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    SpendingPulse

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    Sold by: Mastercard 
    Deployed on AWS
    Mastercard SpendingPulse™ is a macroeconomic indicator of retail sales measuring in-store and online retail sales across all forms of payment. Mastercard SpendingPulse solutions answer key business questions by using anonymized aggregate sales activity in the Mastercard payments network, coupled with survey-based estimates for other payment types, such as cash and check.

    Overview

    SpendingPulse™ Retail Sales and Forecasts

    Data Product Overview

    Mastercard SpendingPulse™ is a macroeconomic indicator of retail sales measuring in-store and online retail sales across all forms of payment. Mastercard SpendingPulse solutions answer key business questions by using anonymized aggregate sales activity in the Mastercard payments network, coupled with survey-based estimates for other payment types, such as cash and check. Key questions include:

    • How does my organization’s performance compare to that of the industry?

    • What are key upcoming sales days for consumers, and how can my organization best capitalize on them?

    • How are consumers spending across channels (online vs. in-store), and how will that change?

    • Based on historical performance, growth, density and volume of spend, where should we open a new location?

    SpendingPulse insights enables organizations to look at sales estimates at the different geographic location granularities: county, DMA and state level. SpendingPulse industry sectors available include: Total Retail excluding Auto, Apparel, Department Stores, Electronics, Fuel & Convenience, Grocery, Home Furniture & Furnishings, Home Improvement, Jewelry, Lodging, Airlines, and Restaurants.

    Use Cases

    • Forecasting: utilize SpendingPulse retail sales estimates and forecasts to triangulate and optimize your own business forecasts nationally, regionally, locally.

    • Performance Benchmarking: compare your own business’ revenue /sales performance versus different SpendingPulse consumer purchase channels (online and in-store). Identify over- and under-performing markets or sales regions relative to overall market demand. Activate sales, promotions, and marketing / advertising incentives to capitalize on growth or recoup potential losses relative to peers.

    • Executive Briefings: contextualize the ever-changing retail landscape, effect of policy changes, and other local / national events with timely insights and granular data for your leadership team, board of directors.

    • Corporate Strategy & Real Estate: monitor overall retail performance for different locations to inform corporate relocations and optimize your omnichannel real estate and distribution footprint.

    • Marketing & Promotions: better align marketing placements with high-demand times of year and purchase channels.

    Metadata

    DescriptionValue
    KPI(s)Actual Sales $ estimates (Total, Online, In-Store) and forecasted spend $
    Geographic coverageTotal USA, 50 States + DC, 210 DMAs, 3000+ counties; Forecasts National and State Only
    Time period coverageActuals: January 1st, 2018, through most recent calendar month; Forecasts: Next 12-months
    Data Source(s)Mastercard Transaction Data, Various survey sources for non-card payments
    Original Publisher of dataMastercard
    Data Set(s) Format(s)CSV data files
    Raw or scraped dataRaw
    Key FieldsDate (daily data), Geography (Country, State, DMA, County), Channel (Total, In-store, Online), Sales $, YoY% $, Yo2Y% $
    Key WordsRetail Sales, POS Sales, Online Sales, In-store Sales, brick-and-mortar, actual sales, forecasts, forecast sales
    Number of companies/brands coveredTotal Retail excluding Auto, Lodging, Jewelry, Apparel
    Data ChannelsPOS Transaction data, Survey data, Modeled estimates and forecasts

    Tables

    The below table illustrates the data file layout, which provides actuals and forecasts by purchase channel (in-store, online, total), by day (2018 – current month + 12-month forecasts), and by several geographies (county, DMA, State, Country).

    GeographyDateSalesChannelisForecast
    Manhattan County01/01/2018In-Store$211,230,000N
    Manhattan County01/01/2018Online$14,156,000N
    Manhattan County01/01/2018Total$225,386,000N
    ...............
    Los Angeles County01/01/2018In-Store$387,062,000N
    Los Angeles County01/01/2018Online$52,537,000N

    Dataset Specification

    The datasets are updated monthly the week after calendar month close. More frequent data updates (weekly) are available directly from Mastercard – please inquire if this is business critical.

    All geographic and purchase channel data splits are internally consistent and sum to total. e.g., sum of all states = Total USA sales $ figure for same time periods.

    In-store transactions are allocated based on the physical address of the brick-and-mortar store, Online transactions are allocated based on cardholder zip codes and scaled for population counts.

    If certain geographies are not reported in SpendingPulse data, they did not pass internal Mastercard data controls for data privacy and obfuscation. Typically meaning a very small number of merchants operate in the sector/geography combination in question.

    Pricing Information

    Full SpendingPulse sector data available for purchase individually. Please inquire for bundled pricing or Mastercard consulting support (available).

    Regulatory and Compliance Information

    SpendingPulse data and insights are for companies’ internal (non-public) business purposes and should not be re-distributed in any way without prior consent of Mastercard. Further, SpendingPulse insights are not investment advice nor should it be relied upon as investment advice.

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    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 >

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    Refunds not applicable

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    Usage information

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    Delivery details

    AWS Data Exchange (ADX)

    AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.

    Additional details

    Data sets (1)

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    You will receive access to the following data sets.

    Data set name
    Type
    Historical revisions
    Future revisions
    Sensitive information
    Data dictionaries
    Data samples
    Spending Pulse All Industries Sample
    Last 1 revisions
    All future revisions
    Not included
    Not included

    Resources

    Vendor resources