Repository for Columbia DS Bootcamp Challenge 1
This analysis is provided in order to help a new playwrite who wishes to use crowdfunding to finance her play, Fever, and decide how to run her fundraising campaign. The purpose of the analysis is to analyze data on various crowdfunding campaigns to determine trends of successful fundraising campaigns on kickstarter. The analysis provides some key outcomes and recommendations from the dataset.
Based on some basic statistics, a goal of raising $10,000 for production cost for the play is about two times higher than the average goal for successful campaigns in this dataset, although there were some successful fundriasing campaigns with higher goals. It is recommended that the timing for the fundraising campaign start in either April or May and end by the end of September; this seems to be the most popular time for fundriasing campaigns and when the most campaigns saw the most success. Basic statistics comparing successful and failed campaigns can be seen in the table below.
Some challenges are understanding why some fundraising campaigns failed. We can make inferences about the goals and costs, but it looks like some campaigns recieved no pledges at all and one challenge is not knowing what went wrong in those cases. Another challenge is that most of the data in this data set is from 2014 to 2017 and there is a possibility that the pandemic could have changed how people feel about going to the theater, menaing that this data could be less representative of fundraising today.
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By far the most successful month for crowfunding is May. May and October are the months with the most failed campaigns, so these months are popular launch dates for a campaign. April through August seem to be the most successful months to start fundraising. The outcomes for crowdfunding for theater projects mirrors the outcomes for all categories in the dataset.
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The goals which were less than $15,000 had higher rates of success then failer as did goals in the range of $35,000 to $40,000. The rate of failure increases dramatically with goals over $45,000. The most successful campaigns had goals less then $5,000.
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This dataset is limited by number and timing. While the play category represents about a quarter of fundraising campaigns in the dataset so is fairly repesentative for this client, that is only data on 1067 fundraising campaigns for plays. Another potential limitation is the prepandemic timing.
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Some other tables and graphs that could be helpful would be how outcomes are impacted by the number of backers for a campaign and what the average donations are for successful campaigns. A chart showingh the breakdown of outcomes based on category shows that in general theater is the most popular category to start a fundraiser for.
