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.

Retail Analytics Market Overview

Retail analytics involves collecting and analyzing data from various sources in retail operations. It helps retailers make informed decisions to improve their business performance, optimize inventory, and enhance customer experience.

By analyzing sales trends, customer behavior, and inventory levels, retailers can make better decisions about pricing, marketing, and supply chain management. This data-driven approach also aids in fraud detection, competitive analysis, and improving overall store layout and merchandising. Ultimately, retail analytics empowers retailers to stay competitive and profitable in today's dynamic market.

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.

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.

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

Introduction:

This analysis delves into the financial performance of top companies by examining key metrics such as revenue, earnings, market capitalisation, P/E ratio, and dividend yield. By comparing these metrics, we gain a comprehensive understanding of a company's scale, profitability, market value, and growth potential. Through visualisations, the analysis also explores correlations between these metrics and offers insights into country-level performance, highlighting economic dominance across various sectors. This holistic approach provides a multi-dimensional view of global financial powerhouses, investor confidence, and regional economic trends.

Key Metrics Used:

1. Revenue (Trailing Twelve Months - TTM): - Definition: This is the total income generated by a company from its operations in the last twelve months. - Potential Insights: High revenue often indicates market dominance or high sales volume. Comparing revenues can reveal which companies are the largest in terms of business volume.

2. Earnings (TTM): - Definition: This refers to the company's profit after taxes and expenses over the trailing twelve months. - Potential Insights: Companies with high earnings are more efficient at converting revenue into profit, suggesting better profitability or cost management. A comparison of earnings provides insight into profitability rather than just scale.

3. Market Capitalisation (Market Cap): - Definition: Market cap is the total value of a company's outstanding shares of stock, calculated as stock price multiplied by the number of shares. It indicates the company’s size in the stock market. - Potential Insights: High market cap usually indicates investor confidence in the company. Comparing market cap among the top 15 companies reveals their relative size in financial markets.

4. P/E Ratio (TTM): - Definition: Price-to-Earnings (P/E) ratio measures a company's current share price relative to its per-share earnings. - Potential Insights: A high P/E ratio may indicate that investors expect high growth in the future, while a low P/E ratio could imply undervaluation or scepticism about growth. Companies are compared by their growth prospects or current valuation.

5. Dividend Yield (TTM): - Definition: Dividend yield is a financial ratio that shows how much a company pays out in dividends each year relative to its share price. - Potential Insights: High dividend yield may indicate that a company returns more income to shareholders. It’s particularly useful for income-focused investors.

In this combined analysis, we will integrate the observations from the visualisations with the key financial metrics definitions and insights, to offer a comprehensive view of the top companies and country-level analysis across various financial dimensions.

Data Visualisations

Visualisation 1: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F2296eddd53ddd4b84346b1ea1324ec0a%2FScreenshot%202024-10-01%2015.16.51.png?generation=1727864461164331&alt=media" alt=""> Visualisation 2: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2Fb35516c91e54eda75a03ff073e94dd73%2FScreenshot%202024-10-01%2015.17.53.png?generation=1727864511265917&alt=media" alt=""> Visualisation 3: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F506ca2428d34b15cd46e4a31261763d7%2FScreenshot%202024-10-01%2015.18.37.png?generation=1727864562835491&alt=media" alt=""> Visualisation 4: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F41e7a3e28c757239d26226f6a0ccdca9%2FScreenshot%202024-10-01%2015.19.20.png?generation=1727864614352037&alt=media" alt=""> A Markdown document with the R code for the above visualisations. link

1. Revenue (Trailing Twelve Months - TTM)

• Definition: The total income generated from a company’s operations over the last 12 months.
• Insights from Charts:
  • Revenue vs Earnings (Visualisation 2): Companies like Saudi Aramco are massive outliers with high revenues and even higher earnings, indicating impressive profitability despite their revenue volume.
  • Top 10 Countries by Average Revenue (Visualisation 3): China, South Korea, and Japan are at the top, with companies generating significant business volumes.
  • Analysis: High revenue companies like Walmart dominate the market but may not always convert this into proportional earnings or market cap growth. This could be due to operational costs or sector-specific challenges (retail margins being lower than tech).

2. Earnings (TTM)

• Definition: Profits...

Explore the top 10 cosmetic companies known for their innovation, quality, and global influence in the beauty and skincare industry. From L'Oréal to LVMH, discover the companies shaping consumer preferences worldwide.

Market research report on top 10 bioremediation companies. This report also provides brief information and overview of the global bioremediation market.

Market research report on top 10 Sensor companies. This report provides detailed information on companies that BCC Research has identified as market leaders in the sensors market.

Success.ai delivers comprehensive access to Small Business Contact Data, tailored to connect you with North American entrepreneurs and small business leaders. Our extensive database includes verified profiles of over 170 million professionals, ensuring direct access to decision-makers in various industries. With AI-validated accuracy, continuously updated datasets, and a focus on compliance, Success.ai empowers businesses to enhance their marketing, sales, and recruitment efforts while staying ahead in a competitive market.

Key Features of Success.ai's Small Business Contact Data:

Extensive Coverage: Access profiles for small business owners and entrepreneurs across the United States, Canada, and Mexico. Our database spans multiple industries, from retail to technology, providing diverse business insights.

Verified Contact Details: Each profile includes work emails, phone numbers, and firmographic data, enabling precise and effective outreach.

Industry-Specific Data: Target key sectors such as e-commerce, professional services, healthcare, manufacturing, and more, with tailored datasets designed to meet your specific business needs.

Real-Time Updates: Continuously updated to maintain a 99% accuracy rate, our data ensures that your campaigns are always backed by the most current information.

Ethical and Compliant: Fully compliant with GDPR and other global data protection regulations, ensuring ethical use of all contact data.

Why Choose Success.ai for Small Business Contact Data?

Best Price Guarantee: Enjoy the most competitive pricing in the market, delivering exceptional value for comprehensive and verified contact data.

AI-Validated Accuracy: Our advanced AI systems meticulously validate every data point to deliver unmatched reliability and precision.

Customizable Data Solutions: From hyper-targeted regional datasets to comprehensive industry-wide insights, we tailor our offerings to meet your exact requirements.

Scalable Access: Whether you're a startup or an enterprise, our solutions are designed to scale with your business needs.

Comprehensive Use Cases for Small Business Contact Data:

1. Targeted Marketing Campaigns:

Refine your marketing strategy by leveraging verified contact details for small business owners. Execute highly personalized email, phone, and multi-channel campaigns with precision.

1. Sales Prospecting:

Identify and connect with decision-makers in key industries. Use detailed profiles to enhance your sales outreach, close deals faster, and build long-term client relationships.

1. Recruitment and Talent Acquisition:

Discover small business leaders and key players in specific industries to strengthen your recruitment pipeline. Access up-to-date profiles for sourcing top talent.

1. Market Research:

Gain insights into small business trends, operational challenges, and industry benchmarks. Leverage this data for competitive analysis and market positioning.

1. Local Business Engagement:

Foster partnerships with small businesses by identifying community leaders and entrepreneurial influencers in your target regions.

APIs to Enhance Your Campaigns:

Enrichment API: Integrate real-time updates into your CRM and marketing systems to maintain accurate and actionable contact data. Perfect for businesses looking to improve lead quality.

Lead Generation API: Maximize your lead generation efforts with access to verified contact details, including emails and phone numbers. Tailored for precise targeting of small business decision-makers.

Tailored Solutions for Diverse Needs:

Marketing Agencies: Create targeted campaigns with verified data for small business owners across diverse sectors.

Sales Teams: Drive revenue growth with detailed profiles and direct access to decision-makers.

Recruiters: Build a talent pipeline with current and verified data on small business leaders and professionals.

Consultants: Provide data-driven recommendations to clients by leveraging detailed small business insights.

What Sets Success.ai Apart?

170M+ Profiles: Access a vast and detailed database of small business owners and entrepreneurs.

Global Standards Compliance: Rest assured knowing all data is ethically sourced and compliant with global privacy regulations.

Flexible Integration: Seamlessly integrate data into your existing workflows with customizable delivery options.

Dedicated Support: Our team of experts is always available to ensure you maximize the value of our solutions.

Empower Your Outreach with Success.ai:

Success.ai’s Small Business Contact Data is your gateway to building meaningful connections with North American entrepreneurs. Whether you're driving targeted marketing campaigns, enhancing sales prospecting, or conducting in-depth market research, our verified datasets provide the tools you need to succeed.

Get started with Success.ai today and unlock the potential of verified Small Business ...

Discover the top 10 trucking companies that are essential components of the supply chain, offering a wide range of services from LTL to truckload and demonstrating a commitment to innovation, technology, and customer satisfaction.

This dataset provides information on the closing price, high price, low price, and volume of stocks for the top 10 companies in the healthcare sector. The dataset consists of time-series data, covering daily stock market data from 2000 to 2023.

The dataset includes the following columns:

Date: Date Company: Company name Close: Closing price of the stock High: High price of the stock Low: Low price of the stock Volume: Volume of trades The data is sourced using the Googlefinance function in Google Sheets, and the selection of the top 10 healthcare companies is based on information from the article "World's Top 10 Health Care Companies" published on Investopedia (https://www.investopedia.com/articles/markets/030916/worlds-top-10-health-care-companies-unh-mdt.asp).

This dataset can be used for various data analysis purposes, such as stock market analysis, predictive modeling, and statistical analysis. However, it is important to note that this dataset is provided for informational purposes only and should not be considered as financial advice or a recommendation for investment decisions. It is always advisable to consult with a professional financial consultant before making any investment decisions.

Identification of the top 10 companies in the market for food safety products and technology, and the rationale behind these selections.

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.

Discover the top 10 cosmetic companies worldwide, ranked by revenue and impact on the industry. From L'Oréal to Kao Corporation, explore the key players shaping global beauty trends with innovative products.

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.

The Infrastructure As Code Market size is expected to reach a valuation of USD 4401.0 million in 2033 growing at a CAGR of 20.6%. The Infrastructure As Code market research report classifies market by share, trend, demand, forecast and based on segmentation.

Discover the top 10 high-quality vitamin companies known for their commitment to rigorous testing, natural ingredients, and sustainability practices in manufacturing.

Context

This dataset provides comprehensive stock market data for some of the world's leading companies, including Apple, Microsoft, Nvidia, Google, Amazon, Saudi Aramco, Meta, Berkshire Hathaway, TSMC, and Eli Lilly. It covers various financial metrics such as opening and closing prices, trading volumes, and market capitalization. The data spans across 2024, offering a valuable resource for analyzing market trends and investment strategies. Ideal for financial analysts, researchers, and data enthusiasts, this dataset enables in-depth analysis and forecasting. Utilize this data to explore stock performance and uncover market insights.

Content

Geography: Worldwide

Time period: Jan 2015- August 2024

Unit of analysis: Top 10 Global Companies Stock Data 2024

Variables

Acknowledgements

This dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F18335022%2F868f5fd280261e81077d7bde565ea17a%2FScreenshot%202024-08-30%20170459.png?generation=1725090902292761&alt=media" alt="">