Enterprise Software Startups: What It Takes To Get VC Funding
While financial markets have rallied in recent weeks, there are still many enterprise software companies that are trading at depressed levels. It’s common for there to be losses of 50%+ for the past year. Just a few include Okta, Twilio, and DocuSign.
This has also put tremendous pressure on funding for startups. During the second quarter, venture capitalists (VCs) struck 24% fewer deals on a quarter-over-quarter basis, according to PitchBook. And the IPO market is having its worst year in a decade, further hurting startup funding.
“VCs are definitely getting more selective,” said Muddu Sudhakar, the CEO and founder of Aisera. “The bar is much higher now.”
As for his own firm, Sudhakar was able to raise $ 90 million in a Series D round. The lead was Goldman Sachs and other investors included True Ventures, Zoom, and Khosla Ventures.
It helped that Aisera has a unique platform that leverages predictive AI for managing customer service, IT and sales. The technology has shown to be effective in lowering operating costs.
Also read: 5 Top VCs For Data Startups
Getting Funded in a Down Market
So what are some other enterprise software startups that have been able to buck today’s tough environment? What are the factors for success in current markets?
Let’s take a look at a few success stories.
CleverTap: AI-based User Engagement
“The best way to attract investors is to build a growing and sustainable business,” said Sunil Thomas, co-founder and executive chairman of CleverTap. “Focus on unit economics, growth, cash efficiency, and profitability.”
The strategy has worked out quite well for him. In August, CleverTap announced a Series D funding for $ 105 million. The lead on the deal was CDPQ, which wrote a check for $ 75 million. Other investors were Tiger Global and Sequoia India.
CleverTap software leverages artificial intelligence (AI) and machine learning (ML) to engage and retain users. Since the launch six years ago, the company has amassed a customer base of 1,200 brands.
“The overall funding environment has gone back to basics,” said Thomas. “Funding is definitely available for great ideas — at the early stages — and sustainable businesses at the growth stage.”
See the Top Artificial Intelligence (AI) Software for 2022
airSlate: Document Automation
airSlate raised $ 51.5 million in June. The lead investors were G Squared and UiPath. The valuation of the round came to $ 1.25 billion.
Founded in 2008, airSlate has created an automation platform that allows for e-signatures, PDF editing, document management and workflow solutions. There are over 100 million users.
“So what attracts investors?” said Borya Shakhnovich, CEO of airSlate. “Put simply, financials that speak for themselves. This means breaking even early on in the company’s journey, procuring impressive revenue figures, and demonstrating growth of the customer base.
“Touting solid financials for venture capital interest might sound painstakingly intuitive, but it’s not always that simple,” Shakhnovich added. “I often liken investors to shoes — there’s a lot of them to choose from, and some will fit better than others. A lot of founders feel like their purpose is to win every investor, but that’s not always possible. Many investors demand brand recognition and a firm customer base over financial stability. The best approach is to stand by your organization’s strength and identify like-minded investors.”
Also read: Top RPA Tools 2022: Robotic Process Automation Software
Tropic: Procurement Analytics
Earlier in the year, Tropic raised $ 40 million in a Series A round that Insight Partners led. The company’s software allows for better procurement. Keep in mind that the average company overpays by 30% for software.
Some of the customers are Vimeo, Zapier and Qualtrics. The company manages over $ 300 million in spend.
“At Tropic, we have a unique vantage point in that we can see how businesses are truly performing based on the purchasing behaviors of hundreds of companies,” said Dave Campbell, CEO and co-founder of Tropic. “We power these purchases, which gives us line of sight into who is performing well, who is churning, and who is struggling to get traction.”
Campbell points out the following learnings for those companies getting funding:
- They offer something that thrives in a downturn like cost-cutting and efficiency-improving approaches.
- They emphasize retention over growth. Companies raising now are in the 120% NRR (Net Revenue Retention) range, even if they are only growing 50% year-over-year. 300% growth with 50% NRR won’t attract investors.
- They have strong efficiency. Sales efficiency of over 1 and CAC (Customer Acquisition Cost) payback of less than 12 months.
- They power a mission-critical service. Nice-to-haves are out.
- They are willing to discount their valuation.
Lightning AI
In June, Lightning AI announced a Series B funding of $ 40 million. The lead was Coatue and other investors included Index, Bain, First Minute Capital, and the Chainsmokers’ Mantis VC.
The company has an open source platform to build AI models. It has been downloaded more than 22 million times since 2019 and used by 10,000 organizations across the globe.
“These latest changes in the funding environment have made it more important than ever for businesses to make it explicitly clear how they create value for their users and customers,” said William Falcon, CEO and co-founder of Lightning AI. “We expect to see an increasing amount of focus placed on the ability to synthesize what a business does into clear and well-articulated value propositions and a larger focus on efficient growth backed by strong unit economics.”
Falcon stresses that founders need to find investors that align with the vision of the company. True, in a rough funding environment, it can be difficult to say “no” to an offer of millions of dollars. But for the long-term prospects, this may be the right choice.
“While there’s no shortage of MLOps products today, it was important to us from the beginning that we found investors who understood that Lightning AI is not building simply another machine learning platform, we are building the foundational platform that will unite the machine learning space,” said Falcon.
Read next:
- 10 Top Data Companies
- 8 Top Data Startups
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