Virtual sales get real big with Cyworld

Social networking is at a point where a lot of us are almost bored to death with the daily launch of new networks. Strangely enough, not many of these social networks, boasting enviable usage and engagement metrics, can really claim to be running on a revenue model which really monetizes off the user engagement on the product. Many have taken the advertising path and it’s clearly not been the best. In the middle of all this, Cyworld from South Korea stands out as an important example of how one can make money off a social network.

South Korea boasts the highest household penetration of broadband internet in the world and online shopping is a huge fad out there with nearly 80% of internet users having shopped online. Cyworld seems to have united the best of both trends by combining social networking with online shopping and emerging as a highly profitable business in a field where Facebook, as the leader, is struggling to break even.

More than 90% of South Koreans in their 20s and more than one-third of the entire population of South Korea are registered users of Cyworld with more than 25 Mn unique users per month. Great stats but not out of the world as far as social networks are concerned. What absolutely bowls one over, though, is the degree to which they’ve monetized this user base.

Cyworld is a lot richer on features than many social networks. Somehow feature-rich seems to have worked for them. Interestingly, Google doesn’t have any significant market share in South Korea and it’s possible that users actually prefer feature-rich and heavy websites, what with the top notch broadband infrastructure that all Koreans have. On Cyworld, every member has a homepage, referred to as a mini-hompy in the Korean Internet world. Basic services on the site are free (as with most social networks) but the site generates close to $250 Mn in annual revenues following a very unique revenue model and makes nearly $10 per user per year (MySpace makes $2-3 per user per year, largely from advertising). Most of these revenues come from the sale of Cyworld’s virtual currency (dotori) which then users use to buy virtual objects to decorate their homepage and accessorize their avatars. Since these digital goods are micro-priced, there are a lot of transactions happening on the site, and given the huge user base, a lot of revenues flowing in.

The craze for virtual goods has resulted in a lot of online vendors setting shop on Cyworld to sell virtual goods. Given the richness of content that the mini-hompy service offers, Cyworld also has a sister service called Cyworld Town where SOHO (Small Office Home Office) owners display their offline goods through videos and graphics on their mini-hompy resulting in online order and offline conversions.

Given low online shopping outside the travel category and low connectivity (thus ruling out feature-rich sites), the model might not necessarily be directly relevant to the Indian scene. There are, however, pertinent points that one can note form Cyworld’s success:

1. A revenue model that monetizes actual actions that user must do to interact with the community can provide a more steady stream of revenues than one where the user has to perform a non-central action (like clicking on an advertisement) for the site to make money
2. Value added services like accessorizing one’s page etc. can be used to good effect on social networks. There is an inherent tendency to go one-up on friends on a social network, especially in showing off popularity, and if a value added service can help users do that, it could prove catchy

Friendster's Asia run

Friendster, the social network we Indians don't really care about turns out to be the most used social networking site in the rest of Asia. While the world raves about Facebook and the yuppie crowd in India cries Orkut, Friendster has beaten every other social network into garnering the largest market in Asia. Considering the fact that this is also the highest growth market, the future looks good.

To focus all the more on Asia, the company recently relocated to Australia and opened new offices in other parts including Singapore.

More interestingly, here are some important statistics on their success in Asia:

1. #1 social network in Asia, with over 75 million registered users from Asia

2. In Asia, it has more monthly unique visitors than any other social network.

3. Top 20 global website in the world in terms of traffic, serving over 19 billion page views a month

4. Leader in "user engagement" among the top five global social networks, with users spending an average of 190 minutes per visitor per month

5. Loyal and growing user base throughout Asia in the following top 10 countries for Friendster: Australia, China, Hong Kong, India, Indonesia, Japan, Malaysia, the Philippines, Singapore and South Korea.

This clearly is one of the top web properties to watch out for in the days that come.

The new world order of Media

Internet comprehensively changed the game when it came to how media was distributed. It reversed the distribution model from Push to Pull so that the end-user could now choose what he consumed instead of having things pushed to him on Television or Radio according to a schedule.

The difference between the old media order and the new one is seen most glaringly in how Google , a search engine, and Yahoo, a portal, approach the game. Of all the reasons cited for their success, I feel it is the understanding of importance of search-driven content distribution that enabled a relatively late entrant in the internet industry to beat existing players.

If distribution was so customizable, advertising couldn't have been left far behind and Google, yet again, in understanding the high degree of relevance in text ads pipped Yahoo to the post. Ironically, it was the Yahoo-acquired Overture which first came up with the idea. Google, though, has gone on to win the advertising game handsomely.

The new media order is on-demand and customization and Facebook and Social are likely the next trends geared towards this. Yahoo seems to have figured this out too and is evidently planning a positioning around making its offerings leverage its huge community. Only time will tell who gets it correct from here.

Local Search in India: Search Relevance and Experience.

Search in India has a unique problem. Most Localities in India are words in local languages. When written in English, there are multiple ways of representing the same word. Resolving all these spellings to that particular location is a non-trivial task. Most search engines at the moment do not do such resolution and a few like Onyomo and Burrp have taken the easy way out by giving a drop down of localities the moment the user starts typing in the locality names. Guruji resolves locations to some extent but still has a long way to go. Justdial doesn’t resolve locations at all and looks for direct matches.

Beyond this, Local Search suffers from all other problems that are common to a categorized directory search ranging from inadequate keyword and category aliases to incorrect categorization to search tuning by category parameters. Technically, a site like Ilaakaa wouldn’t even qualify as a Local Search site because their search merely uses the Indiacom Yellow Pages search.

Since the key to success lies largely in the comprehensiveness and searchability of the data, many of the Local Search players don’t seem to have invested much time or effort on user experience and navigation. Justdial with the best data has one of the poorest user experiences on the site. Onyomo and Burrp have the best user experience and navigation among all the sites, with minimum clutter and ordered presentation.

Local Search in India - Data Woes

The Local Search market in India is heating up. The space is largely taken up by startups at the moment. Considerable hype has been created of late in this space with Guruji getting backed by Sequoia Capital and Onyomo unveiling its SMS search platform.

The primary factors that determine the effectiveness of a Local Search engine are data quality, search relevance and ease of navigation. One of the biggest challenges that players face in this space is the lack of availability of rich local data. Unlike the US, the local data market is highly fragmented and most players are Yellow Page companies whose data is largely outdated. Arguably, the best database of Local listings currently rests with JustDial, a company which serves Local Information primarily on the phone but has recently entered the online fray as well. Ever since its launch, www.justdial.com has had the maximum traffic in this space, rapidly gaining over Guruji.

Most of the other players rely on Yellow Page companies for Local Data. Guruji, a recent entrant sources its data from Infomedia and hence suffers from the problem of outdated listings. Ilaaka, another player in the local space redirects its search to the Indiacom Yellow Pages site while MapMyIndia sources its local listings from GetIt.

Onyomo has adopted a different approach towards data. They have feet-on-street teams which have been collecting local data by street surveys. This is similar to A9’s effort at collecting pictures of Local Listings by feet-on-street except that the economics for such an exercise work far better in India where labor comes much cheaper.

AOL has also launched a local site but its data is very sparse and largely sourced from websites and web directories.

Clearly, the data problem has been solved only by JustDial and remains a huge barrier to entry for any other players who do not wish to take the Yellow Pages route.

One of the ways of solving the data problem over time is to have the user community contribute towards editing and adding new listings. JustDial and Onyomo have already implemented features to facilitate this process.

Over time, data will definitely be one of the key factors to determine success in Local Search.

What the hell is Web 2.0 all about anyway?

Web 2.0 has heralded a shift. Existing wisdom on the net on which previous generation products were based has been rudely challenged and effectively proven to be outdated.

Catering to the Long Tail

Niche websites are on the rise and account for the majority of websites out there now. Initiatives like blogging have just spurred on the trend. The long tail has vital implications for advertisers since niche sites are visited by a very specific user group and provide great targeting opportunities and better ROI on the eyeballs.

Data as a differentiator

The Internet is built around specialized databases today. Whether it is an index of crawled websites or digitized offline data, the web is driven by data and comprehensiveness and searchability of the same differentiates products and services on the net. The need for control and ownership of data is so critical that online media players have even started backward integrating into content creation.

The importance of the User Base

In today’s internet economy, the user base is the key to success. In the past, a user base was all about eyeballs and advertising money. However, users are fast changing from being mere content consumers to being content creators as well. With the growth of annotations and what is popularly known as ‘folksonomy’, the user base has fast come up as a vital source for data enrichment. The era of categorization taxonomy is in the past now and online companies are fast moving towards an "architecture of participation" to allow users to actively help grow the data and hence the business.

Goodbye IPR

The days of IPR are fast coming to an end. IPR restricts users and makes the content economy very centralized. Web 2.0 is all about a distributed economy as epitomized by wiki-based products which thrive on user-generated content and have no issues with IPR promoting regeneration and reuse. The growing discontentment against DRM in the case of online music may herald a similar era in that field.

The Phased-out Launch

Online Products are no longer released one fine day as fully-tested fool-proof products. Phased out launches are common and the beta phase typically extends to almost the entire life-cycle with users actively chipping in as testers too. Features are added incrementally and the product stays in a perpetual state of Beta.

Mash-up era

Mash-ups are the order of the day. Take existing products and come up with an entirely new product, a new user experience, and hence a new way to get money, all this, without having to invest too much on the product creation itself.

Delivery on multiple platforms

Delivery platforms for the internet have extended beyond the PC to include a variety of handhelds. Products that launch well across all platforms go down well with the consumer. Consumers love freedom of use and portability and multiple platform compatibility is the thing for the future.

The Challenge of Content Management

A large number of online media companies source their content from the traditional content-producing media companies like news agencies, recording labels etc. Consequently, handling content and presenting it in a particular common format is a major challenge for these companies especially when content is sourced from several providers with differing presentation patterns. Content management at this level involves two broad tasks:

• Mapping all content to a common format for presentation and for ease of mining.
• Categorization of content by user intent.

Storing content in a common schema is essential if content mining is to be automated to some extent. However, the bigger challenge surfaces after this when the content is to be categorized. Categorization is normally done to aid the user in browsing the content and also in presenting relevant search results.

Categorization can be done based on several parameters. In case of music, the problem is simplified to a great extent since most of music is categorized by genre and further by artists where an artist can fall under several genres. In this case, the categorization can be fully automated once the taxonomy of genres and artists is in place. However, in case of language content which needs to be categorized by subject matter, a good deal of social intelligence is required to understand the topic to which a certain item belongs. In such cases, machine learning and classification will always yield errors. Errors may dip with increased machine learning but will always remain. Hence, some amount of manual effort is essential in such categorization. The trick then is to figure out which parts should be automated and which parts manual since there is a trade off between cost and accuracy here.

Categorization essentially can be broken down into two further tasks:

• Finding categories ‘related’ to an item.
• Deciding which of those categories is/are actually ‘relevant’.

In the case of every item being mapped to only one category (one-to-one mapping), the second problem can essentially be combined with the first. However, in a one-to-many mapping, one needs to use social intelligence (possible with a manual workforce) to determine which categories are relevant.

To provide a general rule (with exceptions), finding related categories should be automated, especially in a one-to-many mapping since an algorithm will do a more exhaustive job than a human. However, in deciding which of these categories are relevant, manual workforce alone can bring in the level of social intelligence that is required to determine the subject matter of a certain item and accordingly categorize it.