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.

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.

Success.ai’s Retail Data for the Retail Sector in North America offers a comprehensive dataset designed to connect businesses with key players across the diverse retail industry. Covering everything from department stores and supermarkets to specialty shops and e-commerce platforms, this dataset provides verified contact details, business locations, and leadership profiles for retail companies in the United States, Canada, and Mexico.

With access to over 170 million verified professional profiles and 30 million company profiles, Success.ai ensures your outreach, marketing, and business development efforts are powered by accurate, continuously updated, and AI-validated data.

Backed by our Best Price Guarantee, this solution empowers businesses to thrive in North America’s competitive retail landscape.

Why Choose Success.ai’s Retail Data for North America?

1. Verified Contact Data for Precision Outreach

   • Access verified phone numbers, work emails, and LinkedIn profiles of retail executives, store managers, and decision-makers.
   • AI-driven validation ensures 99% accuracy, enabling confident communication and efficient campaign execution.

2. Comprehensive Coverage Across Retail Segments

   • Includes profiles of retail businesses across major markets, from large department stores and grocery chains to boutique retailers and online platforms.
   • Gain insights into the operational dynamics of retail hubs in cities such as New York, Los Angeles, Toronto, and Mexico City.

3. Continuously Updated Datasets

   • Real-time updates reflect leadership changes, new store openings, market expansions, and shifts in consumer preferences.
   • Stay aligned with evolving industry trends and emerging opportunities in the North American retail sector.

4. Ethical and Compliant

   • Adheres to GDPR, CCPA, and other privacy regulations, ensuring responsible and lawful use of data in your campaigns.

Data Highlights:

• 170M+ Verified Professional Profiles: Engage with executives, marketing directors, and operations managers across the North American retail sector.
• 30M Company Profiles: Access firmographic data, including revenue ranges, store counts, and geographic footprints.
• Store Location Data: Pinpoint retail outlets, regional offices, and distribution centers to refine supply chain and marketing strategies.
• Leadership Contact Details: Connect with CEOs, CMOs, and procurement officers influencing retail operations and vendor selections.

Key Features of the Dataset:

1. Retail Decision-Maker Profiles

   • Identify and engage with store owners, category managers, and marketing directors shaping customer experiences and product strategies.
   • Target professionals responsible for inventory planning, vendor contracts, and store performance.

2. Advanced Filters for Precision Targeting

   • Filter companies by industry segment (luxury, grocery, e-commerce), geographic location, company size, or revenue range.
   • Tailor outreach to align with regional market trends, customer demographics, and operational priorities.

3. Market Trends and Operational Insights

   • Analyze trends such as online shopping growth, sustainability practices, and supply chain optimization.
   • Leverage insights to refine product offerings, identify partnership opportunities, and design effective campaigns.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and enhance engagement outcomes.

Strategic Use Cases:

1. Sales and Lead Generation

   • Present products, services, or technology solutions to retail procurement teams, marketing departments, and operations managers.
   • Build relationships with retailers seeking innovative tools, efficient supply chain solutions, or unique product offerings.

2. Market Research and Consumer Insights

   • Analyze retail trends, customer behaviors, and seasonal demands to inform marketing strategies and product launches.
   • Benchmark against competitors to identify gaps, emerging niches, and growth opportunities.

3. E-Commerce and Digital Strategy Development

   • Target e-commerce managers and digital transformation teams driving online retail initiatives and omnichannel integration.
   • Offer solutions to enhance online shopping experiences, logistics, and customer loyalty programs.

4. Recruitment and Workforce Solutions

   • Engage HR professionals and hiring managers in recruiting talent for store operations, customer service, or marketing roles.
   • Provide workforce optimization tools, training platforms, or staffing services tailored to retail environments.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality retail data at competitive prices, ensuring strong ROI for your marketing and outreach efforts in North America.

2. Seamless Integration
   ...

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.

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...

How high is the brand awareness of Target in the United States?When it comes to grocery store customers, brand awareness of Target is at **% in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Target in the United States?In total, **% of U.S. grocery store customers say they like Target.What is the usage share of Target in the United States?All in all, **% of grocery store customers in the United States use Target.How loyal are the customers of Target?Around **% of grocery store customers in the United States say they are likely to use Target again. Set in relation to the **% usage share of the brand, this means that **% of their customers show loyalty to the brand.What's the buzz around Target in the United States?In September 2023, about **% of U.S. grocery store customers had heard about Target in the media, on social media, or in advertising over the past three months. Have a look at our analyses of Target's brand KPIs by generation, as well as the most important life aspects of Target customers compared to non-customers of the brand.

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.

Willingness to Pay isn’t just about pricing — it’s about knowing who would buy, at what spend, and why. CMOs and consultants need fast answers to size a market or brief a launch.Panels take weeks and often miss behavior. With only your target segment and product brief, we estimate who’s concerned, who’s likely to buy, and how much they’d spend monthly — scored, sourced, and ready to activate.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F17636898%2F184b6d8052250ba87a287246aa21df07%2FScreenshot%202024-04-15%20at%209.37.34%20AM.png?generation=1713155898550914&alt=media" alt=""> This dataset is designed for learning customer segmentation concepts, such as market basket analysis. It includes basic customer data such as Customer ID, age, gender, annual income, and spending score, which is assigned based on customer behavior and purchasing data. The goal is to help a supermarket mall owner understand their customers better, identify target customers who are likely to converge, and provide insights to the marketing team for strategic planning.

How high is the brand awareness of Target in the United States?When it comes to consumer electronics online shop users, brand awareness of Target is at *** in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Target in the United States?In total, *** of U.S. consumer electronics online shop users say they like Target. However, in actuality, among the *** of U.S. respondents who know Target, *** of people like the brand.What is the usage share of Target in the United States?All in all, *** of consumer electronics online shop users in the United States use Target. That means, of the *** who know the brand, *** use them.How loyal are the customers of Target?Around *** of consumer electronics online shop users in the United States say they are likely to use Target again. Set in relation to the *** usage share of the brand, this means that *** of their customers show loyalty to the brand.What's the buzz around Target in the United States?In July 2022, about *** of U.S. consumer electronics online shop users had heard about Target in the media, on social media, or in advertising over the past three months. Of the *** who know the brand, that's ***, meaning at the time of the survey there's some buzz around Target in the United States.If you want to compare brands, do deep-dives by survey items of your choice, filter by total online population or users of a certain brand, or drill down on your very own hand-tailored target groups, our Consumer Insights Brand KPI survey has you covered.

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

How high is the brand awareness of Stop & Shop in the United States?When it comes to grocery store customers, brand awareness of Stop & Shop is at *** in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is Stop & Shop in the United States?In total, ** of U.S. grocery store customers say they like Stop & Shop. However, in actuality, among the *** of U.S. respondents who know Stop & Shop, *** of people like the brand.What is the usage share of Stop & Shop in the United States?All in all, ** of grocery store customers in the United States use Stop & Shop. That means, of the *** who know the brand, *** use them.How loyal are the customers of Stop & Shop?Around ** of grocery store customers in the United States say they are likely to use Stop & Shop again. Set in relation to the ** usage share of the brand, this means that *** of their customers show loyalty to the brand.What's the buzz around Stop & Shop in the United States?In August 2022, about ** of U.S. grocery store customers had heard about Stop & Shop in the media, on social media, or in advertising over the past three months. Of the *** who know the brand, that's ***, meaning at the time of the survey there's little buzz around Stop & Shop in the United States.If you want to compare brands, do deep-dives by survey items of your choice, filter by total online population or users of a certain brand, or drill down on your very own hand-tailored target groups, our Consumer Insights Brand KPI survey has you covered.

Customer segmentation is the process of dividing a large group of customers into smaller, more manageable and homogeneous groups based on similar characteristics or behaviors. By doing so, businesses can better understand their customers' needs, preferences, and behaviors, allowing them to tailor their marketing strategies and products to meet the specific needs of each segment. Customer segmentation helps businesses identify the most valuable customers, target them effectively, and provide personalized experiences, leading to improved customer satisfaction and loyalty.

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

Please Note : This dataset was acquired from the Analytics Vidhya hackathon.

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.

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.

Demographic distribution of the target population and the study sample.

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