EC Enterprise Applications
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Don’t hate on low-code and no-code
As far as I can tell, low-code and no-code services are rapidly proving that prior models for products as broad as enterprise app creation and AI-powered data analytics were lackluster. My evidence? A mix of public- and private-market low- and no-code companies are putting up impressive results.
The Exchange caught up with Appian CEO Matt Calkins after his enterprise app software company reported its first-quarter performance to discuss the low-code market and what he’s hearing in customer meetings. To round out our general thesis — and shore up our somewhat bratty headline — we’ve compiled a list of recent low-code and no-code venture capital rounds, of which there are many.
As we’ll show, the pace at which venture capitalists are putting funds into companies that fall into our two categories is pretty damn rapid, which implies that they are doing well as a cohort. We can infer as much because it has become clear in recent quarters that while today’s private capital market is stupendous for some startups, it’s harder than you’d think for others.
The Exchange explores startups, markets and money.
Read it every morning on Extra Crunch or get The Exchange newsletter every Saturday.
The dividing factor? Signs of impressive present-day traction: Startups that are growing very fast have nearly unlimited access to capital, while those that are growing at merely fast rates are often finding it difficult to find a dance partner.
So if we can show that a huge, diverse set of no-code and low-code startups are raising oodles of capital, we can infer something relatively sturdy about market demand for their products. (It also doesn’t hurt that no-code automation service Zapier is growing like a weed and has reached IPO scale. In other news, Appian just dropped a new version of its low-code automation platform, for whatever that is worth.)
First Appian’s CEO, then a venture capital roundup. This should be fun.
Public performance
Briefly, Appian reported $88.9 million in Q1 2021 revenue, of which $39.1 million came from its cloud subscription business. The latter figure rose 38% in the quarter compared to the year-ago period. Appian also swung to adjusted EBITDA profit in the period. Investors responded by hammering the company’s stock in the wake of the results. From an April share-price range in the mid-$130s, Appian is now trading in the mid-$80s, though only some of those declines came post-earnings.
But the company’s stock price is only so important. Precisely how conservative any one public company’s guidance is for the current year and how those forecasts play with investor expectations during a period of generally excessive valuations is not our game. What does matter is what the company’s CEO had to say about the low-code space itself.
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SaaS companies can grow to $20M+ ARR by selling exclusively to developers
With more than 200,000 customers, a market cap of nearly $56 billion, and the recent acquisition of Segment for $3.2 billion, Twilio is a SaaS behemoth.
It’s hard to imagine companies like Twilio as anything but a giant. But everybody starts out small, and you can usually trace success back to key decisions made in the early days.
First, you need to have a product that developers can actually sign up for. This means ditching demos for real-time free trials or freemium tools.
For Twilio, a big differentiator was being one of the first technology-focused SaaS organizations that focused on empowering and building for the end user (which in their case is developers) with a self-service function. Another differentiator was, the executive team designed the organization to create tight feedback loops between sales and product with national roadshows, during which CEO Jeff Lawson frequently met with users.
Moreover, Twilio’s “secret sauce” per their S-1 is a developer-focused model and a strong belief in the future of software. They encourage developers to explore and innovate with Twilio’s flexible offering, which led to an incredible 155% net-dollar expansion rate at the time of the IPO.
Most importantly, Twilio put the product in the hands of teams before the sale happened, standing by to answer hard questions about how Twilio would fit into their infrastructure. This was pretty rare at the time — sales engineering resources aren’t cheap — and it was a strong differentiating factor. So much so that when the company went public, they were growing at 106% annually.
Twilio sells to developers at large enterprises by solving a problem that developers come up against regularly: Getting in touch with customers.
But as more successful public software companies emerge, it’s clear that Twilio’s secret sauce can and will be replicated.
Why traditional marketing doesn’t work on developers
Before I started looking at successful developer-focused businesses, I understood the developer-focused playbook to look a little like this:
- Don’t hire marketing (or sales, either). If you do, hire someone super experienced from an enterprise sales background. And then fire them within three to six months.
- Just hire someone who’s passionate about the product to “manage the community.” What is community management? Lots of swag. Cool meetups. Publish 1–2 articles as a stab at content (bonus points if they’re listicles). Oh, wait. How can we show the ROI here? Make the community manager do that until she quits. Repeat.
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The Expensify EC-1
Let’s make it clear from the outset that this story is about an expense management SaaS business called Expensify. As you’d expect, yes, this is about the expense management market and how Expensify has grown, its technology and all of that. Normally, that would make us change the channel. But this is also a story about pirates; peer-to-peer hackers who asked, “Why not work from Thailand and dozens of countries across the globe?” and actually did it using P2P hacker culture as a model for consensus-driven decision-making — all with pre-Uber Travis Kalanick in a guest-starring role.
Most interestingly, this is a story about just not giving a damn about what anyone goddamn thinks, an approach to life and business that led to more than $100 million in annual revenue, and an IPO incoming on what looks to be a very quick timetable. Prodigious revenues, 10 million users and only 130 employees running the whole shebang — that’s a hell of an achievement in only 13 years.
If you’re going a bit “WTF,” well, we’d concur. Expensify is as contradictory as they come in the enterprise world. It’s managed to take what might well be the most boring part of the corporate business stack and turn it into something special. It doesn’t borrow its culture from other startups, it built its own tech stack from the ground up, and even hires in a completely radical way. Oh, and no one really has job titles either, because why the hell bother with hierarchy anyway? They’re pirates after all.
If expense management is about avoiding corporate plunder, then letting the pirates and hackers run the ship is probably the best approach. And now, Expensify is plundering the corporate spend world one travel ticket and business meal at a time just as the world is rebuilding in the wake of COVID-19.
TechCrunch’s writer and analyst for this EC-1 is Anna Heim. Heim is a tech journalist and former startup founder who has written for different tech publications since 2011. She recently joined Extra Crunch as a daily reporter, where she will be sharing insights on startups, particularly in SaaS. The lead editor of this package was Ram Iyer, the series editor was Danny Crichton, the copy editor was Richard Dal Porto, and original illustrations were created by Nigel Sussman with art direction from Bryce Durbin.
Expensify had no say in the content of this analysis and did not get advance access to it. Heim has no financial ties to Expensify or other conflicts of interest to disclose.
The Expensify EC-1 will be a serialized sequence of five articles published over the course of the coming weeks. We interviewed the company in February and March, well before the company announced a confidential filing of its S-1 to the SEC. Let’s take a look:
- Part 1: Origin story “How a band of P2P hackers planted the seeds of a unique expense management giant” (2,400 words/10 minutes) — Explores the colorful history of the Expensify founders’ days with Travis Kalanick’s venture before Uber, a P2P content distribution startup called Red Swoosh, and how that experience would eventually influence what would one day become an expense management giant.
- Parts 2-5: Upcoming shortly.
We’re always iterating on the EC-1 format. If you have questions, comments or ideas, please send an email to TechCrunch Managing Editor Danny Crichton at danny@techcrunch.com.
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How a band of P2P hackers planted the seeds of a unique expense management giant
Individuality often has no place in the enterprise software space. In a market where a single contract can easily run into the millions, homogeneity is the herald of reliability and serves to reassure buyers of the worth of their potential purchase.
So it’s natural to think a company in the expense report management business would keep it simple and play it by the book. But one look at Expensify is enough to tell you that this is a company that never even looked for the book.
Expensify’s origin story is one of a scrappy group of developers who turned travel into a catalyst for ideas and stuck together through highs and lows, ending up building one of the most unexpectedly original companies in enterprise software today.
Right from its famous “workcations,” to its management structure and its decision-making policies, Expensify has it in its DNA to eschew so-called best practices for its own ideas — a philosophy rooted in its founder and early team’s P2P hacker background and do-it-yourself attitude. As a result, Expensify is atypical of startups in many ways, inside and out.
Founder and CEO David Barrett made it clear his company was different in our first call itself: “We hire in a super different way. We have a very unusual internal management structure. Our business model itself is very unusual. We don’t have any salespeople, for example. We’re an incredibly small company. We focus on the employees over the bosses. Our technology stack is completely different. Our approach toward product design is very different.”
That description would make some people call Expensify weird even by startup standards, but this essential difference has set it apart in a space dominated by giants such as SAP Concur and Coupa. And that’s ultimately been to its benefit: Expensify reached $100 million in annual recurring revenue in 2020, with hefty 25% EBITDA margins to boot. There were also rumors of the company planning to go public during our interviews for this EC-1, but they stopped speaking to us in March, and now we know why: Expensify confidentially filed to go public on May 3.
Expensify’s origin story is one of a scrappy group of developers who turned travel into a catalyst for ideas and stuck together through highs and lows, ending up building one of the most unexpectedly original companies in enterprise software today.
When David met Travis …
To truly understand Expensify, you first need to take a close look at a unique, short-lived, P2P file-sharing company called Red Swoosh, which was Travis Kalanick’s startup before he founded Uber. Framed by Kalanick as his “revenge business” after his previous P2P startup Scour was sued into oblivion for copyright infringement, Red Swoosh would be the precursor for Expensify’s future culture and ethos. In fact, many of Expensify’s initial team actually met at Red Swoosh, which was eventually acquired by Akamai Technologies in 2007 for $18.7 million.
Barrett, a self-proclaimed alpha geek and lifelong software engineer, was actually Red Swoosh’s last engineering manager, hired after the failure of his first project, iGlance.com, a P2P push-to-talk program that couldn’t compete against Skype. “While I was licking my wounds from that experience, I was approached by Travis Kalanick who was running a startup called Red Swoosh,” he recalled in an interview.
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Analytics as a service: Why more enterprises should consider outsourcing
With an increasing number of enterprise systems, growing teams, a rising proliferation of the web and multiple digital initiatives, companies of all sizes are creating loads of data every day. This data contains excellent business insights and immense opportunities, but it has become impossible for companies to derive actionable insights from this data consistently due to its sheer volume.
According to Verified Market Research, the analytics-as-a-service (AaaS) market is expected to grow to $101.29 billion by 2026. Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights. Through AaaS, managed services providers (MSPs) can help organizations get started on their analytics journey immediately without extravagant capital investment.
MSPs can take ownership of the company’s immediate data analytics needs, resolve ongoing challenges and integrate new data sources to manage dashboard visualizations, reporting and predictive modeling — enabling companies to make data-driven decisions every day.
AaaS could come bundled with multiple business-intelligence-related services. Primarily, the service includes (1) services for data warehouses; (2) services for visualizations and reports; and (3) services for predictive analytics, artificial intelligence (AI) and machine learning (ML). When a company partners with an MSP for analytics as a service, organizations are able to tap into business intelligence easily, instantly and at a lower cost of ownership than doing it in-house. This empowers the enterprise to focus on delivering better customer experiences, be unencumbered with decision-making and build data-driven strategies.
Organizations that have not started on their analytics journey or are spending scarce data engineer resources to resolve issues with analytics implementations are not identifying actionable data insights.
In today’s world, where customers value experiences over transactions, AaaS helps businesses dig deeper into their psyche and tap insights to build long-term winning strategies. It also enables enterprises to forecast and predict business trends by looking at their data and allows employees at every level to make informed decisions.
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What can the OKR software sector tell us about startup growth more generally?
In the never-ending stream of venture capital funding rounds, from time to time, a group of startups working on the same problem will raise money nearly in unison. So it was with OKR-focused startups toward the start of 2020.
How were so many OKR-focused tech upstarts able to raise capital at the same time? And was there really space in the market for so many different startups building software to help other companies manage their goal-setting? OKRs, or “objectives and key results,” a corporate planning method, are no longer a niche concept. But surely, over time, there would be M&A in the group, right?
During our first look into the cohort, we concluded that it felt likely that there was “some consolidation” ahead for the group “when growth becomes more difficult.” At the time, however, it was clear that many founders and investors expected the OKR software market to have material depth.
They were right, and we were wrong. A year later, in early 2021, we asked the same group how their previous year had gone. Nearly every single company had a killer year, with many players growing by well over 100%.
The Exchange explores startups, markets and money. Read it every morning on Extra Crunch or get The Exchange newsletter every Saturday.
OKR company Ally.io grew 3.3x in 2020, for example, while its competitor Gtmhub grew by 3x over the same time period. More capital followed. Ally.io raised $50 million in a Series C in the first quarter, while Gtmhub put together a $30 million Series B during the same period.
They won’t be the final startups in the OKR cohort to raise this year. We know this because we reached out to the group again this week, this time probing their Q1 performance, and, critically, asking the startups to discuss their level of optimism regarding the rest of 2021.
As before, the group’s recent results are strong, at least when compared to their own planning. But notably, the collection of competing companies is more optimistic than before about the rest of the year than they were before Q1 2021. Things are heating up for the OKR startup world.
A takeaway from our work today is that our prior notes about how impressively deep the software market is proving to be may have been too modest. And frankly, that’s super-good news for startups and investors alike. So much for SaaS-fatigue.
In a sense, we should not be surprised that OKR startups are doing well or that the startup software market is so large. You’d imagine that the historic pace of venture capital investment that we’ve seen so far in 2021 in Europe and the United States was based on results, or evidence that there was lots more room for software-focused startups to grow.
Interestingly, while these companies look similar to outsiders, they are each betting on strategies and differentiators that could help them win in their selected portion of the OKR space. Which also means that the sector may not be as crowded as it seems.
Don’t take our word for it. Let’s hear from Gtmhub COO Seth Elliott, Workboard CEO and co-founder Deidre Paknad, Koan CEO and co-founder Matt Tucker, Ally.io CEO and co-founder Vetri Vellore, and Perdoo CEO and founder Henrik-Jan van der Pol about just what the software market looks like to them.
We’ll start with how the startups performed in Q1 2021, dig into how they feel about the rest of the year, and then talk about how differentiation among the cohort could be helping them not step on each other’s toes.
Rapid growth
WorkBoard is having a strong start to 2021. Paknad’s company, which raised in both March of 2019 and January of 2020, told The Exchange that it hired 82 people in the first three months of 2021, and that it plans on doing it again in the current quarter. WorkBoard is “investing heavily,” Paknad said via DM, and “made [its] Q1 targets.”
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5 emerging use cases for productivity infrastructure in 2021
When the world flipped upside down last year, nearly every company in every industry was forced to implement a remote workforce in just a matter of days — they had to scramble to ensure employees had the right tools in place and customers felt little to no impact. While companies initially adopted solutions for employee safety, rapid response and short-term air cover, they are now shifting their focus to long-term, strategic investments that empower growth and streamline operations.
As a result, categories that make up productivity infrastructure — cloud communications services, API platforms, low-code development tools, business process automation and AI software development kits — grew exponentially in 2020. This growth was boosted by an increasing number of companies prioritizing tools that support communication, collaboration, transparency and a seamless end-to-end workflow.
Productivity infrastructure is on the rise and will continue to be front and center as companies evaluate what their future of work entails and how to maintain productivity, rapid software development and innovation with distributed teams.
According to McKinsey & Company, the pandemic accelerated the share of digitally enabled products by seven years, and “the digitization of customer and supply-chain interactions and of internal operations by three to four years.” As demand continues to grow, companies are taking advantage of the benefits productivity infrastructure brings to their organization both internally and externally, especially as many determine the future of their work.
Automate workflows and mitigate risk
Developers rely on platforms throughout the software development process to connect data, process it, increase their go-to-market velocity and stay ahead of the competition with new and existing products. They have enormous amounts of end-user data on hand, and productivity infrastructure can remove barriers to access, integrate and leverage this data to automate the workflow.
Access to rich interaction data combined with pre-trained ML models, automated workflows and configurable front-end components enables developers to drastically shorten development cycles. Through enhanced data protection and compliance, productivity infrastructure safeguards critical data and mitigates risk while reducing time to ROI.
As the post-pandemic workplace begins to take shape, how can productivity infrastructure support enterprises where they are now and where they need to go next?
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As UiPath closes above its final private valuation, CFO Ashim Gupta discusses his company’s path to market
After an upward revision, UiPath priced its IPO last night at $56 per share, a few dollars above its raised target range. The above-range price meant that the unicorn put more capital into its books through its public offering.
For a company in a market as competitive as robotic process automation (RPA), the funds are welcome. In fact, RPA has been top of mind for startups and established companies alike over the last year or so. In that time frame, enterprise stalwarts like SAP, Microsoft, IBM and ServiceNow have been buying smaller RPA startups and building their own, all in an effort to muscle into an increasingly lucrative market.
In June 2019, Gartner reported that RPA was the fastest-growing area in enterprise software, and while the growth has slowed down since, the sector is still attracting attention. UIPath, which Gartner found was the market leader, has been riding that wave, and today’s capital influx should help the company maintain its market position.
It’s worth noting that when the company had its last private funding round in February, it brought home $750 million at an impressive valuation of $35 billion. But as TechCrunch noted over the course of its pivot to the public markets, that round valued the company above its final IPO price. As a result, this week’s $56-per-share public offer wound up being something of a modest down-round IPO to UiPath’s final private valuation.
Then, a broader set of public traders got hold of its stock and bid its shares higher. The former unicorn’s shares closed their first day’s trading at precisely $69, above the per-share price at which the company closed its final private round.
So despite a somewhat circuitous route, UiPath closed its first day as a public company worth more than it was in its Series F round — when it sold 12,043,202 shares sold at $62.27576 apiece, per SEC filings. More simply, UiPath closed today worth more per-share than it was in February.
How you might value the company, whether you prefer a simple or fully-diluted share count, is somewhat immaterial at this juncture. UiPath had a good day.
While it’s hard to know what the company might do with the proceeds, chances are it will continue to try to expand its platform beyond pure RPA, which could become market-limited over time as companies look at other, more modern approaches to automation. By adding additional automation capabilities — organically or via acquisitions — the company can begin covering broader parts of its market.
TechCrunch spoke with UiPath CFO Ashim Gupta today, curious about the company’s choice of a traditional IPO, its general avoidance of adjusted metrics in its SEC filings, and the IPO market’s current temperature. The final question was on our minds, as some companies have pulled their public listings in the wake of a market described as “challenging”.
Why did UiPath not direct list after its huge February raise?
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Data scientists: Bring the narrative to the forefront
By 2025, 463 exabytes of data will be created each day, according to some estimates. (For perspective, one exabyte of storage could hold 50,000 years of DVD-quality video.) It’s now easier than ever to translate physical and digital actions into data, and businesses of all types have raced to amass as much data as possible in order to gain a competitive edge.
However, in our collective infatuation with data (and obtaining more of it), what’s often overlooked is the role that storytelling plays in extracting real value from data.
The reality is that data by itself is insufficient to really influence human behavior. Whether the goal is to improve a business’ bottom line or convince people to stay home amid a pandemic, it’s the narrative that compels action, rather than the numbers alone. As more data is collected and analyzed, communication and storytelling will become even more integral in the data science discipline because of their role in separating the signal from the noise.
Data alone doesn’t spur innovation — rather, it’s data-driven storytelling that helps uncover hidden trends, powers personalization, and streamlines processes.
Yet this can be an area where data scientists struggle. In Anaconda’s 2020 State of Data Science survey of more than 2,300 data scientists, nearly a quarter of respondents said that their data science or machine learning (ML) teams lacked communication skills. This may be one reason why roughly 40% of respondents said they were able to effectively demonstrate business impact “only sometimes” or “almost never.”
The best data practitioners must be as skilled in storytelling as they are in coding and deploying models — and yes, this extends beyond creating visualizations to accompany reports. Here are some recommendations for how data scientists can situate their results within larger contextual narratives.
Make the abstract more tangible
Ever-growing datasets help machine learning models better understand the scope of a problem space, but more data does not necessarily help with human comprehension. Even for the most left-brain of thinkers, it’s not in our nature to understand large abstract numbers or things like marginal improvements in accuracy. This is why it’s important to include points of reference in your storytelling that make data tangible.
For example, throughout the pandemic, we’ve been bombarded with countless statistics around case counts, death rates, positivity rates, and more. While all of this data is important, tools like interactive maps and conversations around reproduction numbers are more effective than massive data dumps in terms of providing context, conveying risk, and, consequently, helping change behaviors as needed. In working with numbers, data practitioners have a responsibility to provide the necessary structure so that the data can be understood by the intended audience.
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RPA market surges as investors, vendors capitalize on pandemic-driven tech shift
When UIPath filed its S-1 last week, it was a watershed moment for the robotic process automation (RPA) market. The company, which first appeared on our radar for a $30 million Series A in 2017, has so far raised an astonishing $2 billion while still private. In February, it was valued at $35 billion when it raised $750 million in its latest round.
RPA and process automation came to the fore during the pandemic as companies took steps to digitally transform. When employees couldn’t be in the same office together, it became crucial to cobble together more automated workflows that required fewer people in the loop.
RPA has enabled executives to provide a level of workflow automation that essentially buys them time to update systems to more modern approaches while reducing the large number of mundane manual tasks that are part of every industry’s workflow.
When UIPath raised money in 2017, RPA was not well known in enterprise software circles even though it had already been around for several years. The category was gaining in popularity by that point because it addressed automation in a legacy context. That meant companies with deep legacy technology — practically everyone not born in the cloud — could automate across older platforms without ripping and replacing, an expensive and risky undertaking that most CEOs would rather not take.
RPA has enabled executives to provide a level of workflow automation, a taste of the modern. It essentially buys them time to update systems to more modern approaches while reducing the large number of mundane manual tasks that are part of just about every industry’s workflow.
While some people point to RPA as job-elimination software, it also provides a way to liberate people from some of the most mind-numbing and mundane chores in the organization. The argument goes that this frees up employees for higher level tasks.
As an example, RPA could take advantage of older workflow technologies like OCR (optical character recognition) to read a number from a form, enter the data in a spreadsheet, generate an invoice, send it for printing and mailing, and generate a Slack message to the accounting department that the task has been completed.
We’re going to take a deep dive into RPA and the larger process automation space — explore the market size and dynamics, look at the key players and the biggest investors, and finally, try to chart out where this market might go in the future.
Meet the vendors
UIPath is clearly an RPA star with a significant market share lead of 27.1%, according to IDC. Automation Anywhere is in second place with 19.4%, and Blue Prism is third with 10.3%, based on data from IDC’s July 2020 report, the last time the firm reported on the market.
Two other players with significant market share worth mentioning are WorkFusion with 6.8%, and NTT with 5%.
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