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Data Dictionary

Core Tables​

Consumer Spending Industry TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_INDUSTRY_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for spend across industries with breakdowns by demographics (age and income level), purchase channels (online vs. offline) and consumer or merchant location. Geographic estimates range from national estimates for the entire US and go as granular as ZIP codes in the major US Core Based Statistical Areas ("CBSAs"). Each row represents a distinct timeseries, date, and value.

Consumer Spending Merchant TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_MERCHANT_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for spend across merchants with breakdowns by demographics (age and income level), purchase channels (online vs. offline) and consumer or merchant location. Geographic estimates range from national estimates for the entire US and go as granular as ZIP codes in the major US Core Based Statistical Areas ("CBSAs"). Each row represents a distinct timeseries, date, and value.

Consumer Spending POI TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_POI_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for spend across points of interest ("POIs") with breakdowns by demographics (age and income level) and purchase channels (online vs. offline). Each row represents a distinct timeseries, date, and value.

Consumer Spending Merchant Product TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_MERCHANT_PRODUCT_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for spend across merchants and their respective products, e.g. Dashpass Memberships through Doordash, with breakdowns by demographics (age and income level), purchase channels (online vs. offline) and consumer or merchant location. Geographic estimates range from national estimates for the entire US and go as granular as ZIP codes in the major US Core Based Statistical Areas ("CBSAs"). Each row represents a distinct timeseries, date, and value.

Consumer Spending Merchant Platform TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_MERCHANT_PLATFORM_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for spend across merchants through different platforms, e.g. McDonald's sales through DoorDash, with breakdowns by demographics (age and income level), purchase channels (online vs. offline) and consumer or merchant location. Geographic estimates range from national estimates for the entire US and go as granular as ZIP codes in the major US Core Based Statistical Areas ("CBSAs"). Each row represents a distinct timeseries, date, and value.

Consumer Spending Merchant Retention TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_MERCHANT_RETENTION_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for retention rates (user retention, sales retention, etc.) for merchants. Each row represents a measure of a merchant's retention at a given period.

Consumer Spending Merchant Product Retention TimeseriesView Source Documentation

CYBERSYN.CONSUMER_SPENDING_MERCHANT_PRODUCT_RETENTION_TIMESERIES: The Consumer Spending Foundation includes projected consumer spending activity nationally in the United States. The card panel is made up of data from nearly 100M credit and debit cards from a number of banks and financial institutions. The data is aggregated and normalized to create a representative panel of activity in the US consumer economy. Provides historical values for retention rates (user retention, sales retention, etc.) for products. Each row represents a measure of a product's retention at a given period.


Reference Tables​

CYBERSYN.GEOGRAPHY_INDEX: Cybersyn's unified geographic entity index, joinable to all tables, providing unique geographic identifiers with associated names, levels, and ISO codes for various US geographies.

CYBERSYN.POI_INDEX: The POI Index table provides a unique POI_ID along with details about it's associated merchant, address, latitude/longitude, and estimated open/close dates.

Geographic Entity RelationshipsView Source Documentation

CYBERSYN.GEOGRAPHY_RELATIONSHIPS: Relationships between geographic entities of differing levels, including overlaps and contains relationships, using Cybersyn's GEO_IDs.

Merchant Company RelationshipsView Source Documentation

CYBERSYN.MERCHANT_COMPANY_RELATIONSHIPS: Details relationships between merchants from the consumer spending timeseries tables and companies from the company_index table.

CYBERSYN.CALENDAR_INDEX: Index of common calendars; each calendar has an ID (calendar_id) for users to select which calendar type they want to use. Individual periods within the calendar include period start and end dates.