100+ datasets found
  1. People who shopped at Target in the United States, by age 2024

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). People who shopped at Target in the United States, by age 2024 [Dataset]. https://www.statista.com/forecasts/231373/people-who-shopped-at-target-within-the-last-30-days-usa
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Oct 2023 - Sep 2024
    Area covered
    United States
    Description

    This statistic illustrates the share of people who shopped at Target in the United States. As of September 2024, ** percent of 18 - 29 year old consumers do so in the U.S. This is according to exclusive results from the Consumer Insights Global survey which shows that ** percent of 30 - 49 year old customers also fall into this category.Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than ********* interviews.

  2. 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
      ...

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

    • statista.com
    Updated Jun 25, 2025
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    Statista (2025). 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/
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    Dataset updated
    Jun 25, 2025
    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.

  4. d

    US Consumer Demographic Data - 269M+ Consumer Records - Programmatic Ads and...

    • datarade.ai
    Updated Jun 27, 2025
    + more versions
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    Giant Partners (2025). US Consumer Demographic Data - 269M+ Consumer Records - Programmatic Ads and Email Marketing Automation [Dataset]. https://datarade.ai/data-products/us-consumer-demographic-data-269m-consumer-records-progr-giant-partners
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Giant Partners
    Area covered
    United States of America
    Description

    Premium B2C Consumer Database - 269+ Million US Records

    Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

    Core Database Statistics

    Consumer Records: Over 269 million

    Email Addresses: Over 160 million (verified and deliverable)

    Phone Numbers: Over 76 million (mobile and landline)

    Mailing Addresses: Over 116,000,000 (NCOA processed)

    Geographic Coverage: Complete US (all 50 states)

    Compliance Status: CCPA compliant with consent management

    Targeting Categories Available

    Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

    Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

    Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

    Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

    Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

    Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

    Multi-Channel Campaign Applications

    Deploy across all major marketing channels:

    Email marketing and automation

    Social media advertising

    Search and display advertising (Google, YouTube)

    Direct mail and print campaigns

    Telemarketing and SMS campaigns

    Programmatic advertising platforms

    Data Quality & Sources

    Our consumer data aggregates from multiple verified sources:

    Public records and government databases

    Opt-in subscription services and registrations

    Purchase transaction data from retail partners

    Survey participation and research studies

    Online behavioral data (privacy compliant)

    Technical Delivery Options

    File Formats: CSV, Excel, JSON, XML formats available

    Delivery Methods: Secure FTP, API integration, direct download

    Processing: Real-time NCOA, email validation, phone verification

    Custom Selections: 1,000+ selectable demographic and behavioral attributes

    Minimum Orders: Flexible based on targeting complexity

    Unique Value Propositions

    Dual Spouse Targeting: Reach both household decision-makers for maximum impact

    Cross-Platform Integration: Seamless deployment to major ad platforms

    Real-Time Updates: Monthly data refreshes ensure maximum accuracy

    Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

    Compliance Management: Built-in opt-out and suppression list management

    Ideal Customer Profiles

    E-commerce retailers seeking customer acquisition

    Financial services companies targeting specific demographics

    Healthcare organizations with compliant marketing needs

    Automotive dealers and service providers

    Home improvement and real estate professionals

    Insurance companies and agents

    Subscription services and SaaS providers

    Performance Optimization Features

    Lookalike Modeling: Create audiences similar to your best customers

    Predictive Scoring: Identify high-value prospects using AI algorithms

    Campaign Attribution: Track performance across multiple touchpoints

    A/B Testing Support: Split audiences for campaign optimization

    Suppression Management: Automatic opt-out and DNC compliance

    Pricing & Volume Options

    Flexible pricing structures accommodate businesses of all sizes:

    Pay-per-record for small campaigns

    Volume discounts for large deployments

    Subscription models for ongoing campaigns

    Custom enterprise pricing for high-volume users

    Data Compliance & Privacy

    VIA.tools maintains industry-leading compliance standards:

    CCPA (California Consumer Privacy Act) compliant

    CAN-SPAM Act adherence for email marketing

    TCPA compliance for phone and SMS campaigns

    Regular privacy audits and data governance reviews

    Transparent opt-out and data deletion processes

    Getting Started

    Our data specialists work with you to:

    1. Define your target audience criteria

    2. Recommend optimal data selections

    3. Provide sample data for testing

    4. Configure delivery methods and formats

    5. Implement ongoing campaign optimization

    Why We Lead the Industry

    With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

    Contact our team to discuss your specific ta...

  5. m

    Factori Audience | 1.2B unique mobile users in APAC, EU, North America and...

    • app.mobito.io
    Updated Dec 24, 2022
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    (2022). Factori Audience | 1.2B unique mobile users in APAC, EU, North America and MENA [Dataset]. https://app.mobito.io/data-product/audience-data
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    Dataset updated
    Dec 24, 2022
    Area covered
    EUROPE, North America, SOUTH_AMERICA, AFRICA, OCEANIA, ASIA
    Description

    We collect, validate, model, and segment raw data signals from over 900+ sources globally to deliver thousands of mobile audience segments. We then combine that data with other public and private data sources to derive interests, intent, and behavioral attributes. Our proprietary algorithms then clean, enrich, unify and aggregate these data sets for use in our products. We have categorized our audience data into consumable categories such as interest, demographics, behavior, geography, etc. Audience Data Categories:Below mentioned data categories include consumer behavioral data and consumer profiles (available for the US and Australia) divided into various data categories. Brand Shoppers:Methodology: This category has been created based on the high intent of users in terms of their visits to Brand outlets in the real world. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. Place Category Visitors:Methodology: This category has been created based on the high intent of users visiting specific places of interest in the real world. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. Demographics:This category has been created based on deterministic data that we receive from apps based on the declared gender and age data. Marital Status, Education, Party affiliation, and State residency are available in the US. Geo-Behavioural:This category has been created based on the high intent of users in terms of the frequency of their visits to specific granular places of interest in the real world. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. Interests:This segment is created based on users' interest in a specific subject while browsing the internet when the visited website category is clearly focused on a specific subject such as cars, cooking, traveling, etc. We use a deterministic model to assign a proper profile and time that information is valid. The recency of data can range from 14 to 30 days, depending on the topic. Intent:Factori receives data from many partners to deliver high-quality pieces of information about users’ shopping intent. We collect data from sources connected to the eCommerce sector and we also receive data connected to online transactions from affiliate networks to deliver the most accurate segments with purchase intentions, such as laptops, mobile phones, or cars. The recency of data can range from 7 to 14 days depending on the product category. Events:This category was created based on the high interest of users in terms of content related to specific global events - sports, culture, and gaming. Among the event segments, we also distinguish categories related to the interest in certain lifestyle choices and behaviors. To create segments containing users with a high-affinity index, we use a precise determination of the number of occurrences at a given time. App Usage:Mobile category is a branch of the taxonomy that is dedicated only to the data that is based on mobile advertising IDs. It is based on the categorization of the mobile apps that the user has installed on the device. Auto Ownership:Consumer Profiles - Available for US and AustraliaThis audience has been created based on users declaring that they own a certain brand of automobile and other automotive attributes via a survey or registration. These audiences are currently available in the USA. Motorcycle Ownership:Consumer Profiles - Available for US and AustraliaThis audience has been created based on users declaring that they own a certain brand of motorcycle and other motorcycle-based attributes via a survey or registration. These audiences are currently available for the USA. Household:Consumer Profiles - Available for the US and AustraliaThis audience has been created based on users' declaring their marital status, parental status, and the overall number of children via a survey or registration. These audiences are currently available in the USA. Financial:Consumer Profiles - Available for the US and Australia this audience has been created based on their behavior in different financial services like property ownership, mortgage, investing behavior, and wealth and declaring their estimated net worth via a survey or registration. Purchase/ Spending Behavior:Consumer Profiles - Available for the US and AustraliaThis audience has been created based on their behavior in different spending behaviors in different business verticals available in the USA. Clusters:Consumer Profiles - Available for the US and AustraliaClusters are groups of consumers who exhibit similar demographic, lifestyle, and media consumption characteristics, empowering marketers to understand the unique attributes that comprise their most profitable consumer segments. Armed with this rich data, data scientists can drive analytics and modeling to power their brand’s unique marketing initiatives. B2B Audiences;Consumer Profiles - Available for US and AustraliaThis audience has been created based on users declaring their employee credentials, designations, and companies they work in, further specifying business verticals, revenue breakdowns, and headquarters locations. Customizable Audiences Data Segment:Brands can choose the appropriate pre-made audience segments or ask our data experts about creating a custom segment that is precisely tailored to your brief in order to reach their target customers and boost the campaign's effectiveness. Location Query Granularity:Minimum area: HEX 8Maximum area: QuadKey 17/City

  6. 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
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    .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

  7. Consumer characteristics used by marketers in targeting worldwide 2021

    • statista.com
    Updated Jul 9, 2025
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    Statista (2025). Consumer characteristics used by marketers in targeting worldwide 2021 [Dataset]. https://www.statista.com/statistics/1345085/consumer-characteristics-define-target-segments/
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    Dataset updated
    Jul 9, 2025
    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.

  8. Mall Customer Segmentation Dataset

    • kaggle.com
    Updated Sep 17, 2023
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    iNeuBytes (2023). Mall Customer Segmentation Dataset [Dataset]. https://www.kaggle.com/datasets/ineubytes/mall-customer-segmentation-dataset/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 17, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    iNeuBytes
    Description

    This data set is created only for the learning purpose of the customer segmentation concepts , also known as market basket analysis .

    Problem Statement You own the mall and want to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly.

  9. Target brand profile in the United States 2023

    • statista.com
    Updated Jul 18, 2025
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    Statista (2025). Target brand profile in the United States 2023 [Dataset]. https://www.statista.com/forecasts/1335702/target-grocery-stores-brand-profile-in-the-united-states
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    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Sep 2023
    Area covered
    United States
    Description

    How high is the brand awareness of Target in the United States?When it comes to grocery store customers, 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. grocery store customers say they like Target.What is the usage share of Target in the United States?All in all, **% of grocery store customers in the United States use Target.How loyal are the customers of Target?Around **% of grocery store customers 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 September 2023, about **% of U.S. grocery store customers had heard about Target in the media, on social media, or in advertising over the past three months. Have a look at our analyses of Target's brand KPIs by generation, as well as the most important life aspects of Target customers compared to non-customers of the brand.

  10. Cheese Target Market

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Aug 1, 2025
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    IndexBox Inc. (2025). Cheese Target Market [Dataset]. https://www.indexbox.io/search/cheese-target-market/
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    xls, xlsx, docx, pdf, docAvailable download formats
    Dataset updated
    Aug 1, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Aug 7, 2025
    Area covered
    World
    Variables measured
    Price CIF, Price FOB, Export Value, Import Price, Import Value, Export Prices, Export Volume, Import Volume
    Description

    Explore the demographics, psychographics, and geography of the cheese market. Discover why cheese is a popular dairy food with its range of flavors, nutritional benefits, and versatility. Learn about the growing demand for Western cuisine and how it is impacting cheese consumption worldwide.

  11. Retail Store Data | Retail & E-commerce Sector in Asia | Verified Business...

    • datarade.ai
    Updated Feb 12, 2018
    + more versions
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    Success.ai (2018). Retail Store Data | Retail & E-commerce Sector in Asia | Verified Business Profiles & eCommerce Professionals | Best Price Guaranteed [Dataset]. https://datarade.ai/data-products/retail-store-data-retail-e-commerce-sector-in-asia-veri-success-ai
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset updated
    Feb 12, 2018
    Dataset provided by
    Area covered
    Bangladesh, Georgia, Lebanon, Turkmenistan, Cyprus, Malaysia, Kuwait, Singapore, Jordan, Hong Kong
    Description

    Success.ai delivers unparalleled access to Retail Store Data for Asia’s retail and e-commerce sectors, encompassing subcategories such as ecommerce data, ecommerce merchant data, ecommerce market data, and company data. Whether you’re targeting emerging markets or established players, our solutions provide the tools to connect with decision-makers, analyze market trends, and drive strategic growth. With continuously updated datasets and AI-validated accuracy, Success.ai ensures your data is always relevant and reliable.

    Key Features of Success.ai's Retail Store Data for Retail & E-commerce in Asia:

    Extensive Business Profiles: Access detailed profiles for 70M+ companies across Asia’s retail and e-commerce sectors. Profiles include firmographic data, revenue insights, employee counts, and operational scope.

    Ecommerce Data: Gain insights into online marketplaces, customer demographics, and digital transaction patterns to refine your strategies.

    Ecommerce Merchant Data: Understand vendor performance, supply chain metrics, and operational details to optimize partnerships.

    Ecommerce Market Data: Analyze purchasing trends, regional preferences, and market demands to identify growth opportunities.

    Contact Data for Decision-Makers: Reach key stakeholders, such as CEOs, marketing executives, and procurement managers. Verified contact details include work emails, phone numbers, and business addresses.

    Real-Time Accuracy: AI-powered validation ensures a 99% accuracy rate, keeping your outreach efforts efficient and impactful.

    Compliance and Ethics: All data is ethically sourced and fully compliant with GDPR and other regional data protection regulations.

    Why Choose Success.ai for Retail Store Data?

    Best Price Guarantee: We deliver industry-leading value with the most competitive pricing for comprehensive retail store data.

    Customizable Solutions: Tailor your data to meet specific needs, such as targeting particular regions, industries, or company sizes.

    Scalable Access: Our data solutions are built to grow with your business, supporting small startups to large-scale enterprises.

    Seamless Integration: Effortlessly incorporate our data into your existing CRM, marketing, or analytics platforms.

    Comprehensive Use Cases for Retail Store Data:

    1. Market Entry and Expansion:

    Identify potential partners, distributors, and clients to expand your footprint in Asia’s dynamic retail and e-commerce markets. Use detailed profiles to assess market opportunities and risks.

    1. Personalized Marketing Campaigns:

    Leverage ecommerce data and consumer insights to craft highly targeted campaigns. Connect directly with decision-makers for precise and effective communication.

    1. Competitive Benchmarking:

    Analyze competitors’ operations, market positioning, and consumer strategies to refine your business plans and gain a competitive edge.

    1. Supplier and Vendor Selection:

    Evaluate potential suppliers or vendors using ecommerce merchant data, including financial health, operational details, and contact data.

    1. Customer Engagement and Retention:

    Enhance customer loyalty programs and retention strategies by leveraging ecommerce market data and purchasing trends.

    APIs to Amplify Your Results:

    Enrichment API: Keep your CRM and analytics platforms up-to-date with real-time data enrichment, ensuring accurate and actionable company profiles.

    Lead Generation API: Maximize your outreach with verified contact data for retail and e-commerce decision-makers. Ideal for driving targeted marketing and sales efforts.

    Tailored Solutions for Industry Professionals:

    Retailers: Expand your supply chain, identify new markets, and connect with key partners in the e-commerce ecosystem.

    E-commerce Platforms: Optimize your vendor and partner selection with verified profiles and operational insights.

    Marketing Agencies: Deliver highly personalized campaigns by leveraging detailed consumer data and decision-maker contacts.

    Consultants: Provide data-driven recommendations to clients with access to comprehensive company data and market trends.

    What Sets Success.ai Apart?

    70M+ Business Profiles: Access an extensive and detailed database of companies across Asia’s retail and e-commerce sectors.

    Global Compliance: All data is sourced ethically and adheres to international data privacy standards, including GDPR.

    Real-Time Updates: Ensure your data remains accurate and relevant with our continuously updated datasets.

    Dedicated Support: Our team of experts is available to help you maximize the value of our data solutions.

    Empower Your Business with Success.ai:

    Success.ai’s Retail Store Data for the retail and e-commerce sectors in Asia provides the insights and connections needed to thrive in this competitive market. Whether you’re entering a new region, launching a targeted campaign, or analyzing market trends, our data solutions ensure measurable success.

    ...

  12. U.S. pet store revenue distribution by age group 2023

    • statista.com
    Updated Aug 27, 2024
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    Statista (2024). U.S. pet store revenue distribution by age group 2023 [Dataset]. https://www.statista.com/statistics/254111/pet-store-market-segmentation-in-the-us-by-target-group/
    Explore at:
    Dataset updated
    Aug 27, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    United States
    Description

    As of March 2023, shoppers aged between 25 and 44 accounted for the majority of pet store revenue with a 37.2 percent share, thus making them the largest target market in the United States (U.S.). Those aged between 45 and 64 made up the second largest market by a very tight margin, providing 37.1 percent of pet store revenue in the same year. Pet stores in the U.S. There are 18,323 pet store establishments in the U.S. and California is the state with the largest number of pet stores, with 2,120 establishments. Florida closely follows, with 1,606 pet stores. The leading pet store company in the U.S. is the retail chain PetSmart Inc., with a market share of almost one-quarter. PetSmart Inc. and its main competitor, PETCO Animal Supplies, have a total market share of close to 40 percent. Pet stores in the U.S. generate revenue of almost 22 billion U.S. dollars annually. Online purchase of pet food and supplies in the U.S. The sales value of pet food in the U.S. amounts to almost 52 billion U.S. dollars. The store-based retailing channel generates close to 34 billion U.S. dollars of the total sales value, as compared to the e-commerce sale, with approximately 18 billion U.S. dollars. The website chewy.com is the leading online store in the pet supplies segment in the U.S. by a large margin. Chewy's generates over 11.1 billion U.S. dollars in net sales, offering various foods and supplies. However, for the online purchase of pet products in the U.S., the websites of Amazon and Walmart are the main destinations.

  13. A

    ‘Customer Segmentation Classification’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Aug 2, 2020
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2020). ‘Customer Segmentation Classification’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-customer-segmentation-classification-4965/7267b2f5/?iid=015-401&v=presentation
    Explore at:
    Dataset updated
    Aug 2, 2020
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Analysis of ‘Customer Segmentation Classification’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kaushiksuresh147/customer-segmentation on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    Context

    An automobile company has plans to enter new markets with their existing products (P1, P2, P3, P4, and P5). After intensive market research, they’ve deduced that the behavior of the new market is similar to their existing market.

    In their existing market, the sales team has classified all customers into 4 segments (A, B, C, D ). Then, they performed segmented outreach and communication for a different segment of customers. This strategy has work e exceptionally well for them. They plan to use the same strategy for the new markets and have identified 2627 new potential customers.

    You are required to help the manager to predict the right group of the new customers.

    Content

    |Variable|Definition| |--|--| |ID|Unique ID| |Gender|Gender of the customer| |Ever_Married|Marital status of the customer| |Age|Age of the customer| |Graduated|Is the customer a graduate?| |Profession|Profession of the customer| |Work_Experience|Work Experience in years| |Spending_Score|Spending score of the customer| |Family_Size|Number of family members for the customer (including the customer)| |Var_1|Anonymised Category for the customer| |Segmentation|(target) Customer Segment of the customer|

    Acknowledgements

    This dataset was acquired from the Analytics Vidhya hackathon.

    --- Original source retains full ownership of the source dataset ---

  14. Japan Market Dataset

    • kaggle.com
    Updated Aug 15, 2023
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    lastman0800 (2023). Japan Market Dataset [Dataset]. https://www.kaggle.com/datasets/lastman0800/japan-market-dataset/versions/1
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 15, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    lastman0800
    Description

    This dataset is designed for analyzing various product categories within the Japanese market. It provides information about each product category's size, growth rate, market share, competitor market shares, average price, customer demographics, online presence, and market saturation. Here's a breakdown of each column:

    Product Category: The type of products or services being analyzed within the Japanese market.

    Total Market Size (in USD): The estimated total market size in terms of US dollars for each product category. This figure reflects the overall revenue potential for that category.

    Market Growth Rate (%): The projected annual growth rate of each product category's market. This percentage indicates how much the market is expected to expand or contract over time.

    Market Share (%): The percentage of the total market size that each product category holds. This reflects the relative importance of each category within the overall market.

    Competitor 1 Market Share (%): The market share percentage of the first major competitor within each product category. This helps to understand the competitive landscape.

    Competitor 2 Market Share (%): The market share percentage of the second major competitor within each product category. Similar to the previous column, this provides insight into the competitive environment.

    Average Price (in USD): The average price of products or services within each product category. This information helps understand the pricing dynamics of the category.

    Customer Demographics: The primary target audience or customer segments for each product category. Understanding the demographics helps in tailoring marketing efforts.

    Online Presence (%): The percentage of businesses within each product category that have an online presence. This includes websites, social media, and other digital platforms.

    Market Saturation (%): An estimate of how much of the potential market demand has already been captured by existing products or services within each category. A higher percentage indicates a more saturated market.

  15. c

    Consumer Behavior and Shopping Habits Dataset:

    • cubig.ai
    Updated May 28, 2025
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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
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    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. 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.

  17. Mall Customer Segmentation Data

    • kaggle.com
    Updated Aug 11, 2018
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    Vijay Choudhary (2018). Mall Customer Segmentation Data [Dataset]. https://www.kaggle.com/datasets/vjchoudhary7/customer-segmentation-tutorial-in-python/code?sortBy=hotness&group=everyone&pageSize=20&datasetId=42674&language=R
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 11, 2018
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Vijay Choudhary
    Description

    Context

    This data set is created only for the learning purpose of the customer segmentation concepts , also known as market basket analysis . I will demonstrate this by using unsupervised ML technique (KMeans Clustering Algorithm) in the simplest form.

    Content

    You are owing a supermarket mall and through membership cards , you have some basic data about your customers like Customer ID, age, gender, annual income and spending score. Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data.

    Problem Statement You own the mall and want to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly.

    Acknowledgements

    From Udemy's Machine Learning A-Z course.

    I am new to Data science field and want to share my knowledge to others

    https://github.com/SteffiPeTaffy/machineLearningAZ/blob/master/Machine%20Learning%20A-Z%20Template%20Folder/Part%204%20-%20Clustering/Section%2025%20-%20Hierarchical%20Clustering/Mall_Customers.csv

    Inspiration

    By the end of this case study , you would be able to answer below questions. 1- How to achieve customer segmentation using machine learning algorithm (KMeans Clustering) in Python in simplest way. 2- Who are your target customers with whom you can start marketing strategy [easy to converse] 3- How the marketing strategy works in real world

  18. Silver Target Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
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    Dataintelo (2024). Silver Target Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-silver-target-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Dec 3, 2024
    Dataset provided by
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Silver Target Market Outlook



    The global silver target market size is projected to grow from USD 23.5 billion in 2023 to USD 35.8 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 4.8% during the forecast period. This growth is primarily driven by a combination of increasing industrial applications, heightened investment interest, and the expanding jewelry market. As industrial sectors continue to innovate and scale, the demand for silver as an essential component in various manufacturing processes is expected to rise. Moreover, silver's dual status as both a precious metal and an industrial commodity positions it uniquely in the financial and manufacturing landscapes, enhancing its appeal and driving market expansion.



    One of the primary growth factors for the silver target market is its extensive industrial applications, particularly in electronics, photovoltaics, and automotive sectors. Silver's superior electrical conductivity makes it indispensable for electronic devices, and as the world moves towards digitalization and connectivity, the demand for such devices escalates. In the photovoltaics industry, silver plays a crucial role in solar panel production, supporting the global shift towards renewable energy sources. This transition is anticipated to augment silver demand significantly. Additionally, the automotive industry, with its increasing focus on electric vehicles (EVs), relies on silver for its electrical systems, further propelling market growth. The convergence of these industrial needs underscores the metal's vital role in contemporary innovation and technological advancement.



    Investment demand also significantly contributes to the silver market's growth. With economic uncertainties and inflation concerns, investors often turn to precious metals like silver as a hedge against currency devaluation. Silver, being more affordable than gold, provides an attractive investment option for a broader audience, including individual and institutional investors. The accessibility of silver, combined with its potential for appreciation, makes it a popular choice for diversifying investment portfolios. Moreover, the rise of digital and online trading platforms has made silver more accessible to investors, further boosting its demand. As economic conditions fluctuate, the stability and security offered by investing in silver ensure its continued prominence in the investment landscape.



    The jewelry market remains a significant driving force behind the demand for silver. Silver jewelry, renowned for its affordability, versatility, and aesthetic appeal, continues to witness robust demand across various demographics. The growing trend of personalization and customization in jewelry, spurred by consumer preferences for unique and bespoke items, is fueling silver demand. Moreover, cultural and traditional events, particularly in regions like Asia and the Middle East, where silver holds cultural significance, further drive its market. These factors, combined with the evolving fashion trends and increased disposable incomes in emerging economies, are pivotal in sustaining the jewelry market's demand for silver.



    Product Type Analysis



    The silver target market is segmented by product types, including bullion, coins, jewelry, industrial silver, and others. Bullion remains a prominent category, primarily driven by its value storage and investment appeal. Investors globally seek bullion as a tangible and enduring asset, often during economic volatility. The price of bullion is closely tied to market dynamics and investor sentiment, and its demand is expected to rise as more individuals and institutions diversify their portfolios. The intrinsic value and liquidity of bullion make it an attractive option for both short-term and long-term investments.



    Coins represent another significant segment within the silver market. The demand for silver coins is fueled by both collectors and investors who perceive them as a safe investment and a piece of history or art. Unlike bullion, coins offer potential numismatic value, which can appreciate over time. This dual appeal attracts a diverse range of buyers. Moreover, national mints worldwide regularly issue commemorative coins, which draw interest from collectors and investors alike. The limited issuance of certain coin series can also drive demand and increase their value over time, making them a strategic investment choice.



    Jewelry crafted from silver continues to be in vogue, driven by its affordability and versatility. Silver jewelry appeals across a wide demographic, catering to both contemporar

  19. D

    Advertising Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Advertising Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-advertising-market
    Explore at:
    pptx, pdf, csvAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Advertising Market Outlook



    The global advertising market size was valued at approximately $700 billion in 2023 and is projected to reach around $1.2 trillion by 2032, growing at a CAGR of about 6.2% during the forecast period. The primary growth factor driving this market is the rapid expansion of digital platforms and the increasing importance of targeted advertising. The proliferation of smartphones and the internet has significantly transformed the advertising landscape, enabling advertisers to reach their audience more efficiently and effectively.



    A major growth factor for the advertising market is the ever-increasing penetration of digital devices and internet connectivity. With more than half of the global population now having access to the internet, advertisers have an unprecedented opportunity to reach a vast audience. The rise of social media platforms, search engines, and video-sharing sites has further enabled highly targeted and measurable advertising campaigns, which have proven to be more efficient and cost-effective compared to traditional advertising methods.



    Another significant driver is the advancements in data analytics and artificial intelligence. These technologies allow advertisers to analyze vast amounts of consumer data to understand behavior patterns and preferences, enabling them to create highly personalized and relevant advertisements. AI-driven programmatic advertising is gaining traction, as it automates the buying process of ads and optimizes them in real-time based on performance metrics, thus ensuring higher engagement rates and better ROI.



    The shift towards mobile advertising also contributes significantly to market growth. With the increasing use of smartphones and mobile applications, advertisers are focusing more on mobile platforms to reach consumers. Mobile advertising offers unique advantages such as location-based targeting and the use of interactive content, which can enhance user engagement. Additionally, the development of 5G technology is expected to further boost mobile advertising by providing faster data speeds and more reliable connections, creating new opportunities for innovative ad formats.



    In the evolving landscape of advertising, Experiential Advertising Agency Services have become increasingly vital. These services focus on creating immersive and interactive experiences that engage consumers on a deeper emotional level. By leveraging experiential marketing, brands can foster stronger connections with their audience, leading to enhanced brand loyalty and advocacy. This approach allows consumers to experience a brand's message firsthand, often through events, pop-up installations, or interactive digital experiences. As the advertising market continues to grow, the demand for experiential services is likely to rise, offering unique opportunities for brands to differentiate themselves in a crowded marketplace.



    Regionally, the Asia Pacific region is emerging as a significant market for advertising, driven by the expanding middle-class population, increasing urbanization, and growing internet penetration. Countries like China and India are experiencing rapid growth in digital advertising, fueled by their large populations and thriving e-commerce sectors. North America and Europe continue to be mature markets with substantial advertising spending, particularly in digital formats. The Middle East & Africa and Latin America are also witnessing growth, albeit at a slower pace, as they gradually adopt digital advertising technologies.



    Type Analysis



    The advertising market is segmented by type, which includes Digital Advertising, Traditional Advertising, Out-of-Home Advertising, and Others. Digital advertising has seen the most rapid growth and is expected to continue dominating the market. It encompasses various formats such as display ads, video ads, social media ads, search engine marketing, and more. The key advantage of digital advertising is its ability to target specific demographics and measure campaign performance in real-time, providing valuable insights for advertisers. This segment's growth is further fueled by increasing internet usage and the proliferation of digital content platforms.



    Traditional advertising, which includes print media, television, and radio, still holds a significant share of the market. Television remains a powerful medium for reaching a broad audience, especially for brand-building campai

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

    • data.success.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://data.success.ai/products/consumer-marketing-data-api-tailored-consumer-insights-ta-success-ai
    Explore at:
    Dataset updated
    Oct 27, 2021
    Dataset provided by
    Area covered
    Vietnam, Sri Lanka, Mongolia, Barbados, Syrian Arab Republic, Poland, United States Minor Outlying Islands, Bosnia and Herzegovina, Colombia, Svalbard and Jan Mayen
    Description

    Boost your marketing with Success.ai’s Consumer Marketing Data API. Access detailed demographic, behavioral, and purchasing data to craft targeted campaigns that resonate—best price guaranteed!

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Statista (2025). People who shopped at Target in the United States, by age 2024 [Dataset]. https://www.statista.com/forecasts/231373/people-who-shopped-at-target-within-the-last-30-days-usa
Organization logo

People who shopped at Target in the United States, by age 2024

Explore at:
Dataset updated
Jul 10, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Oct 2023 - Sep 2024
Area covered
United States
Description

This statistic illustrates the share of people who shopped at Target in the United States. As of September 2024, ** percent of 18 - 29 year old consumers do so in the U.S. This is according to exclusive results from the Consumer Insights Global survey which shows that ** percent of 30 - 49 year old customers also fall into this category.Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than ********* interviews.

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