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.

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.

The Apple iPhone is arguably one of the most transformative consumer products of the 21st century. Its launch in 2007 not only redefined the mobile phone but also reshaped entire industries. Analyzing its journey provides incredible insights into product strategy, market saturation, pricing power, and its monumental impact on Apple's financial performance.

This synthetic dataset was created to provide a single, clean, and accessible source for exploring the iPhone's complete history. Since Apple stopped reporting official unit sales in 2018, this dataset uses a combination of historical reported data and realistic, revenue-based estimations to provide a continuous timeline from 2007 to a projection for 2025 The dataset consists of a single CSV file, apple_iphone_history_2007_2025.csv, containing annual data with the following columns:

Year: The calendar year.

iPhone_Model_Released: The flagship iPhone model(s) launched that year.

Release_Date: The month and year of the primary launch event.

Units_Sold_in_Year_Millions: An estimated figure of total iPhones sold in the calendar year, in millions.

Average_Selling_Price_USD: An estimated average price of an iPhone sold that year, accounting for the mix of different models and storage tiers.

Annual_iPhone_Revenue_Billions: Estimated revenue from all iPhone sales for the year, in billions of USD.

Annual_Total_Apple_Revenue_Billions: The actual total revenue for Apple, Inc. for the fiscal year, providing context for the iPhone's contribution.

iPhone_Revenue_as_Percentage_of_Total: A calculated field showing how much of Apple's total business is driven by the iPhone.

Average_Stock_Price_USD_Annual: The approximate average stock price (AAPL) for that calendar year, adjusted for all historical stock splits.

Methodology

Pre-2018 Data: Unit sales are based on officially reported figures from Apple's historical financial statements.

Post-2018 Data: Unit sales are carefully estimated based on Apple's publicly reported quarterly iPhone revenue and prevailing market analysis of the Average Selling Price (ASP).

Financials & Stock: Revenue and stock price data are based on publicly available historical financial records.

Projections (2024-2025): The final two rows are conservative forecasts based on recent growth trends and market expectations.

Inspiration (Potential Project Ideas) This dataset is perfect for time-series analysis, business intelligence, and data visualization. Here are a few questions you could explore:

The ASP Shift: Can you visualize the turning point in 2017 (iPhone X) where Apple's strategy shifted from pure unit growth to maximizing revenue through higher Average Selling Prices?

Correlation Analysis: What is the correlation between Annual_iPhone_Revenue_Billions and the Average_Stock_Price_USD_Annual? How has this relationship changed over time?

Peak iPhone? Based on the data, has the iPhone's contribution to Apple's total revenue (iPhone_Revenue_as_Percentage_of_Total) peaked?

Forecasting: Can you build a time-series model to predict iPhone unit sales and revenue for 2026 and beyond?

Historical Dashboard: Create an interactive dashboard that tells the story of the iPhone's journey from 2007 to today.

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.

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.

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...

The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total *** billion users (+***** percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach *** billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.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 *** 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 number of smartphone users in countries like the Americas and Asia.

Mobile Sales Data (2023–2024)

  Overview

This dataset contains information about mobile phone sales, including models, quantities sold, unit prices, total revenue, and sale dates.It has been prepared for students, analysts, and anyone who wants to practice business intelligence, sales analytics, or basic machine learning. The dataset is simple, clear, and suitable for classroom assignments, dashboard building, and Excel or Python practice.

  Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/HassanAhmedAI/mobile-sales-data.

This dataset provides a comprehensive collection of information about all the latest smartphones available in the market as of the current time.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13571604%2Fb608498b1cf7f70b9a22952566197db6%2FScreenshot%202023-08-02%20003740.png?generation=1690961033930490&alt=media" alt="">

The dataset was created by web scraping reputable online sources to gather accurate and up-to-date information about various smartphone models, their specifications, features, and pricing.

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.

About this dataset

Context

The dataset tabulates the Mobile population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Mobile across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Mobile was 182,595, a 0.38% decrease year-by-year from 2022. Previously, in 2022, Mobile population was 183,290, a decline of 1.02% compared to a population of 185,176 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Mobile decreased by 20,735. In this period, the peak population was 203,330 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Mobile is shown in this column.
• Year on Year Change: This column displays the change in Mobile population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mobile Population by Year. You can refer the same here

The number of smartphone users in France was forecast to continuously increase between 2024 and 2029 by in total 3.2 million users (+5.96 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 56.89 million users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.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).Find more key insights for the number of smartphone users in countries like Belgium and Luxembourg.

About this dataset

Context

The dataset tabulates the Mobile City population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Mobile City across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Mobile City was 161, a 4.55% increase year-by-year from 2022. Previously, in 2022, Mobile City population was 154, an increase of 2.67% compared to a population of 150 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Mobile City decreased by 35. In this period, the peak population was 233 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Mobile City is shown in this column.
• Year on Year Change: This column displays the change in Mobile City population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mobile City Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Mobile population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Mobile across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Mobile was 183,289, a 0.93% decrease year-by-year from 2021. Previously, in 2021, Mobile population was 185,017, a decline of 0.85% compared to a population of 186,611 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Mobile decreased by 20,041. In this period, the peak population was 203,330 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Mobile is shown in this column.
• Year on Year Change: This column displays the change in Mobile population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mobile Population by Year. You can refer the same here

Dataset Description: Smartphone Sales Transactions

This dataset contains information about smartphone sales transactions. Each row represents a unique transaction and includes detailed data points such as the date of the transaction, product details, customer demographics, payment methods, and customer ratings. The dataset can be useful for sales analysis, customer behavior study, and market trend prediction.

Columns:

Transaction ID – Unique identifier for each transaction.

Day – Day of the month when the transaction occurred.

Month – Month of the transaction.

Year – Year of the transaction.

Day Name – Name of the day (e.g., Saturday).

Brand – Smartphone brand sold (e.g., Xiaomi, Vivo).

Units Sold – Number of smartphone units sold in the transaction.

Price Per Unit – Selling price per unit (in local currency).

Customer Name – Name of the customer.

Customer Age – Age of the customer.

City – City where the transaction took place.

Payment Method – Method used for payment (e.g., UPI, Credit Card).

Customer Ratings – Rating given by the customer (1–5 scale).

Mobile Model – Specific model of the smartphone sold.

Lebanon Number Data is a list of phone numbers that you can filter in many ways. You can filter by gender, age, or even relationship status. To contact young people, filter the list to show only numbers from that age group. This helps you connect with the right individual quickly. The list also follows GDPR rules, which means it protects people’s privacy. Furthermore, we regularly update the Lebanon Number Data for clarity. It removes invalid numbers, saving time by avoiding outdated contact details. This feature keeps the list fresh and up-to-date and makes your work more efficient. With Lebanon contact data, you can trust accurate, up-to-date details and filter them to meet your needs. Lebanon phone data is a collection of phone numbers that is 100% correct and valid. The companies that provide this data check every number carefully to make sure it works. So, when you use this cellphone data, you don’t have to worry about the wrong numbers. If, for some reason, a number doesn’t work, you get a replacement guarantee. This means, if a number is invalid, they will give you a new dialing number at no extra cost. Moreover, Lebanon phone data comes with all phone number subscribers’ permission. This means the people who own the numbers have agreed to share their information. It’s very important to have this permission because it keeps you out of legal trouble. Using this database without the customer’s permission can be problematic, but this data is safe and secure. Lebanon phone number list is a collection of phone numbers of people living in Lebanon. This list is very helpful for businesses that need to contact people in Lebanon. The information comes from reliable sources, such as government records, websites, and phone service providers. You can even check the URLs where the data came from. This ensures that the phone numbers are accurate. Also, if you need help, 24/7 support is available. Also, the Lebanon phone number list follows the opt-in rule. Number owners know that others use their info, making it safe to use the data. You won’t face any trouble, and it respects people’s privacy. Using the Lebanon contact number list from our List to Data website, you can confidently connect with the right people.

About this dataset

Context

The dataset tabulates the data for the Mobile, AL population pyramid, which represents the Mobile population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Mobile, AL, is 27.2.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Mobile, AL, is 26.2.
• Total dependency ratio for Mobile, AL is 53.4.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Mobile, AL is 3.8.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Mobile population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Mobile for the selected age group is shown in the following column.
• Population (Female): The female population in the Mobile for the selected age group is shown in the following column.
• Total Population: The total population of the Mobile for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Mobile Population by Age. You can refer the same here

This study engaged 409 participants over a period spanning from July 10 to August 8, 2023, ensuring representation across various demographic factors: 221 females, 186 males, 2 non-binary, year of birth between 1951 and 2005, with varied annual incomes and from 15 Spanish regions. The MobileWell400+ dataset, openly accessible, encompasses a wide array of data collected via the participants' mobile phone, including demographic, emotional, social, behavioral, and well-being data. Methodologically, the project presents a promising avenue for uncovering new social, behavioral, and emotional indicators, supplementing existing literature. Notably, artificial intelligence is considered to be instrumental in analysing these data, discerning patterns, and forecasting trends, thereby advancing our comprehension of individual and population well-being. Ethical standards were upheld, with participants providing informed consent.

The following is a non-exhaustive list of collected data:

Data continuously collected through the participants' smartphone sensors: physical activity (resting, walking, driving, cycling, etc.), name of detected WiFi networks, connectivity type (WiFi, mobile, none), ambient light, ambient noise, and status of the device screen (on, off, locked, unlocked).

Data corresponding to an initial survey prompted via the smartphone, with information related to demographic data, effects and COVID vaccination, average hours of physical activity, and answers to a series of questions to measure mental health, many of them taken from internationally recognised psychological and well-being scales (PANAS, PHQ, GAD, BRS and AAQ), social isolation (TILS) and economic inequality perception.

Data corresponding to daily surveys prompted via the smartphone, where variables related to mood (valence, activation, energy and emotional events) and social interaction (quantity and quality) are measured.

Data corresponding to weekly surveys prompted via the smartphone, where information on overall health, hours of physical activity per week, lonileness, and questions related to well-being are asked.

Data corresponding to an final survey prompted via the smartphone, consisting of similar questions to the ones asked in the initial survey, namely psychological and well-being items (PANAS, PHQ, GAD, BRS and AAQ), social isolation (TILS) and economic inequality perception questions.

For a more detailed description of the study please refer to MobileWell400+StudyDescription.pdf.

For a more detailed description of the collected data, variables and data files please refer to MobileWell400+FilesDescription.pdf.

Uruguay number dataset has accurate numbers attached with verified through our team. Most importantly, these cell phone numbers belong to active users only. In fact, these specialties make it a valuable marketing help. if your business is new or old, you can increase your reach and connect to a large audience with this directory. Yet, you will find many people who have an attraction to your products and will purchase from you. The Uruguay number dataset will support you make your brand more renowned. In general, by becoming a known brand in the market, you can grow your brand value significantly. In other words, the contacts on this mobile number list are active and real. As a result, you will benefit greatly if you purchase this cheap but valuable database. Uruguay phone data can be a great solution for telemarketing. Anyone can use the contact lead to reach various people all over the country. Uruguay phone data allows you to give product details with your messages to make them more appealing and reliable. Your product quality and content will increase the awareness of the interested client. Our team gives the number lead in an Excel and CSV file. Uruguay phone data is an opt-in and permission-based contact list. Even, with a cheap yet fresh list like ours, your SMS marketing will be more influential. People can now relate to your business more after you successfully utilize this library from our website. So, order this number package now from List To Data to promote your goods and services everywhere inside the country. Uruguay phone number list is a massive database. However, many people will show interest in your products and services. We promise you sincere service and active support, we create it following GDPR rules. Our special team will solve the issue for you, thus you don’t have to worry about not obtaining the worth of your money. Further, the Uruguay phone number list will aid your business in many new ways. On the other hand, no one wants to miss out on such a huge and versatile audience in Uruguay. To this end, purchasing this contact list will be a gem for any business any day.

Discover the ultimate resource for your B2B needs with our meticulously curated dataset, featuring 148MM+ highly relevant US B2B Contact Data records and associated company information.

Very high fill rates for Phone Number, including for Mobile Phone!

This encompasses a diverse range of fields, including Contact Name (First & Last), Work Address, Work Email, Personal Email, Mobile Phone, Direct-Dial Work Phone, Job Title, Job Function, Job Level, LinkedIn URL, Company Name, Domain, Email Domain, HQ Address, Employee Size, Revenue Size, Industry, NAICS and SIC Codes + Descriptions, ensuring you have the most detailed insights for your business endeavors.

Key Features:

Extensive Data Coverage: Access a vast pool of B2B Contact Data records, providing valuable information on where the contacts work now, empowering your sales, marketing, recruiting, and research efforts.

Versatile Applications: Leverage this robust dataset for Sales Prospecting, Lead Generation, Marketing Campaigns, Recruiting initiatives, Identity Resolution, Analytics, Research, and more.

Phone Number Data Inclusion: Benefit from our comprehensive Phone Number Data, ensuring you have direct and effective communication channels. Explore our Phone Number Datasets and Phone Number Databases for an even more enriched experience.

Flexible Pricing Models: Tailor your investment to match your unique business needs, data use-cases, and specific requirements. Choose from targeted lists, CSV enrichment, or licensing our entire database or subsets to seamlessly integrate this data into your products, platform, or service offerings.

Strategic Utilization of B2B Intelligence:

Sales Prospecting: Identify and engage with the right decision-makers to drive your sales initiatives.

Lead Generation: Generate high-quality leads with precise targeting based on specific criteria.

Marketing Campaigns: Amplify your marketing strategies by reaching the right audience with targeted campaigns.

Recruiting: Streamline your recruitment efforts by connecting with qualified candidates.

Identity Resolution: Enhance your data quality and accuracy by resolving identities with our reliable dataset.

Analytics and Research: Fuel your analytics and research endeavors with comprehensive and up-to-date B2B insights.

Access Your Tailored B2B Data Solution:

Reach out to us today to explore flexible pricing options and discover how Salutary Data Company Data, B2B Contact Data, B2B Marketing Data, B2B Email Data, Phone Number Data, Phone Number Datasets, and Phone Number Databases can transform your business strategies. Elevate your decision-making with top-notch B2B intelligence.