Sold by: Prosper Insights & Analytics
Deployed on AWS
Prosper has conducted the US Monthly survey since 2002 with approximately 7,500 U.S. Adults 18+ respondents each month. This dataset is a subset that begins in January 2010 and focuses on questions dealing with Food for consumption at Home as well as Away from Home. 12+ years of history. An excellent training dataset for AI & Machine Learning and Forecasting applications. Includes Covid-19 questions. Anonymous data. 100% Privacy Compliant. No PII Used. HIPAA and CCPA Compliant.
Overview
Prosper has conducted the US Monthly survey since 2002 with approximately 7,500 U.S. Adults 18+ respondents each month. This dataset is a subset that begins in January 2010 and focuses on questions dealing with the Food category for consumption at Home as well as Away from Home. Tracks how consumers are feeling about the economy, shopping behavior, future purchase intentions, healthy eating habits, organic, GMO & more. Includes Covid-19 & post Pandenic Inflation questions. Anonymous data. 100% Privacy Compliant. No PII Used. HIPAA and CCPA Compliant.
The data is an excellent training dataset for AI & Machine Learning initiatives and Forecasting applications.
The Prosper dataset is unique in its longevity as well as the nature of the questions (future spending intentions and consumer emotional mindset). Since the data has many consistent questions going back 12+ years, it has captured the consumers’ responses and changes to shocks to the economy including the Covid Economic Crisis.
The data covers a variety for consumers choices related to the Food category including:
- Economic attitudes such as sentiment, employment outlook, energy price impacts on spending, deferred spending and more.
- New questions beginning in March 2020 on response and reactions to the Covid crisis with a focus on the Food category.
- Forward looking spending plans for Groceries and Dining Out.
- Unique, unaided write-in answers for the Store Shopped Most Often for Grocery 1st and 2nd Choice
- Quarterly questions on Dining Out: Fast Food, Full Service, Breakfast, Coffee
- Quarterly Dining Out includes unique, unaided write-in answers for the brand frequented Most Often for: Fast Food, Full Service, Breakfast, Coffee, Pizza, Convenience Store and Gas Station.
- Psychographic/Neuromarketing data covering impulsivity, Happiness (10 separate questions) and OCEAN (Big 5) questions and scores.
All questions are not available for the full time period. See Data Dictionary for specifics.
Data is organized by over 100 consumer demographic and geographic segments including:
- US 18+
- Men 18+
- Women 18+
- Ages 18-34
- Ages 35-54
- Ages 55+
- Incomes <$50K
- Incomes $50K+
- Incomes $75K+
- Incomes $100K+
- Business Owners
- Parents
- GenZ
- Millennials
- GenX
- Boomers
- Shoppers of leading retailers
- Census Regions & Divisions
- States
All data in this file comes from Prosper Insights & Analytics Monthly Consumer market survey collected and curated since 2002. The survey is the largest ongoing survey conducted and includes the responses of approximately 7,500 consumers each month. The survey is a representative and scientifically collected instrument. Margin of error +- 1.5%.
Positive Predictive Correlations have been established between government data and Prosper’s Monthly Consumer intent data.
The data is used across multiple industry sectors including Finance/Insurance, such as Wall Street Investment banking firms and Hedge funds, Media, Database marketers, Technology, CPG’s, Credit card companies, Digital marketers, Entertainment and others.
Since 2003, this data has been used by the NRF for all of their highly accurate holiday and seasonal forecasts for investors, media and members.
Over 14 prestigious Academic institutions world- wide apply for and have received grants of the data for classroom work and publication by Faculty. The data has been the foundation for over 30 peer reviewed articles in professional journals ranging from Consumer Behavior, Marketing and Neuroscience.
Bespoke Datasets and Consumer Segments are available upon request. Additional fees apply.
Data Uses and Applications:
- Machine Learning - Training Data Set
- Time Series Forecasts
- Econometric Analysis
- Market Share Analysis
- Competitive Analysis
- Marketing Planning
- Financial Planning
- Capabilities Presentations
- Strategic Consulting
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Dimension | Description | Cost/month |
|---|---|---|
Product Access | Dimension that grants access to the product for subscribers. | $5,000.00 |
Dimensions summary
This listing uses a single pricing dimension called Product Access (Units). You buy access to the time series dataset under a contract term. Pricing is not tiered or based on instance sizes. Instead, you subscribe to one product-access option that grants use of the data. The unit count reflects the access you purchase rather than usage-based scaling or add-on features. This gives you one clear commitment to gain access to the consumer food data covering home and away spending.
Top-of-mind questions for buyers
Each unit grants subscriber access to the time series dataset covering US consumer food spending at home and away. Access is granted under a contract term. The unit count reflects the access you buy, not measured usage of the data or the number of queries you run.
No. Product Access is not usage-based. Your cost is fixed by the access you purchase under the contract. Pulling more records or running more queries does not add charges. There are no per-query, per-record, or overage fees tied to how much data you consume.
You get time series data on US consumer food spending, split into home and away categories. The data comes from monthly consumer behavior signals. It supports forecasting demand and anticipating consumer action before it appears in sales or statistics.
www.prospermodelfactory.com
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Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
Time Series Data: US Consumer Food – Home and Away | All historical revisions | All future revisions | Not included | Not included |
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