Before analyzing how to enhance donation strategies for the Edinburgh International Book Festival, we first need to organize and understand the five datasets available and establish a comprehensive analytical framework. This article outlines the data processing steps and key analytical directions, laying the foundation for further exploration of donation patterns.

1. Data Structure & Cleaning

The five datasets include event details, revenue, donations, audience data, and transaction records. Before analysis, we must perform data preprocessing to ensure completeness, consistency, and correct relationships between different datasets.

Key Data Processing Steps:

1. Standardizing Data Formats:
   • Ensure all date fields follow a consistent format (e.g., YYYY-MM-DD).
   • Identify and align currency values across different datasets to maintain comparability.
2. Deduplication & Data Integration:
   • Are donations recorded separately from transactions?
     • If so, we must distinguish donation_amount from ticket_revenue to prevent double counting.
   • Can each transaction be linked to a specific event?
     • transactions_2024 (event transactions) and income_2024 (daily income) must be correctly mapped to ensure donations are attributed to the right events.
3. Handling Outliers & Missing Data:
   • Negative ticket revenue or refunds—do they impact donation calculations?
   • Are there large one-time donations that could skew the overall trends?

2. Key Analytical Directions

After data cleaning, the analysis will focus on donation behavior patterns to identify the key factors influencing donations. The framework includes the following four core areas:

1. Donation Trends Over Time

• Objective: Identify donation peaks & lows, assessing variations over different time periods.
• Methods:
  • Compare 2023 & 2024 daily income trends to determine year-over-year donation changes.
  • Identify whether specific dates (e.g., festival opening, closing, or specific author talks) correlate with donation spikes.

2. Online vs. Offline Donation Analysis

• Objective: Assess the effectiveness of different donation channels (Web, Phone, Postal, Counter) and their contributions.
• Methods:
  • Calculate total donations & contribution ratios by channel to find the most effective fundraising medium.
  • Analyze conversion rates of online viewers donating, identifying the potential for increasing digital contributions.

3. Impact of Events & Guest Speakers on Donations

• Objective: Identify which events or guest speakers generate the highest donation amounts to inform future programming.
• Methods:
  • Calculate ticket revenue vs. total donations for each event, evaluating the fundraising potential of different event formats.
  • Assess whether high-profile authors or speakers significantly influence donation behavior.

4. Audience Donation Behavior Analysis

• Objective: Understand the characteristics of donors to refine fundraising strategies.
• Methods:
  • Categorize donations into ranges (£0-5, £5-10, £10-50, etc.) to compare small vs. high-value donations.

3. Expected Research Outcomes

By following this analytical approach, we aim to answer the following key questions:

1. When do donations peak? Are there recurring fundraising patterns?
2. Do online or offline audiences donate more?
3. Which events or speakers attract the highest donations? Can we replicate successful models?
4. Do most donations come from small donors or high-net-worth individuals?
5. Can donation strategies be adjusted to improve overall fundraising rates?

This research aims to use data-driven insights to optimize the Edinburgh International Book Festival’s donation model and provide actionable fundraising recommendations.

Mar 10, 2025