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Marc Benioff

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Liz Gannes

A platform for investing in young people to help them pursue entrepreneurship and other opportunities is not a Google-like business. And a company called Upstart, founded by a team of former Googlers to arrange these investments, is not yet having Google-like success. (Not to set the bar high or anything.)

UpstartIn its first year, Upstart has arranged just over $1 million in funding to 83 participants from 135 backers, and repayments have already begun.

But Upstart says its ambitions, and the potential for the idea of “human capital,” are much bigger than that.

“The productive abilities of people represent all the potential of the economy. If we allow people to start investing in income potential, that’s the mother of all asset classes,” said Upstart CEO Dave Girouard in a recent interview.

(Girouard, 47, was formerly president of Google Enterprise and VP of Google Apps; and Upstart co-founder Anna Mongayt, 32, ran Google’s enterprise customer programs and Gmail Consumer Operations. A third co-founder, 22-year-old Paul Gu, was part of Peter Thiel’s 20under20 drop-out-of-college program.)

Having judged its early trials as successful, Upstart has now raised $5.9 million from new investors including Founders Fund, Khosla Ventures, Collaborative Fund, Eric Schmidt, Marc Benioff and Scott Banister, after raising $1.75 million from Kleiner Perkins Caufield & Byers, NEA, Google Ventures, First Round Capital, CrunchFund and Mark Cuban last year.

The company currently hand-reviews applications, rejecting about half of them so far, and running income-potential analysis to determine each person’s investment terms (for instance, $4,000 upfront might promise a return of 1 percent of a person’s income over the next decade). Almost everyone who made it through that process so far has raised a minimum of $10,000, according to Upstart.

So how does Upstart turbocharge its own growth? Girouard said he hopes to fund thousands of applicants within the next year, and that it would take a combination of getting the word out, product improvements like better mentorship communication, and U.S. law changes like the yet-to-be-implemented JOBS Act that would make it easier to publicly solicit investment.

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hal380The advent of Salesforce Marketing Cloud and Adobe Marketing Cloud demonstrates the need for enterprises to develop new ways of harnessing the vast potential of big data. Yet these marketing clouds beg the question of who will help marketers, the frontline of businesses, maximize marketing spending and ROI and help their brands win in the end. Simply moving software from onsite to hosted servers does not change the capabilities marketers require — real competitive advantage stems from intelligent use of big data.

Marc Benioff, who is famous for declaring that “Software Is Dead,” may face a similar fate with his recent bets on Buddy Media and Radian6. These applications provide data to people who must then analyze, prioritize and act — often at a pace much slower than the digital world. Data, content and platform insights are too massive for mere mortals to handle without costing a fortune. Solutions that leverage big data are poised to win — freeing up people to do the strategy and content creation that is best done by humans, not machines.

Big data is too big for humans to work with, at least in the all-important analytical construct of responding to opportunities in real time — formulating efficient and timely responses to opportunities generated from your marketing cloud, or pursuing the never-ending quest for perfecting search engine optimization (SEO) and search engine marketing (SEM). The volume, velocity and veracity of raw, unstructured data is overwhelming. Big data pioneers such as Facebook and eBay have moved to massive Hadoop clusters to process their petabytes of information.

In recent years, we’ve gone from analyzing megabytes of data to working with gigabytes, and then terabytes, and then petabytes and exabytes, and beyond. Two years ago, James Rogers, writing in The Street, wrote: “It’s estimated that 1 Petabyte is equal to 20 million four-door filing cabinets full of text.” We’ve become jaded to seeing such figures. But 20 million filing cabinets? If those filing cabinets were a standard 15 inches wide, you could line them up, side by side, all the way from Seattle to New York — and back again. One would need a lot of coffee to peruse so much information, one cabinet at a time. And, a lot of marketing staff.

Of course, we have computers that do the perusing for us, but as big data gets bigger, and as analysts, marketers and others seek to do more with the massive intelligence that can be pulled from big data, we risk running into a human bottleneck. Just how much can one person — or a cubicle farm of persons — accomplish in a timely manner from the dashboard of their marketing cloud? While marketing clouds do a fine job of gathering data, it still comes down to expecting analysts and marketers to interpret and act on it — often with data that has gone out of date by the time they work with it.

Hence, big data solutions leveraging machine learning, language models and prediction, in the form of self-learning solutions that go from using algorithms for harvesting information from big data, to using algorithms to initiate actions based on the data.

Yes, this may sound a bit frightful: Removing the human from the loop. Marketers indeed need to automate some decision-making. But the human touch will still be there, doing what only people can do — creating great content that evokes emotions from consumers — and then monitoring and fine-tuning the overall performance of a system designed to take actions on the basis of big data.

This isn’t a radical idea. Programmed trading algorithms already drive significant activity across stock markets. And, of course, Amazon, eBay and Facebook have become generators of — and consummate users of — big data. Others are jumping on the bandwagon as well. RocketFuel uses big data about consumers, sites, ads and prior ad performance to optimize display advertising. Turn.com uses big data from consumer Web behavior, on-site behaviors and publisher content to create, optimize and buy advertising across the Web for display advertisers.

The big data revolution is just beginning as it moves beyond analytics. If we were building CRM again, we wouldn’t just track sales-force productivity; we’d recommend how you’re doing versus your competitors based on data across the industry. If we were building marketing automation software, we wouldn’t just capture and nurture leads generated by our clients, we’d find and attract more leads for them from across the Web. If we were building a financial application, it wouldn’t just track the financials of your company, it would compare them to public filings in your category so you could benchmark yourself and act on best practices.

Benioff is correct that there’s an undeniable trend that most marketing budgets today are betting more on social and mobile. The ability to manage social, mobile and Web analysis for better marketing has quickly become a real focus — and a big data marketing cloud is needed to do it. However, the real value and ROI comes from the ability to turn big data analysis into action, automatically. There’s clearly big value in big data, but it’s not cost-effective for any company to interpret and act on it before the trend changes or is over. Some reports find that 70 percent of marketers are concerned with making sense of the data and more than 91 percent are concerned with extracting marketing ROI from it. Incorporating big data technologies that create action means that your organization’s marketing can get smarter even while you sleep.

Raj De Datta founded BloomReach with 10 years of enterprise and entrepreneurial experience behind him. Most recently, he was an Entrepreneur-In-Residence at Mohr-Davidow Ventures. Previously, he was a Director of Product Marketing at Cisco. Raj also worked in technology investment banking at Lazard Freres. He holds a BSE in Electrical Engineering from Princeton and an MBA from Harvard Business School.

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healthy_market

Editor’s Note: This guest post is written by Doug Pepper, who is a General Partner at InterWest Partners where he invests in SaaS, mobile, consumer Internet and digital media companies. He blogs at dougpepper.blogspot.com.

Everyone expects startups, even successful ones, to undergo a cycle of hype, disappointment and ultimately growth on the way to a sustainable business. But what about new technology markets themselves? Does the growth of a new market follow a similar pattern?

Fred Wilson recently wrote about the twists and turns that startups face (expanding on Paul Graham’s astute “Startup Curve”). I’d like to take those ideas further and describe the “Market Curve” — a similar path that new markets take on the path to sustainability.

The chart below shows the basic pattern. Markets often experience a “Hype Cycle” of overheated expectations followed by a trough — call it “Facing Reality.” If the market ultimately succeeds, the next phase is “Liftoff.” But troughs don’t end until several ingredients are present. First, there must be broad adoption of core underlying technologies that support the market. Second, there needs to be compelling reference applications to drive mainstream adoption. Finally, there must be a pioneering company, typically with a charismatic leader, that leads the market out of the trough. Obviously not all markets are destined to make it out of their trough.

For entrepreneurs and investors the most exciting element of the Market Curve is that, once the trough ends, strong technology markets ultimately prove more valuable than anyone imagined even during the Hype Cycle. Here are a few examples of how different technology markets fit into this curve.

Internet: Broadband Penetration and YouTube

The late ‘90s saw extreme hype surrounding the Internet but the market was simply not yet ready to deliver. With only five million fixed broadband connections in 2000 the underlying technology wasn’t there. Plus there were very few truly compelling applications. The Internet entered its “Facing Reality” trough in the early 2000’s and failed to live up to initial expectations.

But, by 2005, there were 43 million U.S. broadband connections and addictive applications like YouTube and eventually Facebook. That year Jeff Bezos launched Amazon Prime and convinced mainstream consumers that they could conveniently and safely shop for anything online. Since then, the Internet has proven to be more transformative to our civilization and more ingrained into mainstream culture than ever imagined.

Amazon has surfed the wave of the Internet’s Market Curve almost from the very beginning. Their stock price clearly follows this pattern.

Mobile: The iPhone and App Store

Between 2000 and 2005, nearly every VC firm had Mobile as a core investment sector. And, with few exceptions, those investments were unsuccessful. During that time, mobile networks were slow and unreliable (remember the CDPD network?), devices were clunky and carriers thwarted innovation. Clearly, that all changed when Steve Jobs launched the iPhone in 2007 and replaced the carrier decks with the App Store. And, with more than one billion mobile broadband subscribers globally, the post-PC mobile computing industry is in a “Liftoff” phase that is accelerating beyond wildest expectations.

SaaS: Salesforce.com and Successfactors

When I first joined my VC firm, InterWest Partners, in September 2000, the Application Service Provider (ASP) concept was all the rage. These ASPs offered off-the-shelf software to enterprises delivered over the Internet. However, between 2001 and 2007, adoption was slow because enterprises were more concerned with security risks than the benefits of hosted software.

Over time, Internet security and reliability improved and several pioneering companies, including Marc Benioff’s Salesforce.com and Lars Daalgard’s Successfactors, emerged with proprietary software applications that proved the benefits of SaaS delivery. Today, this market has broadened into a larger paradigm called Cloud Computing with corporations shifting nearly every aspect of their IT infrastructure into the Cloud. This could not have been imagined during the Hype Cycle of this market.

Market Failures: Troughs That Never End

Of course, not every market recovers from its trough. For example, while there are certainly specific nano technologies that are fundamental to many products, a broader nanotechnology market hasn’t emerged. It’s not clear that it ever will. And, in my opinion, Cleantech currently sits at the bottom of the trough. Because of extreme capital intensity, long sales cycles and wavering enterprise and consumer interest in “Green,” this market has become challenged. The question is whether Cleantech will ever emerge from the depths of the trough where it sits today and become the powerful market that John Doerr, Vinod Khosla and many others had hoped.

In the chart below, I show where a number of current technology Markets sit along the Market Curve.

Takeway: Have Conviction During the Trough

The best investors recognize and take advantage of these troughs and the best entrepreneurs lead Markets out of the trough. When SaaS was in the trough, Marc Benioff built Salesforce.com and Dave Strohm invested in Lars Daalgard at Successfactors. When the Internet was in the trough, Jeff Bezos built Amazon.com and Roelof Botha invested in YouTube. In the case of Steve Jobs, he invented a product and pioneered a business model that altered the Mobile market and led it out of the trough. The key is to have conviction about a Market and, as an investor, look for the technologies, products and leaders that will end the trough. Or, as an entrepreneur, launch market leading products and business models to end it yourself.

Marketo is an example of an investment my firm, InterWest, made during a trough. During the late 1990′s, there was a peak of excitement around Marketing Automation with companies like Annuncio, Rubric, Marketfirst and ePiphany. But, the market was not ready. Marketers were not adopting Internet techniques for acquiring customers and they didn’t have sufficient budgets to adopt and implement enterprise software.

By 2006 when InterWest invested in Marketo, the company’s founders believed, and my colleague Bruce Cleveland and I agreed, that the market had progressed along the Market Curve. Marketers had begun consistently utilizing search engine marketing, landing pages, email marketing, and online content marketing … all the activities that are harnessed and optimized by Marketing Automation and Lead Nurturing products. And, the SaaS delivery and business model meant that marketers could quickly see ROI without big budgets or IT resources.

We had conviction that that the Marketo team would create the compelling products needed to lead the Marketing Automation market out of the trough. Today it seems clear that this market will be larger than expected even during the initial Hype Cycle.

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