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.

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.

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

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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.

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.

After fierce competition among vivo, Samsung, and Xiaomi over the past few years, vivo became the leading smartphone brand in India. Vivo led the market in the last three quarters. However, in the first two quarters of 2024, Xiaomi and Samsung ranked as high as or higher than Vivo. Aside from Samsung, the other four top smartphone brands are Chinese. Smartphone market share in India The number of smartphone users in India, the most populous country in the world, was on the rise. In 2023, the number of smartphone users in the country surpassed one billion for the first time. This figure was forecasted to jump to nearly 1.55 billion by 2040. And, around seven percent of the population in India purchase their phones online. This growth can also be observed in the volume of smartphone shipments in India. The number of smartphone shipments in India increased from four million units in the second quarter of 2012 to 47 million units in the third quarter of 2024. Major players South Korean giant Samsung, a leader in the global smartphone market, had been the top smartphone vendor in India since early 2013, when the company held about 30 percent of the market share, until the end of 2017. But its position has been challenged by the Chinese smartphone manufacturers like vivo, Xiaomi and OPPO. Vivo is a Chinese tech company based in Guangdong. It's one of the top five smartphone manufacturers in the world. And Xiaomi has quickly risen to the top of China's crowded technology market and is now one of the leading consumer electronics manufacturers globally, since its founding in 2010. Xiaomi specializes primarily in smartphones, but is also active in other markets, and it started manufacturing electric vehicles in 2023.

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.

TechCorner Mobile Purchase & Engagement Data (2024-2025)

Context

TechCorner Mobile Sales & Customer Insights is a real-world dataset capturing 10 months of mobile phone sales transactions from a retail shop in Bangladesh. This dataset was designed to analyze customer location, buying behavior, and the impact of Facebook marketing efforts.

The primary goal was to identify whether customers are from the local area (Rangamati Sadar, Inside Rangamati) or completely outside Rangamati. Since TechCorner operates a Facebook page, the dataset also includes insights into whether Facebook marketing is effectively reaching potential buyers.

Additionally, the dataset helps in determining: ✔ How many customers are new vs. returning buyers ✔ If customers are followers of the shop’s Facebook page ✔ Whether a customer was recommended by an existing buyer

This dataset is valuable for:

Retail sales analysis to understand product demand fluctuations.

Marketing impact measurement (Facebook engagement vs. actual purchase behavior).

Customer segmentation (local vs. non-local buyers, social media influence, word-of-mouth impact).

Sales trend analysis based on preferred phone models and price ranges.

With a realistic, non-uniform distribution of daily sales and some intentional missing values, this dataset reflects actual retail business conditions rather than artificially smooth AI-generated data.

Marketing & Customer Queries

Does he/she Come from Facebook Page? → Whether the customer came from a Facebook page (Yes/No). Used to analyze Facebook marketing reach.

Does he/she Followed Our Page? → Whether the customer is already a follower of the shop’s Facebook page (Yes/No). Helps measure brand loyalty and organic engagement.

Did he/she buy any mobile before? → Whether the customer is a repeat buyer (Yes/No). Determines the percentage of returning customers.

Did he/she hear of our shop before? → Whether the customer knew about the shop before purchasing (Yes/No). Identifies the impact of referrals or previous marketing efforts.

Was this customer recommended by an old customer? → Whether an existing customer referred them to the shop (Yes/No). Helps evaluate the effectiveness of word-of-mouth marketing.

Acknowledgements

This dataset is derived from real-world mobile sales transactions recorded at TechCorner, a retail shop in Bangladesh. It accurately reflects customer purchasing behavior, pricing trends, and the effectiveness of Facebook marketing in driving sales. Special appreciation to TechCorner for providing comprehensive insights into daily sales patterns, customer demographics, and market dynamics.

This dataset can be used for:

📊 Predictive modeling of sales trends based on customer demographics and marketing channels. 📈 Marketing effectiveness analysis (impact of Facebook promotions vs. organic sales). 🔍 Clustering customers based on purchasing habits (new vs. returning buyers, Facebook users vs. walk-ins). 📌 Understanding demand for different smartphone brands in a local retail market. 🚀 Analyzing how word-of-mouth recommendations influence new customer acquisition.

💡 Can you build a model to predict if a customer is likely to return? 💬 How effective is Facebook in driving actual sales compared to walk-ins? 🔍 Can we cluster customers based on behavior and brand preferences?

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.

Global B2B Mobile Phone Number Database | 100M+ Verified Contacts | 95% Accuracy Forager.ai provides the world’s most reliable mobile phone number data for businesses that refuse to compromise on quality. With 100 million+ professionally verified mobile numbers refreshed every 3 weeks, our database ensures 95% accuracy – so your teams never waste time on dead-end leads.

Why Our Data Wins ✅ Accuracy You Can Trust 95% of mobile numbers are verified against live carrier records and tied to current job roles. Say goodbye to “disconnected number” voicemails.

✅ Depth Beyond Digits Each contact includes 150+ data points:

Direct mobile numbers

Current job title, company, and department

Full career history + education background

Location data + LinkedIn profiles

Company size, industry, and revenue

✅ Freshness Guaranteed Bi-weekly updates combat job-hopping and role changes – critical for sales teams targeting decision-makers.

✅ Ethically Sourced & Compliant First-party collected data with full GDPR/CCPA compliance.

Who Uses This Data?

Sales Teams: Cold-call C-suite prospects with verified mobile numbers.

Marketers: Run hyper-personalized SMS/WhatsApp campaigns.

Recruiters: Source passive candidates with up-to-date contact intel.

Data Vendors: License premium datasets to enhance your product.

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PostgreSQL: Custom databases for large-scale enrichment

Compliance: Full audit trails + opt-out management

Why Forager.ai? → Proven ROI: Clients see 62% higher connect rates vs. industry averages (request case studies). → No Guesswork: Test-drive free samples before committing. → Scalable Pricing: Pay per record, license datasets, or get unlimited API access.

B2B Mobile Phone Data | Verified Contact Database | Sales Prospecting Lists | CRM Enrichment | Recruitment Phone Numbers | Marketing Automation | Phone Number Datasets | GDPR-Compliant Leads | Direct Dial Contacts | Decision-Maker Data

Need Proof? Contact us to see why Fortune 500 companies and startups alike trust Forager.ai for mission-critical outreach.

Dive into the world of customer insights with the Amazon Mobile Phones Reviews Dataset. This dataset provides comprehensive information on mobile phone reviews available on Amazon, helping businesses, researchers, and analysts unlock the power of consumer feedback.

What Does the Dataset Offer?

The Amazon Mobile Phones Reviews Dataset includes:

• Product Details: Mobile phone names, specifications, and brand information.
• Customer Reviews: Detailed texts highlighting user experiences, likes, and dislikes.
• Ratings: Star ratings provided by customers, reflecting overall satisfaction.
• Sentiment Analysis Potential: The dataset is rich in data points, making it ideal for sentiment analysis and trend tracking.

Use Cases of the Dataset

• Product Improvement: Understand customer expectations and identify areas where mobile phones fall short, enabling businesses to optimize their offerings.
• Market Research: Stay ahead in the competitive landscape by analyzing consumer preferences and emerging trends in the mobile phone industry.
• Competitive Benchmarking: Use the dataset to compare reviews across different brands and identify what makes top products stand out.

Why Choose This Dataset?

Whether you’re a tech company looking to improve product features or a researcher analyzing market trends, the Amazon product review dataset for mobile phones provides the necessary data for meaningful insights. This structured dataset, often available in formats like CSV, makes it easy to integrate with analytics tools for seamless data exploration.

Additional Value for Researchers

The Amazon Mobile Phones Reviews Dataset doesn’t just focus on reviews. It helps researchers uncover sentiment patterns, understand consumer language, and even predict future buying behaviors based on historical data.

For a more detailed analysis, combine this dataset with our broader Amazon product review dataset, which includes reviews across categories for a holistic market view.

Looking to gain insights into the world of mobile phones? Look no further than our comprehensive dataset, which provides detailed specifications and prices for a wide range of smartphones. With data on everything from screen size and camera quality to battery life and processing power, this dataset is a must-have for anyone interested in the mobile phone market. Whether you're a researcher, a tech enthusiast, or just looking to make an informed purchase, our data will give you the information you need to make smart decisions. So why wait? Download our dataset today and start exploring the world of mobile phones like never before! The prices are in PKR. as the dataset is extracted from Pakistan Mobile market website

This is a complementary dataset for DOI: 10.1007/978-3-030-22335-9_6 Following an open data policy as supported by the European Union (https://www.openaire.eu/), this is the dataset used for the following conference paper: Zimmermann R., Auinger A., Riedl R. (2019) Smartphones as an Opportunity to Increase Sales in Brick-and-Mortar Stores: Identifying Sales Influencers Based on a Literature Review. In: Nah FH., Siau K. (eds) HCI in Business, Government and Organizations. eCommerce and Consumer Behavior. HCII 2019. Lecture Notes in Computer Science, vol 11588. Springer, Cham The present work was conducted within the Innovative Training Network project PERFORM funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765395. The EU Research Executive Agency is not responsible for any use that may be made of the information it contains.

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.

Comprehensive dataset tracking mobile device share of Black Friday ecommerce sales from 2020 to 2024, including conversion rates, traffic percentages, year-over-year growth, and demographic breakdowns by generation. Data sourced from Adobe Analytics, Salesforce, and Digital Commerce 360.

This dataset captures retail sales performance data for mobile phones across different regions, brands, and time periods. It can be used for sales trend analysis, forecasting, and customer behavior modeling.

This is a simulated/commercial dataset, not tied to a specific retailer, and can be used for academic or learning purposes.

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.

Comprehensive dataset tracking mobile device share of Cyber Monday online sales from 2019 to 2024, including total sales figures, mobile sales volumes, year-over-year growth rates, and key performance metrics such as conversion rates, page load times, and BNPL transaction data.

Mobile Phone Dataset | Smartphone & Feature Phone

Crowdsourced original images of a wide variety of mobile phones

About Dataset

This dataset is collected by* DataCluster Labs*, India. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 3000+ original Mobile Phone images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.

Dataset Features 1. Dataset size : 3000+ 2. Captured by : Over 1000+ crowdsource contributors 3. Resolution : 99% images HD and above (1920x1080 and above) 4. Location : Captured with 600+ cities accross India 5. Diversity : Various lighting conditions like day, night, varied distances, view points etc. 6. Device used : Captured using mobile phones in 2020-2021 7. Applications : Mobile Phone detection, cracked screen detection, etc.

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai

Visit www.datacluster.ai to know more.

In 2024, the total amount of smartphone shipments reached *** billion units worldwide. Global smartphone shipments worldwide The global smartphone market saw an exceptional growth from 2009, when *** million smartphones were shipped worldwide to 2016 when smartphone shipments amounted to **** billion. Much of this increase can be attributed to the iPhone release in 2007. With its consumer-friendly design, Apple introduced multimedia functions to smartphones, offering more than basic features such as e-mail and web browsing. Apple’s release pushed the competitors to respond with new models, and started to shape the consumers’ habits. This shift can be observed in smartphone vendors’ shipment figures. Nokia and Blackberry/RIM – previous leaders in smartphone shipments – saw their figures slowly decrease over the years, whereas Samsung and Apple increased their market share. In 2024, Apple nearly ** percent of the global market share, and Samsung accounted for nearly ** percent.Google’s Android is the most popular smartphone operating system in the world. As of the fourth quarter of 2024, Android held over ** percent of the global smartphone OS market, whereas Apple dominated less than ** percent.