Venturati

A lot of group buying sites have suddenly mushroomed in India recently in what seems to be a Me-Too aping of the Groupon model. And (with all due respect), some haven’t even bothered changing UI elements while going about it (Check out the Buy button on Snapdeal and compare it with Groupon).

It’s interesting to note what exactly seems to be working for Groupon here to have suddenly shot to a company valued in excess of $1 Billion in record time.

1. Very clear and focused pitch to the user: The pitch to the users is very clear and simple and actually translates into a clutter-free page as well. The home page talks only about the deal of the day. The workings of the deal are simple to understand. It’s not a site that has something for everyone every day of the year but that’s exactly what works for it.
2. Performance-based advertising: As has been the case with earlier coupon models (not just group bargaining), the business pays for actual footfalls which is always better than spending money on a CPM campaign without any guarantee on improvement in business.
3. Network Effect: Sounds like jargon but that’s what works here. A network where adding more users generates value for me has the potential to scale virally and that is exactly what works for group bargaining because a deal goes live only when a minimum number bid for it. Hence, adding more users is that much more valuable to me and I would, hence, want to notify others for whom the deal would be relevant.
4. Business model with low upfront cost and revenues as you go: Unlike so many web businesses out there, this is clearly not one that needs to build a sticky user base and get a ton of data before it can start monetizing. While it caters to the same group of end users, it doesn’t suffer from the initial investment problems that plague a local search model. The product isn’t technologically intensive either and just needs a dedicated sales team bringing deals in steadily.  All these points make it especially attractive for a low-capital startup.
5. Beneficial for both sides of the network: the businesses as well as the users: The theory of a two-sided network states that growth in users on one side spurs growth in users on the other. While Groupon is not exactly a network in the obvious sense, the growth in users on both sides directly impacts the business. More customers translates to more deals going live and more businesses translates to more deal types and hence more customers. Most importantly, both sides see value. The business gets those additional footfalls and the customers get a level of discount that they would not get in regular deals and sales.

In addition to this, the model is also financially sound a group bargaining sites typically buy inventory with businesses upfront and sell it but pay the businesses only after the fulfillment. The model ensures that in the long run, they will always have extra cash.

While this clearly shows that the model, although very simple, is very effective, it remains to be seen whether any of the current players in India will really see the uptake that Groupon has seen in the US. A few matters of concern in the Indian context are as follows:

1. Awareness of performance-based advertising among businesses: Indian SMBs are nowhere near their US counterparts in terms of online adoption and performance-based advertising models are not very common. One may argue that you don’t really need a whole network of SMBs to for this to work (unlike Local Search) but you definitely need to have a steady flow of deals to make this a sustainable business. There is hope in the success of Justdial and a good sales team may still get the business coming in.
2. Openness of businesses to adopt the model and range of deals: Openness to adoption among Indian businesses remains to be seen. So far,  the deals that one sees on these sites are largely from 3 categories:
a. Weekend sports and events: An obvious candidate, since you need critical mass for the event to take off. Group bargaining works perfectly for this segment since it ensures that the critical mass to enable a trip is met with group buying.
b. Spas and salons: In a crowded market, new and unknown spas and salons typically drive traffic by offering discounts. This model works well as they get guaranteed traffic with the discount.
c. Dining out: This is hopefully a category that will spur the growth of group buying simply because of the abundance of restaurants. So far, most of the advertisers are either new restaurants or restaurants that have suffered a loss of footfalls recently. E.g. restaurants in Whitefield, Bangalore or restaurants like Sue’s Place, Bangalore which has seen a downturn in business after the metro construction started.
A larger variety of deals is critical to growing the consumer base and is probably as good as your sales force.
3. Ongoing stream of deals: While Groupon has a daily deal on the site, most Indian sites have deals live for several days. It’s unclear whether this is because of a lack of deals or because of a lack of consumers to make a deal live on day 1 itself.

It’s interesting to see so many startups mushrooming in this space but it remains to be seen which one (if at all) will stay on to see the kind of success that Groupon has seen.

Twitter, and indeed all social media, is often touted as THE place for creating buzz about your product while keeping your purse strings tight. While there are many ways to leverage Twitter (and many more ways to get all excited about it and end up having nothing but a pathetic account for your product with a handful of followers), hashtag campaigns are definitely one of the more effective means of using Twitter.

Hashtag campaigns are Twitter campaigns where users are encouraged to tweet with a certain hashtag, which, if sufficiently popular, can make it to one of the top btrending topics.
I feel that there are three essential elements to running a campaign on Twitter well:
1. Employ hash tags well i.e. ensure people use the hashtag on every tweet, the hashtag is not too long and unwieldy and at the same time is representative of your product and/or positioning
2. Have a competitive angle for the tweeters
3. Create an exciting incentive structure for tweeters

Hashtag campaigns with monetary incentive
Launch a limited duration hashtag campaign to create buzz similar to what Squarespace and Moonfruit have successfully done.
Squarespace launched a very successful twitter hashtag campaign where users were asked to send tweets with #squarespace and 30 random candidates would get 30 Iphones. Within days, #squarespace became the top trending topic on Twitter.
Their rival moonfruit launched a similar campaign with equal success.

Hashtags campaigns with non-monetary incentive
USAToday recently launched a successful hashtag campaign where users were asked to send #AmericaWants tweets stating which charity should get a free full page ad in USA Today. The charity with the most tweets won while USA Today ot all the CSR-heavy buzz that it wanted.

Hashtag campaigns for crowdsourcing
Launch a campaign encouraging people to tweet about the content (e.g. local news) that you need to source and ask users to hashtag their tweets
Unlike the earlier campaigns which would be time-bound, this would have to be an ongoing contest with a prize given out every week or so. Executed successfully, it could help source content while creating the necessary buzz.

LinkedIn, widely known as the #1 professional networking website globally, has a large and rapidly growing base in India and is now establishing a local presence in the country as well. Alexa (a source I would at best consider indicative), ranks it in the top 15 websites in the country in terms of traffic and ~15% of the traffic on the website seems to be from India. What I really like about the company is a very enviable Revenue per employee ratio, something that definitely speaks of scale in the internet industry.

Very logically, it is also pulling down the cost of its subscription packages, which so far, clearly mirrored a US-centered pricing strategy. This should definitely make it a lot more popular among the monetizable segments of its customers viz the recruiters. It will be interesting though to see how LinkedIn makes its way into the country.


Why Orkut or Facebook are not the biggest threat!

This Mint article, in my humble opinion, rather naively suggests Orkut and Facebook (with a professional networking app, of course) as principal competitors to LinkedIn. I disagree on the points made there on more than just a few counts.

1. One third-party app out of a million, focusing on professional networking, will not transform either of these products overnight into a professional social network

2. I have my doubts on the success of a professional networking app on Facebook/Orkut. Utilitarian apps exist on both these networks even now but the majority of the users continue to be obsessed with social gaming (think Xynga) and quizzes

3. Facebook has a better shot at monetization with a Cyworld-like virtual currency model and is already headed in that direction. I don’t see professional networking as being the #1 money spinner for them anytime in the near future.

4. The absolute lack of clutter is something that appeals to me as a serious professional networker, an aspect notably missing in Orkut or Facebook. While that may work for a general purpose social network, I want to keep my navigational challenges at a minimum while networking professionally.

5. Finally, there is that minor point about brand perception. No number of professional networking apps on Facebook is going to make me start perceiving Facebook as the place to network professionally.

The real competition

I don’t see Indian professional social networks (TooStep, PeerPower) as any competition for LinkedIn. I don’t even see them as candidates for alliances. I still can’t understand the need for launching so many carbon-copy social networks when the first mover advantage has clearly been taken by a player.
LinkedIn is a social network all right but rather curiously, it doesn’t monetize the way most other social networks do. Ultimately, competition really kicks through when it comes to the monetization model and the segment whose monetization model is most similar to LinkedIn is the online jobs segment.
I see Naukri and Monster as the real competition for LinkedIn. LinkedIn monetizes through recruiters in much the same way that these job portals do. Yes, the business models are very different; we have active job seekers on one site and at best, passive job seekers and non-seekers on the other; but at the end of the day, both will be competing for the same wallets with the same segment of end users (recruiters and HR professionals). Principally, LinkedIn is a social network with greater engagement than any jobs site and solving for a lot more use cases but purely on its current monetization model of charging recruiters for access to candidates, it is directly competing with Naukri. LinkedIn might do it with a P2P model but any online jobsite with a P2A (Peer to Application) on one side and an A2P on the other side is essentially solving for the same use case.

How could the market change?

This could signify a change in the online jobs market with referral based jobs increasing in number and background checks being engineered on LinkedIn itself. However, the basic market dynamic of the middleman will probably not change. The online jobs market (indeed, the entire online classifieds space as a whole) in India is interestingly different from its counterpart in many western countries in the fact that the middlemen (recruitment agency in case of jobs, real estate brokers in case of real estate and, ahem, family / well-meaning relatives in case of matrimonials ) continue to exist even on a platform that is supposed to aggregate the end users. The entry of LinkedIn doesn’t seem to visibly challenge that scenario and all the so-called value creation associated with disintermediation is unlikely to kick in.

The Asian prospect

It will be interesting to see LinkedIn’s progress in other emerging markets, especially South-East Asia, where the rules of social networking and social gaming are being redefined. There are 2 factors in particular that could really work for the company:

1. The mobile angle: Friendster, having failed in most geographies, was the #1 social network in many Asian countries, until Facebook launched its mobile version and took over many of these markets overnight. Indonesia, in particular, is a case study worth exploring. LinkedIn will have to have a relevant mobile strategy (and I don’t just mean a WAP site or an Iphone app) to cater to this market.

2. The online jobs scenario: A sizable number of S.E. Asian professionals, especially those in the information and/or services economy look for jobs across S.E. Asia. Their needs are underserved with there being not even a single online jobs marketplace that consolidates all S.E. Asian markets. JobsDB probably comes closest but is largely used in the principal markets of Philipines and Singapore. LinkedIn could be that one unifying professional networking and job-sourcing website that S.E. Asia currently lacks.

It’s tricky for an American internet company to succeed in these markets. Outside search, portals and general purpose social networking, the only internet company that has succeeded notably in terms of traffic in these geographies is Ebay. However, Ebay grew entirely through acquisitions.

It remains to be seen which of the internet majors entering these geographies can really succeed not just in generating traffic, but more importantly in monetizing them in a manner that justifies all the hoopla around the emerging markets.

While monetizing a business network, community or marketplace, a successful company would be one which knows what the central proposition of the product is and would know how to monetize that particular proposition. It doesn’t take a genius to figure out that the central proposition for a marketplace is the transaction happening between two parties on it.

Borrowing a parallel from computer science and graph theory, the assets in a network or community may be understood in the following way:

1. Users (graph nodes): N in number
2. Interactions (graph arcs): Potentially, as high as Factorial N in number. For the mathematically nitpicky, this would be approximately NCx (N Combination x) where x is the average number of interactions per user
3. Transactions (weighted graph arcs): Potentially as high as Factorial N times the volume of interactions between any two parties on an average.

Clearly, the value diminishes as we move from monetizing transactions to monetizing users. The further you go away from the central proposition, the lower the likelihood to tap the real value of the marketplace.

Revenue models in order of how close or far they are from the central theme of the site would be:

1. Transaction-based revenue models: Directly monetizes the transaction. The best ones even monetize the volume of the transaction. 
   1. ODesk, which monetizes volume of the transaction by billing by the hour for service provided
      
   2. Cyworld: A social network where SOHOs set up shop and sell to customers, a cut of which goes to the network
2. Lead generation-based model: Monetizes the interaction but fails to create value out of the life-time value in the transaction.
   
   1. Justdial on voice. Yes, it does connect the SMB  to the customer but potentially loses out on the ability to continue monetizing it on an ongoing basis.
3. Value-added service model: Monetizes off the interaction, but not off the transaction. Monetizes secondary services that may be offered to the community while actual transactions are free thereby encouraging people to transact more and hence use the VAS more often.
   1. One of the many monetizing models on Alibaba
4. Subscription model:  Monetize one-time or once a year on a float subscription irrespective of number of transactions. This only monetizes the users in the community offering them special privileges but fails to monetize all the activity.
   1. Indiamart
5. Advertising model: In my opinion, a very poorly thought out business. Anyone owning transactions and interactions and monetizing only the users (or the nodes) would be wasting his asset. You might as well get this done as a media company
   
   So why in the world do people not want to monetize transactions. Some of the major reasons we get to hear from time to time are:
   

• Tracking and monetizing interactions and transactions are more complex to implement technologically than tracking and monetizing users
• Monetizing transactions on an ongoing basis sometimes ends up restricting the users in how they interact on the network. E.g.to monetize transactions, the marketplace may make free interaction more inconvenient than paid interaction to prompt users to pay. More often than not, this is antithetical to the free world of the internet and fails miserably
• Monetizing transactions and interactions usually require multiple payments collection touchpoints with the user. If payment collection from the end-user isn’t online and mobile and involves significant costs, a onetime subscription collection seems better.
• The end user in a few cases is not evolved enough to understand anything beyond the one-time subscription service
• More often than not, the business owner ends up monetizing through advertising because he didn’t think it out well enough. “Get the community and the users will monetize themselves” doesn’t work unless you are a Yahoo!

If it’s the last problem that your company faces, you’re in for a tough time. Any site in the world can sell eyeballs. The power of the community is not in the number of people you have but on the number of connections the community can potentially generate. Monetizing that is the big deal!

There has been a considerable amount of discussion on rural India of late and the opportunity it presents and one almost gets tired of the rate at which CK Prahlad is being quoted these days. Rural India definitely does present immense opportunity but for everyone trying to make millions out of it, there are a few words of caution on the challenges that the landscape presents.

I will draw upon my experience of having worked on three projects in the last 8 years targeting consumers in rural India with internet technologies, MVAS and general ICT infrastructure at Media Labs, IIT Kanpur, Intuit and the Hewlett Packard I-community to highlight some of the challenges involved.

Distribution and logistics: Infrastructure continues to be a challenge in rural India. Moreover, the lack of an efficient distribution network prevents penetration of products/services into rural India. One of the most innovative models in recent times has been the usage of the postal service by mobile operators to penetrate scratch cards to the villages. The Indian Postal Service with 155000 post offices is the largest distribution network in the world, and has all of 120000 outlets in India’s villages.

Payment collection: The majority of the rural population is still unbanked. Clearly, non-cash collection becomes rather unlikely. Cash collections, on the other hand, are messy and difficult to monitor, especially since cash cards or technology-enabled centralized POS (like Suvidha or ItzWorld) have still not reached rural areas. The time-tested manufacturer-distributor-retailer network has been the only real success so far but setting up such a structure is rarely feasible. Partnering with MFIs comes to mind but often, the MFIs don’t cater to the relatively more privileged/affluent segments of the rural economy who are likely to be early adopters.

Pricing: While Sachet pricing may have worked very well for Chik shampoo, the overheads involved in payment collection do not always allow easy execution of sachet pricing. It is easier to collect in larger amounts as every instance of collection and carrying of cash has associated costs. Disposable income, though, isn’t always high since the bulk of rural India is agricultural and income cycles in agricultural are very erratic and not as predictable as in the case of us salaried individuals.

Scaling across geographies: If India is a land of many cultures, the contrast becomes that much starker in the case of rural India. Setting up operations on a pan-India level presents different types of hurdles in different states ranging from political juggling to downright local factors. Any model where scalability involves scaling on-ground operations (and not merely an increase in downloads) is bound to run into myriad issues as we move from one state to the next. Add to that the greater differences in consumer tastes and behavior across geographies than in the relatively more cosmopolitan urban population.

Developing inorganic scale: Developing synthetic scale through partnerships typically results in larger overheads in the rural context. Finding the right partner with reach and presence in villages is difficult to start with. More importantly, there are very few players who are strong on these counts across multiple geographies. Hence, a pan-India rollout typically requires multiple partnerships resulting in higher partner management overheads.

Social and cultural challenges: The cyber café (or kiosk) model has not worked in many parts of rural India due to socio-cultural issues. One of the reasons for the failure of the kiosk model in Kuppam (HP’s i-community) was the lack of usage by women which was largely due to their discomfort in going to kiosks run by men.

I don’t at any point intend to play down the potential that exists. Most of my points just go back to the assumption that rural is a volume market and requires scale and achieving that scale organically or inorganically is a major challenge. Those who succeed in cracking these problems definitely will change the world around us.

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

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.

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.