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?

Success.ai’s Consumer Marketing Data for Food, Beverage & Consumer Goods Professionals Globally provides a comprehensive dataset tailored for businesses seeking to connect with decision-makers and marketing professionals in these dynamic industries. Covering roles such as brand managers, marketing strategists, and product developers, this dataset offers verified contact details, decision-maker insights, and actionable business data.

With access to over 700 million verified global profiles, Success.ai ensures your marketing, sales, and research efforts are powered by accurate, continuously updated, and AI-validated data. Backed by our Best Price Guarantee, this solution is essential for businesses aiming to lead in the food, beverage, and consumer goods sectors.

Why Choose Success.ai’s Consumer Marketing Data?

1. Verified Contact Data for Precision Targeting

   • Access verified work emails, phone numbers, and LinkedIn profiles of marketing professionals, brand leaders, and product strategists.
   • AI-driven validation ensures 99% accuracy, minimizing communication errors and maximizing outreach success.

2. Comprehensive Coverage Across Global Markets

   • Includes profiles of professionals from food and beverage companies, consumer goods manufacturers, and marketing agencies in key markets worldwide.
   • Gain insights into regional trends in product marketing, consumer engagement, and purchasing behaviors.

3. Continuously Updated Datasets

   • Real-time updates capture changes in professional roles, company strategies, and market trends.
   • Stay aligned with the fast-evolving consumer goods industry to identify emerging opportunities.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage.

Data Highlights:

• 700M+ Verified Global Profiles: Connect with decision-makers, marketers, and product managers in the food, beverage, and consumer goods sectors worldwide.
• Leadership Insights: Gain detailed profiles of brand managers, marketing executives, and product developers shaping consumer trends.
• Contact Details: Access verified phone numbers and work emails for precision outreach.
• Industry Trends: Understand global marketing trends, regional consumer preferences, and market dynamics.

Key Features of the Dataset:

1. Comprehensive Professional Profiles

   • Identify and connect with key professionals managing brand strategies, product launches, and marketing campaigns in the food, beverage, and consumer goods industries.
   • Access data on career histories, certifications, and market expertise for targeted outreach.

2. Advanced Filters for Precision Campaigns

   • Filter professionals by industry focus (snack foods, beverages, household goods), geographic location, or job function.
   • Tailor campaigns to align with specific needs such as product placement, consumer engagement, or regional expansion.

3. Regional Trends and Consumer Insights

   • Leverage data on consumer preferences, product demand, and spending patterns in key markets.
   • Use these insights to refine product offerings, marketing strategies, and audience targeting.

4. AI-Driven Enrichment

   • Profiles enriched with actionable data enable personalized messaging, highlight unique value propositions, and improve engagement outcomes.

Strategic Use Cases:

1. Marketing Campaigns and Brand Outreach

   • Design targeted campaigns for food, beverage, and consumer goods products based on verified data and consumer insights.
   • Leverage multi-channel outreach, including email, phone, and digital advertising, to maximize engagement.

2. Product Development and Launch Strategies

   • Utilize consumer trend data to guide product development and market entry strategies.
   • Collaborate with brand managers and marketing professionals to align offerings with consumer preferences.

3. Sales and Partnership Development

   • Build relationships with distributors, retailers, and marketers in the consumer goods supply chain.
   • Present co-branding opportunities, joint marketing campaigns, or distribution strategies to decision-makers.

4. Market Research and Competitive Analysis

   • Analyze global trends in consumer goods marketing, product innovations, and purchasing behaviors to refine strategies.
   • Benchmark against competitors to identify growth opportunities, underserved markets, and high-demand products.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality consumer marketing data at competitive prices, ensuring strong ROI for your marketing, sales, and product development efforts.

2. Seamless Integration

   • Integrate verified data into CRM systems, marketing platforms, or analytics tools via APIs or downloadable formats, streamlining workflows and enhancing productivity.

3. Data Acc...

Marketing Analytics Market Outlook

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.

Component Analysis

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

Contacts:

1. Mobile phone retailers or wholesalers for insights into sales trends and customer behavior.
2. Industry experts or analysts for market research and trends.
3. Online forums or communities (e.g., Reddit's r/phones or r/mobiletech) for user feedback and opinions.

Sources:

1. Online market research reports (e.g., Statista, Euromonitor) for industry trends and statistics.
2. Mobile phone manufacturer websites (e.g., Apple, Samsung) for product information and sales data.
3. E-commerce websites (e.g., Amazon, Best Buy) for pricing and product availability data.
4. Government statistics or economic reports for insights into the mobile phone market's economic impact.

Inspirations:

1. Analyzing sales trends and customer preferences to inform inventory management and marketing strategies.
2. Identifying top-selling phone models and brands to understand market demand.
3. Exploring the impact of pricing, promotions, and discounts on sales.
4. Investigating customer behavior and purchasing patterns to improve customer experience.

Some potential Kaggle datasets or competitions that might inspire your project include:

1. "Mobile Price Classification" dataset
2. "Smartphone Sales in Retail" dataset
3. "Mobile Phone User Behavior" dataset

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.

This dataset, titled "U.S. Consumer Cell Phone Data," provides anonymized records of consumer purchases and ownership of cell phones across the United States. Each entry in the dataset includes vital information such as the name, address, and purchase-related details of individual buyers. The data offers insights into consumer behavior, trends in cell phone adoption, and geographic patterns of mobile technology use.

Key features of the dataset include:

1. Name: The names of cell phone buyers, enabling linkages with other consumer records for demographic and behavioral analysis (while respecting privacy guidelines).

2. Address: Detailed geographic information, including street addresses, cities, states, and ZIP codes. This allows for regional analysis of purchasing trends and the potential for mapping market penetration of specific phone brands or models.

3. Device Details: While not explicitly stated in the description, such datasets often include information about the types of cell phones purchased, brands, models, and potentially the purchase date.

This dataset could be invaluable for businesses, marketers, and researchers aiming to understand consumer preferences, improve mobile marketing strategies, or tailor product offerings to specific regions.

In summary, the U.S. Consumer Cell Phone Data is a robust resource for analyzing the intersection of consumer behavior and mobile technology, provided that its usage adheres to relevant privacy and ethical standards.

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.

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.

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.

This dataset contains information on Samsung mobile sales, 5G network adoption, and market factors. It includes details such as regional 5G coverage, subscriber growth, and marketing influence.

Overview

The mobile games industry is worth billions of dollars, with companies spending vast amounts of money on the development and marketing of these games to an equally large market. Using this data set, insights can be gained into a sub-market of this market, strategy games. This sub-market includes titles such as Clash of Clans, Plants vs Zombies and Pokemon GO.

Background

This is the data of 17007 strategy games on the Apple App Store. It was collected on the 3rd of August 2019, using the iTunes API and the App Store sitemap.

Some ideas

You could use the number of ratings as a proxy indicator for the overall success of a game, and then work out what factors make a successful game. Or you could measure the state of the market over time and try predict where it is headed. And I think an analysis of the icons of the apps would be pretty cool.

About this Dataset

Discover the power of our meticulously curated .csv B2B leads list, a goldmine of information spotlighting enterprises thriving in the dynamic realm of Marketing and Advertising across the United States. Crafted with precision, this dataset is meticulously organized by company size, encompassing a spectrum from 1 to 10, orchestrating the perfect stage for precision-targeted outreach tactics. At every entry, a symphony of indispensable contact and professional particulars unfolds, rendering this treasure trove an indispensable asset for orchestrating impactful marketing campaigns, fostering astute business development, and navigating the intricate tapestry of networking endeavors. Key Insights:

Industry: Marketing and Advertising Geographical Scope: United States Company Magnitude: Spanning a spectrum from 1 to 10 Data Dimensions: Company Name, Website Domain, Location, LinkedIn Profile, Phone Numbers

Illuminating Features:

Segmented Brilliance: Seamlessly discern companies through size for laser-focused marketing pursuits. Holistic Disclosures: Gain access to pivotal company intricacies – names, domains, and the crux of contact particulars. Strategic Revelations: Amplify your influence with LinkedIn profiles, forging profound connections within the industry's inner sanctum. Engagement Amplification: Capitalize on direct communication channels through provided phone numbers, etching lasting impressions. B2B Dedication: Tailored for B2B ventures, encompassing everything from pioneering partnerships to strategic sales prospecting. Analytical Prowess: Perfectly primed for dissecting market trends, conducting perceptive trend analyses, and deciphering the competition's pulse. Instant Gratification: Unleash instant insights, eliminating the toil of manual data curation. Voluminous Horizons: Over 535,000 entries: a symphony of growth avenues, ensuring prosperity.

This .csv leads list becomes the catalyst, propelling businesses toward pinnacles of success as it imparts precise and comprehensive company intelligence within the sprawling canvas of the United States' Marketing and Advertising panorama.

Category

Business Information & Financials

Keywords

Marketing and Advertising leads,B2B leads,Business leads,US companies,Company size 1-10

Row Count

57625

Price

$2400.00

How many people use social media?

              Social media usage is one of the most popular online activities. In 2024, over five billion people were using social media worldwide, a number projected to increase to over six billion in 2028.

              Who uses social media?
              Social networking is one of the most popular digital activities worldwide and it is no surprise that social networking penetration across all regions is constantly increasing. As of January 2023, the global social media usage rate stood at 59 percent. This figure is anticipated to grow as lesser developed digital markets catch up with other regions
              when it comes to infrastructure development and the availability of cheap mobile devices. In fact, most of social media’s global growth is driven by the increasing usage of mobile devices. Mobile-first market Eastern Asia topped the global ranking of mobile social networking penetration, followed by established digital powerhouses such as the Americas and Northern Europe.

              How much time do people spend on social media?
              Social media is an integral part of daily internet usage. On average, internet users spend 151 minutes per day on social media and messaging apps, an increase of 40 minutes since 2015. On average, internet users in Latin America had the highest average time spent per day on social media.

              What are the most popular social media platforms?
              Market leader Facebook was the first social network to surpass one billion registered accounts and currently boasts approximately 2.9 billion monthly active users, making it the most popular social network worldwide. In June 2023, the top social media apps in the Apple App Store included mobile messaging apps WhatsApp and Telegram Messenger, as well as the ever-popular app version of Facebook.

Understanding: UrbanScape Apparel SEO Performance Final Dataset

Company: BrightWave Digital Department: Digital Marketing & SEO Team Industry: E-commerce (fashion and lifestyle products) Brand: UrbanScape Apparel

Story

BrightWave Digital is a fast-growing digital marketing agency that handles full-spectrum SEO, SEM, and content marketing for various clients. The SEO team is tasked with pushing UrbanScape Apparel, a sustainable fashion brand, to the top of the search rankings. The brand sells eco-friendly clothing and accessories aimed at environmentally conscious consumers in North America.

UrbanScape Apparel has recently expanded its product lines and introduced new collections, such as “Urban Outdoors” for hiking gear and “EcoActive” for athleisure. With increased competition in the eco-fashion market, BrightWave Digital’s SEO team must optimize UrbanScape’s site performance, monitor SEO metrics closely, and demonstrate measurable improvements in organic traffic and conversions.

Objectives

Improve rankings for high-intent keywords like "eco-friendly clothing" and "sustainable outdoor gear." Boost organic traffic from both mobile and desktop devices. Increase visibility through backlinks from high domain authority (DA) sites. Optimize Core Web Vitals to ensure the site ranks higher in Google’s search results. The dashboard data includes traffic, keyword rankings, click-through rates (CTR), and other performance metrics to track how well the SEO efforts are contributing to the brand’s growth.

Column Description

1. Date Definition: The specific day for which the data is collected. Importance: Allows tracking of daily trends and pinpointing specific dates of spikes or drops in performance.

2. Month Definition: The month corresponding to the data being analyzed. Importance: Helps in understanding monthly trends and seasonal patterns in traffic and user behavior.

3. Year Definition: The year in which the data was recorded. Importance: Essential for long-term trend analysis and year-over-year performance comparisons.

4. Quarter Definition: The fiscal quarter (Q1, Q2, Q3, Q4) for the given data. Importance: Useful for quarterly business reviews and strategy adjustments based on performance.

5. Time Of Day Definition: The specific time range (e.g., morning, afternoon, evening) when the traffic or engagement was recorded. Importance: Helps in understanding peak traffic times and optimizing content publishing schedules.

6. Primary Keywords Definition: The main keywords targeted for SEO, typically with high search volume and relevance to the brand. Importance: Crucial for understanding the focus of the SEO strategy and the effectiveness of ranking for these terms.

7. Secondary Keywords Definition: Additional keywords that complement primary keywords, often with lower competition and specific niches. Importance: Provides insights into secondary areas of focus that can still drive significant traffic and conversions.

8. Long-Tail Keywords Definition: More specific keyword phrases usually consisting of three or more words, targeting niche search queries. Importance: Important for attracting highly targeted traffic and often associated with higher conversion rates.

9. Location Definition: Geographic region from where the traffic is coming. Importance: Helps in understanding regional performance and tailoring content or promotions to specific markets.

10. Social Media Source Definition: The social media platform (e.g., Instagram, Pinterest) from which traffic is referred to the site. Importance: Measures the impact of social media channels on website traffic and engagement.

11. Media Type Definition: The format of the media content (e.g., image, video, article) driving traffic. Importance: Analyzes which media types resonate best with the audience and contribute to higher engagement.

12. Device Type Definition: The type of device used by visitors (e.g., mobile, desktop, tablet) to access the website. Importance: Essential for optimizing user experience across different devices and identifying potential issues.

13. Organic Traffic Definition: The number of visitors coming to the site through unpaid search results. Importance: Shows how well the site is performing in attracting users through SEO efforts without relying on paid advertising.

14. Keywords Ranking Definition: The position of targeted keywords in search engine results pages (SERPs). Importance: Indicates the effectiveness of SEO strategies in improving keyword visibility and competitiveness.

15. Clicks Definition: The number of times users click on the site’s links from search results. Importance: Reflects user interest and relevance of the search snippets or ads shown to users.

16. Impressions Definition: The number of times a site appears in search r...

Techsalerator’s Business Technographic Data for Vietnam: Unlocking Insights into Vietnam's Technology Landscape

Techsalerator’s Business Technographic Data for Vietnam provides a detailed and comprehensive dataset essential for businesses, market analysts, and technology vendors seeking to understand and engage with companies operating within Vietnam. This dataset offers in-depth insights into the technological landscape, capturing and organizing data related to technology stacks, digital tools, and IT infrastructure used by businesses in the country.

Please reach out to us at info@techsalerator.com or visit Techsalerator Contact.

Top 5 Most Utilized Data Fields

• Company Name: This field lists the names of companies in Vietnam, enabling technology vendors to target potential clients and allowing analysts to assess technology adoption trends within specific businesses.

• Technology Stack: This field outlines the technologies and software solutions a company uses, such as accounting systems, customer management software, and cloud services. Understanding a company's technology stack is key to evaluating its digital maturity and operational needs.

• Deployment Status: This field indicates whether the technology is currently deployed, planned for future deployment, or under evaluation. Vendors can use this information to assess the level of technology adoption and interest among companies in Vietnam.

• Industry Sector: This field specifies the industry in which the company operates, such as manufacturing, retail, or finance. Knowing the industry helps vendors tailor their products to sector-specific demands and emerging trends in Vietnam.

• Geographic Location: This field identifies the company's headquarters or primary operations within Vietnam. Geographic information aids in regional analysis and understanding localized technology adoption patterns across the country.

Top 5 Technology Trends in Vietnam

• E-commerce Expansion: With a rapidly growing digital consumer base, Vietnamese companies are increasingly investing in e-commerce platforms, digital marketing, and online payment systems to capture a larger market share and enhance customer experience.

• Fintech Innovations: Vietnam’s fintech sector is experiencing significant growth, with businesses adopting advanced financial technologies such as mobile payment solutions, digital wallets, and blockchain to improve financial transactions and services.

• Smart Manufacturing: The manufacturing sector in Vietnam is embracing Industry 4.0 technologies, including automation, IoT, and AI-driven analytics, to enhance productivity, efficiency, and competitiveness in the global market.

• Cloud Computing and SaaS: Cloud-based solutions and Software-as-a-Service (SaaS) offerings are gaining traction, providing Vietnamese businesses with scalable and flexible IT infrastructure that supports remote work and digital transformation initiatives.

• Cybersecurity Enhancements: As digital activities increase, so does the need for robust cybersecurity measures. Companies in Vietnam are investing in advanced security solutions, including threat detection systems and data protection tools, to safeguard their operations and customer data.

Top 5 Companies with Notable Technographic Data in Vietnam

• Vietcombank: A leading financial institution, Vietcombank is implementing cutting-edge digital banking solutions, including mobile banking apps and secure online transaction systems, to enhance customer service and operational efficiency.

• Vingroup: As a major conglomerate, Vingroup leverages advanced technologies across its diverse business segments, including real estate, retail, and healthcare, integrating smart technologies and digital platforms into its operations.

• FPT Corporation: A major IT services and software development company, FPT is at the forefront of digital transformation in Vietnam, offering solutions in cloud computing, AI, and cybersecurity to both domestic and international clients.

• Masan Group: A leading consumer goods and retail company, Masan Group is adopting digital tools and e-commerce platforms to optimize its supply chain, enhance customer engagement, and drive business growth.

• VNPT: Vietnam’s largest telecommunications provider, VNPT is expanding its network infrastructure and investing in advanced technologies such as 5G and IoT to improve connectivity and support the digital economy.

Accessing Techsalerator’s Business Technographic Data

For those interested in accessing Techsalerator’s Business Technographic Data for Vietnam, please contact info@techsalerator.com with your specific needs. Techsalerator offers customized quotes based on the required number of data fields and records, with datasets available for delivery within 24 hours. Ongoing access ...

The technology provider firms are bringing new mobile applications (m-apps) with increasing frequency in the agriculture markets to enhance markets access and related pecuniary benefits for the farmers. Considering the importance of technology adoption to achieve such objectives, the data set consists of factors that influence adoption of agri-marketing mobile applications among farmers. Our research extended unified theory of acceptance and use of technology 2(UTAUT2) in agri marketing m-apps using structural equation model (SEM). The survey consisted of 496 farmers intention to adopt agri marketing m-apps.

Saree Retailers Database in India

Accurate Up-to-Date Data for All Types of Business Purposes

By Amresh [source]

About this dataset

This All India Saree Retailers Database is a comprehensive collection of up-to-date information on 10,000 Saree Retailers located all over India. The database is updated in April 2021 and offers an overall accuracy rate of around 90%.

For business owners, marketers, and data analysts and researchers, this dataset is an invaluable resource. It contains contact details of store name, contact person names, phone number and email address along with store location information like city state and pin code to help you target the right audience precisely.

The database can be accessed in Microsoft Excel (.xlsx) format which makes it easy to read or manipulate the file according to your needs. Apart from this wide range of payment options like Credit/Debit Card; Online Transfer; NEFT; Cash Deposit; Paytm; PhonePe; Google Pay or PayPal allow quick download access within 2-3 business hours.

So if you are looking for reliable business intelligence data related to Indian saree retailers that can help you unlock incredible opportunities for your business then make sure to download our All India Saree Retailers Database at the earliest!

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How to use the dataset

This dataset provides a comprehensive list of Saree retailers in India, including store name, contact person, email address, mobile number, phone number, address details like city and state along with pin code. It contains 10 thousand records updated in April 2021 with an overall accuracy rate of around 90%. This data can be used to understand customer behaviour as well as to analyse geographical customer pattern.

Using this dataset you can: - Target specific states or cities where potential customers are located for your Saree business. - Get in touch with local Saree retailers for possible collaborations and partnerships. - Learn more about industry trends from actual store owners who can offer insights into the latest ongoing trends and identify new opportunities for you to grow your business. 4 .Analyse existing competitors’ market share by studying the cities/states where they operate and their contact information such as Mobile Number & Email Ids .
5 .Identify potential new customers for better sales conversion rates by understanding who is already operating in similar products nearby or have similar target audience as yours that help your company reach out to them quickly & effectively using direct marketing techniques such as emails & SMS etc.,

Research Ideas

• Creating targeted email campaigns to increase Saree sales: The dataset can be used to create targeted email campaigns that can reach the 10,000 Saree Retailers in India. This will allow businesses to increase sales by directing their message about promotions and discounts directly to potential customers.
• Customizing online product recommendations for each retailer: The dataset can be used to identify the specific products that each individual retailer is interested in selling, so product recommendations on an e-commerce website could be tailored accordingly. This would optimize customer experience giving them more accurate and relevant results when searching for a particular item they are looking for while shopping online.
• Using GPS technology to generate location-based marketing campaigns: By creating geo-fenced areas around each store using the pin code database, it would be possible to send out marketing messages based on people's physical location instead of just sending them out in certain neighborhoods or cities without regard for store locations within those areas. This could help reach specific customers with relevant messages about products or promotions that may interested them more effectively than a standard marketing campaign with no location targeting involved

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: 301-Saree-Garment-Retailer-Database-Sample.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Amresh.

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