As we have seen in a previous blog post, in order to serve the increasingly complex needs of the music ecosystem, FuturePulse project will develop and pilot test a novel close-to-market music platform in the Record Label use case.

Today, record labels rely on different sources of revenue, for instance music streaming, digital music sales, and advertising revenues from YouTube videos. Furthermore, they often get access to data coming from social media, e.g., artist Facebook page, YouTube channel (or individual videos), and try to manually make sense of them, using a number of platform-specific tools (such as the dashboards offered by Facebook and YouTube). With FuturePulse, professionals will be able to track and understand such data; and most importantly which data are crucial in order to optimize their operations.

Leonidas Kallipolitis and Vasilis Papanikolaou in the Deliverable ‘D4.1 Overall system architecture’, describe the architectural guidelines, the use cases and system requirements that drive FuturePulse platform’s overall system architecture. More importantly, regarding the Record Label use case, they pinpoint 8 significant central functionalities that users can exploit within the FuturePulse platform:
 

1. Select an artist

Users select an artist by providing the artist’s details in the system, e.g. name. They can also manually provide the reference groups that this artist belongs to.
 

2.  See analysis for an artist

Users see the analysis results of the FuturePulse platform for an artist. These data include analysis of streaming information for the artist as well as analysis of media coverage of the artist’s performance, i.e. social media, blogs, broadcast data, charts, etc. They also include predictions on streaming for the artist as described in the following use case.
 

3.  See streaming prediction for an artist

Users can see the predictions of streaming numbers for a new release.
 

 


 

4.  See trending genres per country

Here genre popularity per country can be monitored. Furthermore, aggregated streaming statistics as well as statistics from media channels can be offered to cover this use case.
 

5.  See release day impact on success

Users can see streaming statistics as well as statistics from media channels on a per weekday basis. The statistics can be refined based on several filters such as demographics and genre (when these are available).
 

6.  Select Genre

Users can select a genre so as to get results on streaming statistics as well as social media activity.
 

7. See past streaming analysis

Past Streaming analysis is a core use case of the system which involves analysis of historical streaming data and aggregation/grouping of them by various criteria such as artist, track, season, country, weekday and other that might be available when acquiring data from the sources.

 

8.  See analysis of Media action

This use case is about users being able to view statistical data about the activity of an artist/track/genre in social media, web pages, blogs, etc. The included use cases are about presenting information per monitored platform, per date, age group or specific events in time, e.g. an artist’s live performance.

You can read the Deliverable ‘D4.1 Overall system architecture’ here.

 

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