Clearly, the world of micro-finance consumers’ socio-economic environment is starkly different from that of the banking consumers’. For one, for the usual banking consumers there is enormous amount of structured data. Consider a banking customer’s data about the banking (savings or current account), credit (loan account) or purchase (credit-card) history. One can run every kind of analytics: from simple cross tables to complex multidimensional OLAP cubes. One can run advanced statistics, such as predictive analytics, to predict who will buy what, by when and how much. Or predict other matters of interest such as loan defaults. Not much of data that is image or text is used. Micro-finance consumers have practically none of the structured data that the usual banking consumer has. And there is an increasing potential in using non-structured data, such as image, to answer some of the basic questions.

For instance, the Google Earth Images of night-time data of Dharavi, Mumbai over the past 15 years shows increasing intensity of light. On the other hand similar data of Gardanibagh, Patna shows decreasing intensity of light – an indication of migration. This simple insight can drive the overall market demand estimation in both volume and value of loans terms.

One very senior micro finance entrepreneur remarked that the way he measured the sales potential of a tea-vendor, a potential customer, was by stationing a person for a couple of days measuring number of cups sold, other items sold, etc. While there is novelty in collecting sales data this way (which for a usual customer is just asking for two-years of P&L), the idea cant scale. Imagine the same data collected through an installed camera rolling, a computer vision algorithm counting everyday the number of cups of tea brewed. The scaling potential of collecting such data is immense since computer vision now can recognize almost any item that we ask it to recognize.

The idea can be extended to almost any assessment for a micro finance household. After securing necessary permissions from any household, a rolling mobile camera and thereafter an AI lead Computer Vision can assess the ‘wealth’ by noting the type of house, fridge, TV, bedding, toilet, roof, etc. Of course, one can also assess the number of household members, their gender and probable age. It is quite possible that the demographic data so collected is actually far richer than the ones that is collected and stored in any other manner. It is also easy for us to see that changes in such data can be captured in a similar fashion thereby ensuring that the Micro Finance institution has the latest demographic data. Such latest data is something even accomplished banks find it hard to get; I was looking to compute the credit-risk score for a large South Indian bank and found that several aged customer’s occupation and incomes, filled several years ago at the time of opening the account, were so outdated that using such variables was rendered fruitless.

And then there is the (African) case of rural / agri micro finance determined by cash-flow (nothing new here). But the way cash-flow was generated per customer was new. The micro finance company flew a slew of drones over crop-lands and installed IoT at critical points to estimate quantity of produce. Armed with this data one could closely estimate the actual cash flows of a farmer. There are early evidences of estimating livestock similarly.

As one can see from the above, AI led Computer Vision can help uncover several “dark data” and estimate the market size, the demographics and cash flows critical for some very fundamental decisions. It can be used also for operations.

Attendance of members in a Joint Liability Group (JLG) is an important determinant of risk and continuity of a member. Today the attendance is taken physically by an agent with attendant risks of poor data; one then also transcribes the data at the branch or head office. One can move the attendance to the app which can process a picture, recognise faces and mark attendance directly to the tables. Several other processes, such as cheque clearing and new bank or loan application form processing can be automated using AI lead computer vision.

To conclude, trying the same ways in which to collect and analyse data as is normal in established banks will not help the cause of a distinctly different environment of micro-finance. That is a dead route. However, if one sits up to use really novel ways to collect and process data, e.g. using AI lead Computer Vision, the micro finance analytics is a sleeping giant. Of course, it is neither easy, nor cheap to quickly imbibe such techniques. But that path will create massive competitive advantage, superior customer experience and increased profits.

Automation is the key to achieve efficiency in businesses in the current contemporary world, and artificial intelligence is one of the technologies that is widely being applied in order to do so. However, in a sector like BFSI, which has been used to the manual workforce for a long time now, the application of new-age technologies faces its own set of challenges. In an interview DataQuest, Dr Jayaram K Iyer, co-founder and CEO, DeepQuanty Artificial Intelligence Labs Pvt Ltd talks about the importance of artificial intelligence in BFSI, challenges faced while implementing the same, and the issue of skills shortage in India.

Importance of artificial intelligence in the BFSI sector

From intellectually demanding actions such as computing risk scores to mundanely routine tasks such as transcribing data, the BFSI sector has it all. Improving any of those processes means superior customer experience, leading to improved market share; or can mean lower turn around time or lower costs, leading to improved profits. AI undoubtedly can help so improve. In the times of high competition in the BFSI and even higher costs (say due to NPAs), even small increments in market share or small savings in costs can be a matter of even existence.

Consider just a couple of use-cases. A loan application consists of an application form, past bank statements, statements of accounts, KYC documents and such. It takes time to not just transcribe the data from an application docket, but also to analyse the contents for its creditworthiness. It may take several days. Computer Vision developed basis deep learning Artificial Intelligence can read such forms and statements. It also performs cognitively heavy functions of an analyst – e.g. calculate a credit score. The result is not just lower costs and accuracy but quick turn-around. Another use-case is clearing cheques, especially the handwritten ones. Computer Vision products can read date and suggest if the date is acceptable. It can also read and compare the amount in figures and words. Lastly, it can compare the signature on the cheque with the core banking version.

Are there enough skilled employees in artificial intelligence and advanced analytics in India?

No. There is indeed a humongous shortage of quality talent for AI and Advanced Analytics in India and it is so even in the world. An interplay of three reasons explain why this shortage has come up. (a) Firms are realizing that there are needs that hitherto could not be resolved or difficult to resolve can be resolved now. (b) Technological capability in analytics that can cater to such stated and unstated needs is exploding. The rise and democratisation of Big Data, Cloud Computing, Graphical Processing Units, Python and its array of analytical capabilities. (c) However, the supply of quality data scientists is lagging both in number and quality. This is because, the ecosystem of analytics is vast, complex and fragmented. Data scientists have to learn new languages, algorithms, frameworks and new tools by the hour. If the end delivery in on diverse (edge-) products (e.g. say an app in mobile), then they have to additionally customize and optimize for each type of CPU. A close analogy to this conundrum is the ever-increasing rise of personal transport (cars including Uber) and travel needs but an acute shortage of drivers. Only people passion for analytics, continuous learning and never-say-die attitude can excel in this field.

Challenges faced while integrating new-age technologies in BFSI

A big challenge in BFSI is regulations – especially with respect to the privacy of data. Several applications in Computer Vision based on AI/ML thrive on cloud-based delivery. Banks demand on-prem and it is a challenge. Another problem is that just a few of them warm up to technologies that are nearly 100% open source. Geographic differences in handwriting post some unique challenges. Lastly, Karma. For e.g., consider in cheque processing, signatures matching. In legacy systems, card-signatures are typically stored in very low-resolution noisy images. They are sufficient for human-eye processing and help in fast transmission over net. However, when it comes to Automatic Signature Verification, past images pose problems.

How artificial intelligence is being used in solutions offered by DeepQuanty

At the heart of all DeepQuanty products are Deep Learning and Artificial Neural Network techniques. Products are developed basis learning from thousands of real life samples. Consider for e.g. SnapChek that automates reading and processing handwritten and printed cheques. Thousands of mock cheques were carefully designed and prepared for training. The mock cheques were digitized, processed, and converted to data using patent pending algorithms. Or consider ZapSkore that automates reading and processing bank statements. Post training on synthetic data, the images of bank statements are processed and converted to data using neural network algorithms. Further, on the extracted data, machine learning algorithms work to produce credit risk scores. Likewise, FormEasy is another AI driven product that extracts data from application forms such as Bank Savings / Current Account, Credit Card, etc.

MIMA (Matrimony.com’s Intelligent Matchmaking Algorithm) is a home grown machine learning algorithm that computes results in real-time using big data technologies and data sciences.

It has almost solved all the problems that arouse in match-making as it is a virtual personalised matchmaker. It seeks who are similar to a given profile, analyses the preference of that set, creates a model-profile, compares it with scores of profiles in the site and shows best matches first.

This has resulted in about 31 per cent increase in engagement metrics and 50 per cent increase in success stories.

Chief Strategy and Analytics Officer, Dr. Jayaram K Iyer said that the results are indeed very satisfying and it is one significant step towards their endeavour to understand the stated and more importantly unstated needs of the members.

Murugavel Janakiraman, founder and CEO of Matrimony.com explains that matchmaking is a time consuming and emotional journey for members and their families so they wanted to make the whole experience of finding life partners a lot easier than before and they have achieved that.

The analytics engine and algorithm that would predict the unstated preferences took three months and a team of 60 top-notch programmers and database experts to complete.

Spotify is a rising technology venture which, since its public launch in 2008, has disrupted the way music is distributed. It allows users to listen to music online and share playlists with friends. It also provides an offline service. What differentiates Spotify is not just its product but also its social media marketing strategy. This case study looks at how Spotify evolved its use of marketing tools in keeping with the evolution of the music industry, as well as changes in the way companies and customers now communicate with one another.

The Internet has been disrupting and revolutionising the global music industry all through the past two decades, The traditional pre-recorded forms of music distribution have been heavily substituted by illegal file sharing, downloadable tracks and, more recently, cloud-based streaming. These changes have significantly reduced the music industry’s revenues, which in turn has forced industry players to drastically rethink their strategies and come up with a mass of innovative business models.

The revolution began with the development of the .mp3 format in the mid-1990s. It provided a means to store audio in a compressed format that was far smaller than uncompressed audio. With the relatively small hard drives of the time, this enabled people to store their music collection on their personal computers, and create their own compact discs of mixed compilations.

The natural progression from the.mp3 was the development of Internet-based file sharing platforms. Beginning with Napster, launched in 1999, many large-scale file sharing applications proliferated, all designed to help the illegal sharing of .mp3 files. They cannibalised sales in the traditional music distribution platforms. Many artists and record labels filed lawsuits against the offending companies, and also against individual users exploiting the platforms. Although some progress was made in curbing the use of these sites, there are still today an estimated 16 million Americans who download pirated music.

One of the first companies to try to legitimise downloading of individual tracks was Apple, which opened its iTunes music store in 2002 to complement its iPod device. The store was an immediate success, with more than five million songs downloaded in the first two months.

This provided an attractive proposition to consumers as they could legally obtain access to preferred songs with no need to buy an entire album. The rapid rise in broadband speed and penetration in recent years has opened up the possibility of cloud computing, which allows access to files without the need for local storage.

Access to the cloud has spawned a number of start-ups such as Spotify and Grooveshark. These providers allow access to an almost endless database of music to users, which can be pushed to computers and other devices connected to the Internet.

These sites have a range of revenue models which tend to revolve around subscription services and advertising while a user listens, which enables them to pay royalties to artists. But this continues to be criticised as the royalties paid are said to be miniscule. For instance, Spotify reportedly paid Lady Gaga only $167 for one million streams of her single Poker Face.

Development of the Spotify technology began in 2006 at Spotify AB, the founding company based in Stockholm, Sweden. In October 2008, the founding team launched the technology for public access, launching the paid subscription model at the same time. The initial public access was by invitation only. The company also announced licensing deals with a number of major record labels at the time.

In February 2009 Spotify launched free registration without an invitation in the UK. It also launched its mobile technology offering in 2009. This resulted in a surge in users, leading to a suspension of free registration for the remainder of 2009. The mobile technology remains a “premium” paid-for service, but Spotify returned to free registrations without invitation by 2010.

The parent company moved from Stockholm to London, and is now called Spotify Ltd. The development and research work is still undertaken in Sweden. By September 2010, Spotify had about 10 million users. Its growing popularity highlighted the need for further investment in research and development.

Spotify received $21.6 million in its first round of funding in 2008, prior to the launch of the public access service. The first round was funded by Creandum Northzone Ventures, a technology-focused Nordic venture capital (VC) firm, and Li Ka-Shing, an angel investor and the 11th richest man in the world as estimated by Forbes 2011. The second round of funding for $50 million came in 2009. Li took part again in this round, along with VC firm Wellington Partners.

Sean Parker and Founder’s Fund, where Parker is a board member and one of six partners, participated in the third round of funding for $11.6 million in early 2010. The final funding round took place in 2011, for $100 million, between Accel Partners, Digital Sky Technologies, which funded Facebook and Groupon, and Kleiner Perkins Caufield and Byers, who were early investors in Amazon and Google. These funding rounds, along with the rapid user addition globally, meant the company was valued at $1 billion in June 2011.

In 2009, Spotify’s founding team of CEO Daniel Ek and Martin Lorentzon expanded the company’s board to include Frank Meehan from Horizon Ventures and Sean Parker, the serial entrepreneur linked to Facebook and Napster, among other social media start-ups. In 2011, Spotify added the position of Developer Community manager, hiring Andrew Mager, another serial entrepreneur and blogger with prominence in social media networks.

One reason Spotify has been adding users rapidly is its tie-ups with social media sites. An active Facebook account is needed to register, unless the user had a Spotify account prior to September 2011. With its Facebook page and Twitter stream, Spotify communicates with users the same way many firms use social media to promote their products and gain feedback. Beyond these established forms of social media marketing, Spotify has introduced several innovations. It has incorporated social media extensively into its product, relying heavily on Facebook in particular to enhance the user experience.

Spotify adopts a traditional approach to managing its own social media feeds. Says Andre Sehr Spotify’s Head of Social Media: “[Facebook and Twitter] both provide us with a platform to promote new artists and albums, talk about great new Spotify features and get valuable feedback to improve our product.” In addition, Spotify tries to drive social media users to its premium service by promoting on Facebook and Twitter before releases unique content and competitions that only premium Spotify users can access.

Spotify’s Facebook page has 2.4 million “likes” and an average of one post per day, primarily about bands who played or visited Spotify offices, and curated playlists for bands performing at festivals and award shows that can be listened to via Spotify. On Twitter, Spotify’s stream has 264,000 followers and an average of four to five tweets per day. There is a much higher level of engagement than on Facebook. On Twitter, Spotify answers users’ questions, retweets music-related tweets by both regular and celebrity users such as Ashton Kutcher, and even sends users playlists made for them.

Spotify has used social media feeds to generate buzz among users. When Spotify launched in the US in 2011, it was by invitation only. As demand for Spotify in the US was high, following its success in Europe, it used scarce invitations as a carrot for social media users to hype up the launch. It also teamed up with Klout, a site that rates peoples’ influence within Twitter, Facebook and LinkedIn, to provide 100,000 invites to US users. Klout users could get an invite if they had a high enough Klout score, ensuring Spotify reached users who were most likely to share thoughts through social media with communities that value their opinion.

Interest in securing Spotify invites was so high that the Klout website crashed due to user overload. Spotify has deeply integrated its service with Facebook. It has adapted its business model to ensure that this integration attracts users. Spotify and Facebook are now embedded in each others’ platforms, enhancing the value of both. Music can be shared seamlessly between friends.

Ahead of the launch of its integration with Facebook, Spotify changed its core pricing model. Spotify had initially been adopted mostly by music fans who valued the ability to listen to a wide variety of music on demand. As usage of Spotify began to appear in Facebook users’ news feeds, Spotify gained exposure to a much larger audience than would have previously been aware of the product. Previously, users with free, or ad-supported, accounts were restricted to 10 hours listening per month and five plays of any song. To attract new users and prevent any time or song limit issues when users clicked on songs appearing on Facebook news feeds, Spotify began to allow six months of unlimited listening on free accounts.

Spotify’s innovations in social media are driven by the belief that music is social. Indeed, music has become truly social.

It was only 8:30 in the morning on Saturday the 2nd March 2013 at the IITM Research Park in Taramani but the auditorium was already being filled by entrepreneurs, rookie & experienced, young and old, for the first session of the Super Start-up event organized by TiE Chennai. This event attracted people from Bangalore and Pondicherry as well!

And 9 entrepreneurs (yours truly included) were about to make a pitch of their business via skype to Sramana Mitra, the charismatic founder of the 1Mby1M network aimed at global entrepreneurial development.

And it was like a torrential downpour soon after where each entrepreneur got 5 minutes to talk about the technology and the business side of his offering (how come there wasn’t the 33% reservation for women?) and answered questions from Sramana and the audience for the next 5 minutes or so.

These included very varied products and services like diabetes management, office supplies, marriage gift registry, shopping comparison based on social-media, low-cost high-speed entertainment on the go, wind turbines, MSME network, Field force automation and crowd-sourced content creation and publishing.

Some of us were looking for inputs to further fine-tune or tweak our offering whereas there were others clearly looking for funding. Sramana asked questions largely on the monetization models, the existing revenue levels and the go-to-market strategies but it wasn’t like the Spanish inquisition that I had expected.

After all the presenters were through, Sramana complimented the Chennai ecosystem for working on products and concepts that were quite aligned with the global scenario and in some cases even competing with the best of breed offerings.

5 entrepreneurs were selected for the first round of Premium Membership of 1Mby1M by Sramana and the TiE Chennai team and there would be another iteration after which 3 will be given the scholarship for the same.

This was followed by a speech by Raghu Rajagopal, a serial entrepreneur, investor and mentor where he shared the mistakes and the lessons learnt from 8 different entrepreneurs from different industries based on his interaction with them.

Since most of them were from the IT background, these entrepreneurs didn’t quite understand the importance of financials and more specifically cash flow early in the game and that was a recurring theme. There was also this pattern of hiring people based on hope that they will perform and continuing to give non-performers a long rope. One admitted to taking more initiatives at the same time leading to dilution of focus and it was also common for them to have high expectations of others.

This was followed by an interactive session where Raghu fielded questions on paper-money exits, mentoring, his bandwidth for providing support to upcoming entrepreneurs etc with ease.

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The final session of the morning was one on marketing by Dr Jayaram K Iyer, an employee turned academic who is now donning the hat of Chief Strategy officer for the Bharat Matrimony group of companies.

Although he was talking only of the fundamentals of marketing, he made it so interesting by turning it interactive with subtle doses of humour. He also regaled the audience with short anecdotes and video clips.

He emphasized on the need for the entrepreneurs to identify the need first and define the segment and positioning before creating the products whereas it was usually the reverse. He made some interesting observations on the importance of businesses to make it easy for the prospective consumers to know about the offering, access it, purchase it, use it until the point of disposing it. The session was so engrossing that most of us did not even feel the pangs of hunger until 1:30 pm!!

Post lunch was the UnConference session organized by Dorai Thodla where people can walk into any of the discussion groups located at different parts of the conference room and participate freely.

There were topics like pitching, Marketing for startups, Hiring and HR & Lessons from Failures. Because it was new and people expected someone to talk centrally, there was some confusion initially but once they got started, there were animated conversations at various levels.

There was also a media corner where Murali (ex- Business Line) was giving an opportunity for entrepreneurs to share their journeys on camera in the form of 1-2 minute video capsules. I personally found the experience really gratifying.

Overall, it was a day which offered numerous options for those who wanted to take them, both in the formal and informal sessions. The photos were courtesy Agni Sharman.

TiE Chennai’s Startup Super Day Brings Meaningful Help for Startups

On March 2, as Chennai was feeling a transition from the passing winter into incoming summer, the heat was being felt inside the auditorium in IIT-M Research Park. The occasion was fourth edition of Startup Super Day of TiE Chennai and at the Pitch Fest 10 startups pitched to Sramana Mitra, founder of 1M/1M, who listened to them from Silicon Valley through videoconferencing.

Most pitches seemed intent on solving problems. While some were very ambitious in scope (connecting SMEs to automobile giants), some were novel (surrogate advertising on windmills) and some tried to change the status quo (crowdsourced content for online learning). The Pitch Fest’s winners will walk away with a cool 1M/1M program membership worth $1000 per annum. Three winners were to be finalized from the 10 pitches. The scholarships are sponsored by TiE Chennai charter members.

Chennai on top of technology

“I am impressed with the pitches,” Sramana told the audience from the Valley. Then she listed the biggest trends in the technology space today and Chennai being very part of it. Some companies like Avaaz and OrangeScape are at the forefront of this innovation. Mobile apps like Avaaz, a technology product that helps autistic children communicate, has developed apps for iPhone, Android, Blackberry and in the process of developing one for Windows 8. Similarly OrangeScape, which has developed KISSFlow, a workflow tool to help enterprises through PaaS and Fresh Desk, which has leveraged SaaS to develop a suite of CRM applications, are leading the way in this technology. Big data is another area of expertise that not many are comfortable with but big corporations are increasingly focused on it to make informed, data-driven decisions. Data mining is no longer in fashion but data analytics is a fast catching up trend. Latent View Analytics from Chennai is serving a global audience through its big data analytics. Niche e-commerce is a fast developing trend and Carrot Lane from Chennai is selling diamonds online in partnership with an American company, Blue Nile, based on contract arbitrage. Through this, diamonds worth $16 million are being sold online.

Failure as a stepping stone to success

TiE Chennai Charter Member Raghu Rajagopal, a serial entrepreneur, investor, and startup mentor, gave choicest lessons on failing. Quoting various entrepreneurs from his interviews, he listed the entrepreneurs’ mistakes and lessons they learned from their experience. Most entrepreneurs find finance troubling and do not know how to channelize funds appropriately early on. While entrepreneurship is a learning curve necessarily, a heads-up advice like Raghu’s helps avoid many mistakes that startup entrepreneurs are prone to. The key mistakes were mostly in areas of thinking and functioning, customers and customer intelligence, matters internal to the organization, and finance. “Staying on your core is important,” stressed Raghu. “Don’t compare yourself to other entrepreneurs. Focus and attention to detail, how to be in play, and knowing success is relative are of immense help. It’s a marathon,” warned Raghu, adding those who are there for a quick buck and quick exit cannot make it. The stories were rich and provided good take-aways for entrepreneurs in a practical sense.

Marketing mantras

Prof. J.K. Iyer, strategy head at Consim, that owns Bharat Matrimony.com, enlivened the audience with his interactive marketing “seminar.” After understanding customer needs, it’s imperative to segment, target and position your product, he emphasized. Segmentation and positioning is important, as, in his words, “your product cannot satisfy everyone’s needs.” Sometimes the product might find another use apart from what it is intended for. Quoting a light-hearted marketing folklore, he said entrepreneurs should be open to understanding this. When a survey was done to find out why washing powder Surf wasn’t selling as quickly as the washing machines in Punjab, it was found that washing machines were employed for making lassi. Describing customer need as very crucial to a successful marketing campaign, he said HDFC has a product that serves only 119 customers out of its customer base of 3 million. Such micromarketing efforts contribute to success, he said. Increasingly understanding customer behaviour and developing products around it is emerging as a latest trend in marketing. This is called psychographic segmentation. Fixing value is arbitrary, he said, quoting an experiment where MBA students were asked to suggest price of two shirts, one branded and another of the same brand but with labels removed. The students tend to put higher value for the branded shirt. That plays a big part in us attaching value to a product, he said. Packaging also enhances value, he added. One important part of marketing is understanding what it entails. To illustrate a myth, he quoted another folklore where it is said a marketing person should be able to sell a comb to a bald-headed customer. “Maybe he can convince a few customers but there will not be repeat business,” he joked, and if the product is not used for what it is intended, repeat sales will not happen, he explained.

TiE CHENNAI

It was agony and ecstasy in quick succession for leading Tamil movie star Dhanush last November. He recorded a song for the film 3 – a home production, in which he also plays the lead role – only to discover soon after that a disgruntled employee in his office had leaked it on YouTube.

It put him and his wife Aishwarya, director of the film – she is also the daughter of the superstar Rajinikanth – in an embarrassing position, since Dhanush had just sold the film’s music rights to Sony Music India.

An early, unauthorised release of one of the songs could ruin the commercial prospects of the deal.

“The song was the rough cut of Kolaveri Di. I was terrified,” says Dhanush. There was nothing he could do to get the song off the site.

“I realised to my chagrin that something leaked on the social media cannot be controlled,” he adds. “I wanted to counter it, but how? I was at my wits’ end.”

He considered releasing a CD of the song as a single, but Sony Music informed him that this would take at least two weeks.

“Then someone suggested making a video of the song and releasing that as well on YouTube as the official version,” says Shridhar Subramaniam, President, Sony Music Entertainment, India and Middle East. “The idea was accepted and we scrambled to make the video overnight.”

This vital decision was to make all the difference. Sony Music hired a video camera and promptly shot a four minute video of Dhanush singing Kolaveri at A.R. Rahman’s studio in Chennai. It was all done within half an hour and the video uploaded on YouTube on November 17 at 12.53 a.m.

What followed is now part of Indian music and viral marketing history. As if by magic, the song became a rage, effortlessly transcending language barriers – the first Tamil song, albeit with a smattering of English, to do so.

In the first four days, the video had four million views, swelling to 19 million in three weeks. On Facebook 6.5 million users have shared it, while 40 radio stations have played it across the world. At last count in February-end, the video had registered over 46.5 millions views on YouTube and been downloaded by two million people on their mobiles.

In the most unlikely way, Dhanush’s agony thus turned to ecstasy. A Tamil movie star until then, it brought him a pan-India reputation. He is much sought after now by corporate houses to endorse their brands.

“Doors opened for me,” he says. “Kolaveri’s success exposed me to the world of marketing and I realised how much I had been missing out on.”

The campaign was carefully designed to avoid sounding like a sales pitch. Some radio and TV channels got exclusive rights to use the song for two days. Noting the interest, news channels began discussing Kolaveri

A letter from Tata Group Chairman Ratan Tata, thanking Dhanush for the time spent with him, and seeking to take their business discussion forward, now adorns Dhanush’s office wall.

The film 3, earlier planned only in Tamil, will now be released in two more languages, Hindi and Telugu.

But successful viral marketing campaigns such as Kolaveri do not happen every time, not even for Dhanush. His next song on video, a paean of praise to cricketing icon Sachin Tendulkar, Sachin Anthem, uploaded, like Kolaveri, on YouTube, has garnered only 4.9 million views in three weeks so far.

“Every kind of content has the potential to go viral when the consumer becomes the marketing channel,” says Prashanth Challapalli, Business Head, Jack in the Box Worldwide – the agency which designed Kolaveri’s viral strategy. “But no one knows which particular one will go viral. All we can do is to create content that has the potential to do so.

What are the elements that go into this kind of content? Something that evokes strong emotion is one. Kolaveri did: it is the song of a jilted lover pouring out his anguish.

“Emotions, especially unhappy ones, have a strong viral stimulus,” says Jayaram K. Iyer, who teaches social media marketing and branding at Loyola Institute of Business Administration (LIBA), Chennai. “So do narratives of an underdog beating the establishment. Both were present in Kolaveri.”

By the time minister Sharad Pawar was publicly slapped by a young man on November 24, Kolaveri’s meaning had become known and promptly many riposted: ‘Why this kolaveri?’

The experience of having failed in love is also almost universal. But to counter the sadness, the song also had humour. Humour is key to viral success – outstandingly successful videos on YouTube like ‘Charlie Bit My Finger’ or ‘David at the Dentist’ have plenty of it.

The other aspect is to arouse curiosity. “It is critical to be intriguing. People should wonder what the campaign is all about,” adds Iyer. Both Sony Music and Jack in the Box Worldwide invested intrigue into the process. “Non-Tamil speakers would not know what Kolaveri meant. Neither Dhanush nor any of us explained its meaning either,” says Sony’s Subramaniam. “It was a conscious strategy to evoke people’s curiosity and get a conversation going.” In the first few days after Kolaveri’s release, a good deal of chatter focused on what on earth the word meant. Around 12 per cent of all conversation on Twitter about Kolaveri was confined to this particular point.

“The biggest myth is that viral marketing campaigns make themselves,” says Iyer. “Campaigns have to be orchestrated.” And indeed, once the official version was uploaded, Kolaveri was carefully managed at every stage. Sony Music began by putting a link to the video on its Facebook page, which has a million followers. Next, it began releasing tweets about the video, creating the #whythiskolaveri account on Twitter.

There were 179 tweets on the first day, which rose by 200 per cent daily, to peak at 14,907 tweets on November 24. “For people to share the video, they had to first see it,” says Subramaniam. “We put the YouTube link in all our tweets. We were confident that once a person sees the video, he would share it for sure.”

From the virtual world, the song was also shared with the real one towards the end of the first week, with radio stations and television channels being allowed to air it. FM station Radio Mirchi and MTV got exclusive rights to use the song for two days. Noting the stir in the entertainment space, news channels began discussing Kolaveri, further fuelling its popularity.

Those who were drawn in and tweeted about it included mega star Amitabh Bachchan and leading industrialist Anand Mahindra. There were also critics, but the attacks only reinforced its now iconic status. “Kolaveri-D. Everyone is praising the robes, but the emperor is naked,” tweeted lyricist Javed Akhtar. “Getting celebrities and influential people to seed the campaign through Twitter or Facebook pages is key,” says Iyer, the LIBA professor.

The success even saw parodies, says Challapalli. By the time Union Agriculture Minister Sharad Pawar was publicly slapped by a young man on November 24, Kolaveri’s meaning – ‘extreme frustration’ or ‘murderous rage’ – had become sufficiently well known, and promptly many riposted: ‘Why this kolaveri?’

“People began to own the song and that helped,” says Subramaniam. “Scope for co-creation is a critical factor for any viral campaign to succeed,” adds Challapalli.

Yet the campaign was also carefully designed to avoid sounding like a sales pitch. The film the song figures in, for instance, was never mentioned. “Content that sounds like a sales pitch fails,” says Iyer. “Never use viral marketing as a sales channel. It puts people off instead of getting them excited.” So in the end the video’s success may not guarantee a super hit movie. Kolaveri has set the stage for a good opening but how successful the movie will be would depend on its content,” says Subramaniam.

Dhanush, naturally, is thrilled with the unexpected windfall. Has he identified the office employee who leaked the early version of Kolaveri? “No, but if I do find him, I will thank him,” he says.

But for the leak Kolaveri would never have become the viral marketing phenomenon it did.

2. Academic Committee

3. Examination Committee

Academic Council of Community College

(A) Principal of Community College – (Chairperson) (1)

1. Dr. Sumana Navin

(B) Teachers of the College representing Programme Sectors (4)

1. Dr. S.Suresh, Nephrologist, Sundaram Medical Foundation

2. Dr. Navin Jayakumar, Director – Darshan Eye Clinic

3. Dr. B.Subba Rao, Nephrologist, Apollo Hospitals

4. Dr. R.Vijayakumar, Nephrologist, Govt. Stanley Hospital

(C) Experts from outside the College representing Industry, University and Community (3)

1. Mr. Sanjay Shroff, Director- Vishwashanti Pvt. Ltd.

2. Dr. Ordetta Mendoza, Associate Professor of Botany, Stella Maris College

3. Mr. Govardhan Agrawal, Correspondent, JHA Agrasen College

(D) State Govt./ Local Admin. Representative (1)

1. Dr. J.Amalorpavanathan, State Convenor, Cadaver Transplant Programme.

(E) Regional University Representative (1)

1. Mr. Jayaram K Iyer, Associate Professor – Marketing, Loyola Institute of Business Administration

(F) Local Community Leader (2)

1. Dr. Vijay Vishwanathan, Managing Director, M.V. Diabetes Speciality Centre

2. Dr. D.M. Mohunta, Consultant – Chemical Engineering

(G) Members of College Community Board (2)

1. Dr. Sunil Shroff, Managing Trustee, MOHAN Foundation

2. Dr. T.K.Parthasarathy, Pro Chancellor, Sri Ramachandra University

(H) Nominee of IGNOU (1)

1. Dr. C.K.Ghosh, Nodal Officer, Community College Unit