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An Innovative Big-Data Web Scraping Tech Company

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WebRobot Ltd, the big data approach to web scraping technology

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An Innovative Big-Data Web Scraping Tech Company

  1. 1. Elevator Pitch An Innovative Big-Data Web Scraping Tech Company BUSINESS IDEABUSINESS IDEA
  2. 2. Innovative Big-Data Web Scraping Tech Company HIGHLIGHTS  What is WebRobot?  The Problem  How We Can Solve It  Team  Track Record  Business Model  Trends & Opportunities  Main Competitors  Target  SWOT Analysis  Some Numbers (sales, profit, clients)  Investment Plan 2
  3. 3. 1. THE PROJECT Description  WebRobot Ltd is a London-based company that operates in the web scraping and web mining industry in which it aims to become the leader.  In WebRobot we are building a super scalable infrastructure for data acquisition that customers can use as a web service. It exploits cloud computing and big-data technologies, as well as data-extraction and information-extraction algorithms.  WebRobot will be a great ally to every company that needs to acquire this heterogeneous network of information and wants to reduce its internal management costs. WebRobot’s services will represent a strategic resource essential to its business success. Innovative Big-Data Web Scraping Tech Company 3
  4. 4. 1. THE PROJECT The problem Every company wishing to achieve, keep and improve its business success needs information (data) on both the market, customers, and competitors, but this is challenging. It must get good, reliable, and well-organized data. In addition, it needs to manage them properly. The World Wide Web is made up of a huge amount of semi-structured and unstructured data. Furthermore, it constantly changes its structure. The cost to collect all of these data is often very expensive. For all these reasons, we need robust and scalable algorithms that can reduce this onerous maintenance activity. Innovative Big-Data Web Scraping Tech Company 4
  5. 5. 1. THE PROJECT How We Can Solve the Problem We can guarantee algorithmic and structural scalability with automatic extraction features. We offer a powerful solution in the form of a web service. We integrate cloud computing with big-data technologies applied in the more general web mining context. We use visual support tools and SDK to connect to our stack. WebRobot’s goal is to become a complete ETL service involving data extraction, web mining, machine learning, and big-data analytics. Innovative Big-Data Web Scraping Tech Company 5
  6. 6. 2. THE TEAM CEO, CTO Roger Giuffrè 71% of Equity Mediterraneo Capital Ltd 25% of Equity CCO, CMO Denis Giuffrè 4% of Equity CFO Antonio Censabella Roger Giuffrè Denis Giuffrè Antonio Censabella MEDITERRANEO CAPITAL LTD Innovative Big-Data Web Scraping Tech Company 6
  7. 7. 3. TRACK RECORD We are finalizing the first version of the web service which will include the serverless version on the Lambda technology and Amazon EMR. We need to integrate the wrapper induction algorithms directly into the spark context. This will help us refine them with the latest academic findings. API implementation is fundamentally finished. We have to complete the usability studies of the current interface. We need to complete the dashboard that will be released under an open-source license. We have to design visual tools to support the ETL that has to be generated. We have a new grammar to set up for the query. Innovative Big-Data Web Scraping Tech Company 7
  8. 8. 4. THE BUSINESS MODEL The Strategy We will release the service on the Amazon marketplace, available in three commercial packages: Entry-Level, Professional, and Enterprise. Our average selling price could be around €0.0008 per page scraped, but we will make a distinction between static and dynamic pages that need complex algorithms. We have verified that the execution costs on a serverless environment and on an EMR cluster can guarantee us a margin of at least 50%. This margin represents a cost constraint in our pricing policy. In the future, we will integrate a web agents marketplace and adopt a B2B2C paradigm to fill the gap with the end users, as well as with the actual use cases. Innovative Big-Data Web Scraping Tech Company 8
  9. 9. 5. THE MARKET AND COMPETITORS Trends and opportunities  Markets: Web Scraping, Web Mining, Data Analytics.  Dimension: $2 billion of estimated value in 2020 alone (in just one single year).  Growth: based on the market researches, we expect further growth in the next years induced by (1) an ever-greater centrality of data in the entire business process, and (2) the predisposition of the companies to outsource, more and more often, the above-mentioned activities. Innovative Big-Data Web Scraping Tech Company 9
  10. 10. Main Competitors  Diffbot: an API for data extraction that uses machine learning heuristic and features to crawl the pages. Unfortunately, the results are not 100% precise.  Scrapyhub: a cloud service focused on the Scrapy framework. It offers every single service separately plus automatic extraction functions that are still in beta version. Anyway, the results are not always compliant.  ImportIO: visual tools that customers can use to configure the extractors. However, it is particularly expensive. 5. THE MARKET AND COMPETITORS Innovative Big-Data Web Scraping Tech Company 10
  11. 11. 6. TARGET E-commerce companies that require algorithmic pricing and competition monitoring. Big companies that produce press reviews, carry out social media analysis, opinion mining, and sentiment analysis activities. Hedge funds and financial institutions for which information such as financial data and sentiment indicators are extremely important. Marketing agencies that need web scraping for SEO and web marketing automation purposes. Established and startup companies that run or are developing any kind of vertical search engine. Startups and small businesses that can benefit from building dedicated applications on our stack. Innovative Big-Data Web Scraping Tech Company 11
  12. 12. 7. SWOT ANALYSIS STRENGTHS WEAKNESSES Scalability. Self-service fast big-data extraction solution. We need PhD resources to reinforce the algorithmic extraction. Very specialized high-tech service that requires an effort to make it user-friendly (for non-technical users). OPPORTUNITIES RISKS Global market with big expansion opportunities. Profitable niche with low competition. Restrictive regulations on the use of personal data (in Europe), on data collection (in Asia), on data referring to minors (worldwide). Innovative Big-Data Web Scraping Tech Company 12
  13. 13. 8. THE NUMBERS We are considering a medium / large customer that requires at least 1 million pages per day at a price of €800.00 (there is a global potential request of 100 billion pages per day). EUR (in thousands) Year 2021 Year 2022 Year 2023 Year 2024 Sales 2,880 7,200 13,248 20,160 Gross margin 1,440 3,600 6,624 10,080 Net margin 1,440 3,600 6,624 10,080 Num. Customers 10 25 46 70 Innovative Big-Data Web Scraping Tech Company 13
  14. 14. 9. INVESTMENT PLAN The investment strategy First round: 9% in equity for €300k with a pre-money evaluation of €3 million. Second round: 9% in equity for €2 million. Third round: 9% in equity for €10 million. We plan to eventually go public on the stock exchange. Innovative Big-Data Web Scraping Tech Company 14

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