Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

Success.ai offers B2B marketing data across industries and geographies, tailored to fit your specific business needs. With our white-glove service, you’ll receive curated, ready-to-use company datasets without the hassle of managing data platforms yourself. Whether you’re looking for UK B2B data or global datasets, Success.ai ensures a seamless experience with the most accurate and up-to-date information in the market.

Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

Why Choose Success.ai?

• Best Price Guarantee: We offer industry-leading pricing and beat any competitor.
• Global Reach: Access over 28 million verified company profiles across 195 countries.
• Comprehensive Data: Over 15 data points, including company size, industry, funding, and technologies used.
• Accurate & Verified: AI-validated with a 99% accuracy rate, ensuring high-quality data.
• Real-Time Updates: Stay ahead with continuously updated company information.
• Ethically Sourced Data: Our B2B data is compliant with global privacy laws, ensuring responsible use.
• Dedicated Service: Receive personalized, curated data without the hassle of managing platforms.
• Tailored Solutions: Custom datasets are built to fit your unique business needs and industries.

Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

Company Name: Get the full legal name of the company. LinkedIn URL: Direct link to the company's LinkedIn profile. Company Domain: Website URL for more detailed research. Company Description: Overview of the company’s services and products. Company Location: Geographic location down to the city, state, and country. Company Industry: The sector or industry the company operates in. Employee Count: Number of employees to help identify company size. Technologies Used: Insights into key technologies employed by the company, valuable for tech-based outreach. Funding Information: Track total funding and the most recent funding dates for investment opportunities. Maximize Your Sales Potential: With Success.ai’s B2B contact data and company datasets, sales teams can build tailored lists of target accounts, identify decision-makers, and access real-time company intelligence. Our curated datasets ensure you’re always focused on high-value leads—those who are most likely to convert into clients. Whether you’re conducting account-based marketing (ABM), expanding your sales pipeline, or looking to improve your lead generation strategies, Success.ai offers the resources you need to scale your business efficiently.

Tailored for Your Industry: Success.ai serves multiple industries, including technology, healthcare, finance, manufacturing, and more. Our B2B marketing data solutions are particularly valuable for businesses looking to reach professionals in key sectors. You’ll also have access to small business contact data, perfect for reaching new markets or uncovering high-growth startups.

From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

Key Use Cases:

• Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
• Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
• Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
• Market Research: Enrich your market intelligence initiatives by gain...

Context

You get many visitors to your website every day, but you know only a small percentage of them are likely to buy from you, while most will perhaps not even return. Right now you may be spending money to re-market to everyone, but perhaps we could use machine learning to identify the most valuable prospects?

Content

This data set represents a day's worth of visit to a fictional website. Each row represents a unique customer, identified by their unique UserID. The columns represent feature of the users visit (such as the device they were using) and things the user did on the website in that day. These features will be different for every website, but in this data a few of the features we consider are: - basket_add_detail: Did the customer add a product to their shopping basket from the product detail page? - sign_in: Did the customer sign in to the website? - saw_homepage: Did the customer visit the website's homepage? - returning_user: Is this visitor new, or returning?

In this data set we also have a feature showing whether the customer placed an order (ordered), which is what we predict on.

Annual data on births, deaths and survival of businesses in the UK, by geographical area and Standard Industrial Classification 2007: SIC 2007 groups.

The Business Structure Database is managed by the Secure Data Service (SDS) and can only be accessed through secure conditions. The ‘domestic use’ input-output matrix, contains domestic trade flows describing intermediate demand between Standard-Industrial-Classification (SIC) coded sectors. This was obtained from the ONS.

GRIT (‘Geospatial Restructuring of Industrial Trade’) is an ESRC-funded project in the School of Geography at the University of Leeds. An energy revolution must take place if the worst effects of climate change are to be avoided. Even without the impact this may have (eg through carbon pricing), fuel costs have a very uncertain future. GRIT has two aims:

create a fine-grained picture of the current spatial structure of the UK economy

consider how changing fuel prices could alter that structure over the long term. GRIT examines the web of connections between businesses in the UK to identify sectors and locations facing the greatest changes.

GRIT will work with a unique dataset: the Business Structure Database contains information for nearly every UK business, including location and sector classification. This will be linked to sectoral trade flow data. These two sources offer an opportunity to map the current spatial distribution of economic activity in the UK and to think about how that distribution may change in the future. GRIT combines this data-driven approach with a plan to engage with organisations directly affected. GRIT will work closely with a small number of organisations and engage others through the project website.

This CD-ROM product is an authoritative reference source of 15 key financial ratios by industry groupings compiled from the North American Industry Classification System (NAICS 2007). It is based on up-to-date, reliable and comprehensive data on Canadian businesses, derived from Statistics Canada databases of financial statements for three reference years. The CD-ROM enables users to compare their enterprise's performance to that of their industry and to address issues such as profitability, efficiency and business risk. Financial Performance Indicators can also be used for inter-industry comparisons. Volume 1 covers large enterprises in both the financial and non-financial sectors, at the national level, with annual operating revenue of $25 million or more. Volume 2 covers medium-sized enterprises in the non-financial sector, at the national level, with annual operating revenue of $5 million to less than $25 million. Volume 3 covers small enterprises in the non-financial sector, at the national, provincial, territorial, Atlantic region and Prairie region levels, with annual operating revenue of $30,000 to less than $5 million. Note: FPICB has been discontinued as of 2/23/2015. Statistics Canada continues to provide information on Canadian businesses through alternative data sources. Information on specific financial ratios will continue to be available through the annual Financial and Taxation Statistics for Enterprises program: CANSIM table 180-0003 ; the Quarterly Survey of Financial Statements: CANSIM tables 187-0001 and 187-0002 ; and the Small Business Profiles, which present financial data for small businesses in Canada, available on Industry Canada's website: Financial Performance Data.

This dataset offers a comprehensive overview of over 50,000 companies, detailing essential information such as website domain, company name, and stock ticker. It also includes variables indicating companies' involvement in specific controversial activities. This rich dataset is ideal for a variety of analyses, including ESG (Environmental, Social, and Governance) assessments, allowing users to explore corporate practices concerning these significant metrics. Whether you're a financial analyst, academic researcher, or data enthusiast, this dataset provides fertile ground for in-depth analysis of the global corporate landscape.

Dataset Contents

-**domain**: The official web domain of the company.

-**name**: The name of the company.

-**ticker** : The stock ticker symbol used for the company in stock exchanges.

-**involvement**: Indicators of the company's involvement in various controversial sectors: 1. Alcoholic Beverages: Involvement in alcoholic beverages. 2. Adult Entertainment: Involvement in adult entertainment. 3. Gambling: Involvement in gambling. 4. Tobacco Products: Involvement in tobacco products. 5. Animal Testing: Involvement in animal testing. 6. Fur and Specialty Leather: Involvement in fur and specialty leather. 7. Controversial Weapons: Involvement in controversial weapons. 8. Small Arms: Involvement in small arms. 9. Catholic Values: Involvement in activities contrary to Catholic values. 10. GMO: Involvement in genetically modified organisms. 11. Military Contracting: Involvement in military contracting. 12. Pesticides: Involvement in pesticides. 13. Thermal Coal: Involvement in thermal coal. 14. Palm Oil: Involvement in palm oil.

-**employees**: The number of employees in the company.

-**industry**: The industrial sector to which the company belongs.

-**sector**: The market sector to which the company belongs.

-**altman_score**: The company's Altman Z-score, used to predict bankruptcy risk.

-**piotroski_score**: The company's Piotroski F-score, used to assess the financial health of the company.

-**Controversies**: Indicators of the company's ESG controversies: 1. Environment: Environmental controversies. 2. Social: Social controversies. 3. Customers: Customer-related controversies. 4. Human Rights & Community: Human rights and community-related controversies. 5. Labor Rights & Supply Chain: Labor rights and supply chain-related controversies. 6. Governance: Governance-related controversies.

-**Decarbonization Target**: The company's decarbonization targets: 1. Target Year: The target year for the decarbonization goal. 2. Comprehensiveness: The percentage comprehensiveness of the decarbonization target. 3. Ambition p.a.: The annual percentage ambition of the decarbonization target. 4. Decarbonization Target: Whether the company has a decarbonization target. 5. Decarbonization Target on Temperature Rise: Whether the decarbonization target addresses temperature rise. 6. Temperature Goal: The company's temperature goal in degrees Celsius.

-**sdg**: The company's alignment with the United Nations Sustainable Development Goals: 1. No Poverty: No poverty. 2. No Hunger: Zero hunger. 3. Good Health and Well-Being: Good health and well-being. 4. Quality Education: Quality education. 5. Gender Equality: Gender equality. 6. Clean Water and Sanitation: Clean water and sanitation. 7. Affordable and Clean Energy: Affordable and clean energy. 8. Decent Work and Economic Growth: Decent work and economic growth. 9. Industry, Innovation and Infrastructure: Industry, innovation and infrastructure. 10. Reduced Inequalities: Reduced inequalities. 11. Sustainable Cities and Communities: Sustainable cities and communities. 12. Responsible Consumption and Production: Responsible consumption and production. 13. Climate Action: Climate action. 14. Life under Water: Life under water. 15. Life on Land: Life on land. 16. Peace, Justice and Strong Institutions: Peace, justice and strong institutions. 17. Partnerships for the Goals: Partnerships for the goals.

-**esg**: The company's overall Environmental, Social, and Governance (ESG) score.

-**involvement_msci**: The company's involvement in controversial sectors according to MSCI: 1. Controversial Weapons: Involvement in controversial weapons. 2. Gambling: Involvement in gambling. 3. Tobacco Products: Involvement in tobacco products. 4. Alcoholic Beverages: Involvement in alcoholic beverages.

The data may be incorrect, being scraped from YahooFinance.com, Investing.com, StockAnalysis.com, MSCI

Ebitda-Per-Share Time Series for Askul Corp. ASKUL Corporation engages in e-commerce business in Japan. The company operates ASKUL, a website for small and medium-sized enterprises, as well as SOLOEL ARENA, a website for mid-tier and larger companies that provides office supplies, living supplies, furniture, general medical, pharmaceuticals, and medical equipment products. It also provides various services comprising make printed materials, such as business cards, envelopes, stamps, and personalized novelty goods; office coordinate services; and support services on an e-commerce website where customers can get advice by professional staffs, as well as sells SaaS, communication tools, and seminars for beginners. In addition, the company sells maintenance, repair, and operation supplies; provision of purchase solutions for large companies, and e-commerce website of professional items for dentists; and engages in agent business. Further, it is involved in the operation of e-commerce site for pet and gardening products; provision of logistics and small-cargo transportation, product storage, warehouse management, and delivery services for manufacturers and direct-order companies; and produces and sells bottled natural mineral water. The company was incorporated in 1963 and is headquartered in Tokyo, Japan.

This dataset presents statistics about the businesses which are involved with tourism in specific Local Government Areas (LGA) around Australia. The LGAs covered in the data are a subset of the LGA boundaries classified in the 2016 Australian Statistical Geography Standard (ASGS). The data represents information about the number of businesses involved in tourism by the number of employees they have employed. The data was sourced for the year 2016. Tourism Research Australia (TRA) first developed Local Government Area tourism profiles in 2007 to assist industry and Government decision making and to identify and support investment opportunities, particularly in regional Australia. The latest profiles provide an update for over 200 Local Government Areas. Data are drawn from TRA's International Visitor Survey (IVS) and National Visitor Survey (NVS), along with demographic and business data from the Australian Bureau of Statistics (ABS). Profiles were only prepared for Local Government Areas with adequate International Visitor Survey (IVS) and National Visitor Survey (NVS) sample to present robust results. For more information please visit the Website of the TRA. Please note: AURIN has spatially enabled the original data.

Properties receiving Small Business Rate Relief, either at the maximum amount or on the tapered relief for qualifying properties with Rateable Values (RV) between £12,000 and £17,000. Includes: Liable Party Name; Property Reference; Rateable Value; Property Address; Property Postcode.

For more information on business rates in Calderdale, see the council website: Business Rates.

This dataset presents statistics about the businesses which are involved with tourism in specific Local Government Areas (LGA) around Australia. The LGAs covered in the data are a subset of the LGA …Show full descriptionThis dataset presents statistics about the businesses which are involved with tourism in specific Local Government Areas (LGA) around Australia. The LGAs covered in the data are a subset of the LGA boundaries classified in the 2018 Australian Statistical Geography Standard (ASGS). The data represents information about the number of businesses involved in tourism by the number of employees they have employed. The data was sourced for the year 2018. Tourism Research Australia (TRA) first developed Local Government Area tourism profiles in 2007 to assist industry and Government decision making and to identify and support investment opportunities, particularly in regional Australia. The latest profiles provide an update for over 200 Local Government Areas. Data are drawn from TRA's International Visitor Survey (IVS) and National Visitor Survey (NVS), along with demographic and business data from the Australian Bureau of Statistics (ABS). Profiles were only prepared for Local Government Areas with adequate IVS and NVS sample to present robust results. For more information please visit TRA. Please note: AURIN has spatially enabled the original data. Where data values were, "np", not published or "-", not available, in the original data, they have been set to null. Copyright attribution: Website of Tourism Research Australia, (2019): ; accessed from AURIN on 12/3/2020. Licence type: Creative Commons Attribution 3.0 Australia (CC BY 3.0 AU)

This data uses a national employer survey to show numbers and percentages of people employed in jobs in industries in each broad industrial group. Data is shown for Lincolnshire and Districts, and also for smaller areas (such as Wards, and Lower super output areas (LSOAs from the 2011 Census)). Some limitations of the dataset are that figures for small areas (Wards and LSOAs) exclude employees in farm agriculture (Standard Industrial Classification subclass 01000). The figures include businesses registered for PAYE but not for VAT. Values may be rounded and low numbers suppressed (particularly at smaller geographies) so numbers may not tally precisely with figures for larger areas. Figures are shown for the most recent year available, although these are provisional and may be subject to later revision by ONS. This data is based on the ONS Business Register and Employment Survey (BRES, open access) sourced from the Office for National Statistics (ONS) Nomis website. More detailed breakouts of Standard Industrial Classifications are available from the Source weblink. This dataset is updated annually

Einstellungen von Unternehmen zu Online-Aktivitäten. Themen: Unternehmen verkauft oder tätigt Einkäufe online und / oder nutzt elektronischen Datenaustausch (Electronic Data Interchange (EDI)); Online-Verkauf von Produkten oder Dienstleistungen über: eigene Website oder Apps, kleine Handelsplattform, große Handelsplattform, Transaktionen mit elektronischem Datenaustausch; prozentualer Anteil der Online-Verkäufe aus den folgenden Ländern an den gesamten Online-Verkäufen im Jahr 2014: Land, in dem das Unternehmen ansässig ist, andere EU-Länder, Länder außerhalb der EU; Länder, in denen 2014 online verkauft wurde; prozentualer Anteil der herkömmlichen Verkäufe aus den folgenden Ländern am herkömmlichen Umsatz im Jahr 2014: Land, in dem das Unternehmen ansässig ist, andere EU-Länder, Länder außerhalb der EU; Überlegungen oder Versuche, online in anderen EU-Ländern zu verkaufen; Unternehmen, die bereits Online-Handel praktizieren, wurden gefragt: Bedeutung der einzelnen folgenden Schwierigkeiten beim Online-Verkauf in andere EU-Länder: hohe Lieferkosten, hohe Kosten für Garantien und Rücksendungen, Unkenntnis der einzuhaltenden Vorschriften, mangelnde Sicherheit von Zahlungen aus dem Ausland, Urheberrechtsgründe, komplizierte oder hohe Besteuerung im Ausland, Notwendigkeit zur Anpassung der Produktetikettierung, mangelnde Sprachkenntnisse, Beschränkung oder Verbot von Verkäufen ins Ausland durch die Zulieferer, Verbot zur Nutzung einer Plattform Dritter durch die Zulieferer, Anordnung der Zulieferer zum Verkauf im Ausland zu anderen Preisen, Datenschutzangelegenheiten, unzureichende Interoperabilität, Spezifizität der Produkte, langsame Internetverbindung des Unternehmens oder der Kunden, hohe Kosten bei der Klärung von Beschwerden oder Streitfällen über Landesgrenzen hinweg; Unternehmen, die bisher keinen Online-Handel praktizieren, wurden gefragt: Bedeutung der einzelnen folgenden Schwierigkeiten beim Online-Verkauf: Mangel der nötigen digitalen Kompetenzen, Unkenntnis der einzuhaltenden Vorschriften, hohe Lieferkosten, hohe Kosten für Garantien und Rücksendungen, Beschränkung oder Verbot des Online-Verkaufs durch die Zulieferer, höhere Preise der Zulieferer für online verkaufte Produkte, Verbot zur Nutzung einer Plattform Dritter durch die Zulieferer, Risiko des Preisverfalls online verkaufter Produkte, Risiko der Imageschädigung von Unternehmen und Marken, langsame Internetverbindung des Unternehmens. Demographie: Angaben zum Unternehmen: Anzahl der Mitarbeiter, Gründungsjahr, unabhängig oder Teil eines nationalen oder internationalen Konzerns, Art der verkauften Produkte oder Dienstleistungen und Zielgruppe; Gesamtumsatz im Jahr 2014; Entwicklung des Umsatzes seit Januar 2012; prozentualer Anteil der Online-Verkäufe am Umsatz 2014; prozentualer Anteil des Online-Einkaufs am Gesamt-Einkauf 2014. Zusätzlich verkodet wurde: Befragten-ID; Land; NACE-Code; Unternehmensgröße; präferierte Interviewsprache; Nationengruppe; Gewichtungsfaktor. Companies’ attitudes towards online activities. Topics: company sells or purchases online and / or uses Electronic Data Interchange (EDI) type transactions; online selling of products or services using: own website or apps, small commercial platform, large commercial platform, EDI type transactions; percentage of the company´s online sales in 2014 coming from: country where company is located, other EU countries, countries outside the EU; countries in which online selling was available in 2014; percentage of the company´s non-online sales in 2014 coming from: country where company is located, other EU countries, countries outside the EU; considerations or attempts to sell online in other EU countries; companies already practicing online selling were asked: significance of each of the following difficulties regarding online selling to other EU countries: high delivery costs, expensiveness of guarantees and returns, ignorance of the applicable rules, insufficient security of payments from other countries, copyright reasons, complicated or costly foreign taxation, necessity to adapt product labeling, lack of language skills, restriction or interdiction by suppliers to sell abroad, interdiction by suppliers to use third platform for selling, request of suppliers to sell abroad at different prices, data protection issues, insufficient interoperability, specificity of products, slow internet connection of company or of customers, costs from resolving complaints and disputes cross-border; companies not yet practicing online selling were asked: significance of each of the following difficulties regarding online selling: lack of necessary digital skills, ignorance of the applicable rules, high delivery costs, expensiveness of guarantees and returns, restriction or interdiction by suppliers to sell online, higher prices imposed by suppliers for products sold online, interdiction by suppliers to use third platform for selling, risk of reduction in price for products sold online, risk of damaging image of company and trademarks, slow internet connection of the company. Demography: information about the company: number of employees, year of establishment, independent or part of national or international group, kind of sold products or services and target group; total turnover in 2014; development of turnover since January 2012; percentage of the value of sales in 2014 coming from online sales; percentage of the value of goods and services purchased online by the company in 2014. Additionally coded was: respondent ID; country; NACE-Code; company size; preferred language of the interview; nation group; weighting factor.

A league table of the 120 cryptocurrencies with the highest market cap reveals how diverse each crypto is and potentially how much risk is involved when investing in one. Bitcoin (BTC), for instance, had a so-called "high cap" - a market cap worth more than 10 billion U.S. dollars - indicating this crypto project has a certain track record or, at the very least, is considered a major player in the cryptocurrency space. This is different in Decentralize Finance (DeFi), where Bitcoin is only a relatively new player. A concentrated market The number of existing cryptocurrencies is several thousands, even if most have a limited significance. Indeed, Bitcoin and Ethereum account for nearly 75 percent of the entire crypto market capitalization. As crypto is relatively easy to create, the range of projects varies significantly - from improving payments to solving real-world issues, but also meme coins and more speculative investments. Crypto is not considered a payment method While often talked about as an investment vehicle, cryptocurrencies have not yet established a clear use case in day-to-day life. Central bankers found that usefulness of crypto in domestic payments or remittances to be negligible. A forecast for the world's main online payment methods took a similar stance: It predicts that cryptocurrency would only take up 0.2 percent of total transaction value by 2027.

In the fourth quarter of 2024, TikTok generated around 186 million downloads from users worldwide. Initially launched in China first by ByteDance as Douyin, the short-video format was popularized by TikTok and took over the global social media environment in 2020. In the first quarter of 2020, TikTok downloads peaked at over 313.5 million worldwide, up by 62.3 percent compared to the first quarter of 2019.

              TikTok interactions: is there a magic formula for content success?

              In 2024, TikTok registered an engagement rate of approximately 4.64 percent on video content hosted on its platform. During the same examined year, the social video app recorded over 1,100 interactions on average. These interactions were primarily composed of likes, while only recording less than 20 comments per piece of content on average in 2024.
              The platform has been actively monitoring the issue of fake interactions, as it removed around 236 million fake likes during the first quarter of 2024. Though there is no secret formula to get the maximum of these metrics, recommended video length can possibly contribute to the success of content on TikTok.
              It was recommended that tiny TikTok accounts with up to 500 followers post videos that are around 2.6 minutes long as of the first quarter of 2024. While, the ideal video duration for huge TikTok accounts with over 50,000 followers was 7.28 minutes. The average length of TikTok videos posted by the creators in 2024 was around 43 seconds.

              What’s trending on TikTok Shop?

              Since its launch in September 2023, TikTok Shop has become one of the most popular online shopping platforms, offering consumers a wide variety of products. In 2023, TikTok shops featuring beauty and personal care items sold over 370 million products worldwide.
              TikTok shops featuring womenswear and underwear, as well as food and beverages, followed with 285 and 138 million products sold, respectively. Similarly, in the United States market, health and beauty products were the most-selling items,
              accounting for 85 percent of sales made via the TikTok Shop feature during the first month of its launch. In 2023, Indonesia was the market with the largest number of TikTok Shops, hosting over 20 percent of all TikTok Shops. Thailand and Vietnam followed with 18.29 and 17.54 percent of the total shops listed on the famous short video platform, respectively.

Context

getlatka.com is a SaaS Database, which contains data from over 1,000 manual interviews with CEO's of SAAS (Software as a service) tech companies.

At the time we harvested the data there was a statement on the website that said "You are only seeing a very small percentage of data. Click here to unlock it all and export." It was also stated that there are 1,082 companies in the database. The dataset we have contains 606 rows. So we have 56% of the available data.

The dataset is rare in that the information is all manually generated and contains metrics on private companies typically not publicly available. Having listened to a few of the podcasts it's surprising that Nathan Latka is able to get this information out of these CEO's. Some metrics include Number of Customers, Revenue, Churn Rates, Customer LTV and CEO Age and much more.

If you wish to purchase the data you should. As of March 2019 you are only seeing approx. 50% of it.

Acknowledgements

This data has been provided courtesy of elementive.io

The original blog post - Characteristics of Successful Entrepreneurs (SAAS)

This Hotel Dataset: Rates, Reviews & Amenities(6k+) dataset includes hotel rates, guest reviews, and available amenities from two popular travel websites, TripAdvisor and Booking.com. The dataset can be used to analyze trends and insights in the hospitality industry, and inform decisions related to pricing, marketing, and customer service. Booking.com: Founded in 1996 in Amsterdam, Booking.com has grown from a small Dutch start-up to one of the world’s leading digital travel companies. Part of Booking Holdings Inc. (NASDAQ: BKNG), Booking.com’s mission is to make it easier for everyone to experience the world.

By investing in technology that takes the friction out of travel, Booking.com seamlessly connects millions of travelers to memorable experiences, a variety of transportation options, and incredible places to stay – from homes to hotels, and much more. As one of the world’s largest travel marketplaces for both established brands and entrepreneurs of all sizes, Booking.com enables properties around the world to reach a global audience and grow their businesses.

Booking.com is available in 43 languages and offers more than 28 million reported accommodation listings, including over 6.6 million homes, apartments, and other unique places to stay. Wherever you want to go and whatever you want to do, Booking.com makes it easy and supports you with 24/7 customer support. Tripadvisor, the world's largest travel guidance platform*, helps hundreds of millions of people each month** become better travelers, from planning to booking to taking a trip. Travelers across the globe use the Tripadvisor site and app to discover where to stay, what to do and where to eat based on guidance from those who have been there before. With more than 1 billion reviews and opinions of nearly 8 million businesses, travelers turn to Tripadvisor to find deals on accommodations, book experiences, reserve tables at delicious restaurants and discover great places nearby. As a travel guidance company available in 43 markets and 22 languages, Tripadvisor makes planning easy no matter the trip type. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), own and operate a portfolio of travel media brands and businesses, operating under various websites and apps.

Crowdfunding has become one of the main sources of initial capital for small businesses and start-up companies that are looking to launch their first products. Websites like Kickstarter and Indiegogo provide a platform for millions of creators to present their innovative ideas to the public. This is a win-win situation where creators could accumulate initial fund while the public get access to cutting-edge prototypical products that are not available in the market yet.

At any given point, Indiegogo has around 10,000 live campaigns while Kickstarter has 6,000. It has become increasingly difficult for projects to stand out of the crowd. Of course, advertisements via various channels are by far the most important factor to a successful campaign. However, for creators with a smaller budget, this leaves them wonder,

"How do we increase the probability of success of our campaign starting from the very moment we create our project on these websites?"

Data Sources

All of my raw data are scraped from Kickstarter.com.

1. First 4000 live projects that are currently campaigning on Kickstarter (live.csv)

   • Last updated: 2016-10-29 5pm PDT
   • amt.pledged: amount pledged (float)
   • blurb: project blurb (string)
   • by: project creator (string)
   • country: abbreviated country code (string of length 2)
   • currency: currency type of amt.pledged (string of length 3)
   • end.time: campaign end time (string "YYYY-MM-DDThh:mm:ss-TZD")
   • location: mostly city (string)
   • pecentage.funded: unit % (int)
   • state: mostly US states (string of length 2) and others (string)
   • title: project title (string)
   • type: type of location (string: County/Island/LocalAdmin/Suburb/Town/Zip)
   • url: project url after domain (string)

2. Top 4000 most backed projects ever on Kickstarter (most_backed.csv)

   • Last updated: 2016-10-30 10pm PDT
   • amt.pledged
   • blurb
   • by
   • category: project category (string)
   • currency
   • goal: original pledge goal (float)
   • location
   • num.backers: total number of backers (int)
   • num.backers.tier: number of backers corresponds to the pledge amount in pledge.tier (int[len(pledge.tier)])
   • pledge.tier: pledge tiers in USD (float[])
   • title
   • url

See more at http://datapolymath.paperplane.io/

Context

This dataset contains the results from 50 surveys taken on LinkedIn.

Acknowledgements

These results were gathered by Dr. Mikko J Rissanen, a freelance VR/AR expert. If you're looking to up your freelancer game then I highly recommend you check out his website CoachLancer. Many also know him as 'that coconut guy from LinkedIn'.

Inspiration

I originally approached Mikko after seeing one of his posts where he was discussing some of the insights given by the survey results. I thought that it would be cool to look at the wider dataset and pick out some key themes. By grouping related questions and doing some data visualization, I thought we could get some pretty cool results.

My hope with making this data publicly available on Kaggle is that others could help build on our work and help pick out some cool insights which we may not have thought of!

Content

All of the questions have got 2, 3 or 4 options, so the data columns are as follows:

question - This is the number question that the data refers to, see below for the full list of questions. A - The percentage of respondents that chose option A. B - The percentage of respondents that chose option B. C - The percentage of respondents that chose option C. D - The percentage of respondents that chose option D. respondents - The number of people that responded to the poll on LinkedIn. Polls were done one at a time, so this number varies from 6-478.

Full question list:

1 - How should AdWed continue to promote online freelancers? A - Continue posting on LinkedIn B - Featured CoachLancer articles C - Make a new portfolio website D - No option

2 - Do you get hired for projects of the type that you must tell your client you haven't done before? A - No, never B - Yes, sometimes C - Yes, most of the time D - Absolutely, I do nothing but

3 - Which types of professional organizations do you belong to for finding clients for your freelance business? A - Freelancers' union or similar B - Paid membership organization C - Free membership organization D - None of the above

4 - Is freelancing your Holy Grail? A - Yes, of course it is! B - Yes, maybe it is, actually. C - Yes... no... aaaaaaaaaaaargh! D - No option

5 - What method do you use for screening your clients on a freelance site (e.g. Upwork, PeoplePerHour, etc.)? A - Text messaging B - One audio call C - One video call D - Multiple in-depth discussions

6 - How long would you say you struggled before your freelance business brought you satisfactory income? A - Weeks B - Months C - Half a year D - One year or more

7 - Have you ever pivoted your freelance business from one service to another? A - No, not yet B - No, and never will C - Yes, once D - Yes, many times

8 - Do your clients have the same skillset as yourself A - Yes, all of them B - Yes, some of them C - No, none of them D - No option

9 - Freelancing is great, but are there any parts that you miss from your old day job? A - Great work community B - Stable salary C - Risk-free work life D - Clarity in work assignments

10 - What skill would you like to develop most for making your freelance business grow? A - Finding new sales channels B - Communicating with clients C - Closing deals D - Executing the work

11 - Freelancer, how much time off do you manage to take during Christmas break? A - More than 4 days B - 4 days C - 1-2 days D - What Christmas break?

12 - Do you have any collaborators as part of your freelance business? A - No, don't need anyone B - I have subcontractors C - I have marketing help D - I have sales partners

13 - Freelances, how often do you have a disagreement with a client about the price of your work? A - Never B - Sometimes C - Almost every time D - No, it's called "negotiation"!

14 - How much financial runway did you have when you started freelancing? (Savings for covering your living expenses) A - 0 months, I felt lucky B - <4 months was enough C - 4-6 months as recommended D - >6 months

15 - What do you mainly look for when you are about to work with a new client? A - Money B - Fun collaboration C - Long-term relationship D - Challenging work

16 - What type of issues did you experience in the hardest freelance project you've ever done? A - Deadlines/time management B - Changing requirements C - Communicates with the client D - Own work process/execution

17 - Do you sell your freelance services through an kind of sales partner? A - No, never B - Yes, sometimes I use partners C - Yes, I use partners always D - No option

18 - Which type of business do you think is better for freelancing? A - Be a small fish in a big pond B - Be a big fish in a small pond C - No option D - No option

19 - What kind of clients does your freelance business serve? A - Individuals B - Startups C - Small companies D - Large companies

20 - If you could make one wish to change ...