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Mooga iSearch

Most incumbent internet search companies such as Google, Yahoo, MSN and new start-ups in the mobile search arena are placing significant emphasis on search functionality in the mobile space. They are all competing heavily to emulate internet search functionality on the mobile.

There is no question that this focus will strengthen the value proposition to the end user; however it does not address a number of fundamental issues that the mobile handset and the mobile environment in general present. Strategically it still maintains the mobile operator as a pipe and makes search the gateway for all activities made by the consumers. Last but least, there are fundamental differences between searches on the Internet versus the mobile phone; mobile content is structured content and does not work in a similar fashion to the highly unstructured and dynamic nature of the World Wide Web. Mobile content is not as text based as the market seems to think. For the foreseeable future, mobile content will be based on images, music, videos, mobile TV, mobile games and infotainment services.

Search is reactive not proactive; while mobile content purchases can also be classified as impulse purchases. Without addressing consumer tastes and the lack of options available to the end user; advanced search functionality will only allow users to find items from an already limited content offering faster. Giving an end user an exact search result related to a key word or words provided is not comprehensive enough, there has to be a ranking system to identify what the best search result for that query is. Many search engines on mobile also require the end user to specify not only what item they are looking for but also the content type. This process in itself is time consuming and does not better the experience for the end user.

Mooga's Ranking Algorithm uses a "wisdom of crowd" approach to add relevance/ranking to search results. The power of collective intelligence of all subscribers is used to determine what the top search results for a particular query should be. Mobile consumers want answers directly and quickly and don't have the time or the inclination to go through thousands of "relevant" results. This ranking algorithm continuously evolves based on the collective wisdom of all users and their historical aggregated interactions with Mooga.

If an end user uses a generic search term like cricket, the Mooga Ranking Algorithm determines the most relevant content for cricket irrespective of content types. These results are influenced not only by popularity but several other factors

Mooga iSearch has acknowledged the limitations the mobile medium creates and has been developed to maximize the use of the space available. All items searched for are in context for the end user. The result is a rapid, relevant search process and increased user satisfaction. This in turn ensures increased retention and a higher number of downloads. It also allows for a significantly higher number of related and relevant items to be placed within reach as a result of a search query.

Mooga Ranking Algorithm is part of the system DNA

The Mooga platform intrinsically uses the same ranking algorithm as search; be it serving the best Britney Spears content or to show the best Movies or Music to a new user. This ranking algorithm continuously evolves by learning from the collective wisdom of all users and also based on their aggregate interactions with Mooga. Mooga iSearch provides valid results and relevant recommendations regardless of content type.