This project utilizes 2024 Spotify data to curate and optimize a 6-hour concert experience at Capital One Arena, focusing on maximizing profit while carefully considering logistics costs and talent booking expenses. The analysis includes comprehensive setlist curation, concert naming, merchandise design and costing, and revenue projections.
Using 2024 Spotify streaming data, design and optimize a 6-hour concert event for Capital One Arena that maximizes profitability. The project encompasses several key components:
- Data-Driven Artist Selection: Analyze streaming trends, popularity metrics, and audience demographics to select optimal performers
- Financial Optimization: Balance talent booking costs, logistics expenses, and venue operations against projected ticket sales and merchandise revenue
- Setlist Curation: Create an engaging 6-hour musical experience based on streaming data, audience preferences, and flow optimization
- Brand Development: Design a cohesive concert identity, including naming, branding, and visual elements
- Merchandise Strategy: Develop and cost merchandise offerings with detailed revenue projections
- Utilize authentic 2024 Spotify data for all decision-making processes
- Account for realistic logistics costs, including venue rental, equipment, staffing, and operations
- Create detailed financial models showing cost breakdown and revenue projections
- Design a setlist that maintains audience engagement over the full 6-hour duration
- Develop merchandise concepts with production cost analysis and pricing strategy
- TSNE_clustering.ipynb: Created clusters of Spotify's top songs based on factors like danceability, energy, acousticness, tempo, etc.
- artist_analysis.ipynb: Classifies artists in terms of popularity and type (headliner, support, opener)
- popularity_index.ipynb: Explored and arranged artists in terms of popularity based on Spotify data
- ticket_pricing.ipynb: Uses scraped ticket pricing data of previous Capital One Arena events and a set of formulas to dynamically estimate ticket prices of the venue's events from a base price
- visualizations.ipynb: Stores scripts for visualizations utilized in final proposal
- The final presentation recording can be found here!
- Danyil Butkovs - Clustering, Data Cleaning
- Samiha Naser (@samihanaser) - Artist Selection, Branding, Venue and Artist Cost Estimates
- Maya Patel (@maya-mp) - Ticket Pricing Strategy, Visualizations
- Illia Polishchuk (@ipolishc22) - Clustering, Setlist + Concert Timing, Artist Selection
- Adrien Rosario (@AdrientheFragrance) - Presentation, Artist Selection and Payment
- Diya Sayal (@dsayal) - Ticket Pricing Strategy, Merchandise
- Andy Yang (@yangydna) - Merchandise, Event Naming, Artist Selection
This project was developed as an analytical exercise in event optimization using real-world streaming data and venue constraints. All financial projections and cost estimates are based on industry research and publicly available information.