Activity 5: Activating Network Effects

Source

Last.fm is a web application whose primary focus is on recommending music to their users. This is done by using a desktop or mobile application called "The Scrobbler" which records what songs have been played on the user's computer or device. This information is then synced with the web application, which compares what the user has been playing and how often with other users who also listen to these songs, then makes recommendations. Users can also be recommended artists by using the tagging system and searching for a genre they enjoy. The application also has a range of other capabilities, such as adding and sharing music tastes with friends and sending messages to them. Users can also see gig information, share if they are planning on attending and make comments on them, as well as on the artists, albums, and tracks in general.

Network Effects

Last.fm has made great use of activating network effects. Network effects are the advantages to a platform for having a larger user base^[1]. Positive network effects encourage the growth of the network, and with more people using the application, its value increases. With a higher value, this in turn encourages more users.

Direct Network Effects

The direct network effects of a web application are that its value increases (both according to the users and other stakeholders) as the user base increases. This means that users are more likely to make an investment into the platform as the number of its users increases. In Last.fm's case, as more people use the application, more people are having their musical tastes recorded, allowing the application to make more informed recommendations to its users. It also means that more users are able to interact with each other, making the application more social and enjoyable to use.

Indirect Network Effects

Indirect network effects are those advantages gained from third party complimentary services which increase the value of the original product. Last.fm has allowed these to be created by releasing an API, allowing other developers to create services relating to the web application.

Cross Network Effects

Cross network effects are that a rise in one group of users leads to an increase of value to another group of users. For Last.fm, as with many other websites, an obvious connection would be a rise in casual users would result in a higher number of advertisers, allowing for the website to gain more funding, and in turn, support more users. An increase in users and record label employees who add artist, album, and song information also adds value to the application for those who don't, as they have a wider range of music to share and be recommended, and the information provided is likely to be more correct as more people are checking it.

Local Network Effects

Local network effects, also known as 'social network effects', is that a user's decisions are influenced by those in a typically small set of other users. Therefore the most benefits can be gained from those the user is connected to, not just the size of the user base as a whole. Last.fm encourages its users to connect with friends, providing the option to search a user's Facebook friends for their accounts. By building a network of friends in the application, users are able to get music recommendations from their friends, send them messages, and share what gigs they are going to. Therefore, although all users are able to get benefits from the applications, those with a group of friends who they base their interactions with the platform around are able to gain the most.

Future

Last.fm previously offered a music streaming service, which was available until last year. This signals that they are focusing more on their recommendations system as well as providing more accurate music information. Last.fm should also consider improving their mobile offerings, which currently, at least on Android, are severely lacking. As for extending their use of network effects, they could improve their cross network effects by making it easier for those who edit artist, album, or song information, as well as provide record companies more incentive to take control of their artists' pages.

In what other ways do you think that Last.fm is using network effects well? Tell me about it in the comments.

Reference

1. Shuen, A. (2008). Web 2.0: A strategy guide: Business thinking and strategies behind successful web 2.0 implementations. Sebastopol, CA: O'Reilly Media, Inc. 

Activity 4: Lightweight Models and Cost Effective Scalability

Lightweight models and cost effective scalability is another O'Reilly pattern of web 2.0 applications. This is essentially the pattern of innovation in assembly for business models. It therefore involves getting products to market faster, reducing costs and risks, as well as encouraging simplicity within the application's assembly.

Pinterest

Pinterest is a service operating both web and mobile applications. It allows users pin images or videos to themed boards which they can share with friends or keep private. Users can also follow users or boards which interest them and like or share their content to their own boards.

Best Practices

The first best practice which Pinterest is implementing really effectively is outsourcing wherever practical or possible. The company has utilised Amazon Web Services, namely Amazon Simple Storage Service for its data storage and Amazon Elastic Compute Cloud for its data analysis. This means that the company is not responsible for providing and caring for large data banks which it can use for storage and therefore can divert the resources, such as money and manpower, which it would have devoted to this to other areas of its operation.

Another best practice which Pinterest is performing particularly well in is that it has been designed for scaling. The application experienced rapid growth across a nine month period, going from 50 thousand users to 11 million. This could potentially have been disastrous if the application hadn't been designed in this manner, as the company by itself probably couldn't have kept up with the demand being placed on its servers, and therefore would have had constant outage problems, causing users to give up on their services and turn to others. However, it avoided this by scaling with demand. By outsourcing their data storage and processing to Amazon, they are can (and have) enabled autoscaling on their data storage and load balancing on their processing, allowing for them to have the optimum setup for their current data requirements.

Future

Obviously, Pinterest has a very bright future ahead of it should it continue to implement its strategies as well as it is now. It may begin to look into other areas of this web 2.0 pattern, such as outsourcing its own functionality and expertise to other services, or changing its revenue model, however it doesn't appear to need to make any major changes any time soon.

Do you know of any other companies which have a data strategy which is as light weight and cost effective as Pinterest? Tell me about it in the comments.