100+ datasets found
  1. Target: consumer spending share in the U.S. in 2020, by race and ethnicity

    • statista.com
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    Statista, Target: consumer spending share in the U.S. in 2020, by race and ethnicity [Dataset]. https://www.statista.com/statistics/1201722/share-consumer-spending-target-united-states-by-race/
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2020
    Area covered
    United States
    Description

    In 2020, Hispanic consumers accounted for nearly ** percent of spending at Target, while African Americans represented nearly **** percent. Meanwhile, white consumers accounted for nearly ** percent of the company's consumer spending share.

  2. Target Corporation

    • kaggle.com
    zip
    Updated Mar 25, 2024
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    Ujjwal Mishra (2024). Target Corporation [Dataset]. https://www.kaggle.com/datasets/ujjwalinsights/target-case-study-using-sql/data
    Explore at:
    zip(50219115 bytes)Available download formats
    Dataset updated
    Mar 25, 2024
    Authors
    Ujjwal Mishra
    License

    https://cdla.io/permissive-1-0/https://cdla.io/permissive-1-0/

    Description

    Context:

    Target is a globally renowned brand and a prominent retailer in the United States. Target makes itself a preferred shopping destination by offering outstanding value, inspiration, innovation and an exceptional guest experience that no other retailer can deliver.

    This particular business case focuses on the operations of Target in Brazil and provides insightful information about 100,000 orders placed between 2016 and 2018. The dataset offers a comprehensive view of various dimensions including the order status, price, payment and freight performance, customer location, product attributes, and customer reviews.

    By analyzing this extensive dataset, it becomes possible to gain valuable insights into Target's operations in Brazil. The information can shed light on various aspects of the business, such as order processing, pricing strategies, payment and shipping efficiency, customer demographics, product characteristics, and customer satisfaction levels.

    Dataset: https://drive.google.com/drive/folders/1TGEc66YKbD443nslRi1bWgVd238gJCnb

    The data is available in 8 csv files:

    • customers.csv
    • sellers.csv
    • order_items.csv
    • geolocation.csv
    • payments.csv
    • reviews.csv
    • orders.csv
    • products.csv

    The column description for these csv files is given below. Certainly! Here are separate tables for each CSV file:

    customers.csv:

    FeatureDescription
    customer_idID of the consumer who made the purchase
    customer_unique_idUnique ID of the consumer
    customer_zip_code_prefixZip Code of consumer’s location
    customer_cityName of the City from where order is made
    customer_stateState Code from where order is made (Eg. São Paulo - SP)

    sellers.csv:

    FeatureDescription
    seller_idUnique ID of the seller registered
    seller_zip_code_prefixZip Code of the seller’s location
    seller_cityName of the City of the seller
    seller_stateState Code (Eg. São Paulo - SP)

    order_items.csv:

    FeatureDescription
    order_idA Unique ID of order made by the consumers
    order_item_idA Unique ID given to each item ordered in the order
    product_idA Unique ID given to each product available on the site
    seller_idUnique ID of the seller registered in Target
    shipping_limit_dateThe date before which the ordered product must be shipped
    priceActual price of the products ordered
    freight_valuePrice rate at which a product is delivered from one point to another

    geolocations.csv:

    FeatureDescription
    geolocation_zip_code_prefixFirst 5 digits of Zip Code
    geolocation_latLatitude
    geolocation_lngLongitude
    geolocation_cityCity
    geolocation_stateState

    payments.csv:

    FeatureDescription
    order_idA Unique ID of order made by the consumers
    payment_sequentialSequences of the payments made in case of EMI
    payment_typeMode of payment used (Eg. Credit Card)
    payment_installmentsNumber of installments in case of EMI purchase
    payment_valueTotal amount paid for the purchase order

    **orders.csv:...

  3. Retail Data | Retail Sector in North America | Comprehensive Contact...

    • datarade.ai
    + more versions
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    Success.ai, Retail Data | Retail Sector in North America | Comprehensive Contact Profiles | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/retail-data-retail-sector-in-north-america-comprehensive-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset provided by
    Area covered
    United States
    Description

    Success.ai’s Retail Data for the Retail Sector in North America offers a comprehensive dataset designed to connect businesses with key players across the diverse retail industry. Covering everything from department stores and supermarkets to specialty shops and e-commerce platforms, this dataset provides verified contact details, business locations, and leadership profiles for retail companies in the United States, Canada, and Mexico.

    With access to over 170 million verified professional profiles and 30 million company profiles, Success.ai ensures your outreach, marketing, and business development efforts are powered by accurate, continuously updated, and AI-validated data.

    Backed by our Best Price Guarantee, this solution empowers businesses to thrive in North America’s competitive retail landscape.

    Why Choose Success.ai’s Retail Data for North America?

    1. Verified Contact Data for Precision Outreach

      • Access verified phone numbers, work emails, and LinkedIn profiles of retail executives, store managers, and decision-makers.
      • AI-driven validation ensures 99% accuracy, enabling confident communication and efficient campaign execution.
    2. Comprehensive Coverage Across Retail Segments

      • Includes profiles of retail businesses across major markets, from large department stores and grocery chains to boutique retailers and online platforms.
      • Gain insights into the operational dynamics of retail hubs in cities such as New York, Los Angeles, Toronto, and Mexico City.
    3. Continuously Updated Datasets

      • Real-time updates reflect leadership changes, new store openings, market expansions, and shifts in consumer preferences.
      • Stay aligned with evolving industry trends and emerging opportunities in the North American retail sector.
    4. Ethical and Compliant

      • Adheres to GDPR, CCPA, and other privacy regulations, ensuring responsible and lawful use of data in your campaigns.

    Data Highlights:

    • 170M+ Verified Professional Profiles: Engage with executives, marketing directors, and operations managers across the North American retail sector.
    • 30M Company Profiles: Access firmographic data, including revenue ranges, store counts, and geographic footprints.
    • Store Location Data: Pinpoint retail outlets, regional offices, and distribution centers to refine supply chain and marketing strategies.
    • Leadership Contact Details: Connect with CEOs, CMOs, and procurement officers influencing retail operations and vendor selections.

    Key Features of the Dataset:

    1. Retail Decision-Maker Profiles

      • Identify and engage with store owners, category managers, and marketing directors shaping customer experiences and product strategies.
      • Target professionals responsible for inventory planning, vendor contracts, and store performance.
    2. Advanced Filters for Precision Targeting

      • Filter companies by industry segment (luxury, grocery, e-commerce), geographic location, company size, or revenue range.
      • Tailor outreach to align with regional market trends, customer demographics, and operational priorities.
    3. Market Trends and Operational Insights

      • Analyze trends such as online shopping growth, sustainability practices, and supply chain optimization.
      • Leverage insights to refine product offerings, identify partnership opportunities, and design effective campaigns.
    4. AI-Driven Enrichment

      • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and enhance engagement outcomes.

    Strategic Use Cases:

    1. Sales and Lead Generation

      • Present products, services, or technology solutions to retail procurement teams, marketing departments, and operations managers.
      • Build relationships with retailers seeking innovative tools, efficient supply chain solutions, or unique product offerings.
    2. Market Research and Consumer Insights

      • Analyze retail trends, customer behaviors, and seasonal demands to inform marketing strategies and product launches.
      • Benchmark against competitors to identify gaps, emerging niches, and growth opportunities.
    3. E-Commerce and Digital Strategy Development

      • Target e-commerce managers and digital transformation teams driving online retail initiatives and omnichannel integration.
      • Offer solutions to enhance online shopping experiences, logistics, and customer loyalty programs.
    4. Recruitment and Workforce Solutions

      • Engage HR professionals and hiring managers in recruiting talent for store operations, customer service, or marketing roles.
      • Provide workforce optimization tools, training platforms, or staffing services tailored to retail environments.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality retail data at competitive prices, ensuring strong ROI for your marketing and outreach efforts in North America.
    2. Seamless Integration
      ...

  4. Consumer characteristics used by marketers in targeting worldwide 2021

    • statista.com
    Updated Feb 15, 2022
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    Statista (2022). Consumer characteristics used by marketers in targeting worldwide 2021 [Dataset]. https://www.statista.com/statistics/1345085/consumer-characteristics-define-target-segments/
    Explore at:
    Dataset updated
    Feb 15, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 2021
    Area covered
    Worldwide
    Description

    During a survey carried out in November 2021 among marketers from ** countries worldwide, ** percent stated their organizations used past purchases to define target consumer segments. Consumer demographics, such as age, gender, income, or location, were used most often, named by ** percent of respondents.

  5. w

    Global Kroger Customer Market Research Report: By Customer Demographics (Age...

    • wiseguyreports.com
    Updated Oct 12, 2025
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    (2025). Global Kroger Customer Market Research Report: By Customer Demographics (Age Group, Income Level, Family Size, Gender), By Shopping Behavior (Frequency of Shopping, Preferred Shopping Channel, Product Purchase Patterns), By Product Preferences (Organic Products, Discounted Items, Brand Loyalty, Private Label Purchases), By Technology Adoption (Online Shopping, Mobile App Usage, Social Media Engagement) and By Regional (North America, Europe, South America, Asia Pacific, Middle East and Africa) - Forecast to 2035 [Dataset]. https://www.wiseguyreports.com/reports/kroger-customer-market
    Explore at:
    Dataset updated
    Oct 12, 2025
    License

    https://www.wiseguyreports.com/pages/privacy-policyhttps://www.wiseguyreports.com/pages/privacy-policy

    Time period covered
    Oct 25, 2025
    Area covered
    Global
    Description
    BASE YEAR2024
    HISTORICAL DATA2019 - 2023
    REGIONS COVEREDNorth America, Europe, APAC, South America, MEA
    REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
    MARKET SIZE 202424.6(USD Billion)
    MARKET SIZE 202525.4(USD Billion)
    MARKET SIZE 203535.0(USD Billion)
    SEGMENTS COVEREDCustomer Demographics, Shopping Behavior, Product Preferences, Technology Adoption, Regional
    COUNTRIES COVEREDUS, Canada, Germany, UK, France, Russia, Italy, Spain, Rest of Europe, China, India, Japan, South Korea, Malaysia, Thailand, Indonesia, Rest of APAC, Brazil, Mexico, Argentina, Rest of South America, GCC, South Africa, Rest of MEA
    KEY MARKET DYNAMICSconsumer preferences shift, competitive pricing strategies, technological integration, sustainability focus, e-commerce growth
    MARKET FORECAST UNITSUSD Billion
    KEY COMPANIES PROFILEDMetro AG, Costco Wholesale, Walmart, Target, Whole Foods Market, Trader Joe's, Aldi, Tesco, Amazon, Lidl, Ahold Delhaize, Safeway
    MARKET FORECAST PERIOD2025 - 2035
    KEY MARKET OPPORTUNITIESE-commerce expansion for grocery delivery, Health and wellness product lines, Sustainable packaging initiatives, Personalized shopping experiences, Loyalty program enhancements
    COMPOUND ANNUAL GROWTH RATE (CAGR) 3.2% (2025 - 2035)
  6. d

    Vision Consumer Demographic Data | B2C Audience Purchase Behavior | US...

    • datarade.ai
    .csv, .xls
    + more versions
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    Consumer Edge, Vision Consumer Demographic Data | B2C Audience Purchase Behavior | US Transaction Data | 100M+ Cards, 12K+ Merchants, Industry, Channel [Dataset]. https://datarade.ai/data-products/consumer-edge-vision-demographic-spending-data-b2c-audience-consumer-edge
    Explore at:
    .csv, .xlsAvailable download formats
    Dataset authored and provided by
    Consumer Edge
    Area covered
    United States of America
    Description

    Demographics Analysis with Consumer Edge Credit & Debit Card Transaction Data

    Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. CE Transact Signal is an aggregated transaction feed that includes consumer transaction data on 100M+ credit and debit cards, including 14M+ active monthly users. Capturing online, offline, and 3rd-party consumer spending on public and private companies, data covers 12K+ merchants and deep demographic and geographic breakouts. Track detailed consumer behavior patterns, including retention, purchase frequency, and cross shop in addition to total spend, transactions, and dollars per transaction.

    Consumer Edge’s consumer transaction datasets offer insights into industries across consumer and discretionary spend such as: • Apparel, Accessories, & Footwear • Automotive • Beauty • Commercial – Hardlines • Convenience / Drug / Diet • Department Stores • Discount / Club • Education • Electronics / Software • Financial Services • Full-Service Restaurants • Grocery • Ground Transportation • Health Products & Services • Home & Garden • Insurance • Leisure & Recreation • Limited-Service Restaurants • Luxury • Miscellaneous Services • Online Retail – Broadlines • Other Specialty Retail • Pet Products & Services • Sporting Goods, Hobby, Toy & Game • Telecom & Media • Travel

    This data sample illustrates how Consumer Edge data can be used to compare demographics breakdown (age and income excluded in this free sample view) for one company vs. a competitor for a set period of time (Ex: How do demographics like wealth, ethnicity, children in the household, homeowner status, and political affiliation differ for Walmart vs. Target shopper?).

    Inquire about a CE subscription to perform more complex, near real-time demographics analysis functions on public tickers and private brands like: • Analyze a demographic, like age or income, within a state for a company in 2023 • Compare all of a company’s demographics to all of that company’s competitors through most recent history

    Consumer Edge offers a variety of datasets covering the US and Europe (UK, Austria, France, Germany, Italy, Spain), with subscription options serving a wide range of business needs.

    Use Case: Demographics Analysis

    Problem A global retailer wants to understand company performance by age group.

    Solution Consumer Edge transaction data can be used to analyze shopper transactions by age group to understand: • Overall sales growth by age group over time • Percentage sales growth by age group over time • Sales by age group vs. competitors

    Impact Marketing and Consumer Insights were able to: • Develop weekly reporting KPI's on key demographic drivers of growth for company-wide reporting • Reduce investment in underperforming age groups, both online and offline • Determine retention by age group to refine campaign strategy • Understand how different age groups are performing compared to key competitors

    Corporate researchers and consumer insights teams use CE Vision for:

    Corporate Strategy Use Cases • Ecommerce vs. brick & mortar trends • Real estate opportunities • Economic spending shifts

    Marketing & Consumer Insights • Total addressable market view • Competitive threats & opportunities • Cross-shopping trends for new partnerships • Demo and geo growth drivers • Customer loyalty & retention

    Investor Relations • Shareholder perspective on brand vs. competition • Real-time market intelligence • M&A opportunities

    Most popular use cases for private equity and venture capital firms include: • Deal Sourcing • Live Diligences • Portfolio Monitoring

    Public and private investors can leverage insights from CE’s synthetic data to assess investment opportunities, while consumer insights, marketing, and retailers can gain visibility into transaction data’s potential for competitive analysis, understanding shopper behavior, and capturing market intelligence.

    Most popular use cases among public and private investors include: • Track Key KPIs to Company-Reported Figures • Understanding TAM for Focus Industries • Competitive Analysis • Evaluating Public, Private, and Soon-to-be-Public Companies • Ability to Explore Geographic & Regional Differences • Cross-Shop & Loyalty • Drill Down to SKU Level & Full Purchase Details • Customer lifetime value • Earnings predictions • Uncovering macroeconomic trends • Analyzing market share • Performance benchmarking • Understanding share of wallet • Seeing subscription trends

    Fields Include: • Day • Merchant • Subindustry • Industry • Spend • Transactions • Spend per Transaction (derivable) • Cardholder State • Cardholder CBSA • Cardholder CSA • Age • Income • Wealth • Ethnicity • Political Affiliation • Children in Household • Adults in Household • Homeowner vs. Renter • Business Owner • Retention by First-Shopped Period ...

  7. Target brand profile in the United States 2022

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Target brand profile in the United States 2022 [Dataset]. https://www.statista.com/forecasts/1252087/target-consumer-electronics-online-shops-brand-profile-in-the-united-states
    Explore at:
    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 15, 2022 - Jul 12, 2022
    Area covered
    United States
    Description

    How high is the brand awareness of Target in the United States?When it comes to consumer electronics online shop users, brand awareness of Target is at *** in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Target in the United States?In total, *** of U.S. consumer electronics online shop users say they like Target. However, in actuality, among the *** of U.S. respondents who know Target, *** of people like the brand.What is the usage share of Target in the United States?All in all, *** of consumer electronics online shop users in the United States use Target. That means, of the *** who know the brand, *** use them.How loyal are the customers of Target?Around *** of consumer electronics online shop users in the United States say they are likely to use Target again. Set in relation to the *** usage share of the brand, this means that *** of their customers show loyalty to the brand.What's the buzz around Target in the United States?In July 2022, about *** of U.S. consumer electronics online shop users had heard about Target in the media, on social media, or in advertising over the past three months. Of the *** who know the brand, that's ***, meaning at the time of the survey there's some buzz around Target in the United States.If you want to compare brands, do deep-dives by survey items of your choice, filter by total online population or users of a certain brand, or drill down on your very own hand-tailored target groups, our Consumer Insights Brand KPI survey has you covered.

  8. Sales data based on demographics

    • kaggle.com
    zip
    Updated Jan 12, 2023
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    The Devastator (2023). Sales data based on demographics [Dataset]. https://www.kaggle.com/datasets/thedevastator/demographical-shopping-purchases-data
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    zip(1541029 bytes)Available download formats
    Dataset updated
    Jan 12, 2023
    Authors
    The Devastator
    Description

    Demographical Shopping Purchases Data

    Analyzing customer purchasing patterns and preferences

    By Joseph Nowicki [source]

    About this dataset

    This dataset contains demographic information about customers who have made purchases in a store, including their name, IP address, region, age, items purchased, and total amount spent. Furthermore, this data can provide insights into customer shopping behaviour for the store in question - from their geographical information to the types of products they purchase. With detailed demographic data like this at hand it is possible to make strategic decisions regarding target customers as well as developing specific marketing campaigns or promotions tailored to meet their needs and interests. By gaining deeper understanding of customer habits through this dataset we unlock more possibilities for businesses seeking higher engagement levels with shoppers

    More Datasets

    For more datasets, click here.

    Featured Notebooks

    • 🚨 Your notebook can be here! 🚨!

    How to use the dataset

    This dataset includes information such as customer's names, IP address, age, items purchased and amount spent. This data can be used to uncover patterns in spending behavior of shoppers from different areas or regions across demographics like age group or gender.

    Research Ideas

    • Analyze customer shopping trends based on age and region to maximize targetted advertising.
    • Analyze the correlation between customer spending habits based on store versus online behavior.
    • Use IP addresses to track geographical trends in items purchased from a particular online store to identify new markets for targeted expansion

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. Data Source

    License

    See the dataset description for more information.

    Columns

    File: Demographic_Data_Orig.csv | Column name | Description | |:---------------|:------------------------------------------------------------------------------------------------| | full.name | The full name of the customer. (String) | | ip.address | The IP address of the customer. (String) | | region | The region of residence of the customer. (String) | | in.store | A boolean value indicating whether the customer made the purchase in-store or online. (Boolean) | | age | The age of the customer. (Integer) | | items | The number of items purchased by the customer. (Integer) | | amount | The total amount spent by the customer. (Float) |

    Acknowledgements

    If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Joseph Nowicki.

  9. d

    GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business...

    • datarade.ai
    .json, .csv
    Updated Aug 13, 2024
    + more versions
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    GapMaps (2024). GIS Data | USA & Canada | Over 40k Demographics Variables To Inform Business Decisions | Consumer Spending Data| Demographic Data [Dataset]. https://datarade.ai/data-products/gapmaps-premium-demographic-data-by-ags-usa-canada-gis-gapmaps
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Aug 13, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Canada, United States
    Description

    GapMaps GIS data for USA and Canada sourced from Applied Geographic Solutions (AGS) includes an extensive range of the highest quality demographic and lifestyle segmentation products. All databases are derived from superior source data and the most sophisticated, refined, and proven methodologies.

    GIS Data attributes include:

    1. Latest Estimates and Projections The estimates and projections database includes a wide range of core demographic data variables for the current year and 5- year projections, covering five broad topic areas: population, households, income, labor force, and dwellings.

    2. Crime Risk Crime Risk is the result of an extensive analysis of a rolling seven years of FBI crime statistics. Based on detailed modeling of the relationships between crime and demographics, Crime Risk provides an accurate view of the relative risk of specific crime types (personal, property and total) at the block and block group level.

    3. Panorama Segmentation AGS has created a segmentation system for the United States called Panorama. Panorama has been coded with the MRI Survey data to bring you Consumer Behavior profiles associated with this segmentation system.

    4. Business Counts Business Counts is a geographic summary database of business establishments, employment, occupation and retail sales.

    5. Non-Resident Population The AGS non-resident population estimates utilize a wide range of data sources to model the factors which drive tourists to particular locations, and to match that demand with the supply of available accommodations.

    6. Consumer Expenditures AGS provides current year and 5-year projected expenditures for over 390 individual categories that collectively cover almost 95% of household spending.

    7. Retail Potential This tabulation utilizes the Census of Retail Trade tables which cross-tabulate store type by merchandise line.

    8. Environmental Risk The environmental suite of data consists of several separate database components including: -Weather Risks -Seismological Risks -Wildfire Risk -Climate -Air Quality -Elevation and terrain

    Primary Use Cases for GapMaps GIS Data:

    1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
    2. Customer Profiling: get a detailed understanding of the demographic & segmentation profile of your customers, where they work and their spending potential
    3. Analyse your trade areas at a granular census block level using all the key metrics
    4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
    5. Target Marketing: Develop effective marketing strategies to acquire more customers.
    6. Integrate AGS demographic data with your existing GIS or BI platform to generate powerful visualizations.

    7. Finance / Insurance (eg. Hedge Funds, Investment Advisors, Investment Research, REITs, Private Equity, VC)

    8. Network Planning

    9. Customer (Risk) Profiling for insurance/loan approvals

    10. Target Marketing

    11. Competitive Analysis

    12. Market Optimization

    13. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

    14. Tenant Recruitment

    15. Target Marketing

    16. Market Potential / Gap Analysis

    17. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

    18. Customer Profiling

    19. Target Marketing

    20. Market Share Analysis

  10. s

    Target Spend by Customer Profile Dataset

    • starzdata.com
    csv, xls
    Updated Sep 17, 2025
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    Starzdata (2025). Target Spend by Customer Profile Dataset [Dataset]. https://www.starzdata.com/segments/willingness-to-pay-estimator
    Explore at:
    xls, csvAvailable download formats
    Dataset updated
    Sep 17, 2025
    Dataset authored and provided by
    Starzdata
    License

    https://starzdata.com/platformhttps://starzdata.com/platform

    Area covered
    Global
    Variables measured
    city, gender, region, country, csp_code, urbanicity, age_bracket, wtp_range_eur, glp1_usage_pct, overweight_pct, and 28 more
    Measurement technique
    AI reasoning, web intelligence
    Description

    Willingness to Pay isn’t just about pricing — it’s about knowing who would buy, at what spend, and why. CMOs and consultants need fast answers to size a market or brief a launch.Panels take weeks and often miss behavior. With only your target segment and product brief, we estimate who’s concerned, who’s likely to buy, and how much they’d spend monthly — scored, sourced, and ready to activate.

  11. Share of discount stores shoppers in the U.S. by generation 2025

    • statista.com
    Updated Apr 15, 2025
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    Statista (2025). Share of discount stores shoppers in the U.S. by generation 2025 [Dataset]. https://www.statista.com/statistics/1450627/discount-stores-shoppers-by-generation-us/
    Explore at:
    Dataset updated
    Apr 15, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Apr 1, 2024 - Mar 21, 2025
    Area covered
    United States
    Description

    In 2025, consumers in the United States were surveyed about their regular food and everyday products shopping destinations. Among those who shopped at discount stores, ** percent of Millennials reported doing so, whereas the corresponding share for baby boomers was ** percent. Find this and more survey data in our Consumer Insights tool. Filter by countless demographics, drill down to your own, hand-tailored target audience, and compare results across countries worldwide.

  12. Consumer Marketing Data API | Tailored Consumer Insights | Target with...

    • datarade.ai
    Updated Oct 27, 2021
    + more versions
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    Success.ai (2021). Consumer Marketing Data API | Tailored Consumer Insights | Target with Precision | Best Price Guarantee [Dataset]. https://datarade.ai/data-products/consumer-marketing-data-api-tailored-consumer-insights-ta-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Senegal, Hong Kong, Vanuatu, Estonia, United Arab Emirates, Sweden, Philippines, Burundi, Madagascar, Turkey
    Description

    Success.ai’s Consumer Marketing Data API empowers your marketing, analytics, and product teams with on-demand access to a vast and continuously updated dataset of consumer insights. Covering detailed demographics, behavioral patterns, and purchasing histories, this API enables you to go beyond generic outreach and craft tailored campaigns that truly resonate with your target audiences.

    With AI-validated accuracy and support for precise filtering, the Consumer Marketing Data API ensures you’re always equipped with the most relevant data. Backed by our Best Price Guarantee, this solution is essential for refining your strategies, improving conversion rates, and driving sustainable growth in today’s competitive consumer landscape.

    Why Choose Success.ai’s Consumer Marketing Data API?

    1. Tailored Consumer Insights for Precision Targeting

      • Access verified demographic, behavioral, and purchasing data to understand what consumers truly value.
      • AI-driven validation ensures 99% accuracy, minimizing wasted spend and improving engagement outcomes.
    2. Comprehensive Global Reach

      • Includes consumer profiles from diverse regions and markets, enabling you to scale campaigns and discover emerging opportunities.
      • Adapt swiftly to new markets, product launches, and shifting consumer preferences with real-time data at your fingertips.
    3. Continuously Updated and Real-Time Data

      • Receive ongoing updates that reflect evolving consumer behaviors, interests, and market trends.
      • Respond quickly to seasonal changes, competitor moves, and industry disruptions, ensuring your campaigns remain timely and relevant.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, guaranteeing responsible and lawful data usage.

    Data Highlights:

    • Detailed Demographics: Age, gender, location, and income levels to refine targeting and messaging.
    • Behavioral Insights: Interests, browsing patterns, and content consumption habits to anticipate consumer needs.
    • Purchasing History: Understand consumer spending, brand loyalty, and product preferences to tailor promotions effectively.
    • Real-Time Updates: Keep pace with evolving consumer tastes, ensuring your strategies remain forward-focused and competitive.

    Key Features of the Consumer Marketing Data API:

    1. Granular Targeting and Segmentation

      • Query the API to segment consumers by demographics, interests, past purchases, or engagement patterns.
      • Focus campaigns on the most receptive audiences, enhancing conversion rates and ROI.
    2. Flexible and Seamless Integration

      • Easily integrate the API into CRM systems, marketing automation tools, or analytics platforms.
      • Streamline workflows and eliminate manual data imports, freeing resources for strategic initiatives.
    3. Continuous Data Enrichment

      • Refresh consumer profiles with the latest data, ensuring every decision is backed by current insights.
      • Reduce data decay and maintain top-notch data hygiene to maximize long-term marketing effectiveness.
    4. AI-Driven Validation

      • Rely on advanced AI validation techniques to guarantee high-quality data accuracy and reliability.
      • Increase confidence in your campaigns and decrease budget wasted on irrelevant targets.

    Strategic Use Cases:

    1. Highly Personalized Marketing Campaigns

      • Deliver tailored offers, recommendations, and content that align with individual consumer preferences.
      • Boost engagement and loyalty by making every touchpoint relevant and meaningful.
    2. Market Expansion and Product Launches

      • Identify segments most receptive to new products or services, ensuring successful market entry.
      • Stay ahead of consumer demands, evolving your product line and marketing mix to meet changing preferences.
    3. Competitive Analysis and Trend Forecasting

      • Leverage consumer insights to anticipate emerging trends and outpace competitors in capturing new markets.
      • Adjust marketing strategies proactively to capitalize on seasonal, cultural, or economic shifts.
    4. Customer Retention and Loyalty Programs

      • Use historical purchase and engagement data to identify at-risk customers and implement retention strategies.
      • Cultivate brand advocates by delivering personalized offers and exclusive perks to loyal consumers.

    Why Choose Success.ai?

    1. Best Price Guarantee

      • Access premium-quality consumer marketing data at unmatched prices, ensuring maximum ROI for your outreach efforts.
    2. Seamless Integration

      • Easily incorporate the API into existing workflows, eliminating data silos and manual data management.
    3. Data Accuracy with AI Validation

      • Depend on 99% accuracy to guide data-driven decisions, refine targeting, and elevate your marketing initiatives.
    4. Customizable and Scalable Solutions

      • Tailor datasets to focus on specific demog...
  13. Target: sales share in the U.S. 2024, by product segment

    • statista.com
    Updated Nov 25, 2025
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    Statista (2025). Target: sales share in the U.S. 2024, by product segment [Dataset]. https://www.statista.com/statistics/255960/sales-share-of-target-in-north-america-by-product-segment/
    Explore at:
    Dataset updated
    Nov 25, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    In the financial year 2024, 22.36 percent of Target Corporation's merchandise sales corresponded to the food and beverage segment. Meanwhile, household essentials represented 17.47 percent of the total merchandise sales. Merchandise sales represent the vast majority of Target's revenues. The company also has other streams of revenue, including credit card profit-sharing income from their arrangement with the TD Bank Group. Beauty at Target In a 2024 survey among Generation Z in the United States, 10 percent of teenage girls named Target as a shopping destination they visited to buy beauty products. This may not sound high, but it earned Target third place of all shops in the country, ahead of other major retailers Walmart and Amazon. It was, however, a considerable distance behind the two most popular destinations, specialist beauty brands Sephora and Ulta. These findings are reflected in a different study of the same retailers, with Target having the third lowest average age of female beauty consumers, at 44 years old. Gen Z clothing purchases There is also a large Generation Z market available to Target in the clothing category. In 2023, Gen Z consumers voted big box stores, such as Target and Walmart, as the second most popular shopping destination for apparel, with 16 percent of responses. This was only one percentage point behind online stores.

  14. s

    Seair Exim Solutions

    • seair.co.in
    + more versions
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    Seair Exim, Seair Exim Solutions [Dataset]. https://www.seair.co.in
    Explore at:
    .bin, .xml, .csv, .xlsAvailable download formats
    Dataset provided by
    Seair Info Solutions PVT LTD
    Authors
    Seair Exim
    Area covered
    United States
    Description

    Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

  15. c

    Consumer Behavior and Shopping Habits Dataset:

    • cubig.ai
    zip
    Updated May 28, 2025
    + more versions
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    CUBIG (2025). Consumer Behavior and Shopping Habits Dataset: [Dataset]. https://cubig.ai/store/products/352/consumer-behavior-and-shopping-habits-dataset
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Synthetic data generation using AI techniques for model training, Privacy-preserving data transformation via differential privacy
    Description

    1) Data Introduction • The Consumer Behavior and Shopping Habits Dataset is a tabular collection of customer demographics, purchase history, product preferences, shopping frequency, and online and offline purchasing behavior.

    2) Data Utilization (1) Consumer Behavior and Shopping Habits Dataset has characteristics that: • Each row contains detailed consumer and transaction information such as customer ID, age, gender, purchased goods and categories, purchase amount, region, product attributes (size, color, season), review rating, subscription status, delivery method, discount/promotion usage, payment method, purchase frequency, etc. • Data is organized to cover a variety of variables and purchasing patterns to help segment customers, establish marketing strategies, analyze product preferences, and more. (2) Consumer Behavior and Shopping Habits Dataset can be used to: • Customer Segmentation and Target Marketing: You can analyze demographics and purchasing patterns to define different customer groups and use them to develop customized marketing strategies. • Product and service improvement: Based on purchase history, review ratings, discount/promotional responses, etc., it can be applied to product and service improvements such as identifying popular products, managing inventory, and analyzing promotion effects.

  16. c

    Shopper's Behavior and Revenue Dataset

    • cubig.ai
    zip
    Updated May 28, 2025
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    CUBIG (2025). Shopper's Behavior and Revenue Dataset [Dataset]. https://cubig.ai/store/products/353/shoppers-behavior-and-revenue-dataset
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    CUBIG
    License

    https://cubig.ai/store/terms-of-servicehttps://cubig.ai/store/terms-of-service

    Measurement technique
    Privacy-preserving data transformation via differential privacy, Synthetic data generation using AI techniques for model training
    Description

    1) Data Introduction • The Shopper's Behavior and Revenue Dataset contains more than 12,300 pieces of information about online shopping customers' purchasing behavior and revenue, including customer purchasing patterns, product reviews, discounts, and payment methods.

    2) Data Utilization (1) Shopper's Behavior and Revenue Dataset has characteristics that: • This dataset includes a variety of variables related to your shopping behavior, including demographics, purchase history, products and categories, purchase frequency, review ratings, discounts, and promotion usage. • Provides information that can analyze e-commerce customer behavior from multiple angles, such as whether to purchase (Revenue), visitor type, traffic type, browser, operating system, region, and weekend visitation. (2) Shopper's Behavior and Revenue Dataset can be used to: • Customer Segmentation and Target Marketing: You can analyze customer behavior patterns and characteristics to establish customized marketing strategies, and use them to request reviews and induce repurchases. • Forecast and Sales Analysis: By analyzing purchase conversion rate, review impact, discount effect, etc., you can contribute to increased sales and improved customer satisfaction.

  17. Loan Data Set

    • kaggle.com
    zip
    Updated Oct 2, 2020
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    Data_drinker (2020). Loan Data Set [Dataset]. https://www.kaggle.com/surya08084/loan-data-set
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    zip(1565723 bytes)Available download formats
    Dataset updated
    Oct 2, 2020
    Authors
    Data_drinker
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset

    This dataset was created by Data_drinker

    Released under CC0: Public Domain

    Contents

  18. d

    US Consumer Demographics | Homeowners & Renters | Email & Mobile Phone |...

    • datarade.ai
    .json, .csv, .xls
    Updated Oct 18, 2024
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    CompCurve (2024). US Consumer Demographics | Homeowners & Renters | Email & Mobile Phone | Bulk & Custom | 255M People [Dataset]. https://datarade.ai/data-products/compcurve-us-consumer-demographics-homeowners-renters-compcurve
    Explore at:
    .json, .csv, .xlsAvailable download formats
    Dataset updated
    Oct 18, 2024
    Dataset authored and provided by
    CompCurve
    Area covered
    United States
    Description

    Knowing who your consumers are is essential for businesses, marketers, and researchers. This detailed demographic file offers an in-depth look at American consumers, packed with insights about personal details, household information, financial status, and lifestyle choices. Let's take a closer look at the data:

    Personal Identifiers and Basic Demographics At the heart of this dataset are the key details that make up a consumer profile:

    Unique IDs (PID, HHID) for individuals and households Full names (First, Middle, Last) and suffixes Gender and age Date of birth Complete location details (address, city, state, ZIP) These identifiers are critical for accurate marketing and form the base for deeper analysis.

    Geospatial Intelligence This file goes beyond just listing addresses by including rich geospatial data like:

    Latitude and longitude Census tract and block details Codes for Metropolitan Statistical Areas (MSA) and Core-Based Statistical Areas (CBSA) County size codes Geocoding accuracy This allows for precise geographic segmentation and localized marketing.

    Housing and Property Data The dataset covers a lot of ground when it comes to housing, providing valuable insights for real estate professionals, lenders, and home service providers:

    Homeownership status Dwelling type (single-family, multi-family, etc.) Property values (market, assessed, and appraised) Year built and square footage Room count, amenities like fireplaces or pools, and building quality This data is crucial for targeting homeowners with products and services like refinancing or home improvement offers.

    Wealth and Financial Data For a deeper dive into consumer wealth, the file includes:

    Estimated household income Wealth scores Credit card usage Mortgage info (loan amounts, rates, terms) Home equity estimates and investment property ownership These indicators are invaluable for financial services, luxury brands, and fundraising organizations looking to reach affluent individuals.

    Lifestyle and Interests One of the most useful features of the dataset is its extensive lifestyle segmentation:

    Hobbies and interests (e.g., gardening, travel, sports) Book preferences, magazine subscriptions Outdoor activities (camping, fishing, hunting) Pet ownership, tech usage, political views, and religious affiliations This data is perfect for crafting personalized marketing campaigns and developing products that align with specific consumer preferences.

    Consumer Behavior and Purchase Habits The file also sheds light on how consumers behave and shop:

    Online and catalog shopping preferences Gift-giving tendencies, presence of children, vehicle ownership Media consumption (TV, radio, internet) Retailers and e-commerce businesses will find this behavioral data especially useful for tailoring their outreach.

    Demographic Clusters and Segmentation Pre-built segments like:

    Household, neighborhood, family, and digital clusters Generational and lifestage groups make it easier to quickly target specific demographics, streamlining the process for market analysis and campaign planning.

    Ethnicity and Language Preferences In today's multicultural market, knowing your audience's cultural background is key. The file includes:

    Ethnicity codes and language preferences Flags for Hispanic/Spanish-speaking households This helps ensure culturally relevant and sensitive communication.

    Education and Occupation Data The dataset also tracks education and career info:

    Education level and occupation codes Home-based business indicators This data is essential for B2B marketers, recruitment agencies, and education-focused campaigns.

    Digital and Social Media Habits With everyone online, digital behavior insights are a must:

    Internet, TV, radio, and magazine usage Social media platform engagement (Facebook, Instagram, LinkedIn) Streaming subscriptions (Netflix, Hulu) This data helps marketers, app developers, and social media managers connect with their audience in the digital space.

    Political and Charitable Tendencies For political campaigns or non-profits, this dataset offers:

    Political affiliations and outlook Charitable donation history Volunteer activities These insights are perfect for cause-related marketing and targeted political outreach.

    Neighborhood Characteristics By incorporating census data, the file provides a bigger picture of the consumer's environment:

    Population density, racial composition, and age distribution Housing occupancy and ownership rates This offers important context for understanding the demographic landscape.

    Predictive Consumer Indexes The dataset includes forward-looking indicators in categories like:

    Fashion, automotive, and beauty products Health, home decor, pet products, sports, and travel These predictive insights help businesses anticipate consumer trends and needs.

    Contact Information Finally, the file includes key communication details:

    Multiple phone numbers (landline, mobile) and email addresses Do Not Call (DNC) flags...

  19. Stop & Shop brand profile in the United States 2022

    • statista.com
    Updated Jul 9, 2025
    + more versions
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    Statista (2025). Stop & Shop brand profile in the United States 2022 [Dataset]. https://www.statista.com/forecasts/1335635/stop-and-shop-grocery-stores-brand-profile-in-the-united-states
    Explore at:
    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 17, 2022 - Aug 30, 2022
    Area covered
    United States
    Description

    How high is the brand awareness of Stop & Shop in the United States?When it comes to grocery store customers, brand awareness of Stop & Shop is at *** in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Stop & Shop in the United States?In total, ** of U.S. grocery store customers say they like Stop & Shop. However, in actuality, among the *** of U.S. respondents who know Stop & Shop, *** of people like the brand.What is the usage share of Stop & Shop in the United States?All in all, ** of grocery store customers in the United States use Stop & Shop. That means, of the *** who know the brand, *** use them.How loyal are the customers of Stop & Shop?Around ** of grocery store customers in the United States say they are likely to use Stop & Shop again. Set in relation to the ** usage share of the brand, this means that *** of their customers show loyalty to the brand.What's the buzz around Stop & Shop in the United States?In August 2022, about ** of U.S. grocery store customers had heard about Stop & Shop in the media, on social media, or in advertising over the past three months. Of the *** who know the brand, that's ***, meaning at the time of the survey there's little buzz around Stop & Shop in the United States.If you want to compare brands, do deep-dives by survey items of your choice, filter by total online population or users of a certain brand, or drill down on your very own hand-tailored target groups, our Consumer Insights Brand KPI survey has you covered.

  20. Consumer Behavior Data | Consumer Goods & Electronics Industry Leaders in...

    • datarade.ai
    Updated Jan 1, 2018
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    Success.ai (2018). Consumer Behavior Data | Consumer Goods & Electronics Industry Leaders in Asia, US, and Europe | Verified Global Profiles from 700M+ Dataset [Dataset]. https://datarade.ai/data-products/consumer-behavior-data-consumer-goods-electronics-industr-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Jan 1, 2018
    Dataset provided by
    Area covered
    United States
    Description

    Success.ai’s Consumer Behavior Data for Consumer Goods & Electronics Industry Leaders in Asia, the US, and Europe offers a robust dataset designed to empower businesses with actionable insights into global consumer trends and professional profiles. Covering executives, product managers, marketers, and other professionals in the consumer goods and electronics sectors, this dataset includes verified contact information, professional histories, and geographic business data.

    With access to over 700 million verified global profiles and firmographic data from leading companies, Success.ai ensures your outreach, market analysis, and strategic planning efforts are powered by accurate, continuously updated, and GDPR-compliant data. Backed by our Best Price Guarantee, this solution is ideal for businesses aiming to navigate and lead in these fast-paced industries.

    Why Choose Success.ai’s Consumer Behavior Data?

    1. Verified Contact Data for Precision Engagement

      • Access verified email addresses, phone numbers, and LinkedIn profiles of professionals in the consumer goods and electronics industries.
      • AI-driven validation ensures 99% accuracy, optimizing communication efficiency and minimizing data gaps.
    2. Comprehensive Global Coverage

      • Includes profiles from key markets in Asia, the US, and Europe, covering regions such as China, India, Germany, and the United States.
      • Gain insights into region-specific consumer trends, product preferences, and purchasing behaviors.
    3. Continuously Updated Datasets

      • Real-time updates capture career progressions, company expansions, market shifts, and consumer trend data.
      • Stay aligned with evolving market dynamics and seize emerging opportunities effectively.
    4. Ethical and Compliant

      • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible use and legal compliance for all data-driven campaigns.

    Data Highlights:

    • 700M+ Verified Global Profiles: Connect with industry leaders, marketers, and decision-makers in consumer goods and electronics industries worldwide.
    • Consumer Trend Insights: Gain detailed insights into product preferences, purchasing patterns, and demographic influences.
    • Business Locations: Access geographic data to identify regional markets, operational hubs, and emerging consumer bases.
    • Professional Histories: Understand career trajectories, skills, and expertise of professionals driving innovation and strategy.

    Key Features of the Dataset:

    1. Decision-Maker Profiles in Consumer Goods and Electronics

      • Identify and engage with professionals responsible for product development, marketing strategy, and supply chain optimization.
      • Target individuals making decisions on consumer engagement, distribution, and market entry strategies.
    2. Advanced Filters for Precision Campaigns

      • Filter professionals by industry focus (consumer electronics, FMCG, luxury goods), geographic location, or job function.
      • Tailor campaigns to align with specific industry trends, market demands, and regional preferences.
    3. Consumer Trend Data and Insights

      • Access data on regional product preferences, spending behaviors, and purchasing influences across key global markets.
      • Leverage these insights to shape product development, marketing campaigns, and customer engagement strategies.
    4. AI-Driven Enrichment

      • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

    Strategic Use Cases:

    1. Marketing and Demand Generation

      • Design campaigns tailored to consumer preferences, regional trends, and target demographics in the consumer goods and electronics industries.
      • Leverage verified contact data for multi-channel outreach, including email, social media, and direct marketing.
    2. Market Research and Competitive Analysis

      • Analyze global consumer trends, spending patterns, and product preferences to refine your product portfolio and market positioning.
      • Benchmark against competitors to identify gaps, emerging needs, and growth opportunities in target regions.
    3. Sales and Partnership Development

      • Build relationships with key decision-makers at companies specializing in consumer goods or electronics manufacturing and distribution.
      • Present innovative solutions, supply chain partnerships, or co-marketing opportunities to grow your market share.
    4. Product Development and Innovation

      • Utilize consumer trend insights to inform product design, pricing strategies, and feature prioritization.
      • Develop offerings that align with regional preferences and purchasing behaviors to maximize market impact.

    Why Choose Success.ai?

    1. Best Price Guarantee
      • Access premium-quality consumer behavior data at competitive prices, ensuring maximum ROI for your outreach, research, and ma...
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Statista, Target: consumer spending share in the U.S. in 2020, by race and ethnicity [Dataset]. https://www.statista.com/statistics/1201722/share-consumer-spending-target-united-states-by-race/
Organization logo

Target: consumer spending share in the U.S. in 2020, by race and ethnicity

Explore at:
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2020
Area covered
United States
Description

In 2020, Hispanic consumers accounted for nearly ** percent of spending at Target, while African Americans represented nearly **** percent. Meanwhile, white consumers accounted for nearly ** percent of the company's consumer spending share.

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