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Performing analysis on Kickstarter data to provide Louise data and visualizations to uncover trends.

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Kickstarting with Excel

Overview of Project

Analysis of many Kickstarter Campaigns to uncover trends through various visualizations.

Purpose

As I performed analysis on the Kickstarter data, I gained a couple key points of feedback to share with Louise. This will provide her the visibility and information she needs to understand the many trends found within the data sheet she shared.

Analysis and Challenges

Throughout the course of the project, the bulk of the analysis showcased in Pivot Tables and various Pivot Charts. Initially, diving into the KickStarter spreadsheet was overwhelming as there were many data points. Through organizing the data it showcased key points, it helped create a lens of visualization to aid Louise.

Analysis of Outcomes Based on Launch Date

The primary goal of creating this visualization was to showcase outcomes (ranging from succesful, failed, to canceled) of the all the theater campaigns based off when their launch date was. There was multiple steps before creating this analysis - which included organizing at a granular level, extracting data and create pivot tables, converting them into pivot charts, filtering to show the specific data, and lastly creating a line chart.

After reviewing the chart, there is a trend of May through June being successful months in the campaign.

Theater_Outcomes_vs_Launch

Analysis of Outcomes Based on Goals

The primary goal of this analysis was to pinpoint the % of successful, failed, and canceled plays of all the theater campaigns bassed off the funding goal amount. Before creating the visual, there were multiple steps in this process as well. The most notable was utlizing the COUNTIFS function. This function quickly analyzed the outcomes and goals of the category play and determined the percentages of outcomes based on the goal.

Outcomes_vs_Goals

Challenges and Difficulties Encountered

Initially, not understanding how to utlize excel shortcuts was a big challenge. After browsing through the web and making myself familiar to the dataset, the tasks became easier.

Results

  • What are two conclusions you can draw about the Outcomes based on Launch Date?
  1. After reviewing the chart, there is a trend of May through June being successful months in the campaign. As seen in the data, it was highest in May with 111 successful launches. In June there were 100 and July 87 successful launches. I would recommend Louise to start a campaign during these 3 months to have better throughput.
  • What can you conclude about the Outcomes based on Goals?
  1. After reviewing the Outcomes based on Goals, I've come to the realization that when realistic goals are set campaigns will be more succesful.
  2. Campaigns that were succesful were shown to be ones with a goal <1,000 0r >=4,999.
  • What are some limitations of this dataset?
  1. Though the Kickstarter dataset was large, there were key points that would've made the spreadsheet more inclusive.
  2. Limitations include:
    1. Providing recent data
    2. Providing references to why the campaigns failed. This would provide inisght to Louise when creating a campaign.
    3. Providing awareness of the tools/sites used to advertise the campaigns.
  • What are some other possible tables and/or graphs that we could create?
  1. Utlizing all the feedback on limitations and creating additional analysis on the kickstarter data. Examples could be:
  2. Success Rate on tools used to advertise for successful vs failed theater campaigns.
  3. Comparative analysis based on various countries.

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Performing analysis on Kickstarter data to provide Louise data and visualizations to uncover trends.

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