The average household in the United States used about 13.1 different sources to get their entertainment as of October 2024. Households with kids were most likely to use more sources, with 16.9 sources averaged per such home.

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.

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index.

The CE program is comprised of two separate components (each with its own survey questionnaire and independent sample), the Diary Survey and the quarterly Interview Survey (ICPSR 36237). This data collection contains the Diary Survey component, which was designed to obtain data on frequently purchased smaller items, including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. Each consumer unit (CU) recorded its expenditures in a diary for two consecutive 1-week periods. Although the diary was designed to collect information on expenditures that could not be easily recalled over time, respondents were asked to report all expenses (except overnight travel) that the CU incurred during the survey week.

The 2013 Diary Survey release contains five sets of data files (FMLD, MEMD, EXPD, DTBD, DTID), and one processing file (DSTUB). The FMLD, MEMD, EXPD, DTBD, and DTID files are organized by the quarter of the calendar year in which the data were collected. There are four quarterly datasets for each of these files.

The FMLD files contain CU characteristics, income, and summary level expenditures; the MEMD files contain member characteristics and income data; the EXPD files contain detailed weekly expenditures at the Universal Classification Code (UCC) level; the DTBD files contain the CU's reported annual income values or the mean of the five imputed income values in the multiple imputation method; and the DTID files contain the five imputed income values. Please note that the summary level expenditure and income information on the FMLD files permit the data user to link consumer spending, by general expenditure category, and household characteristics and demographics on one set of files.

The DSTUB file provides the aggregation scheme used in the published consumer expenditure tables. The DSTUB file is further explained in Section III.F.6. 'Processing Files' of the Diary Survey Users' Guide. A second documentation guide, the 'Users' Guide to Income Imputation,' includes information on how to appropriately use the imputed income data.

Demographic and family characteristics data include age, sex, race, marital status, and CU relationships for each CU member. Income information was also collected, such as wage, salary, unemployment compensation, child support, and alimony, as well as information on the employment of each CU member age 14 and over.

The unpublished integrated CE data tables produced by the BLS are available to download through NADAC (click on 'Other' in the Dataset(s) section). The tables show average and percentile expenditures for detailed items, as well as the standard error and coefficient of variation (CV) for each spending estimate. The BLS unpublished integrated CE data tables are provided as an easy-to-use tool for obtaining spending estimates. However, users are cautioned to read the BLS explanatory letter accompanying the tables. The letter explains that estimates of average expenditures on detailed spending items (such as leisure and art-related categories) may be unreliable due to so few reports of expenditures for those items.

Based on market research, the source divided U.S. Generation Z consumers (born between January 1, 1997 and December 31, 2007) into five segments based on their behavior and attitude. The largest segment, making up 35 percent of the total, were the so-called Stress Strivers, defined by the source as "high achievers, driven by a fear of not being good enough." Authentic Activists and Secluded Perfectionists followed, with 22 percent and 20 percent, respectively.

In late 2020, Hispanic and African American consumers each accounted for nearly a tenth all Amazon retail spending in the United States. Meanwhile, white consumers led the list, representing over 70 percent of the e-commerce platform's consumer spending share.

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.

Success.ai’s Consumer Behavior Data for Consumer Goods & Electronics Industry Leaders in Asia, the US, and Europe offers a robust dataset designed to empower businesses with actionable insights into global consumer trends and professional profiles. Covering executives, product managers, marketers, and other professionals in the consumer goods and electronics sectors, this dataset includes verified contact information, professional histories, and geographic business data.

With access to over 700 million verified global profiles and firmographic data from leading companies, Success.ai ensures your outreach, market analysis, and strategic planning efforts are powered by accurate, continuously updated, and GDPR-compliant data. Backed by our Best Price Guarantee, this solution is ideal for businesses aiming to navigate and lead in these fast-paced industries.

Why Choose Success.ai’s Consumer Behavior Data?

1. Verified Contact Data for Precision Engagement

   • Access verified email addresses, phone numbers, and LinkedIn profiles of professionals in the consumer goods and electronics industries.
   • AI-driven validation ensures 99% accuracy, optimizing communication efficiency and minimizing data gaps.

2. Comprehensive Global Coverage

   • Includes profiles from key markets in Asia, the US, and Europe, covering regions such as China, India, Germany, and the United States.
   • Gain insights into region-specific consumer trends, product preferences, and purchasing behaviors.

3. Continuously Updated Datasets

   • Real-time updates capture career progressions, company expansions, market shifts, and consumer trend data.
   • Stay aligned with evolving market dynamics and seize emerging opportunities effectively.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible use and legal compliance for all data-driven campaigns.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with industry leaders, marketers, and decision-makers in consumer goods and electronics industries worldwide.
• Consumer Trend Insights: Gain detailed insights into product preferences, purchasing patterns, and demographic influences.
• Business Locations: Access geographic data to identify regional markets, operational hubs, and emerging consumer bases.
• Professional Histories: Understand career trajectories, skills, and expertise of professionals driving innovation and strategy.

Key Features of the Dataset:

1. Decision-Maker Profiles in Consumer Goods and Electronics

   • Identify and engage with professionals responsible for product development, marketing strategy, and supply chain optimization.
   • Target individuals making decisions on consumer engagement, distribution, and market entry strategies.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (consumer electronics, FMCG, luxury goods), geographic location, or job function.
   • Tailor campaigns to align with specific industry trends, market demands, and regional preferences.

3. Consumer Trend Data and Insights

   • Access data on regional product preferences, spending behaviors, and purchasing influences across key global markets.
   • Leverage these insights to shape product development, marketing campaigns, and customer engagement strategies.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data allow for personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing and Demand Generation

   • Design campaigns tailored to consumer preferences, regional trends, and target demographics in the consumer goods and electronics industries.
   • Leverage verified contact data for multi-channel outreach, including email, social media, and direct marketing.

2. Market Research and Competitive Analysis

   • Analyze global consumer trends, spending patterns, and product preferences to refine your product portfolio and market positioning.
   • Benchmark against competitors to identify gaps, emerging needs, and growth opportunities in target regions.

3. Sales and Partnership Development

   • Build relationships with key decision-makers at companies specializing in consumer goods or electronics manufacturing and distribution.
   • Present innovative solutions, supply chain partnerships, or co-marketing opportunities to grow your market share.

4. Product Development and Innovation

   • Utilize consumer trend insights to inform product design, pricing strategies, and feature prioritization.
   • Develop offerings that align with regional preferences and purchasing behaviors to maximize market impact.

Why Choose Success.ai?

1. Best Price Guarantee
   • Access premium-quality consumer behavior data at competitive prices, ensuring maximum ROI for your outreach, research, and ma...

Abstract

The Consumer Expenditure Survey (CE) program provides a continuous and comprehensive flow of data on the buying habits of American consumers. These data are used widely in economic research and analysis, and in support of revisions of the Consumer Price Index. To meet the needs of users, the Bureau of Labor Statistics (BLS) produces population estimates for consumer units (CUs) of average expenditures in news releases, reports, issues, and articles in the Monthly Labor Review. Tabulated CE data are also available on the Internet and by facsimile transmission (See Section XVI. APPENDIX 5). The microdata are available on CD-ROMs. These microdata files present detailed expenditure and income data from the Interview component of the CE for 2008 and the first quarter of 2009. The Interview survey collects data on up to 95 percent of total household expenditures. In addition to the FMLY, MEMB, MTAB, and ITAB_IMPUTE files, the microdata include files created directly from the expenditure sections of the Interview survey (EXPN files). The EXPN files contain expenditure data and ancillary descriptive information, often not available on the FMLY or MTAB files, in a format similar to the Interview questionnaire. In addition to the extra information available on the EXPN files, users can identify distinct spending categories easily and reduce processing time due to the organization of the files by type of expenditure. Estimates of average expenditures in 2008 from the Interview Survey, integrated with data from the Diary Survey, will be published in the report Consumer Expenditures in 2008 (due out in 2010). A list of recent publications containing data from the CE appears at the end of this documentation. The microdata files are in the public domain and, with appropriate credit, may be reproduced without permission. A suggested citation is: "U.S. Department of Labor, Bureau of Labor Statistics, Consumer Expenditure Survey, Interview Survey, 2008."

Analysis unit

Consumer Units

Kind of data

Sample survey data [ssd]

Sampling procedure

Samples for the CE are national probability samples of households designed to be representative of the total U.S. civilian population. Eligible population includes all civilian non-institutional persons. The first step in sampling is the selection of primary sampling units (PSUs), which consist of counties (or parts thereof) or groups of counties. The set of sample PSUs used for the 2008 and 2009 samples is composed of 91 areas. The design classifies the PSUs into four categories: 21 "A" certainty PSUs are Metropolitan Statistical Areas (MSA's) with a population greater than 1.5 million. 38 "X" PSUs, are medium-sized MSA's. 16 "Y" PSUs are nonmetropolitan areas that are included in the CPI. 16 "Z" PSUs are nonmetropolitan areas where only the urban population data will be included in the CPI. The sampling frame (that is, the list from which housing units were chosen) for the 2008 survey is generated from the 2000 Census of Population 100-percent-detail file. The sampling frame is augmented by new construction permits and by techniques used to eliminate recognized deficiencies in census coverage. All Enumeration Districts (EDs) from the Census that fail to meet the criterion for good addresses for new construction, and all EDs in nonpermit-issuing areas are grouped into the area segment frame. Interviewers are then assigned to list these areas before a sample is drawn. To the extent possible, an unclustered sample of units is selected within each PSU. This lack of clustering is desirable because the sample size of the Diary Survey is small relative to other surveys, while the intraclass correlations for expenditure characteristics are relatively large. This suggests that any clustering of the sample units could result in an unacceptable increase in the within-PSU variance and, as a result, the total variance. The Interview Survey is a panel rotation survey. Each panel is interviewed for five consecutive quarters and then dropped from the survey. As one panel leaves the survey, a new panel is introduced. Approximately 20 percent of the addresses are new to the survey each month.

Mode of data collection

Computer Assisted Personal Interview [capi]

This statistic shows the results of a survey in which respondents were asked if they have bought free-from foods or if they might buy them in future in the United Kingdom (UK) in 2015. A majority of both groups have no food intolerance or allergy sufferers in the household at 56 and 71 percent respectively, followed by those who are sufferers.

Envestnet®| Yodlee®'s Online Purchase Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

GapMaps Segmentation Data from Applied Geographic Solutions (AGS) consists of 68 segments across the US and Canada. Panorama is paired with the industry leading GfK MRI survey and AGS Demographics to provide the essential link between neighborhood demographics and consumer preferences and attitudes.

Introduction

Starbucks Statistics: Starbucks Corporation is an American multinational chain of roasteries and coffee houses based in Seattle, Washington. Founded in 1971, the brand has rapidly grown to become the world's largest coffeehouse chain. Starbucks offers tea, baked goods, sandwiches, and more. Due to its uniqueness, Starbucks has become one of the leading coffee brands globally, with high customer retention and satisfaction rates. Let's take a look at some recent Starbucks statistics to learn more about this coffee brand.

The chart provides an insightful analysis of the estimated sales amounts for Consumer Electronics stores across various platforms. Custom Cart stands out, generating a significant portion of sales with an estimated amount of $1.25T, which is 95.79% of the total sales in this category. Following closely, Shopify accounts for $29.03B in sales, making up 2.22% of the total. WooCommerce also shows notable performance, contributing $9.15B to the total sales, representing 0.70%. This data highlights the sales dynamics and the varying impact of each platform on the Consumer Electronics market.

In 2022, approximately 44 percent of consumers around the world were considered "purpose-driven consumers", which is an increase compared to two years earlier. Purpose-driven shoppers choose brands and products based on how well they line up with their own values. They are more likely and willing to alter their shopping behavior in order to live more sustainably and reduce their impact on the environment. In contrast, the share of value-driven consumers, who are more focused on product value and convenience, has decreased since 2020.

At Accurate Append, we specialize in providing industry-leading US Segmentation Data solutions that empower businesses to connect with the right consumers.

Whether you’re aiming to enhance your marketing campaigns, refine your lead generation efforts, or enrich your customer data, our comprehensive dataset enables you to target the ideal audience based on demographics, wealth insights, donation history, and much more.

With a high match rate and flexible delivery options via batch processing or API integration, our data solutions are built to optimize your outreach, ensuring you achieve measurable results with greater precision.

Why Choose Accurate Append for Audience Targeting? Accurate Append stands out for its quality data, innovative delivery options, and dedicated support, ensuring that businesses can achieve the highest ROI from their marketing campaigns. Our data solutions are designed to help you:

Increase Engagement: Reach the consumers most likely to convert by targeting based on wealth, demographics, and past donation behavior. Boost Campaign Efficiency: Reduce wasted marketing efforts by ensuring your messaging reaches those with the highest potential to respond.

Refine Customer Retargeting: Use enriched data to better understand and re-engage existing customers, increasing lifetime value and retention. Enhance Lead Generation: Generate higher-quality leads with insights into consumers’ demographics and purchasing behaviors.

Expand Sales Opportunities: Reach new segments of your audience with detailed data that can inform upselling, cross-selling, and new product launches.

Key Features of Our Audience Targeting Data Accurate Append’s US audience targeting dataset includes a wide range of attributes, allowing for detailed segmentation and custom targeting that aligns with your specific needs:

Demographic Data: Including age, gender, education level, marital status, homeownership, and more, enabling you to tailor campaigns to match your desired consumer profile.

Wealth Insights: Identify high-net-worth individuals to direct your premium offerings and luxury services toward the right audience. Data on estimated income, assets, and property values help you focus on affluent segments.

Donation History: Target charitable givers and donors with campaigns that resonate. Understanding an individual’s donation history can help you align your messaging with their values and interests.

Geographic Data: Access granular location data to enhance your local or regional campaigns, whether you’re targeting customers by state, city, or neighborhood.

Psychographic Data: Leverage behavioral and lifestyle data to further segment your audience based on interests, activities, and purchase patterns.

Flexible Delivery Options: Batch Processing and API Integration

We understand that every business has unique workflows and requirements. That’s why Accurate Append offers two flexible delivery methods to ensure seamless integration with your existing systems:

Batch Data Delivery: Ideal for businesses needing large-scale data appending or updating. Send us your file, and we’ll return it enriched with the latest audience targeting data.

Real-Time API Access: For those looking for instant data, our API allows you to connect directly with Accurate Append’s database. This is perfect for applications requiring real-time updates, CRM integration, or instant lead qualification.

Use Cases of Audience Targeting Data Accurate Append’s data solutions can be applied across a variety of use cases, enhancing the performance of your marketing efforts and business strategies:

Email Marketing Campaigns: Improve open rates and engagement by sending targeted emails to recipients based on their wealth, demographics, and donation history.

Telemarketing: Enhance the effectiveness of your outbound calling campaigns by focusing on high-quality leads, increasing the likelihood of conversions.

Customer Data Enrichment: Augment your existing CRM records with additional demographic, wealth, and behavioral data to create more complete customer profiles.

Lead Generation: Generate new leads by identifying key audience segments most likely to respond to your offers. Whether you’re selling products or services, our data can help you find the right buyers.

Customer Retargeting: Re-engage past customers or those who have shown interest in your brand. By using enriched data, you can tailor your messaging to their specific interests, driving repeat business.

Accurate Append’s audience targeting data is your key to reaching the right consumers and driving successful marketing campaigns. Whether you’re targeting high-net-worth individuals, seeking to enhance your CRM data, or running telemarketing and email campaigns, our robust dataset and flexible delivery options will ensure you get the most out of your marketing efforts.

For businesses looking to achieve accurate data and amazin...

Explore the statistics for Consumer Electronics eCommerce in 2025, including store count by region and platform, estimated sales amount by platform and region, products sold by platform and region, and total app spend by platform and region. Gain insights into regional preferences, market penetration, consumer trends, and technological investments within the Consumer Electronics sector. Discover the leading regions and platforms, as well as the dynamics of sales and product volumes. Stay informed about the evolving landscape of Consumer Electronics online stores for a comprehensive understanding of the market.

This chart provides a comprehensive view of the total app spend in the Consumer Electronics sector, segmented by region. It illustrates how much stores in different regions are investing in apps and software to enhance their business operations and customer services. In United States, the total app spend is significant, with stores investing $33.38M, which accounts for 52.04% of the overall app expenditure in the Consumer Electronics. United Kingdom follows, with a total spend of $7.11M, making up 11.08% of the category's total. Canada also shows considerable investment in technology, with a spend of $5.12M, representing 7.99% of the total. These figures not only reveal the financial commitment of stores in each region towards technology but also indicate regional trends and priorities in the Consumer Electronics market.

WorldView segments has been developed to segment the global population into 10 consistent consumer types by analysing data including: demographics, value orientation, attitudes, consumer behaviour and consumption volume. The segments have been identified and validated in detailed international primary reserach. They enable the identification of customer target groups and the segmentation of markets consistently across multiple countries. The data is built using a combination of WorldView Demographics enhanced with consumer survey panel data across a number of regions where available.

The Consumer Expenditure Survey (CE) program consists of two surveys: the quarterly Interview survey and the annual Diary survey. Combined, these two surveys provide information on the buying habits of American consumers, including data on their expenditures, income, and consumer unit (families and single consumers) characteristics. The survey data are collected for the U.S. Bureau of Labor Statistics (BLS) by the U.S. Census Bureau. The CE collects all on all spending components including food, housing, apparel and services, transportation, entertainment, and out-of-pocket health care costs. The CE tables are an easy-to-use tool for obtaining arts-related spending estimates. They feature several arts-related spending categories, including the following items: Spending on Admissions Plays, theater, opera, and concerts Movies, parks, and museums Spending on Reading Newspapers and magazines Books Digital book readers Spending on Other Arts-Related Items Musical instruments Photographic equipment Audio-visual equipment Toys, games, arts and crafts The CE is important because it is the only Federal survey to provide information on the complete range of consumers' expenditures and incomes, as well as the characteristics of those consumers. It is used by economic policymakers examining the impact of policy changes on economic groups, by the Census Bureau as the source of thresholds for the Supplemental Poverty Measure, by businesses and academic researchers studying consumers' spending habits and trends, by other Federal agencies, and, perhaps most importantly, to regularly revise the Consumer Price Index market basket of goods and services and their relative importance. The most recent data tables are for 2020 and include: 1) Detailed tables with the most granular level of expenditure data available, along with variances and percent reporting for each expenditure item, for all consumer units (listed as "Other" in the Download menu); and 2) Tables with calendar year aggregate shares by demographic characteristics that provide annual aggregate expenditures and shares across demographic groups (listed as "Excel" in the Download menu). Also, see Featured CE Tables and Economic News Releases sections on the CE home page for current data tables and news release. The 1980 through 2020 CE public-use microdata, including Interview Survey data, Diary Survey data, and paradata (information about the data collection process), are available on the CE website.

Delving into the Consumer Electronics sector, our data presents a revealing look at store distribution by region, highlighting regional preferences and market penetration in this niche. United States leads with 35.24K stores, which is 33.89% of the total. United Kingdom follows, contributing 10.18K stores, which is 9.79% of the total. India comes third, with 6.33K stores, making up 6.08% of the total.