This dataset contains detailed specifications and official launch prices of various mobile phone models from different companies. It provides insights into smartphone hardware, pricing trends, and brand competitiveness across multiple countries. The dataset includes key features such as RAM, camera specifications, battery capacity, processor details, and screen size.

One important aspect of this dataset is the pricing information. The recorded prices represent the official launch prices of the mobile phones at the time they were first introduced in the market. Prices vary based on the country and the launch period, meaning older models reflect their original launch prices, while newer models include their most recent launch prices. This makes the dataset valuable for studying price trends over time and comparing smartphone affordability across different regions.

Features:

• Company Name: The brand or manufacturer of the mobile phone.
• Model Name: The specific model of the smartphone.
• Mobile Weight: The weight of the mobile phone (in grams).
• RAM: The amount of Random Access Memory (RAM) in the device (in GB).
• Front Camera: The resolution of the front (selfie) camera (in MP).
• Back Camera: The resolution of the primary rear camera (in MP).
• Processor: The chipset or processor used in the device.
• Battery Capacity: The battery size of the smartphone (in mAh).
• Screen Size: The display size of the smartphone (in inches).
• Launched Price: (Pakistan, India, China, USA, Dubai): The official launch price of the mobile in the respective country at the time of its release. Prices vary based on the year the mobile was launched.
• Launched Year: The year the mobile phone was officially launched.

In 2022, smartphone vendors sold around 1.39 billion smartphones were sold worldwide, with this number forecast to drop to 1.34 billion in 2023.

Smartphone penetration rate still on the rise

Less than half of the world’s total population owned a smart device in 2016, but the smartphone penetration rate has continued climbing, reaching 78.05 percent in 2020. By 2025, it is forecast that almost 87 percent of all mobile users in the United States will own a smartphone, an increase from the 27 percent of mobile users in 2010.

Smartphone end user sales

In the United States alone, sales of smartphones were projected to be worth around 73 billion U.S. dollars in 2021, an increase from 18 billion dollars in 2010. Global sales of smartphones are expected to increase from 2020 to 2021 in every major region, as the market starts to recover from the initial impact of the coronavirus (COVID-19) pandemic.

About Dataset

This dataset contains detailed information about phones listed on Amazon, including product specifications, user reviews, ratings, and pricing. The dataset can be useful for analyzing product trends, consumer preferences, pricing strategies, and technical features of smartphones sold on the platform. It includes both new and Amazon-renewed phones.

Description

The dataset includes the following key features:

• Color: The available color of the phone.
• Image Links: URLs to the images of the products.
• Descriptions: Detailed descriptions of the phone, including specifications.
• Kind Product: The type or category of the product (smartphones, accessories, etc.).
• Ratings: User ratings (out of 5 stars).
• Number of Ratings: Total count of ratings the product has received.
• Status: Availability status (e.g., In Stock, Out of Stock).
• Number of Buyers Last Month More Than: Approximate number of buyers in the previous month.
• Typical Price: The regular price with usd of the phone without any discounts.
• Price: The current price with usd of the phone.
• You Save: The amount saved if the phone is on discount.
• Discount: The percentage discount offered on the product.
• Brand: The brand name of the phone (e.g., Apple, Samsung).
• OS: The operating system of the phone (e.g., Android, iOS).
• CPU Model: The model of the processor used in the phone.
• Resolution: The screen resolution of the phone.
• Name: The product name as listed on Amazon.
• Wireless Carrier: The supported wireless carrier (e.g., Verizon, AT&T).
• Cellular Technology: The cellular network technology (e.g., 4G, 5G).
• Dimensions: Physical dimensions of the phone.
• ASIN: Amazon Standard Identification Number, a unique product identifier.
• Model: The model number of the phone.
• Amazon Renewed: Indicates whether the product is part of the Amazon Renewed program (refurbished).
• Renewed Smartphones: Additional flag indicating if the phone is renewed.
• Battery Capacity: The capacity of the phone’s battery (in mAh).
• Battery Power: The power rating of the battery.
• Charging Time: Time taken to charge the phone fully.
• RAM: The amount of RAM in the phone.
• Storage: Internal storage capacity of the phone.
• Screen Size: Size of the display (in inches).
• Connectivity Technologies: Wireless technologies supported by the phone (e.g., Bluetooth, Wi-Fi).
• Wireless Network: Type of wireless networks supported (e.g., Wi-Fi 6).
• CPU Speed: The speed of the phone’s CPU (in GHz).
• Reviews USA: User reviews originating from the USA.
• Reviews Other: User reviews from countries other than the USA.

Detail

This dataset includes a comprehensive range of variables, offering insight into both the technical aspects and customer perceptions of various smartphones sold on Amazon. The dataset allows for:

• Product Comparisons: Comparison of specifications like RAM, CPU, storage, battery life, screen size, etc.
• Pricing Analysis: Understanding pricing trends, discounts, and price fluctuations across different brands and models.
• Consumer Insights: Analysis of consumer behavior through ratings, reviews, and the number of buyers over time.
• Product Availability: Insights into stock availability and how often certain products are sold or renewed.

Usage

The dataset can be used for several purposes, including but not limited to:

1. Market Research: Analyze product popularity and trends in smartphone sales on Amazon.
2. Sentiment Analysis: Perform sentiment analysis on reviews (USA and other countries) to understand customer satisfaction.
3. Price Forecasting: Build models to forecast price changes or identify the best time to buy based on historical data.
4. Product Recommendations: Develop recommendation systems based on user reviews, ratings, and product features.
5. Competitive Analysis: Compare different brands and models to identify strengths and weaknesses of various smartphones.
6. Feature Engineering for ML Models: Use product specifications like RAM, CPU speed, and battery power to create features for predictive machine learning models.

Summary

This Amazon product phones dataset provides an in-depth look at smartphones sold on Amazon, covering everything from technical specifications to user reviews and pricing. It is ideal for anyone looking to analyze trends in the smartphone market, consumer preferences, or technical specifications. The data can be leveraged for a wide array of projects such as market analysis, machine learning, and competitive intelligence.

Mobile Wireless Providers Market Share in the US, 2016 Discover more data with ReportLinker!

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🆕 Update History

• v2 (May 2025): Uploaded amazon_cell_phones_updated.csv — this new version includes updated features and additional data fields, while preserving the core structure and main features of the original dataset.
• v1 (September 2024): Original upload of amazon_cell_phones_original_old.csv. The current dataset description refers to this version.

📌 Note: The description below is still based on the original dataset (amazon_cell_phones_original_old.csv). For the latest structure and feature details, please refer directly to amazon_cell_phones_updated.csv.

Various details about cell phones listed on Amazon USA, such as product name, price, rating, number of ratings, and technical specifications like RAM, storage, screen size, and more.

Dataset Overview

This dataset contains detailed information about cellphones listed on Amazon, scraped using Selenium and BeautifulSoup. It includes product details such as the name, price, ratings, specifications (RAM, storage, screen size, etc.), and additional metadata like the number of ratings and discount percentage. The dataset was designed to provide insights into cellphone features, pricing trends, and customer feedback on one of the world's largest e-commerce platforms.

Source

The data was scraped from Amazon's cellphone category pages over multiple pages (up to 250 pages). Given Amazon's structure, the dataset includes a wide variety of cellphone brands and models, including older and newer releases.

Data Fields

• ID: Unique identifier for each product.
• Product Name: The name of the cellphone.
• Product Link: URL link to the Amazon product page.
• Image Link: URL link to the product image on Amazon.
• Price (Dollar): The price of the cellphone in USD.
• Discount Percentage: Discount percentage, if applicable, calculated as the difference between the original price and the current price.
• Price Before Discount: Original price of the cellphone, if available.
• Rating (out of 5): Customer rating, extracted from the product page.
• Number of Ratings: The total number of customer ratings for the product.
• Brand: Brand of the cellphone.
• Operating System: The operating system of the cellphone (e.g., Android, iOS).
• RAM (GB): Amount of RAM in GB.
• Storage (GB): Internal storage capacity in GB.
• Screen Size (Inches): Screen size in inches.
• Cellular Technology: Cellular technology (e.g., 4G, 5G).
• CPU: CPU Speed.
• CPU Model: CPU model used in the cellphone.
• Available Colors: Available colors for the cellphone model.

Potential Uses

• Product Comparison: This dataset can be used to compare various cellphone brands and models based on price, RAM, storage, and other features.
• Trend Analysis: Analyze price trends, discount patterns, and customer preferences based on ratings and reviews.
• Machine Learning: Build machine learning models to predict price trends, ratings, or sales volume.
• Exploratory Data Analysis (EDA): Perform EDA to discover patterns, outliers, and insights into the cellphone market.

Data Cleaning

The dataset has been cleaned to remove duplicates and standardize data entries. Missing values were handled where possible, and units of measurement (e.g., RAM, storage) have been converted for consistency.

Limitations

• Dynamic Content: Prices, ratings, and availability may change on Amazon over time, meaning this dataset represents a snapshot of the listings at the time of scraping.

Mobile Robot Dataset Versioning Market Outlook

According to our latest research, the Global Mobile Robot Dataset Versioning market size was valued at $327 million in 2024 and is projected to reach $1.26 billion by 2033, expanding at a robust CAGR of 16.7% during the forecast period of 2025–2033. The primary growth driver for this market is the increasing adoption of advanced robotics across industries, which demands reliable, scalable, and version-controlled datasets to fuel AI and machine learning algorithms for mobile robots. As industries accelerate their automation initiatives, the need for accurate, up-to-date, and well-managed datasets becomes critical to ensuring operational efficiency, safety, and performance of mobile robotic systems. This trend is further amplified by the proliferation of autonomous systems in logistics, healthcare, and manufacturing, where real-time data integrity and traceability are essential.

Regional Outlook

North America currently holds the largest share of the global Mobile Robot Dataset Versioning market, accounting for approximately 38% of total market value in 2024. The region’s dominance is underpinned by its mature technology ecosystem, significant investments in robotics research, and widespread adoption of mobile robots across sectors such as logistics, automotive, and healthcare. Leading technology companies and research institutes in the United States and Canada are at the forefront of developing sophisticated dataset versioning solutions, leveraging advanced cloud infrastructure and robust cybersecurity frameworks. Additionally, supportive government policies and funding for AI and robotics innovation have accelerated the deployment of dataset versioning tools, making North America a pivotal hub for market growth and technological advancement.

In contrast, the Asia Pacific region is emerging as the fastest-growing market, projected to register an impressive CAGR of 19.4% from 2025 to 2033. This rapid expansion is driven by escalating investments in automation, particularly in China, Japan, and South Korea, where manufacturing and logistics sectors are undergoing digital transformation. The region benefits from a burgeoning startup ecosystem, increased government support for Industry 4.0 initiatives, and a rising demand for smart warehouses and autonomous vehicles. As regional enterprises accelerate the integration of mobile robots, the need for scalable, cloud-based dataset versioning solutions becomes paramount, fueling market growth. Furthermore, collaborations between local universities, global tech giants, and government agencies are fostering innovation and accelerating the adoption of best practices in data management and version control.

Emerging economies in Latin America, the Middle East, and Africa are witnessing gradual adoption of mobile robot dataset versioning solutions, albeit at a slower pace due to infrastructural and regulatory challenges. Limited access to advanced IT infrastructure, a shortage of skilled personnel, and varying data privacy regulations pose significant hurdles to widespread implementation. However, localized demand from sectors such as mining, oil & gas, and agriculture is creating niche opportunities for dataset versioning tools tailored to specific operational environments. Policymakers in these regions are increasingly recognizing the potential of robotics and AI, introducing pilot programs and incentives to stimulate market growth. As awareness grows and digital infrastructure improves, these regions are expected to contribute more significantly to the global market in the latter part of the forecast period.

Report Scope

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.

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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:

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• 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

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   • 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.

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   • Present innovative solutions, supply chain partnerships, or co-marketing opportunities to grow your market share.

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   • Develop offerings that align with regional preferences and purchasing behaviors to maximize market impact.

Why Choose Success.ai?

1. Best Price Guarantee
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Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

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Key Features of the Dataset:

Verified Contact Details

Includes accurate and up-to-date email addresses and phone numbers to ensure you reach your targets reliably.

AI-validated for 99% accuracy, eliminating errors and reducing wasted efforts.

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Comprehensive data points include job titles, skills, work experience, and education to enable precise segmentation and targeting.

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Business-Specific Information

Covers essential details such as industry, company size, location, and more, enabling you to tailor your campaigns effectively. Ideal for profiling and understanding the unique needs of small businesses.

Continuously Updated Data

Our dataset is maintained and updated regularly to ensure relevance and accuracy in fast-changing market conditions. New business contacts are added frequently, helping you stay ahead of the competition.

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Tailored for Small Business Engagement Focused specifically on North American small business owners, this dataset is an invaluable resource for building relationships with SMEs (Small and Medium Enterprises). Whether you’re targeting startups, local businesses, or established small enterprises, our dataset has you covered.

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Lead Generation Business Development Market Research Sales Outreach Customer Acquisition What’s Included in the Dataset: Each profile provides:

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Background

This dataset includes the top 10 search results of smartphone brands on Amazon in the US. The brands included here are SAMSUNG, Apple, HUAWEI, XIAOMI, and OPPO, which are also the top 5 smartphones worldwide by the amount of shipment. The top 10 search results of each brand are based on the current average buyer review grades. This may change when you go to Amazon to cross-check.

Clarification on certain special columns

For the feature headers and feature values, these two columns' data values are separated by space and tab and the order corresponds with each other. For example, in the first line: The feature headers as follows: Brand Model Name Wireless Carrier OS Cellular Technology Memory Storage Capacity Connectivity technologies Color Screen Size Wireless network technology
corresponds to
The feature values as follows: SAMSUNG Samsung Galaxy S23 Unlocked for All Carriers Android 13.0 5G 256 GB Bluetooth, Wi-Fi, USB, NFC Lavender 6.1 Inches GSM, CDMA, LTE

Some inspirations on data analytics

📍 Comparison analysis on brands based on top 10 search result phone models, ratings, and product features including technologies, colors, screen size, etc. Figure out if there exists any significant common or different traits or trends of the top 5 brands. 📍 Clustering analysis to see if there exist any noteworthy groups with certain features. 📍 Regression analysis on features and see how each potentially contributes to the ratings or sales.

Caution

The sample size of this dataset is just 61 records and the data here only represents brands' sales and top-rating products on Amazon. Conclusions drawn can be biased but still give a general idea or some clues on the smartphone market segmentation and potential strategies taken by different brands to differentiate.

Mobile Robot Benchmark Datasets Market Outlook

According to our latest research, the global Mobile Robot Benchmark Datasets market size reached USD 1.12 billion in 2024, driven by the rapid adoption of autonomous systems across various industries and the increasing need for standardized evaluation tools. The market is projected to grow at a robust CAGR of 18.7% from 2025 to 2033, with the market size expected to reach USD 5.89 billion by 2033. Key growth factors include the expanding deployment of mobile robots in logistics, healthcare, and defense, as well as the rising demand for high-quality, diverse datasets to train and benchmark advanced robotic algorithms.

One of the primary drivers fueling the growth of the Mobile Robot Benchmark Datasets market is the surging adoption of autonomous mobile robots (AMRs) across various industrial and commercial sectors. Industries such as logistics, warehousing, and manufacturing are increasingly relying on AMRs to optimize operational efficiency, reduce labor costs, and enhance workplace safety. The deployment of these robots necessitates robust datasets for training, validation, and benchmarking of navigation, perception, and decision-making algorithms. As the complexity of robotic systems grows, so does the need for comprehensive and diverse datasets that can simulate real-world challenges, ensuring that robots can operate reliably in dynamic and unpredictable environments. This trend is further accelerated by the proliferation of Industry 4.0 initiatives and the integration of artificial intelligence (AI) and machine learning (ML) in robotic platforms, making benchmark datasets indispensable for innovation and quality assurance.

Another significant growth factor is the increasing collaboration between academia, research institutions, and industry players to develop standardized and open-source benchmark datasets for mobile robots. These collaborations are crucial for establishing common evaluation metrics, fostering transparency, and accelerating the pace of technological advancements. The availability of high-quality datasets enables researchers and developers to benchmark their algorithms against standardized scenarios, facilitating objective performance comparisons and driving continuous improvement. Moreover, government agencies and international bodies are supporting initiatives aimed at creating publicly accessible datasets to democratize research and development in robotics. This collaborative ecosystem not only enhances the quality and diversity of available datasets but also promotes interoperability and cross-industry adoption of mobile robotics solutions.

The growing emphasis on safety, reliability, and regulatory compliance in autonomous systems is also propelling the demand for benchmark datasets in the mobile robotics sector. Regulatory authorities are increasingly mandating rigorous testing and validation of autonomous systems before their deployment in public and safety-critical environments. Benchmark datasets play a pivotal role in ensuring that mobile robots meet stringent safety and performance standards by providing standardized scenarios for testing navigation, obstacle avoidance, and decision-making algorithms. This regulatory push, coupled with the rising expectations of end-users for seamless and error-free robotic operations, is compelling manufacturers and solution providers to invest heavily in comprehensive benchmarking tools and datasets, thereby driving market growth.

From a regional perspective, North America currently dominates the Mobile Robot Benchmark Datasets market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of leading technology companies, advanced research institutions, and a robust startup ecosystem in the United States and Canada has positioned North America as a hub for innovation in mobile robotics and AI. Europe is witnessing significant growth, driven by strong government support for robotics research and the increasing adoption of automation in manufacturing and logistics. Meanwhile, Asia Pacific is emerging as the fastest-growing region, fueled by rapid industrialization, urbanization, and substantial investments in AI and robotics infrastructure in countries such as China, Japan, and South Korea. The regional dynamics are further influenced by the availability of skilled talent, supportive regulatory frameworks, and the pace of digital transformation across key industries.

Dataset Type Analysis

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Cell Culture Market Growth | Industry Analysis, Size & Forecast Report

Dataset updated: Jun 27, 2024

Provided by: Mordor Intelligence

License: Privacy Policy

Time period: 2019 - 2029

Area: Global

Variables: CAGR, Market size, Market share analysis, Global trends, Industry forecast

Description: The cell culture market is expected to witness a CAGR of 11.0% over the forecast period (2022-2027).

Units: Revenue in USD Billion, Volumes in Units, Pricing in USD

Regions and Countries Covered

Industry Segmentation

Products: Biosafety Equipment, Centrifuges, Cryostorage Equipment, Culture Systems/Bioreactors, Incubators, Pipetting Instruments, Others

Consumables: Media, Sera, Reagents

Application: Biopharmaceuticals, Drug Development, Gene Therapy, Tissue Culture and Engineering, Vaccine Production, Others

Market Players: Thermo Fisher Scientific, Danaher Corporation, Sartorius AG, Merck KGaA, others.

Market Estimates and Statistics

Market Segmentation by Product & Consumables

Market Segmentation by Application

Market Size by Region

The Cellular Towers in USA dataset is a collection of data that provides information about cellular towers located in the United States. The dataset includes information about the location, ownership, and technical specifications of over 47,000 cellular towers.

Each record in the dataset contains the following information:

• Object ID
• Unique System ID
• Licensee
• Latitude
• Longitude
• Structure Type
• Location Address
• Location City
• Location State
• URL

This dataset can be useful for a variety of purposes, including:

• Analyzing the coverage and quality of cellular networks in the United States
• Identifying areas with a high density of cellular towers
• Evaluating the market share of different cellular tower owners

In the third quarter of 2025, Samsung shipped approximately **** million smartphones, marking an increase compared to both the previous quarter and the same period in the prior year. The company’s strong sales performance consistently positions Samsung as the world’s leading smartphone vendor, ahead of Apple. Samsung smartphone sales – how many phones does Samsung sell? Global smartphone sales reached over *** billion units during 2024. While the global smartphone market is led by Samsung and Apple, Xiaomi has gained ground following the decline of Huawei. Together, these three companies hold more than ** percent of the global smartphone market share.

Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

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Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

Why Choose Success.ai?

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Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

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From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

Key Use Cases:

• Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
• Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
• Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
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The smartphone penetration in the United States was forecast to continuously increase between 2024 and 2029 by in total 1.3 percentage points. The penetration is estimated to amount to 97 percent in 2029. Notably, the smartphone penetration of was continuously increasing over the past years.The penetration rate refers to the share of the total population.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the smartphone penetration in countries like Mexico and Canada.

OPPO has significantly increased the production and sales of their smartphone lineup over the past five years, shipping almost 29 million units in the third quarter of 2024. The company – launched in 2004 – shipped 7.3 million units in the first quarter of 2015. Despite considerable growth over the past few years, the total smartphone units shipped by OPPO in the first quarter of 2024 was not the highest. OPPO’s growth: Leading five vendors OPPO’s growth has seen their output consistently place the company among the top five smartphone vendors in the world, shipping around 29 million units in the third quarter of 2024. While many of those shipments were domestic shipments in the company’s home country of China, OPPO has gained a footing in international markets, accounting for four percent of the smartphone market in Europe. OPPOrtunities in emerging markets Many of OPPO’s smartphones are available at a lower price-point than the flagship phones of vendors such as Apple, giving the company opportunities in emerging markets. For instance, the company regularly appears among the top vendors in the African smartphone market. A key reason for OPPO’s success in Africa is that 97 percent of all phones sold in the region sell for less than 400 U.S. dollars.

China is leading the ranking by number of smartphone users, recording ****** million users. Following closely behind is India with ****** million users, while Seychelles is trailing the ranking with **** million users, resulting in a difference of ****** million users to the ranking leader, China. Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

The number of Apple iPhone unit sales dramatically increased between 2007 and 2024. Indeed, in 2007, when the iPhone was first introduced, Apple shipped around **** million smartphones. By 2024, this number reached over ***** million units. The newest models and iPhone’s lasting popularity Apple has ventured into its 17th smartphone generation with its Phone ** lineup, which, released in September 2025, includes the **, ** Plus, ** Pro and Pro Max. Powered by the A19 bionic chip and running on iOS **, these models present improved displays, cameras, and functionalities. On the one hand, such features come, however, with hefty price tags, namely, an average of ***** U.S. dollars. On the other hand, they contribute to making Apple among the leading smartphone vendors worldwide, along with Samsung and Xiaomi. In the first quarter of 2024, Samsung shipped over ** million smartphones, while Apple recorded shipments of roughly ** million units. Success of Apple’s other products Apart from the iPhone, which is Apple’s most profitable product, Apple is also the inventor of other heavy-weight players in the consumer electronics market. The Mac computer and the iPad, like the iPhone, are both pioneers in their respective markets and have helped popularize the use of PCs and tablets. The iPad is especially successful, having remained as the largest vendor in the tablet market ever since its debut. The hottest new Apple gadget is undoubtedly the Apple Watch, which is a line of smartwatches that has fitness tracking capabilities and can be integrated via iOS with other Apple products and services. The Apple Watch has also been staying ahead of other smart watch vendors since its initial release and secures around ** percent of the market share as of the latest quarter.