According to a survey conducted in May 2021, more than half of consumers in the older age groups (** and over) in the United States preferred big box/department stores and pharmacy/convenience stores for their retail purchases compared to consumers in the younger age groups. Online marketplaces were popular across both younger and older consumers. Over ********* of respondents in the age groups 18-34 and 35-54 stated to have used online marketplaces such as Amazon and Etsy in the past three months. This rate was even higher with those aged over ** (at ** percent).

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 ...

According to the results of a recent survey conducted in the United States, most respondents across all age groups preferred to buy products directly in stores. The highest share of in-store buyers was among baby boomers, with 83 percent. On the other hand, the same generation did not seem as interested as others in buying products through companies' apps or social media.

Concerning the five age groups, the group of 25-34 years has the largest share with **** percent. Contrastingly, the group of 18-24 years is ranked last, with **** percent. Their difference, compared to the 25-34 years, lies at *** percentage points. Find other insights concerning similar markets and segments, such as a ranking of subsegments in Russia regarding share in the segment Electronics and a ranking of subsegments in Russia regarding share in the e-commerce market as a whole.

In 2023, the age group of the 35 to 44 year-olds was the largest age group in the United States confectionery market. Approximately ** percent of confectionery consumers fell into this group. The age group of the 25 to 34 year-olds followed closely behind at **** percent.

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

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...

This statistic looks at which age demographic retailers aim for in the United Kingdom in 2016. Of the retailers surveyed ** percent focus on the 18 to 34 year age group compared to just *** percent of the over ** market.

The MENA Retail Market, valued at $405 billion in 2024, is projected to reach $620 billion by 2034, growing at a 4.5% CAGR from 2025 to 2034.

This product provides a monthly breakdown of the shopper profile for individual Points of Interest (POI), offering invaluable insight into the characteristics of who is visiting that location each month. It includes aggregated psychographic and demographic attributes such as age, gender, income level, lifestyle segments, and other key behavioral indicators. Furthermore, it surfaces the distribution of home ZIP codes, illustrating the geographic origins of visitors, and highlights other brands and POIs those same visitors also frequent during the month, revealing broader consumer behavior.

All metrics are consistently expressed as a percentage share of total visits to the POI in that month. This standardized approach allows for robust month-over-month comparison and precise audience trend analysis. Users can therefore comprehensively understand how the composition of shoppers is changing over time, where they live, what defines their consumer preferences, and how they behave across the wider retail landscape.

The data is fully anonymized and aggregated, with no access to individual-level or device-level records. It is delivered monthly and is commonly utilized for in-depth audience profiling, strategic market segmentation, powerful brand affinity analysis, and informed strategic decision-making

The dataset comprises transactional information from previous 5 years from Walmart retail stores, with diverse details such as customer demographics, order specifics, product attributes, and sales logistics. It includes data on the city where purchases were made, customer age, names, and segments, along with any applied discounts and the quantity of products ordered. Each transaction is uniquely identified by an order ID, accompanied by order date, priority, and shipping details like mode, cost, and dates. Product-related information encompasses base margins, categories, containers, names, and sub-categories, enabling insights into profitability, sales, and regional performance. The dataset also provides granular details such as profit margins, unit prices, and ZIP codes, facilitating analysis at multiple levels like customer behavior, product performance, and operational efficiencies within Walmart's retail ecosystem.

The columns in dataset are:

1. City: The city where the purchase was made.
2. Customer Age: Age of the customer making the purchase.
3. Customer Name: Name of the customer.
4. Customer Segment: Segment to which the customer belongs (like retail, wholesale, etc.).
5. Discount: Any discount applied to the purchase.
6. Number of Records: The count of records for each transaction.
7. Order Date: Date when the order was placed.
8. Order ID: Unique identifier for each order.
9. Order Priority: Priority level of the order (like high, medium, low).
10. Order Quantity: Quantity of products ordered.
11. Product Base Margin: Base margin percentage for the product.
12. Product Category: Category to which the product belongs (like electronics, groceries, etc.).
13. Product Container: Container type of the product.
14. Product Name: Name of the product.
15. Product Sub-Category: Sub-category to which the product belongs.
16. Profit: Profit earned from the transaction.
17. Region: Region where the purchase was made.
18. Row ID: Unique identifier for each row.
19. Sales: Total sales amount.
20. Ship Date: Date when the order was shipped.
21. Ship Mode: Mode of shipping (like standard, express, etc.).
22. Shipping Cost: Cost associated with shipping.
23. State: State where the purchase was made.
24. Unit Price: Price per unit of the product.
25. Zip Code: ZIP code of the customer or store location.

The 2018 edition of Woods and Poole Complete U.S. Database provides annual historical data from 1970 (some variables begin in 1990) and annual projections to 2050 of population by race, sex, and age, employment by industry, earnings of employees by industry, personal income by source, households by income bracket and retail sales by kind of business. The Complete U.S. Database contains annual data for all economic and demographic variables for all geographic areas in the Woods & Poole database (the U.S. total, and all regions, states, counties, and CBSAs). The Complete U.S. Database has following components: Demographic & Economic Desktop Data Files: There are 122 files covering demographic and economic data. The first 31 files (WP001.csv – WP031.csv) cover demographic data. The remaining files (WP032.csv – WP122.csv) cover economic data. Demographic DDFs: Provide population data for the U.S., regions, states, Combined Statistical Areas (CSAs), Metropolitan Statistical Areas (MSAs), Micropolitan Statistical Areas (MICROs), Metropolitan Divisions (MDIVs), and counties. Each variable is in a separate .csv file. Variables: Total Population Population Age (breakdown: 0-4, 5-9, 10-15 etc. all the way to 85 & over) Median Age of Population White Population Population Native American Population Asian & Pacific Islander Population Hispanic Population, any Race Total Population Age (breakdown: 0-17, 15-17, 18-24, 65 & over) Male Population Female Population Economic DDFs: The other files (WP032.csv – WP122.csv) provide employment and income data on: Total Employment (by industry) Total Earnings of Employees (by industry) Total Personal Income (by source) Household income (by brackets) Total Retail & Food Services Sales ( by industry) Net Earnings Gross Regional Product Retail Sales per Household Economic & Demographic Flat File: A single file for total number of people by single year of age (from 0 to 85 and over), race, and gender. It covers all U.S., regions, states, CSAs, MSAs and counties. Years of coverage: 1990 - 2050 Single Year of Age by Race and Gender: Separate files for number of people by single year of age (from 0 years to 85 years and over), race (White, Black, Native American, Asian American & Pacific Islander and Hispanic) and gender. Years of coverage: 1990 through 2050. DATA AVAILABLE FOR 1970-2019; FORECASTS THROUGH 2050

1) Data Introduction • The Retail Sales Dataset is data designed to analyze retail sales and customer behavior in a virtual retail environment, including transaction history, customer demographics, and product information.

2) Data Utilization (1) Retail Sales Dataset has characteristics that: • This dataset details retail sales and customer characteristics such as transaction ID, date, customer ID, gender, age, product category, purchase volume, unit price, total amount. (2) Retail Sales Dataset can be used to: • Customer Segmentation and Marketing Strategy: By analyzing purchase patterns by age, gender, and product category, you can use them to establish a customized marketing strategy. • Sales Trends and Inventory Management: It can be used to streamline retail operations such as inventory management and promotion planning by analyzing sales trends by period and product.

Our consumer data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes a variety of data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences.

1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc.
2. Demographics - Gender, Age Group, Marital Status, Language etc.
3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc
4. Persona - Consumer type, Communication preferences, Family type, etc
5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc.
6. Household - Number of Children, Number of Adults, IP Address, etc.
7. Behaviours - Brand Affinity, App Usage, Web Browsing etc.
8. Firmographics - Industry, Company, Occupation, Revenue, etc
9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc.
10. Auto - Car Make, Model, Type, Year, etc.
11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

Consumer Graph Use Cases:

360-Degree Customer View:Get a comprehensive image of customers by the means of internal and external data aggregation.

Data Enrichment:Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment

Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity.

Advertising & Marketing:Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

Using Factori Consumer Data graph you can solve use cases like:

Acquisition Marketing Expand your reach to new users and customers using lookalike modeling with your first party audiences to extend to other potential consumers with similar traits and attributes.

Lookalike Modeling

Build lookalike audience segments using your first party audiences as a seed to extend your reach for running marketing campaigns to acquire new users or customers

And also, CRM Data Enrichment, Consumer Data Enrichment B2B Data Enrichment B2C Data Enrichment Customer Acquisition Audience Segmentation 360-Degree Customer View Consumer Profiling Consumer Behaviour Data

Activewear Market size was valued at USD 510.51 Million in 2023 and is projected to reach USD 783.09 Million by 2031, growing at a CAGR of 6.06% during the forecast period 2024-2031.

Key Market Drivers: • Rise of the Athleisure Trend: Athleisure which combines athletic and leisurewear has emerged as a prominent fashion trend impacting demand for sportswear. This trend reflects a cultural shift in which customer’s value comfort and functionality without sacrificing style. Athleisure apparel has grown in popularity because to its versatility which allows it to be used for both exercises and everyday activities. This trend has been capitalized on by brands such as Lululemon and Nike who offer attractive yet utilitarian clothes. • Increasing Health and Fitness Awareness: As people become more conscious of the value of health and fitness, the activewear market has grown significantly. More people are taking part in physical activities including jogging, yoga, and gym workouts. This shift is partially attributable to the global push for healthy living and preventive healthcare. The COVID-19 epidemic has highlighted the significance of physical well-being resulting in an increase in home exercises and associated rise in demand for comfortable and functional training gear. • Technological Advancements in Fabric and Design: Fabric technology and garment design innovations have been critical to the sportswear market's growth. Activewear's functionality has been boosted by advances such as moisture-wicking fabrics, odor management, and increased breathability. Brands are also introducing smart textiles that measure physical activity which adds value to consumers.

Taiwan Employment: Service: Wholesale & Retail Trade data was reported at 1,716.273 Person th in 2010. Taiwan Employment: Service: Wholesale & Retail Trade data is updated yearly, averaging 1,716.273 Person th from Dec 2010 (Median) to 2010, with 1 observations. Taiwan Employment: Service: Wholesale & Retail Trade data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.G029: Working Age Population and Employment: Population and Housing Census.

The global teleshopping market, valued at $20,570 million in 2025, is experiencing significant growth driven by the increasing penetration of internet and mobile devices, coupled with the rising popularity of online shopping, particularly amongst the 30-49 and 50+ age demographics. The convenience of home shopping, especially for time-constrained individuals, fuels market expansion. While traditional teleshopping channels like television remain important, the integration of e-commerce platforms and social media marketing strategies is transforming the industry. This convergence allows for targeted advertising, personalized offers, and a broader reach. Key players like QVC, HSE24, and ShopHQ leverage their established brands and extensive product catalogs to maintain market leadership, while newer entrants utilize digital platforms for disruptive innovation. However, challenges remain, such as the need to build trust and overcome consumer concerns about product quality and return policies in online teleshopping. Competition from established e-commerce giants also exerts pressure on market participants. Despite these challenges, the market’s future looks bright. Growth will be further fueled by improvements in logistics and delivery services, as well as the increasing adoption of advanced technologies such as augmented reality (AR) and virtual reality (VR) for immersive shopping experiences. This will lead to a more engaging and personalized teleshopping experience, driving further market penetration. Geographic expansion, particularly in emerging markets with rising disposable incomes and increasing internet access, represents another significant growth opportunity. The segmentation of the market by age group allows for tailored marketing strategies, maximizing reach and engagement across different customer demographics. Strategic partnerships and mergers and acquisitions are also likely to shape the competitive landscape, leading to further consolidation in the market. Overall, the teleshopping market is poised for sustained growth throughout the forecast period (2025-2033), driven by technology advancements, evolving consumer behavior, and strategic market initiatives.

Walmart and Amazon shoppers, according to a 2023 survey, are among the oldest compared to beauty shoppers at other stores in the United States. Walmart and Amazon shoppers were, on average, ** years old. Meanwhile, Target consumers were, on average, ** years old.

For the 2023 back-to-school (BTS) shopping season, approximately 45 percent of surveyed shoppers in the United States were buying supplies for elementary school kids. Only about six percent of the survey's respondents were buying school supplies for college students.