Broadcast Song Airplay Analytics With Segmented Station Insights
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Solution Overview
Problem
Existing systems fail to effectively sort airplay data to provide insights for promotional and marketing efforts, identify likely stations for increased airplay, and offer real-time notifications to improve song chart rankings.
Innovation Solution
A system and method that utilize servers with microprocessors, databases, and memory to analyze transaction records, categorize song play data by timeframes and dayparts, and generate dashboards for evaluating song performance, providing insights and recommendations for airplay.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If airplay data is collected from multiple radio stations and streaming services, then the quantity of data increases, but the ability to sort and analyze the data into useful information decreases
Solution Approach 1:
The patent segments airplay data by multiple dimensions including timeframes (current week, previous week, year-to-date), dayparts (morning, midday, afternoon, evening), and station categories (top 100, top 200, top 500). This segmentation transforms raw data volumes into structured, analyzable units that reveal actionable patterns in song performance and station behavior.
2Measurement precision
If comprehensive airplay tracking is implemented across all radio stations, then measurement precision improves, but device complexity and processing requirements increase
Solution Approach 1:
The patent implements a universal data processing platform that handles multiple functions: collecting airplay data from diverse sources (radio stations, streaming services), processing and normalizing data across different formats, analyzing performance metrics, and generating insights for various user needs. This multi-functional system reduces overall complexity by consolidating operations into a single integrated platform rather than separate systems for each function.
3Speed
If real-time airplay data processing is implemented, then the speed of insights delivery improves, but energy consumption and computational resources increase
Solution Approach 1:
The patent implements periodic data processing cycles that update airplay metrics at scheduled intervals (daily, weekly) rather than continuously in real-time. This approach maintains timely insights for marketing decisions while significantly reducing energy consumption and computational resource requirements compared to continuous real-time processing. The system processes data in batches during off-peak hours and delivers updated insights periodically to users.
Data Source
AI summary
The present invention relates to a system and methods for evaluating song play performance of broadcast music. The analytics system comprises one or more data processing resources. The data processing resource receives transaction records that are related to songs being played on radio stations. The transaction records comprise a song identifier, play location, play time, and additional metadata. A user can generate a series of dashboards that comprise indicia or graphics that inform song play performance, radio station airplay performance and insights, generate airplay recommendations and display other information. In an exemplary embodiment, airplay recommendations can include informing the user of song play locations, where a possible space on a radio station's playlist or panel exists. Such possible spaces are opportunities where the user can seek to increase the number of song plays for a desired song at a radio station thus improving the song's rank.