The Long Tail of Steam

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Traditionally (before e-commerce), for a product to be successful it needed to have high-volume appeal. However, due to cost reduction and better targeted marketing (possible due to the Internet), money can be made selling to niche markets. Collectively niches can generate sales numbers similar to or better than traditional markets (Davis, 2005).

Steam is an online digital entertainment company that currently offers 1100 games for purchase, download and play from any computer (Steam, 2010). Compared to department stores that rarely offer more than 100 titles (usually the more popular ones), Steam’s range is simply larger and caters better to specific interests rather than current trends. Such business models are what Anderson referred to when he coined the term leveraging the long tail (Anderson, n.d.).

Traditionally retailers only targeted the ‘head of a market’. However, collectively, products in the tail have the potential for similar or greater sales (Anderson, n.d.).

Companies such as Steam are able to cater to these niche markets by using new technologies to reduce costs (Wikipedia, 2010). Users enter, edit and update their personal information negating the need for some customer service employees. Steam users enter their own details from payment information through to their billing address (Steam, 2010). Self service extends to support, using the Steam forums and knowledge base gamers can ask their peers technical questions. This reduces the amount of money spent on support staff.

Products purchased from Steam are delivered virtually over the Internet in a digital form (Steam, 2010). In contrast to traditional business models, Steam does not pay for products until they have been sold to a customer. Furthermore, like other companies that trade in digital content there are few costs associated with a physical retail front or delivery.

Where the cost of inventory storage and distribution is low it becomes profitable to sell relatively unpopular products (Wikipedia, 2010). As a result vendors no longer need to put consumers in a one size fits all container (Anderson, n.d.). However, as the tail lengthens, consumers may find it hard to navigate to products of interest. Sites such as Steam use algorithmic data management to match supply and demand (O’Reilly, 2005). Based off pages a user visits, Steam recommends other games they might be interested in.

In summary, as Anderson (n.d.) suggests, People gravitate towards niches that are narrow interests (and everyone has them). Trends show that through using new technologies to reduce costs collectively, niche markets are as economically viable as their traditional high appeal counterparts. Businesses can now be built on hitting the growing niche market (Holter, 2006).

As for the future of Steam, I would like to see them follow the trend of the Apple App store and allow more independent developers to submit games for sale (this would lengthen their tail too).

References

• Anderson, C. (n.d.). About Chris Anderson.
• Davis, H. (2005). The Long Tail.
• Holter, E. (2006). Examples of the Long Tail Effect.
• O’Reilly, T. (2005). What is Web 2.0?.
• Steam. (2010). Steam Store.
• Wikipedia. (2010). E-Commerce.
• Wikipedia. (2010). The Long Tail.

Mindmeister: The Perpetual Beta without the Beta Tag

“There's no final version. Nothing is static, everything is changing.”(Chitu, 2007). This is how Google defines the idea of perpetual beta, software as a part of an indefinite and continuous development cycle (Wikipedia, 2010). This is the new way of thinking about software development and one that gives young companies an advantage because they are not in the habit of the traditional software release cycle.

Mindmeister is a collaborative mind mapping tool that demonstrates the Web 2.0 principle of ‘Perpetual Beta’ and has seen success through these innovations. Meisterlabs has made operations a core competency. Their security page boasts 99.9% uptime and the highest data center standards (Mindmeister, 2010) and their product is updated many times a month. Such measures are essential for web 2.0 applications that are offered as services because they won’t perform well without regular maintenance (O’Reilly, 2005).

Mindmeister user numbers.

Meisterlabs subscribes to the benefits of releasing their software early and often. Through the change log it is clear that their service is updated multiple times per month. The improvements made however, are usually small and not always noticeable to users.

Improvements are able to be regularly rolled out through utilizing light weight, flexible and cross-platform programming languages. O’Reilly (2005) refers to such examples as php, AJAX or ruby on rails as prime examples of code which can be written quickly to enable responsiveness. Mindmeister uses HTML, CSS and AJAX client side to allow their application to be rendered by most browsers. Ruby on wheels is used server side (Hollauf, 2010).

Mindmeister uses beta testers who post reports on bugs they identify. Mindmeister aims to be responsive to these reports. O’Rielly(2005) identifies the use of shadow applications which can collect data on how an application being used. These should be planned and implemented with the main application. Based on the data (see below) Mindmeister is able to provide it can be assumed they use shadow applications. Other sites such as Google and Amazon have been know to engage a small percentage of their users in such tests before rolling out products. Testing is used trial new business strategies and application functionality.

Web 2.0 means consumers are now purchasing services instead of artifacts. These services need to be maintained to respond to user requirements and through leaving an application in perpetual beta products see a faster time to market, reduced risk (less up front cost), a closer relationship to customers and the ability to quickly and effectively respond to real time data (O’Rielly, 2005).

Question for thought:

Will we see the Beta label return to products when large versions are released?

References:

Chitu, A. (2007). Perpetual-Beta.

Hollauf, M. (2008). Mindmeister: Development Cast Study.

Meisterlabs. (2010). Change Log.

Mesiterlabs. (2010). About Security.

Meisterlabs. (2010). Mindmesiter Launches Private Beta Test.

O’Reilly, T. (2005). What is Web 2.0?.

O’Reilly, T. (2005). What is Web 2.0: End of the software release cycle.

Wikipedia. (2010). Perpetual Beta.

Location, Location, Web 2.0 – Foursquare is Built From Many Devices

Foursquare is a location based social networking game. Users ‘check in’ at locations announcing they have been there in competition to become mayor. People contribute through submitting their thoughts, locations, pictures, information about their current location and friends (Wikipedia, 2010).

Utilizing features only available on cell phones has heavily contributed to Foursquare’s functionality and success. Photos are taken using cameras, locations recorded using cell location services and the application relies on a phone’s connectivity (Foursquare, 2010). Combined, these features have created an application that couldn’t exist solely on a desktop computer or phone.

In the company of desktop computers, Foursquare can be used on iPhones, Android phones, Blackberrys, Windows mobiles and systems running webOS (Foursquare, 2010). An application is currently being developed for Nokia handsets (Guim, 2010). The way each platform is used to its strength and data is shared between devices and services, makes Foursquare a great example of software above the level of a device.

O’Reilly (2007) uses the example of iPhones being managed by iTunes to show how software can work in tandem to ensure a better user experience. Foursquare follows a similar model allowing users to manage their profiles online. This means users aren’t required to type or read great amounts of information into/from their phones. The mobile applications are then left to perform the task they are great at, being mobile and more so, immediately recording users’ thoughts or pictures in the context of location, harvesting rich forms of media.

Foursquare intends to generate revenue through advertising. Businesses can advertise directly, targeting people who are regularly nearby their businesses in the form of couponing (Carlson, 2009). Data generated by Foursquare has been used to create mash-up applications.

Fourwhere, a desktop web application, uses collected data to display comments made through Foursquare on a map. This is a great example of how Foursquare extends the usability and functionality of their data using the context of location (Sysomos, 2010).

Notably, Foursquare encourages usage by allowing users to import friends from Facebook and Twitter. These services are also used to broadcast a users location.

In summary, Foursquare utilizes the strengths of many devices, including a broad range of phones and desktop computers, to harvest rich media in the context of location. Thinking forward we may soon see such applications incorporating the accelerometer and future phone features as they are released and patterns indicate this trend may lead to richer data being harvested without an increase in conscious human interaction.

Questions for thought:

What other data types could be harvested without the need for human input?

References:

Butler, E.(n.d.).FoursquareX

Carlson, N.(2009).How Will Foursquare Make Money?

Foursquare.(2010).Welcome to Foursquare

Guim, M.(2010).Foursquare App for Nokia N900

O’Reilly, T.(2007).Software Above the Level of a Single Device.

Sysomos Inc.(2010).FourWhere

Wikipedia.(2010).Foursquare (Service)