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 ...

As of February 2025, Meta's largest audience were women and men aged 25 to 34 years, with each group making up 12.2 percent of users, respectively. Overall, less than 15 percent of Meta's audience, which includes platforms Facebook, Instagram, and Messenger, were aged between 65 years and above.

Our People 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.

People Data 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).

People Data 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 People Data 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

Here's the schema of People Data: person_id first_name last_name age gender linkedin_url twitter_url facebook_url city state address zip zip4 country delivery_point_bar_code carrier_route walk_seuqence_code fips_state_code fips_country_code country_name latitude longtiude address_type metropolitan_statistical_area core_based+statistical_area census_tract census_block_group census_block primary_address pre_address streer post_address address_suffix address_secondline address_abrev census_median_home_value home_market_value property_build+year property_with_ac property_with_pool property_with_water property_with_sewer general_home_value property_fuel_type year month household_id Census_median_household_income household_size marital_status length+of_residence number_of_kids pre_school_kids single_parents working_women_in_house_hold homeowner children adults generations net_worth education_level occupation education_history credit_lines credit_card_user newly_issued_credit_card_user credit_range_new
credit_cards loan_to_value mortgage_loan2_amount mortgage_loan_type
mortgage_loan2_type mortgage_lender_code
mortgage_loan2_render_code
mortgage_lender mortgage_loan2_lender
mortgage_loan2_ratetype mortgage_rate
mortgage_loan2_rate donor investor interest buyer hobby personal_email work_email devices phone employee_title employee_department employee_job_function skills recent_job_change company_id company_name company_description technologies_used office_address office_city office_country office_state office_zip5 office_zip4 office_carrier_route office_latitude office_longitude office_cbsa_code
office_census_block_group
office_census_tract office_county_code
company_phone
company_credit_score
company_csa_code
company_dpbc
company_franchiseflag
company_facebookurl company_linkedinurl company_twitterurl
company_website company_fortune_rank
company_government_type company_headquarters_branch company_home_business
company_industry
company_num_pcs_used
company_num_employees
company_firm_individual company_msa company_msa_name
company_naics_code
company_naics_description
company_naics_code2 company_naics_description2
company_sic_code2
company_sic_code2_description
company_sic...

As of October 2025, men aged 25 to 34 represented Facebook’s largest user group, making up **** percent of the platform’s global audience. Across all age groups except those aged 65 and older, male users outnumbered female users. Facebook connects the world Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger, as well as photo-sharing app Instagram. Facebook users The vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with *** million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

A global database that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future.

Leverage up-to-date population trends for market research, ad targeting, and sales territory mapping.

Self-hosted population dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The geodemographic data is standardized, unified, and ready to use.

Use cases for the Global Population Database (Demographic/Geodemographic data)

• Ad targeting

• Market Intelligence

• Customer analytics

• Marketing campaign analysis

• Demand forecasting

• Sales territory mapping

• Retail site selection

• Reporting

Geographic data export methodology

Our location data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Historical population data (55 years)

• Changes in population density

• Urbanization Patterns

• Accurate at zip code and administrative level

• Optimized for easy integration

• Easy customization

• Global coverage

• Updated yearly

• Standardized and reliable

• Self-hosted delivery

• Fully aggregated (ready to use)

• Rich attributes

Why do companies choose our location databases

• Standardized and unified demographic data structure

• Seamless integration in your system

• Dedicated location data expert

Note: Custom population data packages are available. Please submit a request via the above contact button for more details.

The User Profile Data is a structured, anonymized dataset designed to help organizations understand who their users are, what devices they use, and where they are located. Each record provides privacy-compliant linkages between user IDs, demographic profiles, device intelligence, and geolocation data, offering deep context for analytics, segmentation, and personalization.

Built for privacy-safe analytics, the dataset uses hashed identifiers like phone number and email and standardized formats, making it easy to integrate into big-data platforms, AI pipelines, and machine learning models for advanced analytics.

Demographic insights include gender, age, and age group, essential for audience profiling, marketing optimization, and consumer intelligence. All gender data is user-declared and AI-verified through image-based avatar validation, ensuring data accuracy and authenticity.

The dataset’s Device Intelligence Layer includes rich technical attributes such as device brand, model, OS version, user agent, RAM, language, and timezone, enabling technical segmentation, performance analytics, and targeted ad delivery across diverse device ecosystems.

On the location and POI front, the dataset combines GPS-based and IP-based coordinates—including country, region, city, latitude, longitude —to provide high-precision geospatial insights. This enables mobility pattern analysis, market expansion planning, and POI clustering for advanced location intelligence.

Each user record contains onboarding and lifecycle fields like unique IDs, and profile update timestamps, allowing accurate tracking of user acquisition trends, data freshness, and activity duration.

🔍 Key Features • 1st-party, consent-based demographic & device data • AI-verified gender insights via avatar recognition • OS-level app data with 120+ daily sessions per user • Global coverage across APAC and emerging markets • GPS + IP-based geolocation & POI intelligence • Privacy-compliant, hashed identifiers for safe integration

🚀 Use Cases • Audience segmentation & lookalike modeling • Ad-tech and mar-tech optimization • Geospatial & POI analytics • Fraud detection & risk scoring • Personalization & recommendation engines • App performance & device compatibility insights

🏢 Industries Served Ad-Tech • Mar-Tech • FinTech • Telecom • Retail Analytics • Consumer Intelligence • AI & ML Platforms

As of February 2025, 37.5 percent of X’s (formerly Twitter) global audience was aged between 25 and 34 years. The second-largest age group demographic on the platform was represented by users aged between 18 and 24 years, with a share of 32.1 percent. Users aged less than 18 years accounted for two percent of users, while those aged 50 or older accounted for roughly 7.3 percent. X is a male-dominated platform As of January 2024, more than 60 percent of X users were male. Although all mainstream social media platforms tend to have a slightly more male-skewing audience, X stands out above Instagram, Snapchat, TikTok, and Facebook when it comes to user gender demographics. Overall, Pinterest is the only mainstream platform to have a higher share of female users. X Blue for you It is not uncommon for social media users to now have the chance to become subscribers of their chosen online networks for a monthly fee. X Blue is a subscription service from X that gives users special benefits and features. A blue verification mark, edit post functionality, fewer ads, priority ranking in chats, and longer video upload times are some of the perks offered.

63% female, 37% male; top age groups 25–34 and 35–44; audience locations: USA, Canada, UK, Germany, UAE; social reach of 200K followers across Instagram, Facebook, YouTube, TikTok and Pinterest.

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...

Context:

Digital marketing platforms today rely heavily on user profiling to decide which advertisements should be displayed to which audience. Social networks collect demographic information such as age, gender, and income to understand user behavior and improve ad targeting. This dataset captures how different user demographics respond to online advertisements, making it valuable for studying customer behavior, marketing strategies, and purchase prediction.

The dataset is widely used in machine learning education and projects because it is simple, clean, and ideal for building classification models. It helps beginners and professionals understand how demographic features influence a user’s decision to purchase a product after viewing an ad.

Content :

This dataset contains user demographic information and their response to an advertisement. Each row represents one individual from a social media platform, including:

Age : The age of the user

Estimated Salary : Approximate annual salary of the user

Purchased : Target variable indicating whether the user bought the advertised product

0 = No purchase

1 = Purchase

The dataset can be used for:

• Predicting purchase behavior using machine learning models

• Understanding how age and income affect ad response

• Performing exploratory data analysis (EDA)

• Demonstrating classification algorithms such as Logistic Regression, KNN, SVM, Trees, etc.

• Practicing feature scaling, model training, evaluation, and visualization

As of February 2025, it was found that around 14.1 percent of TikTok's global audience were women between the ages of 18 and 24 years, while male users of the same age formed approximately 16.6 percent of the platform's audience. The online audience of the popular social video platform was further composed of 14.6 percent of female users aged between 25 and 34 years, and 20.7 percent of male users in the same age group.

As of October 2025, 33.4 percent of LinkedIn users worldwide were between the ages of 25 and 34 years old. In comparison, users older than 55 years old made up 1.8 percent of the social platform's audience. Furthermore, individuals belonging to the 18- to 24-year-old age group constituted 20.5 percent of the professional social network's user base, and 56.8 percent of global users identified as male. Leading LinkedIn audiences As of April 2024, the United States was home to 230 million LinkedIn users, which made it the country with the largest audience of the online network. India had 130 million users, and Brazil had 71 million users. As of June 2024, 16 percent of social media users in the United States utilized LinkedIn, making it the eighth most popular social network in the country. The growing number of LinkedIn subscribers Users of LinkedIn can upgrade to premium accounts to make the most of additional features and tools to help them with their professional networking. It is estimated that there were 174.5 million premium users on LinkedIn in 2023, up from around 154.4 million in 2022. In 2019, there were around 94 million premium users of LinkedIn, indicating an increase in paid subscribers of around 85 percent over the past four years.

Demografy is a privacy by design customer demographics prediction AI platform.

Core features: - Demographic segmentation - Demographic analytics - API integration - Data export

Key advantages: - 100% coverage of lists - Accuracy estimate before purchase - GDPR-compliance as no sensitive data is required. Demografy can work with only first names or masked last names

Use cases: - Actionable analytics about your customers to get demographic insights - Appending missing demographic data to your records for customer segmentation and targeted marketing campaigns - Enhanced personalization knowing you customer better

Unlike traditional solutions, you don’t need to know and disclose your customer or prospect addresses, emails or other sensitive information. You can provide even masked last names keeping personal data in-house. This makes Demografy privacy by design and enables you to get 100% coverage of your audience since all you need to know is names.

Snapchat has a reach into 75% of the millenial and Gen Z audience.

This filtered view is annual homeless services information for calendar years 2019-2024 and includes demographic information for individuals receiving homeless services from a Mesa-based provider (demographic audience = "provider") or a Mesa resident (demographic audience = "client") from any Maricopa County provider. A Mesa resident is an individual whose last permanent address > 90 days prior to becoming homeless was in Mesa.

Audience Measurement Computer Vision Market Outlook

According to our latest research, the Global Audience Measurement Computer Vision market size was valued at $2.7 billion in 2024 and is projected to reach $9.8 billion by 2033, expanding at a CAGR of 15.2% during 2024–2033. The primary factor fueling this robust growth is the increasing adoption of advanced computer vision technologies by retailers, advertisers, and event organizers to gain real-time insights into audience engagement and demographics. As digital transformation accelerates across industries, organizations are leveraging audience measurement computer vision solutions to optimize content, personalize customer experiences, and maximize ROI on marketing and operational investments. The convergence of AI-powered analytics, improved camera hardware, and cloud-based data processing is creating new possibilities for accurate, scalable, and privacy-compliant audience measurement, further propelling market expansion globally.

Regional Outlook

North America currently holds the largest share of the Audience Measurement Computer Vision market, accounting for approximately 38% of global revenue in 2024. This dominance is attributed to the region’s mature technology infrastructure, widespread adoption of AI and machine learning, and the presence of leading industry players. The United States, in particular, has seen significant investments in retail analytics and digital advertising, with major brands deploying advanced audience measurement solutions in stores, events, and public spaces. Regulatory frameworks in North America support innovation while ensuring privacy compliance, further encouraging adoption. The high penetration of smart devices and robust digital signage networks also contribute to the region’s leadership in deploying computer vision applications for real-time audience analysis.

The Asia Pacific region is poised to be the fastest-growing market, with a projected CAGR of 18.4% from 2024 to 2033. Rapid urbanization, a burgeoning middle class, and increasing digitalization across retail, transportation, and entertainment sectors are driving demand for audience measurement computer vision solutions. Countries such as China, Japan, and South Korea are investing heavily in smart city initiatives and public safety infrastructure, integrating computer vision technologies for crowd monitoring and demographic analysis. The proliferation of affordable hardware, coupled with government support for AI innovation, is accelerating market growth. Local startups and global technology giants are forming strategic partnerships to localize solutions, further boosting adoption in diverse application areas.

Emerging economies in Latin America and the Middle East & Africa are gradually embracing audience measurement computer vision, albeit at a slower pace due to infrastructural and regulatory challenges. In these regions, adoption is often concentrated in urban centers and driven by multinational retail chains, airports, and event venues seeking to enhance customer engagement and operational efficiency. Localized demand is shaped by unique demographic trends and cultural preferences, necessitating tailored solutions. However, limited access to high-quality data, concerns around privacy regulation, and the need for skilled technical personnel remain barriers to widespread deployment. Despite these challenges, ongoing investments in digital infrastructure and pilot projects by global technology providers signal promising future growth.

Report Scope

As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.

              Instagram’s Global Audience

              As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
              As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.

              Who is winning over the generations?

              Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.

Data recorded during the data collection period 17 October– 11 December 2014.

A global database of Census Data that provides an understanding of population distribution at administrative and zip code levels over 55 years, past, present, and future.

Leverage up-to-date census data with population trends for real estate, market research, audience targeting, and sales territory mapping.

Self-hosted commercial demographic dataset curated based on trusted sources such as the United Nations or the European Commission, with a 99% match accuracy. The global Census Data is standardized, unified, and ready to use.

Use cases for the Global Census Database (Consumer Demographic Data)

• Ad targeting

• B2B Market Intelligence

• Customer analytics

• Real Estate Data Estimations

• Marketing campaign analysis

• Demand forecasting

• Sales territory mapping

• Retail site selection

• Reporting

• Audience targeting

Census data export methodology

Our consumer demographic data packages are offered in CSV format. All Demographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Historical population data (55 years)

• Changes in population density

• Urbanization Patterns

• Accurate at zip code and administrative level

• Optimized for easy integration

• Easy customization

• Global coverage

• Updated yearly

• Standardized and reliable

• Self-hosted delivery

• Fully aggregated (ready to use)

• Rich attributes

Why do companies choose our demographic databases

• Standardized and unified demographic data structure

• Seamless integration in your system

• Dedicated location data expert

Note: Custom population data packages are available. Please submit a request via the above contact button for more details.

Context and Objective:

This dataset is developed as part of a business analysis project aimed at exploring sales performance and customer demographics. It is inspired by real-world scenarios where companies strive to enhance their marketing strategies by understanding consumer behavior. The project focuses on the year 2023 and provides insights into how targeted marketing impacts sales while emphasizing demographic characteristics such as age and gender.

Source:

The dataset is synthetically generated, designed to simulate real-world sales scenarios for 20 products. It includes data points that mirror industry practices, ensuring a realistic and comprehensive foundation for analysis. The structure and data content are informed by common business intelligence practices and hypothetical yet plausible marketing scenarios.

Inspiration:

This dataset is inspired by the challenges businesses face in balancing targeted and broad marketing strategies. Companies frequently debate whether niche marketing for specific demographics or campaigns targeting a wider audience yields better outcomes. The dataset serves as a sandbox for exploring these questions, combining data analytics, visualization, and storytelling to drive actionable business insights.

Key Features:

Sales Data: Includes monthly sales records for 20 products, categorized by revenue, units sold, and discounts applied.

Demographic Information: Covers customer age, gender, and location to enable segmentation and trend analysis.

Applications:

Business Insights: Explore product popularity trends across different demographic groups. Revenue Analysis: Understand revenue patterns throughout 2023 and their correlation with customer age and gender.

Marketing Strategy Optimization: Evaluate the effectiveness of targeted vs. broad campaigns, particularly those targeting specific gender or age groups.

Visualization and Storytelling: Build dashboards and presentations to communicate insights effectively. This dataset is ideal for analysts and students seeking hands-on experience in SQL, exploratory data analysis, and visualization tools like Power BI. It bridges the gap between data science and practical business decision-making.