After twenty years of Salesforce, what Marc Benioff got right and wrong about the cloud

As we enter the 20th year of Salesforce, there’s an interesting opportunity to reflect back on the change that Marc Benioff created with the software-as-a-service (SaaS) model for enterprise software with his launch of Salesforce.com.

This model has been validated by the annual revenue stream of SaaS companies, which is fast approaching $100 billion by most estimates, and it will likely continue to transform many slower-moving industries for years to come.

However, for the cornerstone market in IT — large enterprise-software deals — SaaS represents less than 25 percent of total revenue, according to most market estimates. This split is even evident in the most recent high profile “SaaS” acquisition of GitHub by Microsoft, with over 50 percent of GitHub’s revenue coming from the sale of their on-prem offering, GitHub Enterprise.  

Data privacy and security is also becoming a major issue, with Benioff himself even pushing for a U.S. privacy law on par with GDPR in the European Union. While consumer data is often the focus of such discussions, it’s worth remembering that SaaS providers store and process an incredible amount of personal data on behalf of their customers, and the content of that data goes well beyond email addresses for sales leads.

It’s time to reconsider the SaaS model in a modern context, integrating developments of the last nearly two decades so that enterprise software can reach its full potential. More specifically, we need to consider the impact of IaaS and “cloud-native computing” on enterprise software, and how they’re blurring the lines between SaaS and on-premises applications. As the world around enterprise software shifts and the tools for building it advance, do we really need such stark distinctions about what can run where?

Source: Getty Images/KTSDESIGN/SCIENCE PHOTO LIBRARY

The original cloud software thesis

In his book, Behind the Cloud, Benioff lays out four primary reasons for the introduction of the cloud-based SaaS model:

  1. Realigning vendor success with customer success by creating a subscription-based pricing model that grows with each customer’s usage (providing the opportunity to “land and expand”). Previously, software licenses often cost millions of dollars and were paid upfront, each year after which the customer was obligated to pay an additional 20 percent for support fees. This traditional pricing structure created significant financial barriers to adoption and made procurement painful and elongated.
  2. Putting software in the browser to kill the client-server enterprise software delivery experience. Benioff recognized that consumers were increasingly comfortable using websites to accomplish complex tasks. By utilizing the browser, Salesforce avoided the complex local client installation and allowed its software to be accessed anywhere, anytime and on any device.
  3. Sharing the cost of expensive compute resources across multiple customers by leveraging a multi-tenant architecture. This ensured that no individual customer needed to invest in expensive computing hardware required to run a given monolithic application. For context, in 1999 a gigabyte of RAM cost about $1,000 and a TB of disk storage was $30,000. Benioff cited a typical enterprise hardware purchase of $385,000 in order to run Siebel’s CRM product that might serve 200 end-users.
  4. Democratizing the availability of software by removing the installation, maintenance and upgrade challenges. Drawing from his background at Oracle, he cited experiences where it took 6-18 months to complete the installation process. Additionally, upgrades were notorious for their complexity and caused significant downtime for customers. Managing enterprise applications was a very manual process, generally with each IT org becoming the ops team executing a physical run-book for each application they purchased.

These arguments also happen to be, more or less, that same ones made by infrastructure-as-a-service (IaaS) providers such as Amazon Web Services during their early days in the mid-late ‘00s. However, IaaS adds value at a layer deeper than SaaS, providing the raw building blocks rather than the end product. The result of their success in renting cloud computing, storage and network capacity has been many more SaaS applications than ever would have been possible if everybody had to follow the model Salesforce did several years earlier.

Suddenly able to access computing resources by the hour—and free from large upfront capital investments or having to manage complex customer installations—startups forsook software for SaaS in the name of economics, simplicity and much faster user growth.

Source: Getty Images

It’s a different IT world in 2018

Fast-forward to today, and in some ways it’s clear just how prescient Benioff was in pushing the world toward SaaS. Of the four reasons laid out above, Benioff nailed the first two:

  • Subscription is the right pricing model: The subscription pricing model for software has proven to be the most effective way to create customer and vendor success. Years ago already, stalwart products like Microsoft Office and the Adobe Suite  successfully made the switch from the upfront model to thriving subscription businesses. Today, subscription pricing is the norm for many flavors of software and services.
  • Better user experience matters: Software accessed through the browser or thin, native mobile apps (leveraging the same APIs and delivered seamlessly through app stores) have long since become ubiquitous. The consumerization of IT was a real trend, and it has driven the habits from our personal lives into our business lives.

In other areas, however, things today look very different than they did back in 1999. In particular, Benioff’s other two primary reasons for embracing SaaS no longer seem so compelling. Ironically, IaaS economies of scale (especially once Google and Microsoft began competing with AWS in earnest) and software-development practices developed inside those “web scale” companies played major roles in spurring these changes:

  • Computing is now cheap: The cost of compute and storage have been driven down so dramatically that there are limited cost savings in shared resources. Today, a gigabyte of RAM is about $5 and a terabyte of disk storage is about $30 if you buy them directly. Cloud providers give away resources to small users and charge only pennies per hour for standard-sized instances. By comparison, at the same time that Salesforce was founded, Google was running on its first data center—with combined total compute and RAM comparable to that of a single iPhone X. That is not a joke.
  • Installing software is now much easier: The process of installing and upgrading modern software has become automated with the emergence of continuous integration and deployment (CI/CD) and configuration-management tools. With the rapid adoption of containers and microservices, cloud-native infrastructure has become the de facto standard for local development and is becoming the standard for far more reliable, resilient and scalable cloud deployment. Enterprise software packed as a set of Docker containers orchestrated by Kubernetes or Docker Swarm, for example, can be installed pretty much anywhere and be live in minutes.

Sourlce: Getty Images/ERHUI1979

What Benioff didn’t foresee

Several other factors have also emerged in the last few years that beg the question of whether the traditional definition of SaaS can really be the only one going forward. Here, too, there’s irony in the fact that many of the forces pushing software back toward self-hosting and management can be traced directly to the success of SaaS itself, and cloud computing in general:

  1. Cloud computing can now be “private”: Virtual private clouds (VPCs) in the IaaS world allow enterprises to maintain root control of the OS, while outsourcing the physical management of machines to providers like Google, DigitalOcean, Microsoft, Packet or AWS. This allows enterprises (like Capital One) to relinquish hardware management and the headache it often entails, but retain control over networks, software and data. It is also far easier for enterprises to get the necessary assurance for the security posture of Amazon, Microsoft and Google than it is to get the same level of assurance for each of the tens of thousands of possible SaaS vendors in the world.
  2. Regulations can penalize centralized services: One of the underappreciated consequences of Edward Snowden’s leaks, as well as an awakening to the sometimes questionable data-privacy practices of companies like Facebook, is an uptick in governments and enterprises trying to protect themselves and their citizens from prying eyes. Using applications hosted in another country or managed by a third party exposes enterprises to a litany of legal issues. The European Union’s GDPR law, for example, exposes SaaS companies to more potential liability with each piece of EU-citizen data they store, and puts enterprises on the hook for how their SaaS providers manage data.
  3. Data breach exposure is higher than ever: A corollary to the point above is the increased exposure to cybercrime that companies face as they build out their SaaS footprints. All it takes is one employee at a SaaS provider clicking on the wrong link or installing the wrong Chrome extension to expose that provider’s customers’ data to criminals. If the average large enterprise uses 1,000+ SaaS applications and each of those vendors averages 250 employees, that’s an additional 250,000 possible points of entry for an attacker.
  4. Applications are much more portable: The SaaS revolution has resulted in software vendors developing their applications to be cloud-first, but they’re now building those applications using technologies (such as containers) that can help replicate the deployment of those applications onto any infrastructure. This shift to what’s called cloud-native computing means that the same complex applications you can sign up to use in a multi-tenant cloud environment can also be deployed into a private data center or VPC much easier than previously possible. Companies like BigID, StackRox, Dashbase and others are taking a private cloud-native instance first approach to their application offerings. Meanwhile SaaS stalwarts like Atlassian, Box, Github and many others are transitioning over to Kubernetes driven, cloud-native architectures that provide this optionality in the future.  
  5. The script got flipped on CIOs: Individuals and small teams within large companies now drive software adoption by selecting the tools (e.g., GitHub, Slack, HipChat, Dropbox), often SaaS, that best meet their needs. Once they learn what’s being used and how it’s working, CIOs are faced with the decision to either restrict network access to shadow IT or pursue an enterprise license—or the nearest thing to one—for those services. This trend has been so impactful that it spawned an entirely new category called cloud access security brokers—another vendor that needs to be paid, an additional layer of complexity, and another avenue for potential problems. Managing local versions of these applications brings control back to the CIO and CISO.

Source: Getty Images/MIKIEKWOODS

The future of software is location agnostic

As the pace of technological disruption picks up, the previous generation of SaaS companies is facing a future similar to the legacy software providers they once displaced. From mainframes up through cloud-native (and even serverless) computing, the goal for CIOs has always been to strike the right balance between cost, capabilities, control and flexibility. Cloud-native computing, which encompasses a wide variety of IT facets and often emphasizes open source software, is poised to deliver on these benefits in a manner that can adapt to new trends as they emerge.

The problem for many of today’s largest SaaS vendors is that they were founded and scaled out during the pre-cloud-native era, meaning they’re burdened by some serious technical and cultural debt. If they fail to make the necessary transition, they’ll be disrupted by a new generation of SaaS companies (and possibly traditional software vendors) that are agnostic toward where their applications are deployed and who applies the pre-built automation that simplifies management. This next generation of vendors will more control in the hands of end customers (who crave control), while maintaining what vendors have come to love about cloud-native development and cloud-based resources.

So, yes, Marc Benioff and Salesforce were absolutely right to champion the “No Software” movement over the past two decades, because the model of enterprise software they targeted needed to be destroyed. In the process, however, Salesforce helped spur a cloud computing movement that would eventually rewrite the rules on enterprise IT and, now, SaaS itself.

Salesforce deepens data sharing partnership with Google

Last Fall at Dreamforce, Salesforce announced a deepening friendship with Google . That began to take shape in January with integration between Salesforce CRM data and Google Analytics 360 and Google BigQuery. Today, the two cloud giants announced the next step as the companies will share data between Google Analytics 360 and the Salesforce Marketing Cloud.

This particular data sharing partnership makes even more sense as the companies can share web analytics data with marketing personnel to deliver ever more customized experiences for users (or so the argument goes, right?).

That connection certainly didn’t escape Salesforce’s VP of product marketing, Bobby Jania. “Now, marketers are able to deliver meaningful consumer experiences powered by the world’s number one marketing platform and the most widely adopted web analytics suite,” Jania told TechCrunch.

Brent Leary, owner of the consulting firm CRM Essentials says the partnership is going to be meaningful for marketers. “The tighter integration is a big deal because a large portion of Marketing Cloud customers are Google Analytics/GA 360 customers, and this paves the way to more seamlessly see what activities are driving successful outcomes,” he explained.

The partnership involves four integrations that effectively allow marketers to round-trip data between the two platforms. For starters, consumer insights from both Marketing Cloud and Google Analytics 360, will be brought together into a single analytics dashboard inside Marketing Cloud. Conversely, Market Cloud data will be viewable inside Google Analytics 360 for attribution analysis and also to use the Marketing Cloud information to deliver more customized web experiences. All three of these integrations will be generally available starting today.

A fourth element of the partnership being announced today won’t be available in Beta until the third quarter of this year. “For the first time ever audiences created inside the Google Analytics 360 platform can be activated outside of Google. So in this case, I’m able to create an audience inside of Google Analytics 360 and then I’m able to activate that audience in Marketing Cloud,” Jania explained.

An audience is like a segment, so if you have a group of like-minded individuals in the Google analytics tool, you can simply transfer it to Salesforce Marketing Cloud and send more relevant emails to that group.

This data sharing capability removes a lot of the labor involved in trying to monitor data stored in two places, but of course it also raises questions about data privacy. Jania was careful to point out that the two platforms are not sharing specific information about individual consumers, which could be in violation of the new GDPR data privacy rules that went into effect in Europe at the end of last month.

“What we’re [we’re sharing] is either metadata or aggregated reporting results. Just to be clear there’s no personal identifiable data that is flowing between the systems so everything here is 100% GDPR-compliant,” Jania said.

But Leary says it might not be so simple, especially in light of recent data sharing abuses. “With Facebook having to open up about how they’re sharing consumer data with other organizations, companies like Salesforce and Google will have to be more careful than ever before about how the consumer data they make available to their corporate customers will be used by them. It’s a whole new level of scrutiny that has to be apart of the data sharing equation,” Leary said.

The announcements were made today at the Salesforce Connections conference taking place in Chicago this week.

Broadening education investments to full-stack solutions

As an education investor, one of my favorite sayings is that education is the next industry to be disrupted by technology, and has been for the past twenty years.

When I started my career at Warburg Pincus, I inherited a portfolio of technology companies that senior partners naively believed would solve major problems in our education system.

It would have worked out fine, of course, except for all the people. Teachers weren’t always interested in changing the way they taught. IT staff weren’t always capable of implementing new technologies. And schools weren’t always 100% rational in their purchasing decisions. And so while, given the size of the market, projections inexorably led to $100M companies, sales cycles stretched asymptotically and deals never seemed to close, particularly in K-12 education.

My current firm, University Ventures, began life in 2011 with the goal of funding the next wave of innovation in higher education. Much of our early work did revolve around technology, such as backing companies that helped universities develop and deploy online degree programs. But it turned out that in making traditional degree programs more accessible, we weren’t addressing the fundamental problem.

At the time, America was in the process of recovering from the Great Recession, and it was clear that students were facing twin crises of college affordability and post-college employability. The fundamental problem we needed to solve was to help individuals traverse from point A to point B, where point B is a good first job – or a better job – in a growing sector of the economy.

Once we embarked on this journey, we figured out that the education-to-employment missing link was in the “last mile” and conceptualized “last-mile training” as the logical bridge over the skills gap. Last-mile training has two distinct elements.

The first is training on the digital skills that traditional postsecondary institutions aren’t addressing, and that are increasingly listed in job descriptions across all sectors of the economy (and particularly for entry-level jobs). This digital training can be as extensive as coding, or as minimal as becoming proficient on a SaaS platform utilized for a horizontal function (e.g., Salesforce CRM) or for a particular role in an industry vertical. The second is reducing friction on both sides of the human capital equation: friction that might impede candidates from getting the requisite last-mile training (education friction), and friction on the employer side that reduces the likelihood of hire (hiring friction). Successful last-mile models absorb education and hiring friction away from candidates and employers, eliminating tuition and guaranteeing employment outcomes for candidates, while typically providing employers with the opportunity to evaluate candidates’ work before making hiring decisions. Today we have eight portfolio companies that take on risk themselves in order to reduce friction for candidates and employers.

The first clearly viable last-mile training model is the combination with staffing. Staffing companies are a promising investment target for our broadened focus because they have their finger on the pulse of the talent needs of their clients. Moreover, staffing in the U.S. is a $150B industry consisting of profitable companies looking to move up the value chain with higher margin, differentiated products.

Because fill rates on job reqs can be as low as 20% in some skill gap areas of technology and health care, there is no question that differentiation is required; many companies view staffing vendors as commodities because they continue to fish in the same small pool of talent, often serving up the exact same talent as competitors in response to reqs.

Adding last-mile training to staffing not only frees the supply of talent by providing purpose-trained, job-ready, inexpensive talent at scale, but also increases margins and accelerates growth. It is this potential that has prompted staffing market leader Adecco (market cap ~$12B) to acquire coding bootcamp leader General Assembly for $412.5M. The acquisition launches Adecco down a promising new growth vector combining last-mile training and staffing.

We believe that staffing is only the most obvious last-mile training model. Witness the rise of pathways to employment like Education at Work. Owned by the not-for-profit Strada Education Network, Education at Work operates call centers on the campuses of universities like University of Utah and Arizona State for the express purpose of providing last-mile training to students in sales and customer support roles. Clients can then hire proven talent once students graduate. Education at Work has hired over 2,000 students into its call centers since its inception in 2012.

Education at Work is the earliest example of what we call outsourced apprenticeships. For years policy makers have taken expensive junkets to Germany and Switzerland to view their vaunted apprenticeship models – ones we’ll never be able to replicate here for about a hundred different reasons. This week, Ivanka Trump’s Task Force on Apprenticeship Expansion submitted a report to the President with a “roadmap… for a new and more flexible apprenticeship model,” but no clear or compelling vision for scaling apprenticeships in America.

Outsourced apprenticeships are a uniquely American model for apprenticeships, where service providers like call centers, marketing firms, software development shops and others decide to differentiate not only based on services, but also based on provision of purpose-trained entry-level talent. Unlike traditional apprenticeship models, employers don’t need to worry about bringing apprentices on-site and managing them; in these models, apprentices sit at the service provider doing client work, proving their ability to do the job, reducing hiring friction with every passing day until they’re hired by clients.

America leads the world in many areas and outsourcing is one of them. Outsourced apprenticeships are an opportunity for America to leapfrog into leadership in alternative pathways to good jobs. All it will take is service providers to recognize that clients will welcome and pay for the additional value of talent provision. We foresee such models emerging across a range of industries and intend to invest in companies ideally positioned to launch them.

All of these next generation last-mile training businesses will deliver education and training – predominantly technical/digital training as well as soft-skills where employers also see a major gap. They’ll also be highly driven by technology; technology will be utilized to source, assess and screen talent – increasingly via methods that resemble science fiction more than traditional HR practices – as well as to match talent to employers and positions. But they’re not EdTech businesses as much as they are full-stack solutions for both candidates and employers: candidates receive guaranteed pathways to employment that are not only free – they’re paid to do it; and employers are able to ascertain talent and fit before hiring.

While last-mile solutions can help alleviate the student loan debt and underemployment plaguing Millennials (and which put Gen Z in similar peril), they also have the potential to serve two other important social purposes. The first is diversity.

Just as last-mile providers have their finger on the pulse of the skill needs of their clients, they can do the same for other needs, like diversity. Last-mile providers are sourcing and launching cohorts that directly address skill needs, as well as diversity needs.

The second is retraining and reskilling of older, displaced workers. For generations, college classrooms were the sole option provided to such workers. But we’re unlikely to engage those workers in greatest need of reskilling if college classrooms – environments where they were previously unsuccessful – are the sole, or even initial modality. As last-mile training models are in simulated or actual workplaces, they are much more accessible to displaced workers.

Finally, the emergence of last-mile full-stack solutions like outsourced apprenticeships raises the question of whether enterprises might not only seek to outsource entry-level hiring, but all hiring. Why even hire an experienced worker from outside the company if there’s an intermediary willing to source, assess and screen, upskill, match, and provide workers on a no-risk trial basis? As sourcing, screening, skill-building, and matching technologies become more advanced, why not offload the risk of a bad hire to an outsourced talent partner? Most employers would willingly pay a premium to reduce the risk of bad hires, or even mediocre hires. If the market does evolve in this direction, education investors with a full-stack focus have the potential to create value in every sector of the economy, making traditional investment categories of “edtech” seem not only naïve, but also quaint.

 

The formula behind San Francisco’s startup success

Why has San Francisco’s startup scene generated so many hugely valuable companies over the past decade?

That’s the question we asked over the past few weeks while analyzing San Francisco startup funding, exit, and unicorn creation data. After all, it’s not as if founders of Uber, Airbnb, Lyft, Dropbox and Twitter had to get office space within a couple of miles of each other.

We hadn’t thought our data-centric approach would yield a clear recipe for success. San Francisco private and newly public unicorns are a diverse bunch, numbering more than 30, in areas ranging from ridesharing to online lending. Surely the path to billion-plus valuations would be equally varied.

But surprisingly, many of their secrets to success seem formulaic. The most valuable San Francisco companies to arise in the era of the smartphone have a number of shared traits, including a willingness and ability to post massive, sustained losses; high-powered investors; and a preponderance of easy-to-explain business models.

No, it’s not a recipe that’s likely replicable without talent, drive, connections and timing. But if you’ve got those ingredients, following the principles below might provide a good shot at unicorn status.

First you conquer, then you earn

Losing money is not a bug. It’s a feature.

First, lose money until you’ve left your rivals in the dust. This is the most important rule. It is the collective glue that holds the narratives of San Francisco startup success stories together. And while companies in other places have thrived with the same practice, arguably San Franciscans do it best.

It’s no secret that a majority of the most valuable internet and technology companies citywide lose gobs of money or post tiny profits relative to valuations. Uber, called the world’s most valuable startup, reportedly lost $4.5 billion last year. Dropbox lost more than $100 million after losing more than $200 million the year before and more than $300 million the year before that. Even Airbnb, whose model of taking a share of homestay revenues sounds like an easy recipe for returns, took nine years to post its first annual profit.

Not making money can be the ultimate competitive advantage, if you can afford it.

Industry stalwarts lose money, too. Salesforce, with a market cap of $88 billion, has posted losses for the vast majority of its operating history. Square, valued at nearly $20 billion, has never been profitable on a GAAP basis. DocuSign, the 15-year-old newly public company that dominates the e-signature space, lost more than $50 million in its last fiscal year (and more than $100 million in each of the two preceding years). Of course, these companies, like their unicorn brethren, invest heavily in growing revenues, attracting investors who value this approach.

We could go on. But the basic takeaway is this: Losing money is not a bug. It’s a feature. One might even argue that entrepreneurs in metro areas with a more fiscally restrained investment culture are missing out.

What’s also noteworthy is the propensity of so many city startups to wreak havoc on existing, profitable industries without generating big profits themselves. Craigslist, a San Francisco nonprofit, may have started the trend in the 1990s by blowing up the newspaper classified business. Today, Uber and Lyft have decimated the value of taxi medallions.

Not making money can be the ultimate competitive advantage, if you can afford it, as it prevents others from entering the space or catching up as your startup gobbles up greater and greater market share. Then, when rivals are out of the picture, it’s possible to raise prices and start focusing on operating in the black.

Raise money from investors who’ve done this before

You can’t lose money on your own. And you can’t lose any old money, either. To succeed as a San Francisco unicorn, it helps to lose money provided by one of a short list of prestigious investors who have previously backed valuable, unprofitable Northern California startups.

It’s not a mysterious list. Most of the names are well-known venture and seed investors who’ve been actively investing in local startups for many years and commonly feature on rankings like the Midas List. We’ve put together a few names here.

You might wonder why it’s so much better to lose money provided by Sequoia Capital than, say, a lower-profile but still wealthy investor. We could speculate that the following factors are at play: a firm’s reputation for selecting winning startups, a willingness of later investors to follow these VCs at higher valuations and these firms’ skill in shepherding portfolio companies through rapid growth cycles to an eventual exit.

Whatever the exact connection, the data speaks for itself. The vast majority of San Francisco’s most valuable private and recently public internet and technology companies have backing from investors on the short list, commonly beginning with early-stage rounds.

Pick a business model that relatives understand

Generally speaking, you don’t need to know a lot about semiconductor technology or networking infrastructure to explain what a high-valuation San Francisco company does. Instead, it’s more along the lines of: “They have an app for getting rides from strangers,” or “They have an app for renting rooms in your house to strangers.” It may sound strange at first, but pretty soon it’s something everyone seems to be doing.

It’s not a recipe that’s likely replicable without talent, drive, connections and timing. 

list of 32 San Francisco-based unicorns and near-unicorns is populated mostly with companies that have widely understood brands, including Pinterest, Instacart and Slack, along with Uber, Lyft and Airbnb. While there are some lesser-known enterprise software names, they’re not among the largest investment recipients.

Part of the consumer-facing, high brand recognition qualities of San Francisco startups may be tied to the decision to locate in an urban center. If you were planning to manufacture semiconductor components, for instance, you would probably set up headquarters in a less space-constrained suburban setting.

Reading between the lines of red ink

While it can be frustrating to watch a company lurch from quarter to quarter without a profit in sight, there is ample evidence the approach can be wildly successful over time.

Seattle’s Amazon is probably the poster child for this strategy. Jeff Bezos, recently declared the world’s richest man, led the company for more than a decade before reporting the first annual profit.

These days, San Francisco seems to be ground central for this company-building technique. While it’s certainly not necessary to locate here, it does seem to be the single urban location most closely associated with massively scalable, money-losing consumer-facing startups.

Perhaps it’s just one of those things that after a while becomes status quo. If you want to be a movie star, you go to Hollywood. And if you want to make it on Wall Street, you go to Wall Street. Likewise, if you want to make it by launching an industry-altering business with a good shot at a multi-billion-dollar valuation, all while losing eye-popping sums of money, then you go to San Francisco.

Zuora’s IPO is another step in golden age of enterprise SaaS

Zuora’s founder and CEO Tien Tzuo had a vision of a subscription economy long before most people ever considered the notion. He knew that for companies to succeed with subscriptions, they needed a bookkeeping system that understood how they collected and reported money. The company went public yesterday, another clear sign post on the road to SaaS maturation.

Tzuo was an early employee at Salesforce and their first CMO. He worked there in the early days in the late 90s when Salesforce’s Marc Benioff famously rented an apartment to launch the company. Tzuo was at Salesforce 9 years, and it helped him understand the nature of subscription-based businesses like Salesforce.

“We created a great environment for building, marketing and delivering software. We rewrote the rules, the way it was built, marketed and sold,” Tzuo told me in an interview in 2016.

He saw a fundamental problem with traditional accounting methods, which were designed for selling a widget and declaring the revenue. A subscription was an entirely different model and it required a new way to track revenue and communicate with customers. Tzuo took the long view when he started his company in early 2007, leaving a secure job at a growing company like Salesforce.

He did it because he had the vision, long before anyone else, that SaaS companies would require a subscription bookkeeping system, but before long, so would other unrelated businesses.

Building a subscription system

As he put it in that 2016 interview, if you commit to pay me $1 for 10 years, you know that $1 was coming in come hell or high water, that’s $10 I know I’m getting, but I can’t declare the money until I get it. That recurring revenue still has value though because my investors know that I’m secure for 10 years, even though it’s not on the books yet. That’s where Zuora came in. It could account for that recurring revenue when nobody else could. What’s more, it could track the billing over time, and send out reminders, help the companies stay engaged with their customers.

Photo: Lukas Kurka/Getty Images

As Ray Wang, founder and principal analyst at Constellation Research put it, they pioneered the whole idea of a subscription economy, and not just for SaaS companies. Over the last several years, we’ve heard companies talking about selling services and SLAs (service/uptime agreements) instead of a one-time sale of an item, but not that long ago it wasn’t something a lot of companies were thinking about.

“They pioneered how companies can think about monetization,” Wang said. “So large companies like a GE could go from selling a wind turbine one time to selling a subscription to deliver a certain number of Kw/hr of green energy at peak hours from 1 to 5 pm with 98 percent uptime.” There wasn’t any way to do this before Zuora came along.

Jason Lemkin, founder at SaaStr, a firm that invests in SaaS startups, says Tzuo was a genuine visionary and helped create the underlying system for SaaS subscriptions to work. “The most interesting part of Zuora is that it is a “second” order SaaS play. It could only thrive once SaaS became mainstream, and could only scale on top of other recurring revenue businesses. Zuora started off as a niche player helping SaaS companies do billing, and it dramatically expanded and thrived as SaaS became … Software.”

Market catches up with idea

When he launched the company in 2007, perhaps he saw that extension of his idea out on the distant horizon. He certainly saw companies like Salesforce needing a service like the one he had decided to create. The early investors must have recognized that his vision was early and it would take a slow, steady climb on the way to exiting. It took 11 years and $242 million in venture capital before they saw the payoff. The revenue after 11 years was a reported $167 million. There is plenty of room to grow.

But yesterday the company had its initial public offering, and it was by any measure a huge success. According TechCrunch’s Katie Roof, “After pricing its IPO at $14 and raising $154 million, the company closed at $20, valuing the company around $2 billion.” Today it was up a bit more as of this writing.

When you consider the Tzuo’s former company has become a $10 billion company, that companies like Box, Zendesk, Workday and Dropbox have all gone public, and others like DocuSign and Smartsheet are not far behind, it’s pretty clear that we are in a golden age of SaaS — and chances are it’s only going to get better.

Salesforce is working on a blockchain product

Salesforce has always been a company that is looking ahead to the next big technology, whether that was mobile, social, internet of things or artificial intelligence. In an interview with Business Insider’s Julie Bort at the end of March, Salesforce co-founders Marc Benioff and Parker Harris talked about a range of subjects including how the company came to be working on one of the next hot technologies, a blockchain product.

Benioff told a story of being at the World Economic Forum in Switzerland where a bit of serendipity led him to start thinking about blockchain and how it could be used as part of the Salesforce family of products.

As it turned out, there was a crypto conference going on at the same time as the WEF and the two worlds collided at a Salesforce event at the Intercontinental Hotel. While there, one of the crypto conference attendees engaged Benioff in a conversation and it was the start of something.

“I had been thinking a lot about what is Salesforce’s strategy around blockchain, and what is Salesforce’s strategies around cryptocurrencies and how will we relate to all of these things,” Benioff said. He is actually a big believer in the power of serendipity, and he said just by having that conversation, it started him down the road to thinking more seriously about Salesforce’s role in this developing technology.

He said the more he thought about it, the more he believed that Salesforce could make use of Blockchain. Then suddenly something clicked for him and he saw a way to put blockchain and cryptocurrencies to work in Salesforce. “That’s kind of how it works and I hope by Dreamforce we will have a blockchain and cryptocurrency solution.”

Benioff is clearly a visionary and says a lot of that comes from simply paying attention as he did when he talked to this person in Davos, and recognizing an opportunity to expand Salesforce in a meaningful way. “A lot [these ideas] comes from paying attention, listening. There’s new ideas coming all the time,” he said. He recognizes that there are more ideas out there than they can possibly execute, but part of his job is understanding which ones are the most important for Salesforce customers.

Blockchain is the electronic ledger used to track Bitcoin or other digital currencies, but it also has a more general business role. As an irrefutable and immutable record, it can track just about anything of value.

Dreamforce is Salesforce’s enormous annual customer conference. It will be held this year from September 25-28 in San Francisco, and if it all works as planned, they could be announcing a blockchain product this year.

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Check out the whole interview between Salesforce founders Parker Harris and Marc Benioff and Julie Bort from Business Insider:

Salesforce is buying MuleSoft at enterprise value of $6.5 billion

Salesforce today announced that it intends to buy MuleSoft in a deal valued at a whopping $6.5 billion. That’s not the selling price, but the amount the company has been valued at based on stocks, bonds and cash on hand. The exact price was not available yet, but the company did indicate it was paying 44.89 per share for Mulesoft, a price that represents 36 percent premium over yesterday’s closing price, according to Salesforce .

What’s more, the deal values each MuleSoft share at $36 in cash and 0.0711 shares of Salesforce common stock.

Rumors began swirling this morning after a story broke by Reuters that the CRM giant was interested in MuleSoft, which launched in 2006, and went public almost exactly a year ago.  It gives Salesforce a mature company to add to its arsenal with 1200 customers. It also gives them an API integration engine that should help the company access data across organizations regardless of where it lives.

This is particularly important for Salesforce, which tends to come in and work with a company across enterprise systems. As it builds out its artificial intelligence and machine learning layer, which it has branded as Einstein, it needs access to data across the company. A company like MuleSoft gives them that.

But of course, Salesforce gets more than tech with this purchase, which it can integrate into its growing family of products. It also gets major customers like Coca-Cola, VMware, GE, Accenture, Airbus, AT&T and Cisco. While Salesforce may have a presence already in some of these companies already, Mulesoft gives them entree into areas they might not have had and gives them the ability to expand that presence.

What’s more, the company has big revenue goals. Having reached $10 billion in revenue faster than any software company ever has, a point that Chairman and co-founder Marc Benioff has been happy to make, they have actually set their sites on $60 billion by 2034. That’s a long way away, of course, but having a company like MuleSoft in the fold, which made $300 million in revenue will certainly help.

Ray Wang, founder and principal analyst at Constellation Research says this about building a microservices future, Microservices are a way of building applications made up of small, distinct pieces, rather than a single, monolithic application we tended to build in the past. This makes changing and updating easier and more efficient.

“This is the heart of Salesforce’s M&A strategy. They have to integrate, orchestrate, and manage microservices in their future roadmap,” he said.

This is a developing story.

Late-blooming startups can still thrive

It seems like startup news is full of overnight success stories and sudden failures, like the scooter rental company that went from zero to a $300 million valuation in months or the blood-testing unicorn that went from billions to nearly naught.

But what about those other companies that mature more gradually? Is there such a thing as slow and successful in startup-land?

To contemplate that question, Crunchbase News set out to assemble a data set of top late-blooming startups. We looked at companies that were founded in or before 2010 that raised large amounts of capital after 2015, and we also looked at companies founded a least five years ago that raised large early-stage funds in the last year. (For more details on the rules we used to select the companies, check “Data Methods” at the end of the post.)

The exercise was a counterpoint to a data set we did a couple of weeks ago, looking at characteristics of the fastest growing startups by capital raised. For that list, we found plenty of similarities between members, including a preponderance of companies in a few hot sectors, many famous founders and a lot of cancer drug developers.

For the late bloomers, however, patterns were harder to pinpoint. The breakdown wasn’t too different from venture-backed companies overall. Slower-growing companies could come from major venture hubs as well as cities with smaller startup ecosystems. They could be in biotech, medical devices, mobile gaming or even meditation.

What we did find, however, was an interesting and inspiring collection of stories for those of us who’ve been toiling away at something for a long time, with hopes still of striking it big.

Pivots and patience

Even youthful startups have been known to make a major pivot or two. So it’s not surprising to see a lot of pivots among late bloomers that have had more time to tinker with their business models.

One that fits this mold is Headspace, provider of a popular meditation app. The company, founded in 2010 by a British-born Buddhist monk with a degree in circus arts, started as a meditation-focused events startup. But it turned out people wanted to build on their learning on their own time, so Headspace put together some online lessons. Today, Santa Monica-based Headspace has millions of users and has raised $75 million in venture funding.

For late bloomers, the pivot can mean going from a model with limited scalability to one that can attract a much wider audience. That’s the case with Headspace, which would have been limited in its events business to those who could physically show up. Its online model, with instant, global reach, turns the business into something venture investors can line up behind.

Sometimes your sector becomes hip

They say if you wait long enough, everything comes back in style. That mantra usually works as an excuse for hoarding ’80s clothes in the attic. But it also can apply to entrepreneurial companies, which may have launched years before their industry evolved into something venture investors were competing to back.

Take Vacasa, the vacation rental management provider. The company has been around since 2009, but it began raising VC just a couple of years ago amid a broad expansion of its staff and property portfolio. The Portland-based company has raised more than $140 million to date, all of it after 2016, and most in a $103 million October round led by technology growth investor Riverwood Capital.

CloudCraze, which was acquired by Salesforce earlier this week, also took a long time to take venture funding. The Chicago-based provider of business-to-business e-commerce software launched in 2009, but closed its first VC round in 2015, according to Crunchbase records. Prior to the acquisition, the company raised about $30 million, with most of that coming in just a year ago.

Meanwhile, some late bloomers have always been fashionable, just not necessarily as VC-funded companies. Untuckit, a clothing retailer that specializes in button-down shirts that look good untucked, had been building up its business since 2011, but closed its first venture round, a Series A led by VC firm Kleiner Perkins, last June.

Slow-growing venture-backed startups are still not that common

So yes, there is still capital available for those who wait. However, the truth of the matter is most companies that raise substantial sums of venture capital secure their initial seed rounds within a couple years of founding. Companies that chug along for five-plus years without a round and then scale up are comparatively rare.

That said, our data set, which looks at venture and seed funding, does not come close to capturing the full ecosystem of slow-growing startups. For one, many successful bootstrapped companies could raise venture funding but choose not to. And those who do eventually decide to take investment may look at other sources, like private equity, bank financing or even an IPO.

Additionally, the landscape is full of slow-growing startups that do make it, just not in a venture home run exit kind of way. Many stay local, thriving in the places they know best.

On the flip side, companies that wait a long time to take VC funding have also produced some really big exits.

Take Atlassian, the provider of workplace collaboration tools. Founded in 2002, the Australian company waited eight years to take its first VC financing, despite plentiful offers. It went public two years ago, and currently has a market valuation of nearly $14 billion.

The moral: Those who take it slow can still finish ahead.

Data methods

We primarily looked at companies founded in 2010 or earlier in the U.S. and Canada that raised a seed, Series A or Series B round sometime after the beginning of last year, and included some that first raised rounds in 2015 or later and went on to substantial fundraises. We also looked at companies founded in 2012 or earlier that raised a seed or Series A round after the beginning of last year and have raised $30 million or more to date. The list was culled further from there.

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