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This synthetic yet realistic dataset offers insights into smartphone features, customer reviews, and sales data. It includes over 90 customer reviews for six popular smartphone models from leading brands such as Apple, Samsung, and Google. The dataset is designed to help understand how various product specifications influence purchasing decisions and overall customer satisfaction. It combines detailed product specifications, customer star ratings, review texts, and verified purchase status with estimated sales figures per model.
The dataset is typically provided in a CSV file format. It comprises over 90 customer review records, along with corresponding smartphone product specifications and sales data for 6 distinct phone models. The exact total number of rows or the specific file size in MB/GB is not specified.
This dataset is ideal for various analytical applications, including: * Feature importance analysis: Determining which smartphone specifications (e.g., battery life, camera quality) most significantly influence customer ratings and purchasing decisions. * Sentiment analysis: Applying Natural Language Processing (NLP) techniques to extract insights and sentiment from customer review texts. * Pricing strategy optimisation: Analysing the correlation between price and customer satisfaction or sales volume. * Market research: Comparing performance and customer perception across different brands (e.g., Apple vs. Samsung vs. Google) and models. * Sales vs. features correlation: Investigating how product features and pricing impact estimated units sold.
This dataset has a Global region coverage. It includes data pertaining to six smartphone models from three major brands: Apple (iPhone 14, iPhone 15), Samsung (Galaxy S22, Galaxy S23), and Google (Pixel 7, Pixel 8). The review dates are indicative of data from around 2023. While it includes customer reviews, specific demographic details of the reviewers are not available beyond randomly generated usernames. As a synthetic dataset, it is designed to be realistic for general market analysis.
CC0
This dataset is suitable for: * Data Analysts and Scientists: For performing regression analysis, sentiment analysis, and predictive modelling. * Marketing Professionals: To understand consumer preferences, optimise product features, and refine marketing strategies. * Product Managers: To inform product development, feature prioritisation, and competitive analysis. * Market Researchers: To study market trends, brand comparisons, and consumer behaviour in the smartphone industry. * Academics and Students: For educational purposes and research projects related to consumer electronics, e-commerce, and data analysis.
Original Data Source: Smartphone Feature Optimization (Marketing Mix)
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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.
According to our latest research, the global marketing analytics market size in 2024 stands at USD 5.8 billion, demonstrating robust momentum driven by the increasing adoption of data-driven decision-making across industries. The market is projected to register a CAGR of 13.2% from 2025 to 2033, reaching an estimated market size of USD 17.1 billion by 2033. This accelerated growth is primarily attributed to the proliferation of digital channels, the surge in big data, and the imperative for organizations to achieve higher ROI from their marketing investments. The marketing analytics market is evolving rapidly, with advanced analytics tools enabling businesses to gain actionable insights, optimize campaigns, and enhance customer engagement across diverse sectors.
One of the most significant growth factors for the marketing analytics market is the exponential increase in data generation from multiple digital touchpoints. The rise of omnichannel marketing strategies has resulted in vast and complex datasets, encompassing customer interactions from social media, websites, mobile applications, and email campaigns. Businesses are increasingly leveraging marketing analytics solutions to aggregate, process, and analyze this data in real time, gaining deeper insights into customer behavior, preferences, and purchase patterns. The ability to transform raw data into actionable intelligence is empowering marketers to personalize campaigns, improve targeting accuracy, and maximize conversion rates, thereby fueling the demand for sophisticated analytics platforms.
Another critical driver is the growing emphasis on measuring marketing effectiveness and optimizing marketing spend. As organizations face mounting pressure to justify marketing budgets and demonstrate tangible ROI, marketing analytics tools have become indispensable. These solutions enable marketers to track key performance indicators (KPIs), attribute revenue to specific channels, and identify underperforming campaigns. The integration of artificial intelligence and machine learning into marketing analytics platforms is further enhancing predictive capabilities, allowing businesses to forecast trends, automate campaign adjustments, and refine customer segmentation. This technological evolution is driving widespread adoption across both large enterprises and small and medium businesses.
The surge in regulatory requirements and data privacy concerns is also shaping the marketing analytics market. With the implementation of stringent data protection regulations such as GDPR and CCPA, organizations are compelled to adopt analytics solutions that ensure compliance while maintaining data integrity and security. Modern marketing analytics platforms are incorporating advanced data governance features, encryption, and anonymization techniques, enabling businesses to harness the power of analytics without compromising customer trust. This focus on compliance, coupled with the increasing need for transparency in marketing practices, is accelerating the adoption of analytics tools across regulated industries such as BFSI and healthcare.
Regionally, North America dominates the marketing analytics market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The United States, in particular, is at the forefront due to the presence of major analytics vendors, high digital adoption, and substantial marketing expenditure by enterprises. However, the Asia Pacific region is poised for the fastest growth over the forecast period, driven by rapid digital transformation, expanding e-commerce ecosystems, and increasing investments in marketing technology. Latin America and the Middle East & Africa are also witnessing steady growth as organizations in these regions recognize the strategic value of data-driven marketing.
The marketing analytics market is segmented by component into software and services, each playing a vital role in the overall ecosystem. The software segment dominates th
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In this study, 403 Chinese consumers generalizable to the broader population were surveyed on their motivations to shop for fashion apparel in both high street and e-commerce environments. Statistical analysis was undertaken through multiple T-Tests and MANOVA with the assistance of SPSS and G*Power.
To increase the profits of international brands, this paper presents the motivations of Chinese consumers to engage in fashion retail, building upon established theory in hedonic and utilitarian motivations. With China set to capture over 24% of the $212 billion fashion market, international brands need to understand the unique motivations of Chinese consumers in order to capitalise on the market. However, the motivations of Chinese people to engage in fashion retail are as yet undefined, limiting the ability for international fashion retailers to operate with prosperity in the Chinese market.
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The Database Marketing market is experiencing robust growth, driven by the increasing need for personalized customer experiences and the availability of sophisticated data analytics tools. The market's expansion is fueled by the rising adoption of advanced technologies like AI and machine learning, enabling businesses to segment their audiences more precisely and deliver targeted marketing campaigns. This results in improved customer engagement, higher conversion rates, and ultimately, increased return on investment (ROI). The market is witnessing a shift towards multi-channel strategies, integrating database marketing efforts across various platforms like email, social media, and mobile applications. This omnichannel approach allows businesses to reach their target audience more effectively and create a cohesive brand experience. While data privacy regulations present a challenge, the market is adapting by emphasizing transparency and consent-based marketing practices. Key players are innovating to enhance data security and compliance, ensuring ethical and responsible use of customer data. We estimate the current market size (2025) at approximately $15 billion, with a Compound Annual Growth Rate (CAGR) of 12% projecting a market size of over $30 billion by 2033. This growth is projected across various segments, including software, services, and consulting, with significant contributions from North America and Europe. The competitive landscape is marked by both established players like Adobe (Marketo) and Oracle, and emerging companies focusing on niche solutions and specialized technologies. These companies are constantly innovating to offer advanced functionalities such as predictive analytics, customer journey mapping, and real-time personalization. The strategic partnerships and acquisitions within the industry indicate a dynamic and rapidly evolving market. To maintain a competitive edge, companies are prioritizing investment in research and development, focusing on improving their platforms' capabilities and expanding their service offerings to meet the evolving needs of businesses. The future of database marketing hinges on responsible data usage, continuous technological advancements, and a focus on delivering personalized and engaging customer experiences.
Unlock the power of direct engagement with our comprehensive dataset of 34 million verified global phone numbers. This dataset is curated for businesses and data-driven teams looking to enhance customer acquisition, power targeted outreach, enrich CRM records, and fuel B2C growth at scale.
Whether you're running SMS marketing campaigns, telemarketing, building a mobile app user base, or performing identity validation, this dataset offers a scalable, compliant foundation to reach real users worldwide.
🔍 What’s Included: ✅ 34,000,000+ mobile and landline numbers
🌍 Global coverage, including high volumes from the US, UK, Canada, Europe, and emerging markets
🧹 Clean, structured format (CSV/JSON/SQL) for easy integration
📱 Includes carrier, country code, line type, and location data (where available)
🧠 Ideal Use Cases: B2C & D2C marketing campaigns
SMS and voice call outreach
Lead generation & prospecting
Mobile app user acquisition
Identity verification & enrichment
Market analysis and segmentation
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The app analytics market, valued at $7.29 billion in 2025, is experiencing robust growth, projected to expand at a compound annual growth rate (CAGR) of 21.09% from 2025 to 2033. This surge is driven by several key factors. The increasing adoption of mobile applications across diverse industries, coupled with the rising need for businesses to understand user behavior and optimize app performance, fuels the demand for sophisticated analytics solutions. Furthermore, advancements in data analytics technologies, including artificial intelligence (AI) and machine learning (ML), are enabling more insightful and actionable data analysis, further propelling market expansion. The diverse application of app analytics across marketing/advertising, revenue generation, and in-app performance monitoring across various sectors like BFSI, e-commerce, media, travel and tourism, and IT and telecom significantly contributes to this growth. The market is segmented by deployment (mobile apps and website/desktop apps) and end-user industry, with mobile app analytics currently dominating due to the widespread adoption of smartphones. The competitive landscape is characterized by a mix of established technology giants like Google and Amazon alongside specialized app analytics providers like AppsFlyer and Mixpanel. These companies are continuously innovating, integrating new technologies, and expanding their product offerings to cater to the evolving needs of businesses. While the North American market currently holds a significant share, the Asia-Pacific region is expected to witness substantial growth in the coming years driven by increasing smartphone penetration and digitalization initiatives. However, factors like data privacy concerns and the rising complexity of integrating various analytics tools could pose challenges to market growth. Nonetheless, the overall outlook for the app analytics market remains positive, indicating substantial opportunities for players across the value chain. Recent developments include: June 2024 - Comscore and Kochava unveiled an innovative performance media measurement solution, providing marketers with enhanced insights. This cutting-edge cross-screen solution empowers marketers to understand better how linear TV ad campaigns impact both online and offline actions. By integrating Comscore’s Exact Commercial Ratings (ECR) data with Kochava’s sophisticated marketing mix modeling, the solution facilitates the measurement of crucial metrics, including mobile app activities (such as installs and in-app purchases) and website interactions., June 2024 - AppsFlyer announced its integration of the Data Collaboration Platform with Start.io, an omnichannel advertising platform that focuses on real-time mobile audiences for publishers. Through this collaboration, businesses leveraging the AppsFlyer Data Collaboration Platform can merge their Start.io data with campaign metrics and audience insights, creating a more comprehensive dataset for precise audience targeting.. Key drivers for this market are: Increasing Usage of Mobile/Web Apps Across Various End-user Industries, Increasing Adoption of Technologies like 5G Technology and Deeper Penetration of Smartphones; Increase in the Amount of Time Spent on Mobile Devices Coupled With the Increasing Focus on Enhancing Customer Experience. Potential restraints include: Increasing Usage of Mobile/Web Apps Across Various End-user Industries, Increasing Adoption of Technologies like 5G Technology and Deeper Penetration of Smartphones; Increase in the Amount of Time Spent on Mobile Devices Coupled With the Increasing Focus on Enhancing Customer Experience. Notable trends are: Media and Entertainment Industry Expected to Capture Significant Share.
Solution Publishing by Allforce: Marketing Professionals
Redefining B2B Marketing and Advertising Outreach
Connect with over 2 million U.S. marketing and advertising contacts across approximately 500,000 companies.
Extensive Marketing Specialties Coverage
Our database encompasses professionals in: - Market Research and Analysis - Brand Management - Product Marketing - Content Creation and Management - Social Media and Digital Marketing - Advertising and Public Relations - SEO/SEM and Analytics - CRM and Marketing Operations - Strategic Planning - Creative Design - Email and Influencer Marketing - Partnership Marketing
Comprehensive Contact Information
Multi-Channel Marketing Capabilities
Execute campaigns through email, direct mail, telemarketing, mobile, and digital advertising channels.
All data is maintained for compliance and safe for email marketing
Success.ai’s Phone Number Data offers direct access to over 50 million verified phone numbers for professionals worldwide, extracted from our expansive collection of 170 million profiles. This robust dataset includes work emails and key decision-maker profiles, making it an essential resource for companies aiming to enhance their communication strategies and outreach efficiency. Whether you're launching targeted marketing campaigns, setting up sales calls, or conducting market research, our phone number data ensures you're connected to the right professionals at the right time.
Why Choose Success.ai’s Phone Number Data?
Direct Communication: Reach out directly to professionals with verified phone numbers and work emails, ensuring your message gets to the right person without delay. Global Coverage: Our data spans across continents, providing phone numbers for professionals in North America, Europe, APAC, and emerging markets. Continuously Updated: We regularly refresh our dataset to maintain accuracy and relevance, reflecting changes like promotions, company moves, or industry shifts. Comprehensive Data Points:
Verified Phone Numbers: Direct lines and mobile numbers of professionals across various industries. Work Emails: Reliable email addresses to complement phone communications. Professional Profiles: Decision-makers’ profiles including job titles, company details, and industry information. Flexible Delivery and Integration: Success.ai offers this dataset in various formats suitable for seamless integration into your CRM or sales platform. Whether you prefer API access for real-time data retrieval or static files for periodic updates, we tailor the delivery to meet your operational needs.
Competitive Pricing with Best Price Guarantee: We provide this essential data at the most competitive prices in the industry, ensuring you receive the best value for your investment. Our best price guarantee means you can trust that you are getting the highest quality data at the lowest possible cost.
Targeted Applications for Phone Number Data:
Sales and Telemarketing: Enhance your telemarketing campaigns by reaching out directly to potential customers, bypassing gatekeepers. Market Research: Conduct surveys and research directly with industry professionals to gather insights that can shape your business strategy. Event Promotion: Invite prospects to webinars, conferences, and seminars directly through personal calls or SMS. Customer Support: Improve customer service by integrating accurate contact information into your support systems. Quality Assurance and Compliance:
Data Accuracy: Our data is verified for accuracy to ensure over 99% deliverability rates. Compliance: Fully compliant with GDPR and other international data protection regulations, allowing you to use the data with confidence globally. Customization and Support:
Tailored Data Solutions: Customize the data according to geographic, industry-specific, or job role filters to match your unique business needs. Dedicated Support: Our team is on hand to assist with data integration, usage, and any questions you may have. Start with Success.ai Today: Engage with Success.ai to leverage our Phone Number Data and connect with global professionals effectively. Schedule a consultation or request a sample through our dedicated client portal and begin transforming your outreach and communication strategies today.
Remember, with Success.ai, you don’t just buy data; you invest in a partnership that grows with your business needs, backed by our commitment to quality and affordability.
• 500M B2B Contacts • 35M Companies • 20+ Data Points to Filter Your Leads • 100M+ Contact Direct Dial and Mobile Number • Lifetime Support Until You 100% Satisfied
We are the Best b2b database providers for high-performance sales teams. If you get a fake by any chance, you have nothing to do with them. Nothing is more frustrating than receiving useless data for which you have paid money.
Every 15 days, our devoted team updates our b2b leads database. In addition, we are always available to assist our clients with whatever data they are working with in order to ensure that our service meets their needs. We keep an eye on our b2b contact database to keep you informed and provide any assistance you require.
With our simple-to-use system and up-to-date B2B contact list, we hope to make your job easier. You’ll be able to filter your data at Lfbbd based on the industry you work in. For example, you can choose from real estate companies or just simply tap into the healthcare business. Our database is updated on a regular basis, and you will receive contact information as soon as possible.
Use our information to quickly locate new business clients, competitors, and suppliers. We’ve got your back, no matter what precise requirements you have.
We have over 500 million business-to-business contacts that you may segment based on your marketing and commercial goals. We don’t stop there; we’re always gathering leads from the right tool so you can reach out to a big database of your clients without worrying about email constraints.
Thanks to our database, you may create your own campaign and send as many email or automated messages as you want. We collect the most viable b2b database to help you go a long way, as we seek to increase your business and enhance your sales.
The majority of our clients choose us since we have competitive costs when compared to others. In this digital era, marketing is more advanced, and customers are less willing to pay more for a service that produces poor results.
That’s why we’ve devised the most effective b2b database strategy for your company. You can also tailor your database and pricing to meet your specific business requirements.
• Connect directly with the right decision-makers, using the most accurate database of emails and direct dials. Build a clean prospecting list that you can plug into your sales tools and generate new leads from, right away • Over 500 million business contacts worldwide. • You could filter your targeted leads by 20+ criteria including job title, industry, location, Revenue, Technology, and more. • Find the email addresses of the professionals you want to contact one by one or in bulk.
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The global marketing analytics tools market is experiencing significant growth, with a market size estimated at $2.5 billion in 2023 and projected to reach $6.9 billion by 2032, reflecting a compound annual growth rate (CAGR) of 11.7%. This growth is primarily fueled by the rising demand for data-driven marketing strategies among businesses seeking to enhance customer engagement, improve decision-making, and optimize marketing ROI. As digital transformation continues to accelerate across industries, marketing analytics tools have become indispensable for organizations aiming to maintain a competitive edge in an increasingly digital-centric marketplace.
A key driver of this market's growth is the exponential increase in data generation facilitated by digital channels. With the proliferation of social media platforms, mobile applications, and e-commerce websites, the volume of consumer data available to businesses has surged. This data offers invaluable insights into consumer behavior and preferences, enabling companies to tailor their marketing strategies more effectively. Consequently, the demand for advanced analytics solutions that can process and analyze vast datasets in real-time is expected to grow, further boosting the market for marketing analytics tools.
Another significant growth factor is the increasing adoption of artificial intelligence (AI) and machine learning (ML) technologies in marketing analytics. AI and ML are transforming how businesses interpret and utilize data by providing predictive insights and automating complex data analysis processes. These technologies enable marketers to identify trends, forecast consumer behaviors, and optimize campaigns with greater precision, thereby enhancing the overall effectiveness of marketing efforts. As AI and ML capabilities become more sophisticated, their integration into marketing analytics tools is expected to drive further market expansion.
The shift towards personalized customer experiences is also propelling the growth of the marketing analytics tools market. TodayÂ’s consumers expect personalized interactions with brands, and businesses are increasingly leveraging analytics to deliver customized content and offers. Marketing analytics tools help organizations understand individual customer journeys and preferences, allowing them to craft personalized marketing strategies that resonate with their target audience. This trend towards personalization is anticipated to continue, driving the demand for advanced analytics tools that can manage and analyze complex customer datasets.
Regionally, North America holds a significant share of the marketing analytics tools market, owing to the early adoption of advanced technologies and the presence of key market players. The region's strong focus on digital marketing and data-driven strategies has accelerated the adoption of marketing analytics solutions. Meanwhile, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, driven by the rapid digital transformation of businesses and increasing investments in analytics infrastructure. The burgeoning e-commerce sector in countries like China and India is also contributing to the growth of the marketing analytics tools market in this region.
The marketing analytics tools market can be segmented by component into software and services. The software segment encompasses various analytics platforms and solutions designed to collect, process, and analyze marketing data. These software solutions offer functionalities such as data visualization, predictive analytics, and real-time reporting, enabling marketers to make informed decisions. The demand for marketing analytics software is driven by the need for businesses to process large volumes of data efficiently and extract actionable insights that can enhance marketing strategies and outcomes.
Marketing Attribution Software is becoming increasingly vital for businesses aiming to understand the effectiveness of their marketing efforts across multiple channels. This software helps organizations allocate credit to various touchpoints in a customer's journey, providing insights into which marketing strategies are driving conversions. By leveraging marketing attribution software, companies can optimize their marketing spend and improve ROI by focusing on the most impactful channels. As the marketing landscape becomes more complex wit
GeoLifestyle Consumer Behavior Data: Scalable Behavioral and Audience Intelligence Across 6 Emerging Markets
GeoLifestyle provides companies with instant access to 561 million geo-coded consumer behavior profiles across six of the world’s most dynamic emerging economies. Designed for organizations focused on behavioral analytics, audience modeling, market research, and precision-targeted marketing, this dataset offers high-value, real-world intelligence ready for direct integration into AI, marketing, and research workflows.
Key Features: • Volume: 561,000,000 records • Countries Covered: 6 key emerging markets • Historical Span: 12 months of behavior and location history • Attributes: 78 lifestyle and behavioral attributes per profile • Location Precision: Latitude/Longitude at 2-meter radius • Data Delivery: On-premise, quarterly updates, fully compliant
What’s Inside: Each record includes rich lifestyle indicators across major categories — such as shopping preferences, travel behaviors, media consumption, household composition, mobility patterns, income estimation, and affluence segmentation — combined with precise geolocation signals. This allows for granular, real-world audience understanding at scale.
Primary Use Cases: • Behavioral and predictive analytics • Location-based audience segmentation • AI-driven audience modeling • Data-driven market research • Personalization and hyper-targeted marketing strategies
Ideal For: • Marketing technology firms • Financial institutions • AI/ML teams building customer models • Retailers expanding into emerging markets • Agencies designing precision marketing campaigns
Data Quality and Compliance: GeoLifestyle is stored securely on-premise with regulatory alignment to GDPR, LGPD, PDPA, and similar frameworks. With continuous quarterly refresh cycles, buyers are assured of current, compliant, and operationally ready datasets.
Pricing and additional samples available upon request.
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A comprehensive dataset providing insights into the advertising industry for 2025, highlighting global advertising spending, digital and traditional marketing trends, the influence of social media advertising, mobile ad growth, advertising impact on consumer behavior, and the rise of programmatic advertising.
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Mobility data is collected through location-aware mobile apps using an SDK-based implementation. Users explicitly consent to share their location data via a clear opt-in process and are provided with clear opt-out options. Factori ingests, cleans, validates, and exports all location data signals to ensure the highest quality data is available for analysis.
Our data reach encompasses the total counts available across various categories, including attributes such as country location, MAU (Monthly Active Users), DAU (Daily Active Users), and Monthly Location Pings.
We collect data dynamically, offering the most updated data and insights at the best-suited intervals (daily, weekly, monthly, or quarterly).
Our data supports various business needs, including consumer insight, market intelligence, advertising, and retail analytics.
Company Domain to MAID | Company IP Data | Monthly Feed | 200M+ MAIDs to Business Domain Connections Introducing our "Company Domain to MAID" dataset, a groundbreaking resource that links over 200 million Mobile Advertising IDs (MAIDs) to corresponding business domains. Updated monthly, this expansive dataset is engineered for organizations aiming to revolutionize their mobile marketing strategies, enhance customer engagement, and gain deeper insights into mobile user behaviors. As a perfect complement to our "Company Domain to IP Address Linkage Database," this product extends the value of your digital marketing and cybersecurity efforts by integrating mobile data for comprehensive B2B insights. Company IP Data Company Data Ideal Add-On for Domain to IP Product This dataset serves as an ideal add-on to our "Company Domain to IP Address Linkage Database," enabling a multi-dimensional approach to digital strategy by encompassing both traditional and mobile digital landscapes. Together, these products offer a holistic view of digital footprints, ensuring your marketing, security, and analytical capabilities are both broad and deeply integrated. Key Features: • Massive Dataset: Access a robust linkage of over 200 million MAIDs to business domains, providing unparalleled coverage across various industries and markets. • High-Quality Data: Benefit from a dataset characterized by its high accuracy and monthly updates, ensuring you have the most current and reliable information for your mobile marketing and engagement strategies. • Seamless Compatibility: Designed for easy integration with existing marketing, CRM, and cybersecurity platforms, enhancing your digital outreach and security protocols with valuable mobile user insights. Benefits: • Advanced Mobile Marketing: Leverage precise MAID to domain mappings to target and engage mobile users more effectively, driving higher engagement rates and improving campaign ROI. • Enhanced Customer Insights: Gain deeper understanding of customer mobile behaviors and preferences, enabling more personalized and impactful marketing strategies. • Comprehensive Digital Footprint: Combine with our Domain to IP product for a complete overview of corporate digital presence, from desktop to mobile, enhancing all aspects of digital marketing and cybersecurity. • Improved Data-Driven Decisions: Utilize the extensive insights provided by linking MAIDs to business domains to inform strategic decisions, from marketing to security to product development. Applications: • Holistic Marketing Strategies: Employ our dataset to craft comprehensive digital marketing campaigns that effectively reach business audiences across all devices, maximizing coverage and impact. • Enhanced B2B Targeting: Perfectly complement your Domain to IP strategies by including mobile targeting, ensuring that your messages reach the right audience, no matter the device. • Robust Cybersecurity Posture: Enhance your cybersecurity measures by incorporating mobile data, providing a more complete picture of potential vulnerabilities and threat vectors. • Market and Competitor Analysis: Analyze mobile engagement trends and behaviors for insights into market dynamics and competitor strategies, guiding your business decisions with rich, actionable data. Our "Company Domain to MAID" dataset is a must-have for businesses looking to capitalize on the immense potential of mobile marketing and engagement, offering a significant advantage in understanding and reaching B2B audiences. As a standalone product or in conjunction with our "Company Domain to IP Address Linkage Database," it represents the pinnacle of digital insight, enabling businesses to navigate the complexities of the modern digital landscape with confidence and precision.
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This synthetic but realistic dataset contains 90+ customer reviews for 6 smartphone models (from Apple, Samsung, and Google), along with: - Product specifications (Price, Screen Size, Battery, Camera, RAM, Storage, 5G, Water Resistance) - Customer reviews (Star Ratings, Review Text, Verified Purchase Status) - Sales data (Units Sold per Model)
Potential Use Cases: ✅ Feature importance analysis (Which specs drive ratings?) ✅ Sentiment analysis (NLP on reviews) ✅ Pricing strategy optimization ✅ Market research (Comparing Apple vs. Samsung vs. Google)
Objective: Understand how product features influence purchasing decisions and satisfaction.
Which smartphone brand did you purchase?
brand
column.Which model did you purchase?
model_name
column.Where did you purchase the phone?
verified_purchase
(assumed online = verified).How would you rate the following features? (1 = Poor, 5 = Excellent)
star_rating
(average of these).Which feature is MOST important to you?
review_text
keywords (e.g., "battery" mentions).How do you feel about the price of your phone?
price
vs. star_rating
correlation.Would you recommend this phone to others?
star_rating
(5 = Definitely Yes).Column Details (Metadata)
Column Name (Type) Description "Example"**
model_id (Integer) Unique ID for each phone model 1 (iPhone 14)
brand (String) Manufacturer (Apple, Samsung, Google) "Apple"
model_name (String) Name of the phone model "iPhone 15"
price (Integer) Price in USD 999
screen_size (Float) Screen size in inches 6.1
battery (Integer) Battery capacity in mAh 4000
camera_main (String) Main camera resolution (MP) "48MP"
ram (Integer) RAM in GB 8
storage (Integer) Storage in GB 128
has_5g (Boolean) Whether the phone supports 5G TRUE
water_resistant (String) Water resistance rating (IP68 or None) "IP68"
units_sold (Integer) Estimated units sold (for market analysis) 15000
review_id (Integer) Unique ID for each review 1
user_name (String) Randomly generated reviewer name "John"
star_rating (Integer) Rating from 1 (worst) to 5 (best) 5
verified_purchase (Boolean) Whether the reviewer bought the product TRUE
review_date (Date) Date of the review (YYYY-MM-DD) "2023-05-10"
review_text (String) Simulated review text based on features & rating "The 48MP camera is amazing!"
Suggested Analysis Ideas to inspire data analysis: A. Feature Impact on Ratings Regression: star_rating ~ battery + camera_main + price Key drivers: Does battery life affect ratings more than camera quality?
B. Sentiment Analysis (NLP)
Use tidytext (R) or NLTK (Python) to extract most-loved/hated features.
Example:
r
library(tidytext)
reviews_tidy <- final_data %>% unnest_tokens(word, review_text)
reviews_tidy %>% count(word, sort = TRUE) %>% filter(n > 5)
C. Brand Comparison Apple vs. Samsung vs. Google: Which brand has higher average ratings? Price sensitivity: Do cheaper phones (e.g., Pixel) get better value ratings?
D. Sales vs. Features Correlation: units_sold ~ price + brand Premium segment analysis: Do iPhones sell more despite higher prices?
As of April 2024, it was found that men between the ages of 25 and 34 years made up Facebook largest audience, accounting for 18.4 percent of global users. Additionally, Facebook's second largest audience base could be found with men aged 18 to 24 years.
Facebook connects the world
Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger,
as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.
🌍 Global B2B Person Dataset | 755M+ LinkedIn Profiles | Verified & Bi-Weekly Updated Access the world’s most comprehensive professional dataset, enriched with over 755 million LinkedIn profiles. The Forager.ai Global B2B Person Dataset delivers work-verified professional contacts with 95%+ accuracy, refreshed every two weeks. Ideal for recruitment, sales, research, and talent mapping, it provides direct access to decision-makers, specialists, and executives across industries and geographies.
Dataset Features Full Name & Job Title: Up-to-date first/last name with current professional role.
Emails & Phone Numbers: AI-validated work and personal email addresses, plus mobile numbers.
Company Info: Current employer name, industry, and company size (employee count).
Career History: Detailed work history with job titles, durations, and role progressions.
Skills & Endorsements: Extracted from public LinkedIn profiles.
Education & Certifications: Universities, degrees, and professional certifications.
Location & LinkedIn URL: City, country, and direct link to public LinkedIn profile.
Distribution Data Volume: 755M+ total profiles, with 270M+ containing full contact information.
Formats Available: CSV, JSON via S3 or Snowflake; API for real-time access.
Access Methods: REST API, Enrichment API (lookup), full dataset delivery, or custom solutions.
Usage This dataset is ideal for a variety of applications:
Executive Recruitment: Source passive talent, build role-based maps, and assess mobility.
Sales Intelligence: Find decision-makers, personalize outreach, and trigger campaigns on job changes.
Market Research: Understand talent concentration by company, geography, and skill set.
Partnership Development: Identify key stakeholders in target firms for business development.
Talent Mapping & Strategic Hiring: Build full organizational charts and skill distribution heatmaps.
Coverage Geographic Coverage: Global – including North America, EMEA, LATAM, and APAC.
Time Range: Continuously updated; profiles refreshed bi-weekly.
Demographics: Cross-industry coverage of seniority levels from entry-level to C-suite, across all sectors.
License CUSTOM
Who Can Use It Recruiters & Staffing Firms: For building target lists and sourcing niche talent.
Sales & RevOps Teams: For targeting by department, title, or decision-making authority.
VCs & PE Firms: To assess leadership teams and monitor executive movement.
Data Scientists & Analysts: To train models for job mobility, hiring trends, or org structure prediction.
B2B Platforms: For enriching internal databases and powering account-based marketing (ABM).
As of January 2024, Instagram was slightly more popular with men than women, with men accounting for 50.6 percent of the platform’s global users. Additionally, the social media app was most popular amongst younger audiences, with almost 32 percent of users aged between 18 and 24 years.
Instagram’s Global Audience
As of January 2024, Instagram was the fourth most popular social media platform globally, reaching two billion monthly active users (MAU). This number is projected to keep growing with no signs of slowing down, which is not a surprise as the global online social penetration rate across all regions is constantly increasing.
As of January 2024, the country with the largest Instagram audience was India with 362.9 million users, followed by the United States with 169.7 million users.
Who is winning over the generations?
Even though Instagram’s audience is almost twice the size of TikTok’s on a global scale, TikTok has shown itself to be a fierce competitor, particularly amongst younger audiences. TikTok was the most downloaded mobile app globally in 2022, generating 672 million downloads. As of 2022, Generation Z in the United States spent more time on TikTok than on Instagram monthly.
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The global Customer Relationship Management (CRM) system market is projected to reach a valuation of USD XX billion by 2032, growing at a CAGR of XX% from 2024 to 2032. The adoption of CRM systems is being driven primarily by the increasing need for businesses to streamline their customer interactions and enhance their customer service capabilities.
One of the most influential growth factors for the CRM system market is the burgeoning demand for customer-centric strategies. As businesses increasingly recognize the importance of maintaining strong customer relationships, the adoption of CRM solutions has surged. These systems facilitate the efficient management of customer data, enabling companies to tailor their interactions and marketing efforts to individual customers. This personalized approach not only boosts customer satisfaction and loyalty but also drives sales and revenue growth. Furthermore, the integration of advanced technologies such as Artificial Intelligence (AI) and Machine Learning (ML) into CRM platforms has enhanced their capabilities, allowing for predictive analytics and more nuanced customer insights.
Another significant growth driver for the CRM market is the rapid digital transformation across various industries. The shift towards digitalization has made the adoption of CRM systems a necessity for businesses aiming to stay competitive. Traditional methods of managing customer relationships are becoming obsolete, and modern CRM solutions offer the tools needed to meet the demands of the digital age. With features like automated workflows, real-time data analysis, and multichannel communication capabilities, CRM systems are helping businesses streamline their operations and improve efficiency. As more organizations undergo digital transformation, the demand for robust CRM solutions is expected to rise.
The growing Small and Medium Enterprises (SMEs) sector is also contributing to the expansion of the CRM market. Unlike larger enterprises, SMEs often lack the resources to invest in extensive customer management infrastructure. CRM systems offer an affordable and scalable solution for these businesses to manage their customer interactions effectively. By adopting CRM systems, SMEs can compete more effectively in the market by providing personalized customer experiences and building stronger customer relationships. The increasing availability of cloud-based CRM solutions has further lowered the entry barriers for SMEs, making CRM technology more accessible and driving market growth.
Regionally, North America dominates the CRM system market, largely due to the presence of major technology companies and early adoption of cutting-edge solutions. However, the Asia Pacific region is anticipated to witness the highest growth rate over the forecast period. The rapid economic growth in countries like China and India, combined with increasing digitalization and a growing number of SMEs, is driving the demand for CRM systems in the region. The rising adoption of cloud computing and mobile CRM solutions is also contributing to the market expansion in Asia Pacific.
The CRM system market can be segmented by component into software and services. The software segment holds a substantial share of the market, driven by the increasing need for businesses to manage their customer interactions and data more efficiently. CRM software provides a comprehensive suite of tools that help organizations automate their sales, marketing, and customer service processes. With features like contact management, sales automation, and analytics, CRM software enables businesses to enhance their customer engagement and improve operational efficiency. The ongoing advancements in CRM software, including the integration of AI and ML, are further propelling the growth of this segment.
On the other hand, the services segment encompasses a range of professional and managed services that support the implementation, customization, and maintenance of CRM solutions. As businesses strive to maximize the value of their CRM investments, the demand for consulting, training, and support services is on the rise. Professional services help organizations tailor CRM systems to their specific needs, ensuring a seamless integration with existing processes and systems. Managed services, including system monitoring and maintenance, provide ongoing support and help businesses optimize their CRM performance. The growing complexity of CRM systems and the need for specialized expertise are driving the demand for services in the CRM
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This synthetic yet realistic dataset offers insights into smartphone features, customer reviews, and sales data. It includes over 90 customer reviews for six popular smartphone models from leading brands such as Apple, Samsung, and Google. The dataset is designed to help understand how various product specifications influence purchasing decisions and overall customer satisfaction. It combines detailed product specifications, customer star ratings, review texts, and verified purchase status with estimated sales figures per model.
The dataset is typically provided in a CSV file format. It comprises over 90 customer review records, along with corresponding smartphone product specifications and sales data for 6 distinct phone models. The exact total number of rows or the specific file size in MB/GB is not specified.
This dataset is ideal for various analytical applications, including: * Feature importance analysis: Determining which smartphone specifications (e.g., battery life, camera quality) most significantly influence customer ratings and purchasing decisions. * Sentiment analysis: Applying Natural Language Processing (NLP) techniques to extract insights and sentiment from customer review texts. * Pricing strategy optimisation: Analysing the correlation between price and customer satisfaction or sales volume. * Market research: Comparing performance and customer perception across different brands (e.g., Apple vs. Samsung vs. Google) and models. * Sales vs. features correlation: Investigating how product features and pricing impact estimated units sold.
This dataset has a Global region coverage. It includes data pertaining to six smartphone models from three major brands: Apple (iPhone 14, iPhone 15), Samsung (Galaxy S22, Galaxy S23), and Google (Pixel 7, Pixel 8). The review dates are indicative of data from around 2023. While it includes customer reviews, specific demographic details of the reviewers are not available beyond randomly generated usernames. As a synthetic dataset, it is designed to be realistic for general market analysis.
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This dataset is suitable for: * Data Analysts and Scientists: For performing regression analysis, sentiment analysis, and predictive modelling. * Marketing Professionals: To understand consumer preferences, optimise product features, and refine marketing strategies. * Product Managers: To inform product development, feature prioritisation, and competitive analysis. * Market Researchers: To study market trends, brand comparisons, and consumer behaviour in the smartphone industry. * Academics and Students: For educational purposes and research projects related to consumer electronics, e-commerce, and data analysis.
Original Data Source: Smartphone Feature Optimization (Marketing Mix)