Demographical Shopping Purchases Data

Analyzing customer purchasing patterns and preferences

By Joseph Nowicki [source]

About this dataset

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

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How to use the dataset

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

Research Ideas

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

Acknowledgements

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

License

See the dataset description for more information.

Columns

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

Acknowledgements

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

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

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

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

1. Tailored Consumer Insights for Precision Targeting

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

2. Comprehensive Global Reach

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

3. Continuously Updated and Real-Time Data

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

4. Ethical and Compliant

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

Data Highlights:

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

Key Features of the Consumer Marketing Data API:

1. Granular Targeting and Segmentation

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

2. Flexible and Seamless Integration

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

3. Continuous Data Enrichment

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

4. AI-Driven Validation

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

Strategic Use Cases:

1. Highly Personalized Marketing Campaigns

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

2. Market Expansion and Product Launches

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

3. Competitive Analysis and Trend Forecasting

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

4. Customer Retention and Loyalty Programs

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

Why Choose Success.ai?

1. Best Price Guarantee

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

2. Seamless Integration

   • Easily incorporate the API into existing workflows, eliminating data silos and manual data management.

3. Data Accuracy with AI Validation

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

4. Customizable and Scalable Solutions

   • Tailor datasets to focus on specific demog...

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...

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.

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.

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.

Learn about the different segments of the cosmetics industry target market, including demographics, lifestyle, behavior, and personal values, to better understand how companies market their products to diverse audiences.

🏪 Dehradun Retail Node Map - Footfall & Commercial Analysis

Overview

Comprehensive retail footfall and commercial property analysis for Dehradun's major shopping areas. This dataset provides actionable business intelligence for retail location planning, covering 8 prime retail nodes with detailed footfall patterns, rental costs, and customer demographics.

🎯 Dataset Focus

Target Market: Women's retail business planning in Dehradun, India's fastest-growing Tier-2 city Coverage: 8 major retail locations with 500+ daily data points Time Period: 2024-2025 with seasonal patterns

📊 Key Insights Included

• Paltan Bazaar: 50,000 peak daily footfall, ₹120-180/sqft rent
• Rajpur Road: 35,000 daily footfall, 52% female visitors, premium location
• Pacific Mall: 25,000 daily visitors, 175 stores, modern retail environment
• Peak Hours: 6-9 PM across all locations for maximum customer traffic

📁 Data Tables (11 CSV sections)

1. Primary Retail Nodes - Footfall, rent, demographics for 8 locations
2. Mall-specific Analysis - Detailed metrics for 3 major malls
3. Street-wise Commercial - 4 commercial corridors analysis
4. Footfall Patterns - Daily/weekly/seasonal variations
5. Rental Matrix - Property costs by zone and type
6. Customer Demographics - Age, gender, spending patterns by location
7. Peak Hours Analysis - Optimal business timing insights
8. Competition Density - Market saturation levels
9. Smart City Impact - Infrastructure development effects
10. Seasonal Variations - Monthly footfall index (12 months)

🔍 Key Business Intelligence

• Best Female Footfall: Rajpur Road (52%), Pacific Mall (55%)
• Highest Volume: Paltan Bazaar (50K peak), Clock Tower (40K)
• Premium Locations: Pacific Mall (₹250-400/sqft), Rajpur Road (₹200-300/sqft)
• Peak Shopping: April-May (+35-40% footfall), Evening 6-9 PM
• Weekend Boost: 30-80% higher than weekdays

🎯 Use Cases

✅ Retail Location Selection - Compare footfall vs rent across 8 prime areas ✅ Footfall Optimization - Peak hours and seasonal planning ✅ Rental Budgeting - Detailed cost analysis by location type ✅ Target Demographics - Customer profile matching by area ✅ Competition Analysis - Market saturation and opportunity gaps ✅ Seasonal Planning - Monthly demand forecasting

📈 Data Sources & Methodology

• Primary Research: Market surveys, footfall counters, property analysis
• Digital Analytics: Google Popular Times, social media check-ins
• Commercial Data: CREDAI property rates, mall visitor analytics
• Tourism Data: Smart city infrastructure, seasonal patterns
• Validation: Cross-referenced with multiple sources for accuracy

🌟 Why This Dataset

First comprehensive retail footfall analysis for Dehradun combining traditional markets (Paltan Bazaar) with modern retail (Pacific Mall). Essential for entrepreneurs planning retail entry in India's emerging Tier-2 cities.

🏷️ Perfect For

• Retail business planning & location strategy
• Commercial real estate investment analysis
• Market research on Tier-2 city retail dynamics
• Footfall pattern analysis and optimization
• Customer behavior studies in emerging markets

📊 Data Quality

• Methodology: Professional market research standards
• Time Coverage: Current data with seasonal analysis
• Accuracy: Cross-validated across multiple sources
• Completeness: 100% coverage of major retail nodes

Geographic Scope: Dehradun city, Uttarakhand, India
Last Updated: June 2025
Data Type: Commercial footfall & property analysis

Learn about the diverse and ever-growing beer market, including target demographics, types of beer, and marketing strategies to increase sales and brand awareness. From mainstream lagers to artisanal craft beer, there's something for everyone in this booming industry.

Dataset Description This dataset contains information about 8,500+ mobile service customers, including demographic details, device usage, billing patterns, and call behavior. The primary goal of this dataset is to enable analysis and modeling to predict customer churn — i.e., customers who decide to drop their mobile service provider.

The data includes 33 features and one binary target column (customer_dropped). This dataset is ideal for exploring churn prediction models, customer segmentation, lifetime value analysis, and marketing strategy development.

Features - customer_id: Unique identifier for each customer - age: Age of the customer - job: Occupation or profession of the customer - urban_rural: Indicates whether the customer resides in an urban or rural area - marital_status: Marital status of the customer - kids: Number of children the customer has - disposable_income: Disposable income of the customer - mobiles_changed: Number of times the customer has changed their mobile device - mobile_age: Age of the current mobile device - own_smartphone: Indicates whether the customer owns a smartphone - current_mobile_price: Price of the customer's current mobile device - credit_card_type: Type of credit card held - own_house: Indicates whether the customer owns a house - own_cr_card: Indicates whether the customer owns a credit card - monthly_bill: Monthly bill for mobile service - call_mins: Total call minutes used - basic_plan_amount: Basic mobile plan amount - extra_mins: Extra minutes used beyond the plan - roam_call_mins: Roaming call minutes - call_mins_delta: Change in call minutes compared to the previous billing period - bill_amount_delta: Change in bill amount compared to the previous billing period - incoming_call_mins: Total incoming call minutes - outgoing_calls: Number of outgoing calls - incoming_calls: Number of incoming calls - day_night_call_ratio: Ratio of call minutes during the day versus night - day_night_call_delta: Change in day vs night call minutes compared to the previous period - calls_dropped: Number of calls dropped - loyalty_months: Customer tenure in months - complaint_calls: Number of complaint calls made - promo_calls_made: Number of promotional calls made - promo_offers_accepted: Number of promotional offers accepted - new_numbers_called: Number of new contacts called - customer_dropped: Target column indicating churn (1 = churned, 0 = retained)

Use Cases - Develop machine learning models for churn prediction - Perform customer segmentation and behavioral profiling - Analyze call usage trends and billing sensitivity - Identify key drivers of customer loyalty or attrition - Design data-driven retention strategies

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

According to the results of a survey conducted in October 2023 among communications specialist worldwide, people between 17 and 19 years-old were targeted with influencer marketing by ** percent of respondents. The most targeted age group was the 20-29-year-old consumers, targeted by ** percent of influencer marketing professionals.

The Silver Target market, which primarily focuses on the demographic of older adults aged 50 and above, represents a significant and growing segment of the consumer landscape. As the global population ages, this market has gained traction, driven by an increasing life expectancy and a rising number of baby boomers e

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.

This statistic looks at which socio-economic demographics retailers target in the United Kingdom in 2016. According to the survey, ** percent of retailers focus on the AB social-economic group (upper middle and middle classes) while only one percent focus on groups DE (working and non-working classes).

This dataset was sourced from KPMG AU's Data Analytics virtual internship course on Forage

Sprocket Pvt Ltd is a client of KPMG AU. Sprocket is a bike and bike accessories retail business. They need to find the right customer segment to target for marketing to boost revenue. The following dataset is of their customer demographics for the past 3 years.

The original dataset of 3 separate sheets of Customer demographic, Transactions, and Customer Addresses was fully cleaned and merged using a power query. Data types of columns were changed, and values of certain columns which had illegal values were corrected using a standard approach. This final master dataset can be used for customer segmentation projects using clustering methods.

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.

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.