The document discusses how listening experiences may change in the next 10 years. It notes that people enjoy listening to music selected for them by other people or services through playlists. It also discusses how data analytics can be used to measure the success of playlists, while data science can help with playlist creation and curation. The document suggests that in 10 years, playlists may be created through a combination of human input and algorithms.
4. % Penetration of Target Audience
AvgHoursConsumed
0% 50% 100%
0 hrs/month
12 hrs/month
24 hrs/month
People love listening to music selected for them by
other people
5. % Penetration of Target Audience
AvgHoursConsumed
0% 50% 100%
0 hrs/month
12 hrs/month
24 hrs/month
People love listening to music selected for them by
other people
6. % Penetration of Target Audience
AvgHoursConsumed
0% 50% 100%
0 hrs/month
12 hrs/month
24 hrs/month
People love listening to music selected for them by
other people
7. % Penetration of Target Audience
AvgHoursConsumed
0% 50% 100%
0 hrs/month
12 hrs/month
24 hrs/month
People love listening to music selected for them by
other <people|services>
17. Playlists as a feature
ref https://blog.intercom.io/before-you-plan-your-product-roadmap/
Search Social Editorial Library Playlists Purchases
18. Playlists as a feature
All
of the time
Most
of the time
Some
of the time
Very little
of the time
Few
of the people
Some
of the people
Most
of the people
All
of the people
ref https://blog.intercom.io/before-you-plan-your-product-roadmap/