Envestnet®| Yodlee®'s Retail Transaction 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

CE Scanner US provides financial services investors with point-of-sale transaction data. Proprietary M&A attribution and volume equivalency offer rollup views to ticker and brand level with comparative detailed category/subcategory views into retail sales, volumes, distribution, and trends.

The awareness among worldwide consumers about companies selling their personal data to third parties has grown in recent years. As of July 2022, three in four consumers in selected countries worldwide said they knew that companies sell personal information. In comparison, in 2020, this share was a little over 60 percent.

All available on the tool. 24 hours a day/7 days a week/ 365 days a year.

NATIONAL USA DATA: 251 million individuals, 170 million households, over 1000 targeting variables and filters available including income, children, home type, investments, vehicle, life stage, and more. Full postal address on the full file. Email/phone/IP.

app.trakdatainc.com

Retail Sales of Consumer Goods: Year to Date: Zhejiang data was reported at 929.300 RMB bn in Mar 2025. This records an increase from the previous number of 603.900 RMB bn for Feb 2025. Retail Sales of Consumer Goods: Year to Date: Zhejiang data is updated monthly, averaging 660.297 RMB bn from Jan 2003 (Median) to Mar 2025, with 233 observations. The data reached an all-time high of 3,390.000 RMB bn in Dec 2024 and a record low of 26.993 RMB bn in Jan 2003. Retail Sales of Consumer Goods: Year to Date: Zhejiang data remains active status in CEIC and is reported by Zhejiang Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Retail Sales of Consumer Goods: Provincial and Municipal Statistical Bureau.

According to Cognitive Market Research, the global Data Broker Services market size is USD 268154.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 8.00% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD 107261.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.2% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD 80446.26 million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD 61675.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.0% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD 13407.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.4% from 2024 to 2031.
Middle East and Africa held the major market ofaround 2% of the global revenue with a market size of USD 5363.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.7% from 2024 to 2031.
The Subscription Paid held the highest Data Broker Services market revenue share in 2024.

Market Dynamics of Data Broker Services Market

Key Drivers of Data Broker Services Market

Increasing Demand for Personalized Marketing Solutions to boost the demand globally

The Data Broker Services Market is being driven by the increasing demand for personalized marketing solutions. Companies across various industries are leveraging data broker services to access valuable consumer insights and enhance their marketing strategies. Data brokers offer a wide range of data sets, including demographic, behavioral, and transactional data, which can be used to create targeted marketing campaigns. By utilizing data broker services, companies can tailor their marketing messages to specific consumer segments, leading to higher engagement and conversion rates. This trend is expected to continue driving the growth of the Data Broker Services Market as businesses increasingly prioritize personalized marketing approaches to remain competitive in the digital age.

Growing Focus on Data Monetization to Propel Market Growth

Another key driver of the Data Broker Services Market is the growing focus on data monetization. Organizations are realizing the value of their data assets and are looking for ways to monetize them. Data broker services enable companies to sell their data to third parties, such as marketers, researchers, and other businesses, generating additional revenue streams. This trend is particularly prevalent in industries with large amounts of consumer data, such as retail, finance, and healthcare. By monetizing their data, companies can unlock new revenue opportunities and offset the costs associated with data collection and management. As the demand for data-driven insights continues to grow, the Data Broker Services Market is expected to expand, driven by the increasing number of organizations looking to capitalize on their data assets.

Restraint Factors Of Data Broker Services Market

Regulatory Challenges and Data Privacy Concerns to Limit the Sales

One of the key restraints in the Data Broker Services Market is the increasing regulatory challenges and data privacy concerns. With the implementation of regulations such as the GDPR in Europe and the CCPA in California, data brokers are facing stricter requirements for data collection, processing, and sharing. Compliance with these regulations requires significant resources and can limit the ability of data brokers to collect and monetize data. Additionally, concerns about data privacy and security among consumers are leading to greater scrutiny of data broker practices, further complicating the operating environment for these companies. As regulatory pressures continue to increase, data brokers may face challenges in expanding their operations and maintaining profitability.

Opportunity for the Data Broker Services Market

The Data Broker Service Market is poised to benefit significantly from the integration of blockchain technology.

By leveraging blockchain's decentralized and immutable nature, data brokers can ensure tamper-proof data exchange, enable secure data sharing, and provide auditable trails. This can increase trust and confidence in data exchange, driving growth in the data broker...

Consumer-based survey responders of the brands to which they are most loyal. From acne products to baby wipes, coffee to pet food, this file has the most responsive data from consumers who respond to Direct to Consumer (DTC) offers. Compiled using a variety of surveying techniques including point of purchase surveying as part of the check out process. 30-day hotline available to ensure the freshest information possible.

Fields Include but are not limited to: Product Categories - Acne Products - Tooth Whiteners - Allergy/Cold Remedies - Baby Wipes - Dog Treats - Imported Beer - Energy Bars - Meat Alternatives -Product Brands, such as: - L'Oreal Paris - Crest - Pepcid - Tylenol - Pampers - Purina - Meow Mix - Budweiser - Keurig - Beyond Meat - Recency of purchase - Email

Competitive Pricing - Available for transactional orders. Yearly data licenses available for unlimited use cases, including marketing and analytics.

Track share of shelf, predict revenue surprises, and drill down into brand and category level performance by household demography across thousands of brands and hundreds of manufacturers. Scanner Consumer Packaged Goods (CPG) data is sourced from thousands of retail stores and millions of underlying US households across grocery and drugstore chains. Available exclusively to investors.

Retail Sales of Consumer Goods: Shanxi data was reported at 818.050 RMB bn in 2024. This records an increase from the previous number of 798.180 RMB bn for 2023. Retail Sales of Consumer Goods: Shanxi data is updated yearly, averaging 306.360 RMB bn from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 818.050 RMB bn in 2024 and a record low of 37.595 RMB bn in 1995. Retail Sales of Consumer Goods: Shanxi data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Retail Sales of Consumer Goods: Province.

Retail Sales in the United States increased 0.60 percent in June of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

China Retail Sales of Consumer Goods: YoY: Year to Date: Above Designated Size Enterprise data was reported at 5.700 % in Mar 2025. This records an increase from the previous number of 4.300 % for Feb 2025. China Retail Sales of Consumer Goods: YoY: Year to Date: Above Designated Size Enterprise data is updated monthly, averaging 7.800 % from Feb 2011 (Median) to Mar 2025, with 156 observations. The data reached an all-time high of 43.900 % in Feb 2021 and a record low of -23.400 % in Feb 2020. China Retail Sales of Consumer Goods: YoY: Year to Date: Above Designated Size Enterprise data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.HA: Retail Sales of Consumer Goods: Above Designated Size Enterprise: by Commodity . [COVID-19-IMPACT]

This spreadsheet contains information reported by over 200 investor-owned utilities to the Federal Energy Regulatory Commission in the annual filing FERC Form 1 for the years 1994-2019. It contains 1) annual capital costs for new transmission, distribution, and administrative infrastructure; 2) annual operation and maintenance costs for transmission, distribution, and utility business administration; 3) total annual MWh sales and sales by customer class; 4) annual peak demand in MW; and 5) total customer count and the number of customers by class. Annual spending on new capital infrastructure is read from pages 204 to 207 of FERC Form 1, titled Electric Plant in Service. Annual transmission capital additions are recorded from Line 58, Column C - Total Transmission Plant Additions. Likewise, annual distribution capital additions are recorded from Line 75, Column C - Total Distribution Plant Additions. Administrative capital additions are recorded from Line 5, Column C - Total Intangible Plant Additions, and Line 99, Column C - Total General Plant Additions. Operation and maintenance costs associated with transmission, distribution, and utility administration are read from pages 320 to 323 of FERC Form 1, titled Electric Operation and Maintenance Expenses. Annual transmission operation and maintenance are recorded from Line 99, Column B - Total Transmission Operation Expenses for Current Year, and Line 111, Column B - Total Transmission Maintenance Expenses for Current Year. Likewise, annual distribution operation and maintenance costs are recorded from Line 144, Column B - Total Distribution Operation Expenses, and Line 155, Column B - Total Distribution Maintenance Expenses. Administrative operation and maintenance costs are recorded from: Line 164, Column B - Total Customers Accounts Expenses; Line 171, Column B - Total Customer Service and Information Expenses; Line 178, Column B - Total Sales Expenses; and Line 197, Column B - Total Administrative and General Expenses. The annual peak demand in MW over the year is read from page 401, titled Monthly Peaks and Output. The monthly peak demand is listed in Lines 29 to 40, Column D. The maximum of these monthly reports during each year is taken as the annual peak demand in MW. The annual energy sales and customer count data come from page 300, Electric Operating Revenues. The values are provided in Line 2 - Residential Sales, Line 4 - Commercial Sales, Line 5 - Industrial Sales, and Line 10 - Total Sales to Ultimate Consumers. More information about the database is available in an associated report published by the University of Texas at Austin Energy Institute: https://live-energy-institute.pantheonsite.io/sites/default/files/UTAustin_FCe_TDA_2016.pdf Also see an associated paper published in the journal Energy Policy: Fares, Robert L., and Carey W. King. "Trends in transmission, distribution, and administration costs for US investor-owned electric utilities." Energy Policy 105 (2017): 354-362. https://doi.org/10.1016/j.enpol.2017.02.036 All data come from the Federal Energy Regulatory Commission FERC Form 1 Database available in Microsoft Visual FoxPro Format: https://www.ferc.gov/docs-filing/forms/form-1/data.asp

China Retail Sales of Consumer Goods: YoY: Above Designated Size Enterprise: Catering data was reported at 6.800 % in Mar 2025. This records an increase from the previous number of 1.200 % for Dec 2024. China Retail Sales of Consumer Goods: YoY: Above Designated Size Enterprise: Catering data is updated monthly, averaging 6.100 % from Jan 2011 (Median) to Mar 2025, with 143 observations. The data reached an all-time high of 115.200 % in Mar 2021 and a record low of -46.700 % in Mar 2020. China Retail Sales of Consumer Goods: YoY: Above Designated Size Enterprise: Catering data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HA: Retail Sales of Consumer Goods: Above Designated Size Enterprise: by Commodity .

High-Value Consumer Contact Data for Strategic Market Penetration in New York State
Subject: Exclusive Opportunity: Acquisition of 13 Million New York State Consumer Contacts for Strategic Market Expansion (Including African Immigrants from the Diaspora) Now with Limited-Time Promotional Pricing! This proposal highlights a compelling and time-sensitive opportunity for companies to acquire a comprehensive database of consumer contact information for over 13 million residents of New York State, including 4 million within New York City. More importantly, includes Africans that have migrated from the continent to New York. This highvolume, cost-effective acquisition, now coupled with a significant promotional discount, presents an unparalleled chance to significantly deepen market penetration and capitalize on the immense potential of the financial capital of the world. The Opportunity: We are offering access to a meticulously compiled database that includes a combination of names, addresses, genders, dates of birth, with a high percentage of telephone numbers and/or email addresses. This data is subject to constant real-time changes based on individual consumer lifestyle activity, ensuring its ongoing relevance and value. Why New York State and New York City? • Financial Capital of the World: New York City's unparalleled economic influence and diverse population present a prime target for a wide range of services and products, particularly within the financial and business sectors. • Massive Untapped Potential: With over 13 million residents in New York State, this database offers a substantial pool of potential customers for various industries. • Strategic Expansion: For a global telecommunications, this data provides a direct avenue to explore and establish a strong foothold in a key Western market, diversifying your portfolio and opening new revenue streams. Key Advantages of Our Offering: • Unbeatable Promotional Price: We are offering this extensive database at a highly competitive rate of $0.01 (one cent) per contact. For a limited time, we are providing an exclusive offer of 50% off the purchase of the entire New York State database OR 50% off the purchase of the entire New York City listings. This is significantly below the industry standard of approximately $0.10 per contact, representing an exceptional return on investment. • Immediate Market Access: Gain instant access to a vast consumer base, enabling rapid deployment of targeted marketing campaigns and business development initiatives. • Resale Potential: One could leverage this acquisition not only for its own marketing efforts but also explore opportunities to resell portions of the data at higher data broker rates, generating additional revenue. • Versatile Application: This comprehensive list is invaluable for a wide array of industries, including but not limited to: o Real Estate: Identifying potential buyers, sellers, and investors. o List Buyers: For further segmentation and resale to specialized niches. o Developers: Pinpointing demographics for new projects. o Financial Services: Reaching potential clients for banking, investment, and insurance products. o NGOs: Engaging with communities for outreach and fundraising. o Marketing Agencies: Crafting highly effective and localized campaigns. o Health Care Providers: Connecting with patients and promoting services. o Debt Collectors: Locating individuals for recovery efforts. o And many more: The possibilities are extensive due to the broad nature of the data. • Future Expansion: Should there be serious interest in Ghana regarding the sales of New York Consumer Data, we are prepared to offer similar high-volume consumer contact databases for other major US states, including California, Florida, Texas, and even the entire United States of America's nearly 340 million consumers listings, at the same advantageous pricing structure. Data Details: • Total Contacts: Over 13,000,000 New York State residents. • New York City Contacts: Over 4,000,000 residents. • Included Data Points: Names, addresses, genders, dates of birth, with a high percentage including telephone numbers and/or email addresses. Pricing Structure (with Limited-Time Offer): • Per Contact Cost: $0.01 USD • Option 1: Purchase Entire New York State Database (13M+ Contacts) o Original Price: $130,000 USD o Promotional Price (50% Off): $65,000 USD • Option 2: Purchase Entire New York City Listings (4M+ Contacts) o Original Price: $40,000 USD o Promotional Price (50% Off): $20,000 USD

Ethical and Legal Considerations We understand that the acquisition and utilization of consumer data require strict adherence to privacy regulations and ethical guidelines. We operate with the understanding of evolving data privacy landscapes, particularly in the United States. While the New York Privacy Act (NYPA) and other comprehensive privacy laws are still under legislative consideration in New York (with th...

This dataset gathers 19 files containing all the data presented in the scientific article entitled Consumer behavior at sale point and consumption according to strawberry quality: how to use those data to evaluate food waste?

The global consumer data storage devices market is projected to experience significant growth over the forecast period, 2025-2033. The market is anticipated to reach a value of XX million by 2033, expanding at a CAGR of XX% during the forecast period. The growth can be attributed to factors such as the increasing adoption of digital devices, the proliferation of data-intensive applications, and the growing need for data storage security. The market is segmented based on type and application. By type, the market is divided into hard disk drives (HDDs) and solid-state drives (SSDs). HDDs are traditional storage devices that use spinning disks to store data, while SSDs are newer devices that use flash memory to store data. SSDs are faster and more durable than HDDs, but they are also more expensive. The market is also segmented based on application, with online sales and offline sales being the two major segments. The online sales segment is expected to grow at a faster rate than the offline sales segment due to the increasing popularity of e-commerce. The major players in the consumer data storage devices market include IBM, Dell, HPE, Huawei, Western Digital, Seagate Technology, Lenovo, Toshiba, NetApp, Pure Storage, Kingston Technology, ADATA, Micron Technology, CMC Magnetics (Verbatim), RITEK Group, and Sony.

From our comprehensive US Data Lake, we proudly present 23M+ high-quality US decision-makers and influencers.

Take your ABM strategy to the next level, build a strong pipeline and close deals by laser targeting key decision-makers and influencers based on their department, job functions, job responsibilities, interest areas and expertise, then utilise essential prospect information, including verified work email addresses and business phone and social links.

Our data is sourced directly from executives, businesses, official sources and registries, standardised, de-duped, and verified, and then processed through vigorous compliance procedures for GDPR/PECR on a legitimate interest basis and RTBI etc. This results in a highly accurate single source of quality and compliant B2B data.

It is with our B2B Live Data Lake that we can enrich your CRM data, supply new prospect data, verify leads, and provide you with a custom dataset tailored to your target audience specifications. We also cater for big data licensing to software providers and agencies that intend to supply our data to their customers and use it in their software solutions.

and much more

Why Choose 1 Stop Data?

• We offer our clients a unique, single source of quality and compliant data.
• We don't rely on 3rd party vendors.
• We utilise extensive verification processes to help ensure phone numbers and emails are accurate and connect to the right person.
• We are budget-friendly and our team are highly experienced.

Products and Services:

The oscar4.io web platform for self-service data on demand Bulk data feeds Data hygiene, standardisation, cleansing and enrichment Know Your Business (KYB)

Keywords:

B2B,Prospect Data,Validated Work Emails,Personal Emails,Email Enrichment,Company Data,Lead Enrichment,Data Enhancement,Account Based Marketing (ABM),Customer Data,Phone Enrichment,LinkedIn URL,Market Intelligence,Business Intelligence,Data Append,Contact Data,Lead Generation,360-Degree Customer View,Data Cleansing,Lead Data,Email and Phone Validation,Data Augmentation,Segmentation,Data Enrichment,Email Marketing,Data Intelligence,Direct Marketing,Customer Insights,Audience Targeting,Audience Generation,Mobile Phone,B2B Data Enrichment,Social Advertising,Due Diligence,B2B Advertising,Audience Insights,B2B Lead Retargeting,Contact Information,Demographic Data,Consumer Data Enrichment,People-Based Marketing,Contact Data Enrichment,Customer Data Insights,Prospecting,Sales Intelligence,Predictive Analytics,Email Address Validation,Company Data Enrichment,Audience Intelligence,Cold Outreach,Analytics,Marketing Data Enrichment,Customer Acquisition,Data Cleansing,B2C Data,People Data,Professional Information,Recruiting and HR,KYC,B2B List Validation,Lead Information,Sales Prospecting,B2B Sales,B2B Data,Lead Lists,Contact Validation,Competitive Intelligence,Customer Data Enrichment,Identity Resolution,Identity Validation,Data Science,B2C Data Enrichment,B2C,Lead Data Enrichment,Social Media Data.

Retail Sales of Consumer Goods: Year to Date: Zhejiang: Hangzhou data was reported at 142.438 RMB bn in Feb 2025. This records a decrease from the previous number of 788.382 RMB bn for Dec 2024. Retail Sales of Consumer Goods: Year to Date: Zhejiang: Hangzhou data is updated monthly, averaging 205.690 RMB bn from Dec 2001 (Median) to Feb 2025, with 201 observations. The data reached an all-time high of 788.382 RMB bn in Dec 2024 and a record low of 13.430 RMB bn in Jan 2008. Retail Sales of Consumer Goods: Year to Date: Zhejiang: Hangzhou data remains active status in CEIC and is reported by Hangzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Consumer Goods and Services – Table CN.HE: Retail Sales of Consumer Goods: Prefecture Level City: Monthly.

Our consumer data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

Our comprehensive data enrichment solution includes a variety of data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences. 1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc. 2. Demographics - Gender, Age Group, Marital Status, Language etc. 3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc 4. Persona - Consumer type, Communication preferences, Family type, etc 5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc. 6. Household - Number of Children, Number of Adults, IP Address, etc. 7. Behaviours - Brand Affinity, App Usage, Web Browsing etc. 8. Firmographics - Industry, Company, Occupation, Revenue, etc 9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc. 10. Auto - Car Make, Model, Type, Year, etc. 11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

Consumer Graph Use Cases: 360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation. Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity. Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

Here's the schema of Consumer Data: person_id first_name last_name age gender linkedin_url twitter_url facebook_url city state address zip zip4 country delivery_point_bar_code carrier_route walk_seuqence_code fips_state_code fips_country_code country_name latitude longtiude address_type metropolitan_statistical_area core_based+statistical_area census_tract census_block_group census_block primary_address pre_address streer post_address address_suffix address_secondline address_abrev census_median_home_value home_market_value property_build+year property_with_ac property_with_pool property_with_water property_with_sewer general_home_value property_fuel_type year month household_id Census_median_household_income household_size marital_status length+of_residence number_of_kids pre_school_kids single_parents working_women_in_house_hold homeowner children adults generations net_worth education_level occupation education_history credit_lines credit_card_user newly_issued_credit_card_user credit_range_new
credit_cards loan_to_value mortgage_loan2_amount mortgage_loan_type
mortgage_loan2_type mortgage_lender_code
mortgage_loan2_render_code
mortgage_lender mortgage_loan2_lender
mortgage_loan2_ratetype mortgage_rate
mortgage_loan2_rate donor investor interest buyer hobby personal_email work_email devices phone employee_title employee_department employee_job_function skills recent_job_change company_id company_name company_description technologies_used office_address office_city office_country office_state office_zip5 office_zip4 office_carrier_route office_latitude office_longitude office_cbsa_code
office_census_block_group
office_census_tract office_county_code
company_phone
company_credit_score
company_csa_code
company_dpbc
company_franchiseflag
company_facebookurl company_linkedinurl company_twitterurl
company_website company_fortune_rank
company_government_type company_headquarters_branch company_home_business
company_industry
company_num_pcs_used
company_num_employees
company_firm_individual company_msa company_msa_name
company_naics_code
company_naics_description
company_naics_code2 company_naics_description2
company_sic_code2
company_sic_code2_description
company_sic_code4 company_sic_code4_description
company_sic_code6
company_sic_code6_description
company_sic_code8
company_sic_code8_description company_parent_company
company_parent_company_location company_public_private company_subsidiary_company company_residential_business_code company_revenue_at_side_code company_revenue_range
company_revenue company_sales_volume
company_small_business company_stock_ticker company_year_founded company_minorityowned
company_female_owned_or_operated company_franchise_code company_dma company_dma_name
company_hq_address
company_hq_city company_hq_duns company_hq_state
company_hq_zip5 company_hq_zip4 co...

Consumer Good Sales: Beer data was reported at 83.892 05Aug2019-11Aug2019=100 in 11 May 2020. This records a decrease from the previous number of 86.310 05Aug2019-11Aug2019=100 for 04 May 2020. Consumer Good Sales: Beer data is updated weekly, averaging 82.050 05Aug2019-11Aug2019=100 from Aug 2019 (Median) to 11 May 2020, with 41 observations. The data reached an all-time high of 105.935 05Aug2019-11Aug2019=100 in 06 Apr 2020 and a record low of 67.252 05Aug2019-11Aug2019=100 in 06 Jan 2020. Consumer Good Sales: Beer data remains active status in CEIC and is reported by Federal Statistics Office Germany. The data is categorized under Global Database’s Germany – Table DE.C004: Consumer Good Sales.