Already an established investment trend, big data is becoming increasingly mainstream. From a VC perspective, the money will be made by going specialist and helping clients turn numbers into commercial action
More than 150 new words were added to the Meriam-Webster dictionary last year. Many of them – gamification, hashtag, selfie, crowdfunding – find their roots in technology. Another tech-related word to make the list was “big data.” This term has already become commonplace in venture capital, first entering the invest lexicon several years ago, but acknowledgment by Meriam- Webster is an indicator of just how mainstream the idea has become.
To many, big data represents a broad technological mega trend – much like mobile or cloud computing – that cuts across all technology segments. However, there is also a growing ecosystem of start-ups that identify themselves a big data companies.
“The fundamental premise behind big data is that the world is starting to go more digital and so there is more data available about every transaction,” says Manik Arora, founder and managing director with IDG Ventures India. “You have this unprecedented situation where you have massive amounts of data being generated from these transactions – and the question now is what are you going to do with it?” Many venture capital investors are looking to tap into the big data growth opportunity by targeting companies offering to solve these data issues, although the services they provides can be very different. While it is generally accepted that big data is important, opinions vary not only in terms of how the concept should be defined but also where the best opportunities lie.
Given the broad definition of big data, and the fact it is still in its nascent stages, getting a consistent picture of the size of the Asian market is challenging. International Data Corporation (IDC) recently predicted that the global market for big analytics – which includes big-data related hardware, software, and services – would reach around $125 billion this year and see compound annual growth of 30% over the next five years.
Unsurprisingly, North America and Europe account for a large chunk of that activity, but Asia – with its large populations and increasing mobile adoption – is where investors are shifting their focus. Jixun Foo, a managing partner with GGV Capital in Shanghai, points out that because the internet is generally a mobile-first experience for consumers in emerging markets, tackling big data is all the more important for consumer internet firms dealing with limited screen size.
“Whether you are an e-commerce provider or a transportation services provider, you need to be able to make relevant recommendations to the end user so data affects the whole user experience,” he says. “There is social element because the information about what you like and what your friends like can be captured. You have to do a better prediction and recommendation.
There is little consolidated information on investment in big data as a single sector. However, Preqin does track transactions across the analytics and performance, and system management software sectors. It has records of $208 million committed across nine deals so far this year, compared to $244 million across 50 deals in 2014, and $238 million across 52 deals the year before that.
This does not come close to capturing the full extent of GP activity. Most investors divide big data into three sub-sectors: data capture, data analytics and platforms. The latter, which includes analytics-as-aservice (AaaS), allows companies to act on data that is collected.
Many of the early entrants into Asia’s big data scene were based in India and offered analytical services. It was an obvious hub for this burgeoning sector. In many ways it represented a natural evolution for a country in which IT-related knowledge process outsourcing (KPO) and business processing outsourcing (BPO) industries have proliferated for well over a decade.
Examples of this earlier iteration of big data include companies like Mu Sigma, an India and US-based company that has raised several rounds of VC funding. It capitalizes on the need for businesses to understand and create value from the intelligence they receive by supplying analytics and decision support services to global enterprises.
“India has always been good with applications, even going back into software services industry. There is a lot of domain expertise,” says Mohan Kumar, a partner at Norwest Venture Partners in India. “Essentially what you are doing is taking that business knowledge and applying it to big data.” However, increasing demand for big data services is moving away from traditional data analytics and towards platforms that not only help users understand the information being collected but also provide actionable insights. Manthan Software Services, for example, offers business intelligence and big data analytics via a software-as-a-solution (SaaS) intended to help retailers and consumer products companies better understand their customers and drive growth.
The firm recently received a $60 million round of funding led by Singapore’s Temasek Holdings with participation from Norwest. The deal also provide IDG Venture India with a full exit while Fidelity Growth Partners India made a partial exit.
“More and more we will see big data transitioning into products, which is really about how big data analytics can be embedded with a product, and there are some very interesting companies coming up,” says Jishnu Bhattacharjee, a managing director with Nexus Venture Partners in Silicon Valley. Qubole is another Indian analytics start-up that falls into this category. The Bangalore- and US-based firm secured $13 million in its Series B round of financing led by Norwest in December. It has platform product, known as QDS, that helps users access big data generated by their companies to gain insights without the expense of maintaining the additional hardware infrastructure.
“Our belief is the best data analytic companies from India will be global and focusing on specific verticals and industries” says IDG’s Arora. “There are many talented sales and delivery people with a deep understanding of a particular industry, such as retail or financial services. That domain expertise is creating verticalized/industry-specific big data companies. We believe that there will be several large verticalized big data companies emerging from India.”
Companies in China have also recognized the value of such platforms – in part because they are especially important in countries where internet start-ups often more consumer-driven than enterprisedriven. “From a consumer internet point of view there is a definitely a big data opportunity,” says James Mi, a co-founder and managing director of Lightspeed China Partners. “The big challenge for these companies is how you acquire users cost effectively.”
MediaV is big data company trying to solve these issues. Launched in 2009, the company leverages big data to help merchants market their products to the right groups of consumers. The business raised three rounds of funding from Lightspeed China, GGV and Soros Fund Management-affiliated Quantum Strategic Partners before it was acquired by Qihoo360 Technology last year.
Another firm targeting the e-commerce opportunity is Baifendian, a data analytics start-up backed by IDG, which provides a platform analyzes customers’ online shopping preferences in order to help companies increase their online traffic. The company raised a $25 million Series C round of funding in July of last year. However, industry participants insist that the proliferation of big data start-ups has yet to reflect the size of the opportunity.
One defining characteristic of many of these platforms is that are becoming increasingly specialized and therefore the barrier to entry is high. Unlike other tech start-ups, big data firms demand both a highlevel of technological expertise as well as deep domain knowledge. The flip-side is that attracting talent can be a challenge.
“You definitely need intellectual horsepower,” explains Nexus’ Bhattacharjee. “It’s not about somebody setting up a website and putting up products like a e-commerce company. You need know-how and domain understanding as well.”
IDG’s Arora also stresses the importance of human capital to big data start-ups. One of the key challenges is understanding how take the deluge of data, process it, and apply it to specific purposes in a way that is useful to the client. For this reason, it is important to have talent across the three competences: data analytics, engineering, and product management.
“The main barrier to entry is having phenomenal talent you can retain, and retain for a long time because it take two or three years to build a good product and, unlike other start-ups, if you lose that talent during that process it can be a huge issue,” says Arora.
Looking further down the evolutionary curve, another potential threat to big data start-ups is the increasing willingness of companies to take these functions in-house, which could limit demand for third-party analytics providers. Many argue that as more tech companies place a higher value on big data, the analytics function will become a more important part of the business – and therefore a priority in terms of internal infrastructure investments.
“Big data is not just about standalone services,” says GGV’s Foo. “It is going to be an integral part of many businesses looking to understand their consumers, understand risk, and do behavioral predictions.”
However, not all functions can easily be brought in-house and there are some horizontals in which thirdparty services are expected to remain in high-demand. Lightspeed’s Mi points to companies like MediaV. “We think online advertising is a big sector,” he says. “Not everyone can afford to do big advertising technology – it is just not cost efficient. Even [US-listed Chinese e-commerce player] JD.com, which is a $22 billion market capitalization company, still uses Media V.”
In India, VCs are also looking at horizontal opportunities in the advertising space. Vserv, for example, is a smart data platform for mobile marketing in India and Southeast Asia. The start-up, which was previously backed by IDG Ventures India, offers a flagship platform, AudiencePro, that ties together data from multiple sources such as offline and online marketers, telecom operators, mobile app developers and other third party sources.
It has raised a total of $18 million to date, including a round raised this week from Maverick Capital. Meanwhile, investors see a lot of growth among start-ups leveraging big data expertise to serve very specific industries. Security is seen as having enormous potential. Mi notes that a new generation of companies in China is using big data to monitor devices, servers and firewalls in real time in order to identify security threats. GGV’s Foo share a similar view.
“There will be niches area like security, especially as we share more and more information online and more of your behavior is being tracked,” he says. “Security is a specialized area where you would need to have a third-party provider. We have invested in a number of security plays in the US.”
Big data is likely to remain in our lexicon for some time. As it continues to plow a furrow from nascent to entrenched technology, the companies most likely to flourish are the ones able to make the most of the big data and provide tailored solutions to end users. In the long term, some still see big data becoming just another part of doing business.
“In the future intelligence will be built in,” says Nexus’ Bhattacharjee “Big data investments might not be called big data but instead it will be next generation CRM, next generation marketing workflow, or next generation HR management systems – all of those things will involve processing massive amounts of information.”