Client: Louise
Our client Louise has a lot of experience in organizing crowdfunding. Our company was able to carefully display the potentials and treads based on her past crowdfunding data.
The purpose of this analysis is to find the outcome on given criteria: Based on launch date Based on goals Based on pledged amount Successful and canceled shows
The client is submitted with different charts and tables using Excel. We extracted and created different sheets based on the single datasheet that was provided to us. We have designed the project to make it easier for our client to filter her findings and plan for future crowdfunding. The data was not sorted properly, hence our company was able to clean the data and change the dates and make it more readable. The client is provided with different statistics and charts for the convenience of Louise, our client. Given is the graph to show how crowdfunding in GB can be successful if we focus in Pop Genre.
Based on launch date, month of May is best month for crowdfunding. Based on theatre- category itself, there were total of 166 shows with 111 successful and just 52 and 3 failed and canceled shows accordingly. On the given chart and graph” Theatre outcomes based on launch date”, there were 1369 shows with 849 successful shows.
The main challenge was not clear data. Our company was able to submit clear and organized datasheet to our client. Given the data was raw, our company was able to create more organized and filtered sheet. Difficulties encountered was error while putting in the formulas.
Given the graph most successful category is to focus on Theatre category which helps Louise to gain more crowdfunding. The client presented with well=prepared sheet after applying different filters and formulas. We were also able to provide client with different statistics based on categories and countries. Different Pivot tables were created so that client has better understanding of the dataset provided.
- What can you conclude about the Outcomes based on Goals?
Based on goals there were zero canceled show. There were many projects in the area of $1000 to $4900, which was the most successful with 73 percent and 27% failed. Similarly, $45000 to $49000 was the worst one with 100% failed projects. Louise can focus more on medium range projects in order to have more successful projects.
Based on goals there were zero canceled show. There were many projects in the area of $1000 to $4900, which was the most successful with 73 percent and 27% failed. Similarly, $45000 to $49000 was the worst one with 100% failed projects. Louise can focus more on medium range projects in order to have more successful projects.
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What are some limitations of this dataset? Lacked AGE, SEX and GENDER categories.
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What are some other possible tables and/or graphs that we could create? More tables could be created based on weather and demographics. Client can also target the AGE and GENDER in order to get better crowdfunding.
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