In 2023, the leading market research company in terms of global research revenue was Gartner, generating approximately *** billion U.S. dollars. In the same year, American company IQVIA accrued roughly *** billion U.S. dollars. Market research companies - global players Market research is an important business strategy involving the gathering of information about an organization’s target market. In terms of global research revenue, American company Gartner was the leading market research company worldwide. Headquartered in the United States, the number of employees working for the company totaled ****** people in 2023. The sixth largest market research company in terms of global research revenue was Kantar. Kantar Group is a UK-based international network of ** companies, including Millward Brown and IMRB International. In 2022, the research revenue of Kantar amounted to approximately ***** billion U.S. dollars. Another European leader, and ranked seventh in the global ranking, was Ipsos. The company had a research revenue of over *** billion U.S. dollars. The largest share of market research revenue made by Ipsos was generated in Europe, the Middle East and Africa in 2023. United States dominant in a global market The global revenue of the market research industry reached over ** billion U.S. dollars in 2023, over half of which came from the United States. The number of full-time employees working for the top ten market research companies in the United States totaled almost ****** in 2020.

In 2021, Gartner was the leading company in the market research and data analytics sector in the United States. Roughly ** million U.S. dollars separated the top two companies, as Nielsen generated a revenue of approximately *** billion U.S. dollars compared to the **** billion U.S. dollars generated by Gartner.

The dataset contains a total of 25,161 rows, each row representing the stock market data for a specific company on a given date. The information collected through web scraping from www.nasdaq.com includes the stock prices and trading volumes for the companies listed, such as Apple, Starbucks, Microsoft, Cisco Systems, Qualcomm, Meta, Amazon.com, Tesla, Advanced Micro Devices, and Netflix.

Data Analysis Tasks:

1) Exploratory Data Analysis (EDA): Analyze the distribution of stock prices and volumes for each company over time. Visualize trends, seasonality, and patterns in the stock market data using line charts, bar plots, and heatmaps.

2)Correlation Analysis: Investigate the correlations between the closing prices of different companies to identify potential relationships. Calculate correlation coefficients and visualize correlation matrices.

3)Top Performers Identification: Identify the top-performing companies based on their stock price growth and trading volumes over a specific time period.

4)Market Sentiment Analysis: Perform sentiment analysis using Natural Language Processing (NLP) techniques on news headlines related to each company. Determine whether positive or negative news impacts the stock prices and volumes.

5)Volatility Analysis: Calculate the volatility of each company's stock prices using metrics like Standard Deviation or Bollinger Bands. Analyze how volatile stocks are in comparison to others.

Machine Learning Tasks:

1)Stock Price Prediction: Use time-series forecasting models like ARIMA, SARIMA, or Prophet to predict future stock prices for a particular company. Evaluate the models' performance using metrics like Mean Squared Error (MSE) or Root Mean Squared Error (RMSE).

2)Classification of Stock Movements: Create a binary classification model to predict whether a stock will rise or fall on the next trading day. Utilize features like historical price changes, volumes, and technical indicators for the predictions. Implement classifiers such as Logistic Regression, Random Forest, or Support Vector Machines (SVM).

3)Clustering Analysis: Cluster companies based on their historical stock performance using unsupervised learning algorithms like K-means clustering. Explore if companies with similar stock price patterns belong to specific industry sectors.

4)Anomaly Detection: Detect anomalies in stock prices or trading volumes that deviate significantly from the historical trends. Use techniques like Isolation Forest or One-Class SVM for anomaly detection.

5)Reinforcement Learning for Portfolio Optimization: Formulate the stock market data as a reinforcement learning problem to optimize a portfolio's performance. Apply algorithms like Q-Learning or Deep Q-Networks (DQN) to learn the optimal trading strategy.

The dataset provided on Kaggle, titled "Stock Market Stars: Historical Data of Top 10 Companies," is intended for learning purposes only. The data has been gathered from public sources, specifically from web scraping www.nasdaq.com, and is presented in good faith to facilitate educational and research endeavors related to stock market analysis and data science.

It is essential to acknowledge that while we have taken reasonable measures to ensure the accuracy and reliability of the data, we do not guarantee its completeness or correctness. The information provided in this dataset may contain errors, inaccuracies, or omissions. Users are advised to use this dataset at their own risk and are responsible for verifying the data's integrity for their specific applications.

This dataset is not intended for any commercial or legal use, and any reliance on the data for financial or investment decisions is not recommended. We disclaim any responsibility or liability for any damages, losses, or consequences arising from the use of this dataset.

By accessing and utilizing this dataset on Kaggle, you agree to abide by these terms and conditions and understand that it is solely intended for educational and research purposes.

Please note that the dataset's contents, including the stock market data and company names, are subject to copyright and other proprietary rights of the respective sources. Users are advised to adhere to all applicable laws and regulations related to data usage, intellectual property, and any other relevant legal obligations.

In summary, this dataset is provided "as is" for learning purposes, without any warranties or guarantees, and users should exercise due diligence and judgment when using the data for any purpose.

Market research companies have benefited from research and development (R&D) expenditure growth as companies develop new products to satisfy consumer demand. Downstream companies continue to rely on market research to create new products and campaigns that fit evolving consumer preferences. As companies strive to enhance consumer-centric strategies amid increased consumer spending, demand for tailored market research solutions has surged. A 10.7% surge in corporate profit over the past five years enabled businesses to outsource more of their research operations to professional market researchers. The digital shift has further transformed the landscape, with companies pioneering new research tools to tap into the vast potential of big data to enhance accessibility and participation. These trends have led to revenue growing at a CAGR of 3.8% to an estimated $36.4 billion over the past five years, including an estimated 2.1% boost in 2025 alone. Consumers' and advertisers' growing reliance on the internet has led to new metrics market researchers can use to better understand consumers. These have allowed new companies to enter the industry and driven providers to adjust services and implement new technologies. The rising use of social media to advertise and market new products across platforms like TikTok and Instagram also contributed to the growing demand for market research. These technological advancements improved data collection and analysis methods, offering actionable insights that helped companies refine marketing strategies and develop better products. New opportunities continue to drive revenue growth, but expansions to services and onboarding of new technology cut researchers’ profitability. Moving forward, the industry will benefit from acceleration in R&D budgets and technological and a data procurement evolution. Companies will strengthen their R&D budgets as economic conditions improve, further driving demand for advanced market research tools. The proliferation of online commerce and smart technologies will give researchers unprecedented access to consumer data. Technological developments, such as artificial intelligence (AI), are poised to create new metrics based on human reactions, which companies can leverage to better understand consumer behavior and preferences. Access to these metrics, however, will lead to tightening data privacy regulations, which may result in higher compliance costs that eat into profitability. Finally, growing emphasis on ethical practices, transparency and data security will shape consumer trust and research standards, creating new opportunities and challenges in a rapidly evolving marketplace. Revenue is poised to grow at a CAGR of 2.4% to an estimated $41.0 billion through the end of 2030.

Discover the top companies in the cycling industry known for quality, innovation, and impact on the cycling community, including Trek, Specialized, Giant, Shimano, Santa Cruz, and Canyon.

The global market research industry reached a record high market size of approximately ** billion U.S. dollars in 2023. Over the last decade, the global market research industry has performed contrary to broader economic trends as the industry has continued to grow. Figures for 2023 signaled an increase of about *** billion U.S. dollars compared to the previous year. Market research industryMarket research is the activity of gathering information about markets in which an organization sells their produces and/or services. This often includes detailed qualitative understandings of consumer attitudes and preferences through tools such interviews, surveys, and increasingly, big-data analytics. The leading market research company worldwide was U.S.-based Gartner in 2022. Slow growth in EuropeWhile growth in the United States has been significant, the revenue of the market research industry in Europe grew just slightly since 2014. Some analysts expect this poor performance to continue into the near future for *** reasons. First is the short- and mid-term uncertainty created by Brexit, impacting the reliability of any market research conducted prior to the issue being resolved. Second is the implementation of the EU General Data Protection Regulation (GDPR) laws in May 2018, which limit what companies are able to do with personal data. A majority of IT professionals in France, Germany and the UK agree the GDPR laws will prevent personal data being passed on to third parties, reducing the amount of data available to researchers in Europe compared to other regions.

Stock Data of Top USA Companies: Apple, Tesla, Amazon

👨‍💻 Author: Azhar Saleem

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Dataset Description

This dataset provides daily stock data for some of the top companies in the USA stock market, including major players like Apple, Microsoft, Amazon, Tesla, and others. The data is collected from Yahoo Finance, covering each company’s historical data from its starting date until today. This comprehensive dataset enables in-depth analysis of key financial indicators and stock trends for each company, making it valuable for multiple applications.

Column Descriptions

The dataset contains the following columns, consistent across all companies:

• Date: The date of the stock data entry.
• Open: The stock's opening price for the day.
• High: The highest price reached during the trading day.
• Low: The lowest price during the trading day.
• Close: The stock’s closing price for the day.
• Volume: The total number of shares traded on that day.
• Dividends: Any dividends paid out on that day.
• Stock Splits: Records stock split events, if any, on that day.

Potential Use Cases

1. Machine Learning & Deep Learning:

   • Stock Price Prediction: Use historical prices to train models for forecasting future stock prices.
   • Sentiment Analysis and Price Correlation: Combine with external sentiment data to predict price movements based on market sentiment.
   • Anomaly Detection: Detect unusual price patterns or volume spikes using classification algorithms.

2. Data Science:

   • Trend Analysis: Identify long-term trends for each company or compare trends between companies.
   • Volatility Analysis: Calculate volatility to assess risk and return patterns over time.
   • Correlation Analysis: Compare stock performance across companies to study market relationships.

3. Data Analysis:

   • Historical Performance: Review historical data to understand growth trends, market impact of stock splits, and dividends.
   • Seasonal Patterns: Analyze data for seasonal trends or recurring patterns across years.
   • Investment Strategy Backtesting: Test various investment strategies based on historical data to assess potential profitability.

4. Financial Research:

   • Economic Impact Studies: Investigate how major events affected stock prices across top companies.
   • Sector-Specific Analysis: Identify performance differences across sectors, such as tech, healthcare, and retail.

This dataset is a powerful tool for analysts, researchers, and financial enthusiasts, offering versatility across multiple domains from stock analysis to algorithmic trading models.

H-1B visa sponsorship trends for Market Research Analyst, covering top employers, salary insights, approval rates, and geographic distribution. Explore how job title impacts the U.S. job market under the H-1B program.

Discover the top 10 diamond companies in the world and learn about their impact on the global diamond market from mining to retail.

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Explore the Top 50 US Tech Companies Dataset with metrics like revenue, market cap, employee size, and more. Perfect for market research, business analysis, and AI projects.

Key strategies adopted by top tier companies involved in the global cold chain market and their market shares, growth strategies and financial details.

Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.

Key Features of Success.ai's Company Financial Data:

Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.

Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.

Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.

Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.

Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.

Why Choose Success.ai for Company Financial Data?

Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.

AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.

Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.

Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.

Comprehensive Use Cases for Financial Data:

1. Strategic Financial Planning:

Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.

1. Mergers and Acquisitions (M&A):

Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.

1. Investment Analysis:

Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.

1. Lead Generation and Sales:

Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.

1. Market Research:

Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.

APIs to Power Your Financial Strategies:

Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.

Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.

Tailored Solutions for Industry Professionals:

Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.

Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.

Consulting Firms: Deliver informed recommendations to clients with access to detailed financial datasets and key stakeholder profiles.

Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.

What Sets Success.ai Apart?

Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.

Ethical Practices: Our data collection and processing methods are fully comp...

This dataset contains detailed information on the top 100 American companies, ranked by revenue. The dataset includes key metrics such as company rank, name, industry, revenue (in USD millions), revenue growth percentage, number of employees, and headquarters location. This comprehensive dataset provides a rich resource for analyzing industry trends, financial performance, and the geographic distribution of major companies in the U.S. economy. It is ideal for market research, competitive analysis, and business strategy development.

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Supply Chain Training Market Outlook

According to our latest research, the global supply chain training market size in 2024 reached USD 4.3 billion, reflecting robust and sustained demand across industries seeking to enhance supply chain competencies. The market is expected to grow at a CAGR of 8.6% from 2025 to 2033, with the forecasted market size reaching USD 8.7 billion by 2033. This impressive growth trajectory is primarily driven by increasing supply chain complexities, digital transformation initiatives, and the urgent need for agile, resilient operations in a post-pandemic business environment. As per the latest research, organizations worldwide are prioritizing supply chain training to mitigate risks, improve efficiency, and stay competitive in a rapidly evolving global market.

A primary growth factor for the supply chain training market is the accelerating pace of digitalization across supply chain functions. The proliferation of advanced technologies such as artificial intelligence, machine learning, blockchain, and Internet of Things (IoT) is fundamentally reshaping supply chain management. Organizations are compelled to upskill their workforce to effectively leverage these innovations, driving demand for specialized training programs. Furthermore, the shift towards data-driven decision-making and the adoption of integrated supply chain platforms necessitate comprehensive training to ensure seamless technology integration and operational excellence. As companies embrace automation and advanced analytics, the need for continuous learning and upskilling in supply chain processes becomes a strategic imperative, fueling market growth.

Another significant driver is the heightened focus on supply chain resilience and risk management. The disruptions caused by global events such as the COVID-19 pandemic, geopolitical tensions, and natural disasters have underscored the vulnerabilities in traditional supply chain models. Organizations are investing heavily in training programs that emphasize risk assessment, scenario planning, and crisis management to build resilient supply chains. This trend is particularly pronounced in sectors like healthcare, food & beverage, and logistics, where uninterrupted supply and regulatory compliance are mission-critical. As regulatory requirements become more stringent and customer expectations for transparency and sustainability rise, supply chain professionals must stay abreast of best practices through ongoing training, further propelling the market.

The evolving nature of global trade and the increasing complexity of supply chain networks also contribute to the growth of the supply chain training market. As companies expand into new markets and manage multi-tier supplier relationships, they face challenges related to cross-border logistics, compliance, and cultural nuances. Training solutions tailored to global supply chain management, international trade regulations, and cross-cultural communication are gaining traction. Additionally, the rise of e-commerce and omnichannel retailing has introduced new logistical challenges, prompting retailers and manufacturers to invest in specialized training for last-mile delivery, inventory optimization, and customer service excellence. These factors collectively create a fertile environment for the expansion of the supply chain training market.

Regionally, North America leads the global supply chain training market, accounting for the largest share due to the presence of advanced manufacturing, a mature logistics sector, and a strong emphasis on workforce development. Europe follows closely, driven by stringent regulatory standards and a focus on sustainability. The Asia Pacific region is witnessing the fastest growth, propelled by rapid industrialization, expanding e-commerce, and increasing investments in supply chain infrastructure. Latin America and the Middle East & Africa are also emerging as promising markets, supported by economic diversification efforts and government initiatives to enhance supply chain capabilities. This regional diversification underscores the global significance of supply chain training as a strategic enabler of business success.

The Best Employer Consulting Firm market has seen significant growth in recent years, underscoring the increasing importance of workplace culture and employee satisfaction in driving organizational success. As companies strive to attract and retain top talent, consulting firms specializing in employer branding and w

Success.ai’s Consumer Marketing Data for Food, Beverage & Consumer Goods Professionals Globally provides a comprehensive dataset tailored for businesses seeking to connect with decision-makers and marketing professionals in these dynamic industries. Covering roles such as brand managers, marketing strategists, and product developers, this dataset offers verified contact details, decision-maker insights, and actionable business data.

With access to over 700 million verified global profiles, Success.ai ensures your marketing, sales, and research efforts are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution is essential for businesses aiming to lead in the food, beverage, and consumer goods sectors.

Why Choose Success.ai’s Consumer Marketing Data?

1. Verified Contact Data for Precision Targeting

   • Access verified work emails, phone numbers, and LinkedIn profiles of marketing professionals, brand leaders, and product strategists.
   • AI-driven validation ensures 99% accuracy, minimizing communication errors and maximizing outreach success.

2. Comprehensive Coverage Across Global Markets

   • Includes profiles of professionals from food and beverage companies, consumer goods manufacturers, and marketing agencies in key markets worldwide.
   • Gain insights into regional trends in product marketing, consumer engagement, and purchasing behaviors.

3. Continuously Updated Datasets

   • Real-time updates capture changes in professional roles, company strategies, and market trends.
   • Stay aligned with the fast-evolving consumer goods industry to identify emerging opportunities.

4. Ethical and Compliant

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

Data Highlights:

• 700M+ Verified Global Profiles: Connect with decision-makers, marketers, and product managers in the food, beverage, and consumer goods sectors worldwide.
• Leadership Insights: Gain detailed profiles of brand managers, marketing executives, and product developers shaping consumer trends.
• Contact Details: Access verified phone numbers and work emails for precision outreach.
• Industry Trends: Understand global marketing trends, regional consumer preferences, and market dynamics.

Key Features of the Dataset:

1. Comprehensive Professional Profiles

   • Identify and connect with key professionals managing brand strategies, product launches, and marketing campaigns in the food, beverage, and consumer goods industries.
   • Access data on career histories, certifications, and market expertise for targeted outreach.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (snack foods, beverages, household goods), geographic location, or job function.
   • Tailor campaigns to align with specific needs such as product placement, consumer engagement, or regional expansion.

3. Regional Trends and Consumer Insights

   • Leverage data on consumer preferences, product demand, and spending patterns in key markets.
   • Use these insights to refine product offerings, marketing strategies, and audience targeting.

4. AI-Driven Enrichment

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

Strategic Use Cases:

1. Marketing Campaigns and Brand Outreach

   • Design targeted campaigns for food, beverage, and consumer goods products based on verified data and consumer insights.
   • Leverage multi-channel outreach, including email, phone, and digital advertising, to maximize engagement.

2. Product Development and Launch Strategies

   • Utilize consumer trend data to guide product development and market entry strategies.
   • Collaborate with brand managers and marketing professionals to align offerings with consumer preferences.

3. Sales and Partnership Development

   • Build relationships with distributors, retailers, and marketers in the consumer goods supply chain.
   • Present co-branding opportunities, joint marketing campaigns, or distribution strategies to decision-makers.

4. Market Research and Competitive Analysis

   • Analyze global trends in consumer goods marketing, product innovations, and purchasing behaviors to refine strategies.
   • Benchmark against competitors to identify growth opportunities, underserved markets, and high-demand products.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality consumer marketing data at competitive prices, ensuring strong ROI for your marketing, sales, and product development efforts.

2. Seamless Integration

   • Integrate verified data into CRM systems, marketing platforms, or analytics tools via APIs or downloadable formats, streamlining workflows and enhancing productivity.

3. Data Acc...

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