) | Micro-Geography (Zip+4) | Audience 1 Modeled Probability | … | Audience n Modeled Probability |
|---|---|---|---|---|
| 10001 | 0001 | 0.95 | … | 0.65 |
| 10001 | 0002 | 0.46 | … | 0.43 |
| 10001 | 0003 | 0.84 | … | 0.25 |
Binary Threshold Flag (Applied to Demi-Decile or Propensity outputs for simplification)
| Geography (Zip5) | Micro-Geography (Zip+4) | Standard Audience 1 | … | Standard Audience n |
|---|---|---|---|---|
| 10001 | 0001 | 1 | … | 1 |
| 10001 | 0002 | 0 | … | 0 |
| 10001 | 0003 | 1 | … | 0 |
Dataset Specification
The datasets are updated monthly the week after calendar month close.
Pricing Information
Mastercard Audiences segments are available to purchase. Pease inquire with Mastercard at aws.sales@mastercard.com for pricing information.
Need Help?
For questions related to Amazon Data Exchange billing or invoicing, please reach out to your AWS Technical Account Manager or contact Amazon Data Exchange customer support directly.
For product-related questions, please reach out to Media_Delivery@mastercard.com.
About Your Company
Mastercard (NYSE: MA) Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.
www.mastercard.com
Provided By
Fulfillment Method
AWS Data Exchange
Data sets (1)
You will receive access to the following data sets
Revision access rules
All historical revisions | All future revisions
Name | Type | Data dictionary | AWS Region |
|---|---|---|---|
Mastercard Audiences | Not included | US East (N. Virginia) |
Usage information
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