The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 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 Mexico and Canada.

Percentage of smartphone users by selected smartphone use habits in a typical day.

The global smartphone penetration in was forecast to continuously increase between 2024 and 2029 by in total 20.3 percentage points. After the fifteenth consecutive increasing year, the penetration is estimated to reach 74.98 percent and therefore a new peak 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 North America and the Americas.

Description for each of the variables:

1. Brands: The brands of smartphones included in the dataset.
2. Colors: The colors available for the smartphones.
3. Memory: The storage capacity of the smartphones, typically measured in gigabytes (GB) or megabytes (MB).
4. Storage: The internal storage capacity of the smartphones, often measured in gigabytes (GB) or megabytes (MB).
5. Rating: The user ratings or scores assigned to the smartphones, reflecting user satisfaction or performance.
6. Selling Price: The price at which the smartphones are sold to consumers.
7. Original Price: The original or list price of the smartphones before any discounts or promotions.
8. Mobile: Indicates whether the device is a mobile phone.
9. Discount: The discount applied to the original price to calculate the selling price.
10. Discount percentage: The percentage discount applied to the original price to calculate the selling price.

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 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.

We will create a customized phones dataset tailored to your specific requirements. Data points may include brand names, model specifications, pricing information, release dates, market availability, feature sets, and other relevant metrics.

Utilize our phones datasets for a variety of applications to boost strategic planning and market analysis. Analyzing these datasets can help organizations grasp consumer preferences and technological trends within the mobile phone industry, allowing for more precise product development and marketing strategies. You can choose to access the complete dataset or a customized subset based on your business needs.

Popular use cases include: enhancing competitive benchmarking, identifying pricing trends, and optimizing product portfolios.

Percentage of Canadians using a smartphone for personal use and selected habits of use during a typical day.

About Dataset

This dataset contains information about mobile phones available in Ghana, including details about various phone models, their specifications, and pricing. The data was collected through web scraping, providing a comprehensive overview of the mobile phone market in Ghana.

Key Features

• Brand & Model: The dataset includes details on various phone models from different brands, allowing users to explore a wide range of options.

• Specifications: Detailed phone specifications are provided, such as whether the phone supports an SD card, the main camera setup, resolution, display type, SIM card configuration, operating system, color options, and more.

• Geographical Information: Users can filter and analyze the dataset based on region and location in Ghana, making it useful for understanding the availability of different phone models in specific areas.

• Hardware & Software: Essential hardware features like screen size (in inches), battery capacity (in mAh), storage (in GB), RAM (in GB), and selfie camera resolution (in MP) are included.

• Pricing: The dataset also provides pricing information (in Ghanaian Cedis - ¢), enabling users to compare the cost of various phone models.

This dataset is valuable for consumers, researchers, and businesses interested in the mobile phone market in Ghana. It can be used for market analysis, consumer insights, and decision-making related to mobile phone purchases. Researchers can also use the data for further analysis and modeling.

The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 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 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 Australia & Oceania and Asia.

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.

Records of one cellphone user in the mobile phone data.

The average time spent daily on a phone, not counting talking on the phone, has increased in recent years, reaching a total of * hours and ** minutes as of April 2022. This figure was expected to reach around * hours and ** minutes by 2024.

Dataset Overview: A collection of features characterizing mobile phones, including battery power, camera specifications, network support, memory, screen dimensions, and other attributes. The 'price_range' column categorizes phones into price ranges, making this dataset suitable for mobile phone classification and price prediction tasks.

Model:

Description: The name of the smartphone model. Example: "Samsung Galaxy S21", "iPhone 13", "Google Pixel 6". Notes: This is a categorical variable that uniquely identifies each phone. Price:

Description: The cost of the smartphone, typically in the local currency (e.g., USD). Example: 999, 799, 699. Notes: This is a numerical variable, which can be used to analyze the affordability and market positioning of different models. RAM:

Description: The amount of random-access memory (RAM) in the smartphone, typically measured in gigabytes (GB). Example: 4 GB, 8 GB, 12 GB. Notes: This numerical variable impacts the phone's ability to handle multiple tasks simultaneously and affects overall performance. Display:

Description: The specifications of the smartphone's display, often given in terms of size (in inches) and resolution. Example: "6.1 inches, 1080x2400 pixels". Notes: This variable is usually a mix of numerical and categorical data, reflecting the screen size and resolution. Rear Camera:

Description: The specifications of the main (rear) camera(s), often including the number of cameras, megapixels (MP), and other features (e.g., wide-angle, telephoto). Example: "12 MP + 12 MP dual", "108 MP". Notes: This is often a categorical variable with numerical components, indicating the camera's capabilities. Front Camera:

Description: The specifications of the front (selfie) camera, typically measured in megapixels. Example: "10 MP", "32 MP". Notes: Similar to the rear camera, this is a categorical variable with numerical components, indicating the quality of the front camera. Battery:

Description: The battery capacity of the smartphone, typically measured in milliampere-hours (mAh). Example: 4000 mAh, 5000 mAh. Notes: This numerical variable impacts the phone's battery life and usage duration. Processor:

Description: The type and model of the smartphone's processor (CPU). Example: "Snapdragon 888", "Apple A14 Bionic". Notes: This categorical variable indicates the processing power and efficiency of the phone. Star Ratings:

Description: The average user rating of the smartphone, typically on a scale from 1 to 5 stars. Example: 4.5, 3.8. Notes: This numerical variable reflects user satisfaction and can be used to gauge the overall reception of the phone. Ratings:

Description: The total number of user ratings received for the smartphone. Example: 1500, 5000. Notes: This numerical variable indicates the popularity and extent of user feedback.

Objective: The goal of this study was to compare cell phone usage behaviors while driving across 3 types of cell phones: handheld (HH) cell phones, portable hands-free (PHF) cell phones, and integrated hands-free (IHF) cell phones. Naturalistic driving data were used to observe HH, PHF, and IHF usage behaviors in participants’ own vehicles without any instructions or manipulations by researchers.Methods: In addition to naturalistic driving data, drivers provided their personal cell phone call records. Calls during driving were sampled and observed in naturalistically collected video. Calls were reviewed to identify cell phone type used for, and duration of, cell phone subtasks, non–cell phone secondary tasks, and other use behaviors. Drivers in the study self-identified as HH, PHF, or IHF users if they reported using that cell phone type at least 50% of the time. However, each sampled call was classified as HH, PHF, or IHF if the talking/listening subtask was conducted using that cell phone type, without considering the driver's self-reported group.Results: Drivers with PHF or IHF systems also used HH cell phones (IHF group used HH cell phone in 53.2% of the interactions, PHF group used HH cell phone for 55.5% of interactions). Talking/listening on a PHF phone or an IHF phone was significantly longer than talking/listening on an HH phone (P <.05). HH dialing was significantly longer in duration than PHF or IHF begin/answer tasks. End phone call task for HH phones was significantly longer in duration than the end phone call task for PHF and IHF phones. Of all the non–cell phone–related secondary tasks, eating or drinking was found to occur significantly more often during IHF subtasks (0.58%) than in HH subtasks (0.15%). Drivers observed to reach for their cell phone mostly kept their cell phone in the cup holder (36.3%) or in their seat or lap (29.0% of interactions); however, some observed locations may have required drivers to move out of position.Conclusions: Hands-free cell phone technologies reduce the duration of cell phone visual–manual tasks compared to handheld cell phones. However, drivers with hands-free cell phone technologies available to them still choose to use handheld cell phones to converse or complete cell phone visual–manual tasks for a noteworthy portion of interactions.

We present the dataset for the article "Keep on scrolling? Using intensive longitudinal smartphone sensing data to assess how everyday smartphone usage behaviors are related to well-being". The data were collected as part of the Smartphone Sensing Panel Study and comprise several dataset parts, as we replicated our analysis for two different 14-day measurement periods (A and B). At the macro level, we aggregated different measures of smartphone use (measured by mobile sensing) over 14 days and examined their associations with global survey-based measures of well-being (Flourishing, Satisfaction WIth Life, Positive Activation, Negative Activation, Valence; Dataset A: N = 236, Dataset B: N = 305). At the micro level, we aggregated various measures of smartphone use (measured via mobile sensing) over 60-minute windows before asking participants about their current mood using experience sampling questionnaires (Dataset A: N = 378, n = 5775; Dataset B: N = 534, n = 7287). In our supplementary analysis, we also aggregated the smartphone usage data for 15-minute windows to analyse social and non-social situations. Demographic variables (age, gender, education) that were not used for the data analyses were removed for privacy reasons, but can be provided upon request. The datasets are documented by a comprehensive accompanying codebook. Additional materials (e.g., preprocessing and analysis code) can also be found at https://osf.io/ckwge/ Further details on the variables provided and the associated study procedures can be found in the journal article: große Deters, F., & Schoedel, R. (2024). Keep on scrolling? Using intensive longitudinal smartphone sensing data to assess how everyday smartphone usage behaviors are related to well-being, Computers in Human Behavior, 150, 107977, https://doi.org/10.1016/j.chb.2023.107977

Data is cleaned. All inconsistencies and erroneous records have been removed. These two datasets are used to see how the composition of the contact-book of emergent users differ from those of traditional users in aspects like its size, prevalence use of special symbols, the proportion of dialed contacts through the phone-book, and percentage of unintelligible contact names, etc. Aggregated data for 30 emergent users and 30 traditional users is provided in the form of CSV files to replicate the data analysis results. To reproduce the graphs for usability analysis, R scripts are also provided in the same repository. These scripts contain the required data vectors. These graphs show the efficiency, effectiveness, and satisfaction of emergent users on conventional contact-book interfaces.

📄 Dataset Description: Smartprix Mobile Dataset Title: Smartprix Mobile Dataset Source: https://www.smartprix.com/mobiles License: Apache 2.0

📝 Overview This dataset contains detailed specifications of mobile phones scraped from Smartprix — a popular product comparison site. The data includes technical specifications, pricing, and ratings for a wide range of mobile devices available in the Indian market.

📦 Columns Included Column Name Description Name Full name of the smartphone Price Price in Indian Rupees (INR) Rating User rating (if available) SIM SIM type (Dual/Single SIM, 4G/5G supported) Processor Chipset used in the phone (e.g., Snapdragon 8 Gen 1) RAM Amount of RAM Battery Battery capacity (e.g., 5000 mAh) Display Display size and resolution Camera Primary camera specification Card Expandable storage support (e.g., microSD) OS Operating system (e.g., Android 13)

📊 Potential Use Cases Market trend analysis for mobile phones

Feature comparison across brands

Recommendation systems for e-commerce

NLP applications (e.g., generating product summaries)

⚠️ Disclaimer This dataset was collected using publicly available data from Smartprix.com and is intended for educational and research purposes only. Ensure compliance with the source’s terms of service before commercial use.

This dataset provides statistics on the use and allocation of various telecommunications numbers, including codes (network mobile codes, portable network codes, signal point codes), identification codes (dial-up network identification codes, special service numbers), user numbers (mobile phone numbers, landline numbers, Internet of Things numbers, network telephone numbers), to be used for analysis and utilization by data users.