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Performing analysis on Kickstarter data to uncover trends

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kickstarter-analysis

Overview of Project

Purpose

"Background: Louise’s play Fever came close to its fundraising goal in a short amount of time. Now, she wants to know how different campaigns fared in relation to their launch dates and their funding goals. Using the Kickstarter dataset that you’ve already combed through, you’ll visualize campaign outcomes based on their launch dates and their funding goals. You’ll then submit a written report based on your analysis and the visualizations you create."

This analysis was performed at customer request. Louise, our customer, is wondering how other campaigns did based on their launch dates and fundraising goals. The easiest way to present the data requested would be through two charts. One chart would show time versus output. The other chart demonstrates goals versus percentage of outcomes.

Analysis and Challenges

Outcomes_vs_Goals Figure 1: Outcomes versus Goals

Theater_Outcomes_vs_Launch Figure 2: Theater Outcomes versus Launch

Analysis of Outcomes Based on Launch Dates

Based on the graph, it is safe to assume that the holidays/end of the fiscal year seem to have an impact on successful campaigns. This could be due to people spending more on friends and family.

Analysis of Outcomes Based on Goals

Based on the graph, as your fundraising goal rises there is a higher chance of failure. Goals less than 20k seem to have the highest chance for success, but a higher goal doesn't necessarily mean guaranteed failure. It just becomes more difficult. In the plays category no campaigns were canceled. They either succeeded or failed.

Challenges and Difficulties Encountered

In "Deliverable 2", I did not understand step 4. I tried using “COUNTIFS” to find the number of successes of plays and then count the number of successes in the plays category. I repeated the same for failures and canceled. When I skimmed the instructions, I must of misunderstood the assignment. I also find difficulties knowing when to use the cell as a reference or text/number.

Results

  • What are two conclusions you can draw about the Outcomes based on Launch Date?

Canceled campaigns happen all year round. Midyear seems to have the best chance of a successful campaign, but also raises the number of failed campaigns as well. This likely also means that most fundraising campaigns begin in the midyear time frame.

  • What can you conclude about the Outcomes based on Goals?

You increase the chance of failure with a higher goal, but it’s not guaranteed. It shows that regardless of goal that management plays into the success of the fundraising campaign.

  • What are some limitations of this dataset?

Based on running some statistical analysis, all values greater than zero dollars up to eight thousand dollars are valid pledges. If you only include the successful campaigns, you can see that ten thousand seems to be a better upper limit. There could be an assortment of other factors that contributed to the success or failure of a fundraising campaign.

  • What are some other possible tables and/or graphs that we could create?

Box and whisker plot are an easy way for someone like our customer to visually see how reasonable the data set is for outliers. A pareto chart could also be useful if you are trying to relate two parameters that a customer would like to see if there is any relationship or not.

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Performing analysis on Kickstarter data to uncover trends

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