A playwriter requires an in-depth analysis of her crowdfunding project which will help her to fund her play “Fever” The analysis is performed using the Pivot tables and Pivot chart function on MS Excel to figure out the factors that make the campaign successful.

The overview of the project is to help an upcoming playwriter to start a crowdfunding campaign that will help fund her play “Fever” and to analyse the specific factors that will make her play successful with the help of MS Excel. ###Analysis and Challenges

The analysis was performed based on the data given by Louise. Though the data straightforward it was a little old and did not considering the factor of COVID in play. I performed various analysis and it showed that the theatre followed by music were the most successfully funded campaign journalism was given the least importance all over the world. Within the theatre category the most funded were the “plays” category. When Louise was specially interested on the funding for musicals in Great Britain, I was able to analyse that the goal amount should be reduced to its current value to ensure the success of the campaign. This was performed using descriptive statistics data and a box and whisker plot. The analysis was further continued based on two categories, *Based on Launch Date *Based on Goals

• Analysis of Outcomes Based on Goals

From the initial analysis performed it was seen that the most successful campaigns occurred in May followed very closely by June. With further analysis it was seen that the theatre saw the most successful campaigns during the year 2014 and 2015 where 2015 recorded a high of 304 successful campaigns out of the 518 campaigns followed by 2014 where almost 241 campaigns were deemed successful out of 403 campaigns.

• Analysis of Outcomes based on Goals

The first conclusion driven from the data obtained was that, the lesser the goal amount the higher was the chance of the campaign being successful. However, it was seen that the trend did not hold true for all goal amounts and it rose and fell as the goal amount increased (the second most successful goals fell between $30,000 to $45,000.

There were a few limitations in the dataset which can be due to not taking factors such as a pandemic which change the dynamic of the economy in every possible field. This is due to the data being old and not taking into account the present economy and taking into account the current trend.

The possible ways to analyse the data is limitless.

• We could have analysed the most successful campaign based on the year, country and category.
• We could have included various charts to compare the pledged amount with the actual goal amount and see if the expected trend was the trend that occurred.