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.

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 targeting requirements and receive custom pricing for your marketing objectives.

According to a March 2022 survey of companies from selected countries that have already invested in the metaverse, most of the responding businesses saw big companies, men, and Gen Z as the target audience for their metaverse activities. In total, **** percent of respondents stated that men were a metaverse target audience, compared to only *** percent who stated the same about women. Additionally, big businesses were approximately * times more attractive than SMBs.

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.

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.

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.
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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.
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3. Continuous Data Enrichment

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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...

Discover the booming Influencer Marketing market, projected to hit $13.8B in 2025 with a 31.95% CAGR. This in-depth analysis explores key trends, drivers, restraints, and regional breakdowns, featuring top players like Upfluence and Aspire. Learn how to leverage this powerful marketing strategy. Recent developments include: August 2024: The Tourism Authority of Thailand (TAT) has unveiled its new influencer marketing platform, 'TAT Connex', marking a significant step in its digital transformation strategy for promoting and developing tourism. 'TAT Connex' invites a diverse range of participants, including local and international Key Opinion Leaders (KOLs), influencers, bloggers, media personalities, and celebrities. They can connect with ten distinct categories of tourism-related businesses. These categories encompass dining establishments, hotels and homestays, transportation services, recreational activities and attractions, travel agencies, health and beauty services, shopping centers, entertainment venues, and souvenir shops.July 2024: Collective Artists Network, a new media entity focused on pop culture, is venturing into AI by acquiring Galleri5. Galleri5 is an AI-driven platform specializing in influencer marketing analytics and content management, catering to brands and influencers. Its offerings encompass AI-generated visual content, creator intelligence, campaign oversight, and trend prediction. By acquiring Galleri5, the firm is making a significant stride in weaving deep tech and AI into the fabric, bolstering its capacity to deliver state-of-the-art solutions to talents, content platforms, and brands.July 2024: Publicis Groupe has agreed to acquire Influential, the leading global influencer marketing platform. Influential specializes in authentically linking brands to their audiences through creating, deploying, and optimizing digital campaigns driven by creators. As the world's largest influencer marketing firm by revenue, Influential boasts a proprietary AI-driven technology platform that analyzes over 100 billion data points. Its expansive network includes over 3.5 million creators, granting access to data on 90% of global influencers with over 1 million followers. Currently, Influential provides its services to more than 300 brands worldwide.June 2024: Qoruz, an influencer marketing platform based in India, has partnered with Dabur, a brand celebrated for its natural and Ayurvedic products. This collaboration enhances Dabur's influencer marketing strategy, fostering more authentic and impactful connections with its audience. Leveraging Qoruz's sophisticated analytics and influencer management tools, Dabur aims to pinpoint influencers that resonate with the brand's fundamental values. Through Qoruz’s platform, Dabur gains data-driven insights into influencer performance and audience engagement, enabling them to craft campaigns that effectively resonate with their target demographic.. Key drivers for this market are: Firms Increasing Necessity to Utilize Influencer Marketing Platforms for Enhanced Consumer Engagement, Increasing Penetration of Social Media Platforms. Potential restraints include: Firms Increasing Necessity to Utilize Influencer Marketing Platforms for Enhanced Consumer Engagement, Increasing Penetration of Social Media Platforms. Notable trends are: Fashion and Lifestyle is Expected to Hold Significant 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.

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

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.

This statistic shows the results of a consumer survey conducted by Packaged Facts in August 2012. People were asked if they suffer from celiac disease or wheat/gluten intolerance and if they buy gluten-free products. The results indicated that only 0.1 percent of the U.S. population are diagnosed celiacs, whereas 18 percent of the consumers actually buy products tagged as gluten-free. Hence, there was a large gap between the number of people who really need to stick to a gluten-free diet and those who actually buy gluten-free products.

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

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.

🏪 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

This statistic shows the retail sales market share of Target Corporation in the United States in 2012 and 2013. In 2013, Target held a market share of over *** percent in the United States.

Business Task This dataset aims to analyze the current trends in the usage of non-Bellabeat smart devices to gain valuable insights into consumer behavior and inform future marketing strategies for Bellabeat, a women-focused, wellness company.

By examining how consumers are utilizing these non-Bellabeat devices, this dataset provides an opportunity to understand the preferences, habits, and needs of the target audience more comprehensively.

The dataset encompasses a diverse range of user data, including device usage patterns and generational demographics. With this data, Bellabeat can identify the most popular features, functionalities, and activities that resonate with its target market. This analysis will enable the company to uncover potential gaps in its current product offerings and develop innovative strategies to enhance its market position.

By studying who and how consumers engage with non-Bellabeat smart devices, Bellabeat aims to gain valuable insights into the preferences and behaviors of its target demographic. Understanding how users interact with similar devices in the market will allow the company to tailor its future marketing efforts to meet the specific needs and desires of its customers effectively. This dataset serves as a foundation for data-driven decision-making, helping Bellabeat identify opportunities for growth, improve user experiences, and shape the direction of its product development and marketing initiatives.