VC data analysis tools Concise Guide: American VC who is using what data analysis tools?a long time, the method of venture capital is as an art in a relatively small circle of circulation. Experienced VC tend to like their success is attributed to this art of timeless, but know people surgery is the top priority of this art. A start-up company's team (team), or product (product), or is the market / product attractiveness (traction), will be an important indicator to affect investment decisions of each VC. For a start-up companies (especially early in the team is still early-stage startup), in addition to the actual existence of possible products (Including semi-finished products and develop a prototype), Nike Basketball Shoes the rest of the indicators can be said nada. It has long been accustomed to such a screening mechanism: investors care about is feeling, perhaps more useful to look pleasing to the eye than the product concept. As this mechanism is successful, we need a different matter: Association of American VCs (National Venture Capital Association) of a set of data shows that in the first decade of the 21st century, the US venture capital industry overall return rate is negative. In this era of rampant Big Data concept, so long as the venture capital industry is located in the technology industry on the cusp of new technology and monasteries of various industries, data analysis should be Nike Air Max 89 incorporated into traditional practices in the attempt has also been an old tune new shells. Data analysis is widely used in various industries, especially in the financial sector. Asset Management (asset management) and fund companies are already decades ago large-scale application of mathematical theory to measure the quality of the company's investment products as well as predict future market performance. And with a wall, VC companies belong to the financial industry who use data analysis to quantitative evaluation should be an investment looks as it should do. We have on several occasions discussed before the impact and value of the data analysis in the field of venture capital may occur. In Google Ventures represented, including our familiar KPCB and Sequoia Capital (Sequoia Capital), including a public interest in the data analysis of investment venture has been going on for several years, but like IronStone this industry newcomers and YC such incubators Gangster also join them, even though the industry has to 'whether a computer algorithm can find the next Steve Jobs' This issue has not reached a consensus. Even as Google Ventures behind this 'data company' Google is the world's largest database and cloud computing backing of rich handsome, also has not been able universal standard formula, and how to more accurately quantify the team's chemistry and product market appeal, among other factors still an urgent industry issues. But Google Ventures claims to have acquired considerable progress in data analysis. They refused to disclose the results, but comprehensive information on all aspects opinion, Google Ventures formula may not have imagined so profound: They start as the city, the average age of the team, in the past entrepreneurial experience through the analysis of the use of such factors to consider every potential investment opportunities. However, before the establishment of Facebook Mark Zuckerberg sell your product prototypes without entrepreneurial experience, even Google Ventures of both boss, Larry Page and Sergey Brin, if you use such an algorithm evaluation, it estimated that it is difficult to pass. Google Ventures also quite self-knowledge, to see sense (intuition) and look pleasing to the eye (chemistry) is still quite important considerations in their investment decisions. KPCB and Sequoia such senior players also tried by analyzing the start-up companies mentioned on Twitter the number of start-up companies or products App Store ranking this data to analyze the value of a startup company. And IronStone, this was founded by the William Hambrecht as foreigners venture, the data analysis surpassed colleagues farther and faster. According to some information has been published, claiming that a start-up companies will account for 12 percent team factor in their consideration of the entire process, the most important factors in a team and even have long been regarded as a traditional venture capital; and Air Jordan 14 Another 20 percent were distributed to various other indicators start-up companies, and the remaining 68% of the market factors have all been occupied: to enter the market environment, the company's adjustment period, whether changes in the market can be expected, and so on. Now known or publicly stated that are or will be using quantitative analysis to vote startups, including major institutions mentioned above Google Ventures, KPCB, Sequoia Capital, IronStone, Y Combinator, and 500Startups, August Capital, Accel Partners, Andreessen Horowitz , Floodgate Fund, Greylock Partners, SVAngel like. Wherein, Accel Partners has earmarked $ 100 million fund as large data (Big Data Fund), and Greylock already using its internal data team created proprietary data analysis tools. Google +, Facebook and Twitter and other social networks are a major source of currently collected as data. VC traditional decision-making process can be roughly divided into five stages: potential market be? How many potential market opportunities? From a competitor to grab market? What are the potential business model? Revenue and profits can achieve what level? A conservative Nike Air Max 2013 KPU estimate of potential operational / production costs how much? With this round of financing to meet the cycle operations team? 5-10 years, whether there will be a potential IPO exit opportunities or opportunities? The most important thing is the majority of VC in front 2015 Latest Nike Shoes finalized, will ask themselves: Do I like this team / team is worth the investment? But after the introduction of data analysis, this process will be what kind of impact? The figure is based on my experience and organize various VC bigwigs article after making a chart reflecting tools related to data the American mainstream VC investment stage is mainly used in different analysis. For example, a data analysis to promote investment and focus on the early years of investment (early stage / seed stage) of the VC will be looking for investment targets in the early auditions and Seedsummit through AngelList startups such a database, and then use CapLinked sort of process relationship network management platform to establish contacts and set certain selection investment process. Currently the company's early for the quantitative assessment of what is yet to come fly tools, but will use some VC called YouNoodle Nike Air Presto Womens a start-up company to gather information on competitors, in order to evaluate the market competitiveness of the team. OwnYourVenture provides a platform, VC and entrepreneurs can obtain the value of equity allocation after several rounds of investment in the input data. And at the end of a round of financing, VC can be self-built database to track the company's operations to vote, also can track company information or local business market through this platform Startup Genome. In this we had to focus on the next CB Insights and PitchBook. CB Insights as a company with the financial industry in New York start-up data company background, done in the integration industry data and data analysis very well, they regularly report to VC industry data analysis and other relevant media institutions widely used, but they are not introduced less visual data analysis tools are also valuable. PitchBook also has excellent data visualization platform, but their products are for various start-up companies provide more specific information, a wealth of VC database for entrepreneurs and investors to provide the specific information to view each VC platform. Of course, 36Kr + database for domestic VC and entrepreneurs is a good tool, we will continue to improve and perfect our database, add new features to better serve the country's entrepreneurs and investment people. CB Insights Visual Database PitchBook information provided by the VC interface fairness, the current size of the data analysis and perhaps impossible to talk about big data, but if the database will be analyzed scale 10 times or even 100 times, so large data The technology is enough to dramatically improve the speed of venture Nike Air Max 90 Current capital, but as for the quality of the results, may need a relatively long time to give us the answer. Large amounts of data generated by the rapid development of mobile technology is a good example. He said development of mobile technology is dramatically changing every industry, even each individual's life, which can be used as venture capital industry. The era of big data has only just arrived, and the ability and potential of mobile Internet and mobile devices are difficult to estimate generated data, the best example is in the last two-eleven years, 15% of Taobao transactions from mobile end. For those who want to master the user needs and habits of entrepreneurs, and hoping to find the growth potential of the product and entrepreneurs VC who, this time may be an unprecedented golden age. The VC, the following data on hand with, the question is how to effectively analyze the data and quantitative evaluation criteria. For example, a real estate investor can use this quantitative indicators Case Shiller house price index to measure the current market environment, with open data and government documents to evaluate a home development company specific operating conditions; and focus on investment in listed companies to invest in who simply S \u0026 P 500 index and the earnings of a company will be able to outline the contours of an investment opportunity. For the VC and angel investors, such as investment and start-up screen when the company is unimaginable. VC due diligence (Due Diligence) very often can only be done through interpersonal exchange network of investors and subjective experience, rather than Excel and fine due diligence reports like the investment banks did throw a bundle. Even as CB Insights, Crunchbase, large numbers AngelList such data platform capable of changing VC were living in the past that the lack of data, but how to select the data, how to convert data into useful information, it is the VC's next challenge. Unless noted, articles are original or compiled site, please indicate: articles from 36 Krypton