The Anatomy of Modern AI Startups

Most AI startups today follow a tripartite architecture: a foundation of third-party or open-source LLMs (think OpenAI, Anthropic, or DeepSeek), a layer of proprietary data for fine-tuning, and an application layer tailored to specific use cases. This structure gives rise to four distinct categories, each with its own degree of resilience OR vulnerability:

• #1 API Wrappers: These startups slap a thin application layer atop third-party models like OpenAI’s or Anthropic’s. Think chatbots or basic automation tools. Quick to build, but fragile.

• #2 Fine-Tuned Models: These take open-source or third-party LLMs and tweak them with proprietary datasets for niche applications, like a customer service bot trained on a company’s support logs.

• #3 Vertical AI Startups: These go deeper, crafting AI products for specific industries (e.g., legal, healthcare) and integrating them into end-to-end workflows. Think enterprise-grade products.

• #4 Model Builders: Relatively few startups choose to build their own foundational models.

The Erosion of Defensibility

Here’s the hard truth: as general-purpose LLMs get better and cheaper, the moats for categories #1 and #2 are shrinking fast. API wrappers face an existential threat as large enterprises, armed with budgets and talent, integrate AI directly into their operations, bypassing middlemen. Fine-tuned models aren’t much safer; as foundation models improve, the marginal edge of proprietary fine-tuning diminishes. commoditization is relentless, and the pace of innovation in open-source models only accelerates this trend.

The Data Moat Myth

The idea of a "data moat" has long been championed as a way to defend AI-driven businesses. In fact, many argue that access to proprietary data is one of the most valuable assets an AI company can have. In sectors such as healthcare and finance, where datasets are both rare and valuable, having the right data can enable a company to build models that are nearly impossible to replicate.

But here’s the catch: very few companies possess truly proprietary datasets.

Take Miele, for instance, the German high-end consumer appliance manufacturer. Miele likely holds a treasure trove of data about how customers use their products inside their homes, which is intimate and valuable. However, competitors like Electrolux, Samsung, and LG likely have similar data sets, diminishing its uniqueness.

Most companies overestimate the value of their data moat. Simply owning data is not enough. It must be exclusive, costly to acquire, and hard to replicate.

The Real Moat: Domain Expertise

So where does an enduring moat reside in this AI era? After diligencing dozens of startups and investing in a select few, I’ve come to a conviction: domain expertise is the irreproducible advantage. In a world where anyone can spin up an LLM-powered app in a weekend, technology is no longer the bottleneck—understanding and servicing the problem the right away is.

Consider Harvey AI, a standout in the legal tech space. Their team isn’t just building AI. They’re solving law firms’ thorniest problems with a precision that only insiders can muster. Harvey AI co-founder Winston Weinberg was a securities and antitrust litigator at O'Melveny & Myers. Harvey AI’s team includes lawyers who’ve endured law school, passed the grueling bar exams, and toggled between grunt work and high-stakes cases. They know the bottlenecks: endless document reviews, clunky research processes, and the inertia of manual workflows. Harvey’s CEO and head of legal research are lawyers who “speak the lingo” and empathize with their customers. Their product and AI teams embed legal experts alongside engineers, ensuring the tech doesn’t just work—it wows lawyers, a notoriously tough crowd to impress.

A quote from their team captures it perfectly:

What Harvey does really well is embedding legal expertise across all functions… Our CEO is a lawyer, our head of legal research is a lawyer… They go to a firm, speak the language, and are super empathetic. On the product and AI side, we have lawyers working hand-in-hand with engineers. - Aatish Nayak, Head of Product at Harvey AI

This isn’t just about data or algorithms. It’s about lived experience. A generic AI tool couldn’t crack the legal market without understanding how lawyers think, work, and resist change. Harvey’s moat isn’t their tech stack. It’s their ability to meet customers where they are and deliver value that sticks.

Consider Forest Flager, a construction industry veteran with deep roots in sustainable design, who saw firsthand the clunky inefficiencies plaguing construction material sourcing. The process was a mess, with emails ping-ponging between distributors and buyers, one-off spreadsheets, and critical data and context vanishing in the shuffle, all while eating up time with bespoke, disjointed workflows. Flager’s first-hand experience laid bare the vast potential for improvement, leading him to launch Parspec. Leveraging AI, Parspec digitizes and streamlines this tangled process, empowering construction buyers to source cost-effective, sustainable materials with ease.

Conclusion: Domain Expertise Wins

AI-driven software doesn’t just compete with other tools—it battles (entrenched) human workflows. In enterprise software, legacy vendors offer a clear benchmark to beat. But when AI replaces a manual process—like a lawyer’s research or a doctor’s chart review—the challenge is stickier. Success demands four things:

1. Minimize Friction: Adoption hinges on seamless integration into existing habits. No one rewrites their day for a shiny new tool.

2. Provide Proof: AI must prove it’s reliable and worth the leap, delivering a wow every time.

3. Enable Scalability: Success relies on the product’s ability to grow with its users, handling increased complexity and volume without breaking.

4. Cultivate Stickiness: Beyond initial adoption, long-term success requires users coming back and continuously deriving value.

This is brutally hard. Founders who’ve lived the problem, who’ve been the customer, have an unfair edge. They see the pain points others miss, anticipate resistance, and design products that stick. That’s why I over-index on founder-market fit at the early stage.

The founders I back don’t have a hammer looking for a nail. They’re building companies in domains where they have extreme expertise. They are doing their life’s work.

Achieving the coveted $1 million mark in annual recurring revenue (ARR) is an exciting milestone for any startup. It’s a sign that your product has achieved some early evidence of product-market fit and that you might be on the path to building a scalable, profitable business. While there is pressure to hit this milestone as quickly as possible, there is no shortage of iconic software companies that we admire that might have taken four years or longer to surpass the $1 million milestone.

For VCs, it’s tempting to focus heavily on revenue as a key metric when evaluating companies. In the midst of the uncertainty and ambiguity that comes with assessing early-stage startups, revenue can appear to be a clear, quantifiable measure of success. However, after being an investor for 10 years, I’ve learned over time where to be flexible in my thinking and not overly anchor myself to the excitement of early revenue or the lack thereof.

Revenue metrics and growth always matter. Yet, the growth-at-all-costs mentality isn’t the only path to success, as proven by companies like Atlassian and Procore, which took four to five years to surpass $1 million in ARR. There are plenty of examples of startups where a “slow” start led to breakout success and category leadership.

So let’s get specific. I’ve observed four key dynamics that often mean a startup might be slower in revenue generation out of the gate but still has compelling potential for hyper-growth, than the “storybook” startups that gobble up headlines. Alone or in combination, these dynamics determine when it is reasonable to expect growth to begin in earnest.

The Four Dynamics That Impact Time to $1M ARR

1. Product Development

At Sorenson, we often emphasize the importance of developing products that solve mission-critical problems for customers and have “lots of guts”. Developing high-quality products necessitates a comprehensive and often prolonged development phase. This valuable process, while essential for building a robust and innovative product, can indeed delay a startup’s journey to $1 million in revenue. However, this delay should not be seen as a setback but rather as a strategic investment. By focusing on creating a product with deep technological foundations, startups are more likely to achieve lasting impact and success in the market.

One of the core values at Couchbase, a Sorenson portfolio company that exited, is “Attack Hard Problems.” Tackling complex challenges and creating a robust, all-encompassing product is a time-consuming process. This involves collecting insights from design partners and early customers, then using that feedback to add features and iterate the product over several cycles.

Known today as a leader in electronic signature technology, DocuSign faced a classic “chicken or the egg” problem early on. The company struggled initially to identify the most receptive market vertical. While they eventually found a stronghold in real estate, a sector greatly benefited by the digitization of signing processes, getting there wasn’t straight-forward. The real estate industry is typically slow to adopt new technologies, which meant DocuSign had to invest considerable time in educating potential users and iterating the product to meet specific industry needs. This phase in DocuSign’s story was critical to developing a product that could achieve wide adoption and become indispensable to its users.

Another example is Bridgecrew, a codified cloud security startup and an exited Sorenson portfolio company. Bridgecrew relied heavily on its open-source model to build a user base and gather valuable feedback, which was indispensable for product development. However, transitioning from an open-source model to a scalable revenue-generating business model takes significant time and effort. The need to add substantive value beyond the basic free tools required continuous innovation and development, which resulted in the company taking time to ramp up ARR, but ultimately was the right investment to make. Bridgecrew was widely recognized as the leader in the emerging space of “shift left” cloud security, bridging the gap between developer and Chief Information Security Officer (CISO), and acquired by Palo Alto Networks in March 2021.

2. Land-and-Expand

Land-and-expand is a common growth strategy used by software startups to initially gain a foothold in a new customer’s organization (“land”) and then gradually increase their presence within that organization over time (“expand”). This strategy can take several forms. Often, it involves starting with a smaller, often low-friction-to-adopt solution that scratches an itch, and then leveraging this initial success and trust to upsell and cross-sell additional products. Sometimes, it takes the form of landing a small number of initial users and then spreading across other teams and users in the organization.

Slack is frequently cited as the poster child for land-and-expand success – one team finds value in the product, which incentivizes them to convince other teams inside the organization to adopt it, and the momentum snowballs from there.

Another example is PlanGrid, the digital blueprint company acquired by Autodesk for $875m million. Initially adopted by individuals on construction sites, workers equipped with iPads could effortlessly display and share blueprints on-site using PlanGrid, contrasting sharply with their colleagues who had to manage cumbersome paper blueprints. This striking difference not only highlighted the efficiency of PlanGrid but also sparked interest among other teams who observed these interactions. As a result, the demand for PlanGrid spread organically across the site, facilitating wide adoption without the need for aggressive sales tactics.

Land-and-expand is the type of organic growth that B2B marketers drool over, but it takes time for even the most compelling software offering to win the hearts of users one by one and spread across a customer organization.

3. Market Education

If you are building a product in a nascent space “where the puck is going”, the market often needs time to understand the problem and decide how it wants to solve it.

Take LLM (Large Language Model) security as an example. While there is no doubt that enterprise use of generative AI will introduce new attack vectors, the specific applications of generative AI within enterprises are still developing and evolving. It is challenging to establish defenses when these new frontiers are not yet clearly defined. As a result, many CISOs are cautious about investing in LLM security tools immediately. If you are developing an LLM security startup, even with the best product on the market, adoption may take time as the market continues to learn about the emerging challenges, and benefits of your product.

Sometimes, the problem may already exist but represent a new category. For instance, Talon Security’s browser-based security solution was a new category that the company pioneered. Founded in 2021 during the peak of the COVID-19 pandemic, the shift towards a fully digital workforce created a fertile ground for security breaches. Bad actors exploited vulnerabilities arising from employees working remotely on devices beyond company oversight. The Internet browser emerged as a vulnerable gateway to business-critical assets. Talon focused on educating CISOs about the newfound criticality of browser security in a modern work environment. This educational process took time, but as demonstrated by Palo Alto Networks’ recent acquisition of Talon for $625 million, taking the time to create and educate a market about a new category can indeed be highly rewarding.

4. Sales Cycle and Industry Dynamics

Selling into large enterprises typically involves long-ish sales cycles, especially when the offerings are complex or high-value. These cycles vary by industry but often involve considerable time spent identifying leads, navigating through organizational decision-making, and finalizing deals. Particularly in highly regulated sectors like healthcare and financial services, additional hurdles, such as compliance and security reviews, are common. These challenges can result in low initial revenue velocity, but may nonetheless be fruitful investments in the long term.

At Sorenson, I interface with a lot of startups that are facilitating the production of goods and services (dubbed “Future of Industry”) and those that are enhancing the movement of these goods and services (dubbed “Future of Commerce”). The companies in these markets often serve a large number of human users of varying levels of sophistication, and may even involve hardware as the enabling layer, which can add to the implementation burden. For these reasons, it is not atypical for startups in these industries to have slow initial revenue ramp.

Take Afresh, for example, which offers inventory management and fresh food ordering software for grocery retailers. Grocery retailers have traditionally been technology-averse. Afresh starts its customer engagement by analyzing historical data from retailers to simulate and benchmark actual performance with a performance they would have had if they had used Afresh. This analysis helps demonstrate possible ROI through reduced waste and increased profits. If the customer makes a go decision, they start with a small-scale deployment, typically one to five stores, then move to a larger deployment. This all takes time. The first set of Afresh’s paying customers were small regional retailers who took a leap of faith, but over time they have expanded to serve the likes of Albertsons and have been able to build a scale business in an end-market that is typically seen as challenging.

Companies like Sight Machine, a Sorenson portfolio company, that operate in the manufacturing sector face similar challenges. Manufacturers are risk-averse when it comes to new software purchases. Sight Machine, as a Manufacturing Data Platform, aids factories in optimizing production and improving efficiency through data analysis. The initial engagement usually begins with a Proof of Concept (POC). While the key buyer tends to be operations management (e.g. General Manager, Head of Factory), CFO and IT are also important stakeholders in the sale. While getting started with customers in this type of end market may take time, successful implementations often lead to multi-year, multi-facility high-value contracts in the six to seven figures.

The journey to $1 million in revenue may be slow for startups in these sectors, but as demonstrated by Sight Machine’s and Afresh’s success, the long game can still lead to a scalable and profitable business.

Advice to Early-Stage Founders

For early-stage founders who find themselves operating in a “delayed growth” environment, the journey can often feel daunting. Here is some advice for how to lay a strong foundation for long-term success.

1. Understand why it will take longer to get revenue traction.

The first step is to understand precisely why it should take longer and make it a deliberate decision. It may be due to some combination of the four dynamics above. If the path to $1 million in ARR is unclear because the market doesn’t genuinely value the current iteration of your product, you might need to pivot. This period of introspection can be invaluable in figuring out a plan for the long game.

2. Find the right set of investors.

It’s crucial to partner with investors who grasp your venture’s nuances and are willing to support you through the extended phase of scaling to $1 million ARR. Investigate successful companies that serve as benchmarks for your own venture and initiate discussions with their investors. They’re more likely to respect the revenue dynamics, risk profile, and overall potential of your business. These seasoned backers can offer not only capital but also invaluable guidance and understanding of the unique opportunities you face, as well as empathy.

3. Optimize for the long-run, not short-run.

It is totally okay to have conviction that in the earliest stages of your venture the right thing to do is prioritizing something other than revenue. Resist generating revenue for the sake of it.

In pursuit of initial revenue, there’s a temptation to onboard any customer who shows interest. However, aligning with the wrong customers can be detrimental in the long run. Focus on those whose needs closely match the solution you offer, even if it means slower revenue growth initially. This approach ensures that your product development is in line with genuine market needs and sets a solid foundation for scaling.

Remember, some of the most successful companies today faced early challenges and slow starts. What often sets successful founders apart is their ability to stay the course, adapt their strategies, and maintain a clear focus on their ultimate goals. Stay positive, stay focused, and keep building towards the future you envision. Your patience and persistence will be your greatest assets as you work towards turning your vision into a thriving business. And if you ever need advice or want to brainstorm together, please reach out.

Construction often gets a bad rep as one of the “dinosaur” industries. This is not entirely unwarranted: Productivity growth in the sector averaged just 1% over the past 20 years versus 2.8% for other industries. Nonetheless, having spoken with many developers, builders, materials suppliers, construction tech entrepreneurs, and investors over the last 12 months, the industry is far more open to experimenting and embracing technology than many realize. 

The built environment is confronted with opportunities and challenges of unprecedented scale, including the growing global demand for infrastructure and housing, an ongoing, escalating labor shortage, cost inflation, supply chain disruptions, and ESG (environmental, social, and governance) requirements. These challenges are pushing construction to evolve faster than ever–and there are plenty of ways founders can capitalize on new trends in the space.

The construction industry has become more sophisticated and well-versed in software over the last five years. For instance, 84 percent of general contractors implemented autonomous solutions over the past year. Innovative technology and ideas are influencing construction wherever you look. These new technologies help builders achieve higher levels of productivity, profitability, and safety. Tech founders may find that construction customers are more selective when it comes to sharing data or buying, compared to five years ago. On the flip side, most general contractors now have a technology budget and a well-defined evaluation process and team. Construction tech founders who solve the most important priorities for general contractors - building on-budget, on-time, and on-scope - are well-positioned for growth in 2024.

Here are my five predictions for construction tech in 2024, and how tech founders can take advantage of big opportunities in the construction sector.

1. Capitalize on growing subsectors of construction tech, in a hot market for funding. 

Please note not all financings completed in 2023 have been announced to date and the number will likely rise substantially.

Venture capital interest in construction tech reached all-time highs in the past four years, and the last three months of 2023 were an incredibly active time for construction tech startup funding. I predict 2024 to be another active year, outpacing 2023, with approximately $1.0 to $1.5 billion in total capital invested (shown in light blue).

In terms of opportunity, IT spending in construction comprises a mere 1-2% of revenue (versus 3-5% across other industries), so construction tech has plenty of runway. Buyers are also becoming more sophisticated – they increasingly value software tools that not only digitize workflows but help deliver superior outcomes leveraging data, AI, or automation. Seizing these opportunities and market demand, 2024 should be a good year for founders to launch construction tech startups and raise capital.

2. Bring forth sustainable practices that help customers meet ESG goals. 

There is an ever-increasing focus on sustainability in the construction and real estate industries today. Per the International Energy Agency, the built environment accounts for 30% of the global energy footprint and 26% of global energy-related emissions. As such, governments are tightening the screws on builders and real estate owners to ensure buildings are up to code in regard to energy consumption and carbon emissions during construction and operations.

For example, a new law in New York City will require any building of more than 25,000 square feet to meet new energy efficiency and greenhouse gas emission standards. The penalties are stiff: $268 for every metric ton of carbon dioxide above the allotted limit, which studies estimate could amount to $200M per year for some buildings.

Regulations, building standards, and pressure from owners and tenants are pushing the construction industry to increasingly prioritize sustainability. In 2024, we can expect to see a wave of construction tech startups that focus on ESG, too. Ranging from green materials to AI that helps design sustainable buildings, technology can help the industry adopt sustainable practices across the entire building lifecycle.

For example, Snaptrude is a collaborative, browser-based conceptual BIM (Building Information Modeling) tool - think of it as a modern alternative or complement to Autodesk Revit. Snaptrude has partnered with Cove.Tool, to incorporate LEED-compatible performance metrics right inside its design platform. Architects, designers, and LEED consultants can iterate on design collaboratively to achieve performance targets.

Green building practices are becoming the norm, and there are major behavior changes underway in the construction industry. Construction tech founders will need to think about how their products can serve customers with their ESG goals. If you don’t get sustainability, you can’t understand construction customers.

3. Build modern collaboration and communication tools–which are being aggressively adopted in construction.

Given the prevailing market conditions, the construction industry is more focused on profitability than ever. But picture hundreds of back-and-forth replies on a single email thread with 20+ people cc’d–how does work ever get done? Details get buried or misconstrued, possibly cratering an entire project. In an era where tools like Figma, Miro, Slack, Airtable, and Notion have become the norm in other industries, many construction companies are stuck in the 20^th century with legacy software tools.

Better collaboration and communication are some of the lowest-hanging fruits that can elevate operational excellence and unlock savings. This will lead the industry to start focusing more on thesestart embracing modern collaboration and communication tools more aggressively in 2024. 

Collaborative delivery, negotiated bids, and self-perform contracts, which are growing in popularity, depend on collaboration and communication for success and are pushing builders to seek best practices and tooling in these areas. Better collaboration and communication can make the next stage of construction more informed and less risky, bringing more transparency and certainty to projects. Every software founder should think about incorporating modern collaboration and communication features into their products, and construction is no exception.

In 2024, startups like Planera will introduce true real-time collaboration to the construction industry and remedy other collaborative issues posed by legacy software tools, such as Oracle Primavera P6, emails, or spreadsheets. Planera’s digital whiteboard helps more builders accurately lay out their scope of work, develop estimates and bids, and create a timeline for project completion. In addition, better planning means better equipment utilization and less idling and wastage. This not only improves margin but also lowers the total carbon footprint of each project.

4. Help construction firms achieve more with less by increasing automation and/or integrating HR technology.

Talk to 5 general contractors, 4 of them will bring up labor shortage and brain drain as the biggest challenge today. To achieve more with fewer resources, construction firms will turn to automation and HR tech in 2024.

The availability of skilled construction talent continues to dwindle. Associated Builders and Contractors, a trade association, reports that one in four construction workers is older than 55 and there aren’t enough younger workers interested in entering the profession.

These labor shortages present a sterling opportunity for construction tech startups focused on bolstering productivity. Companies like Field Materials, a construction tech company that digitizes procurement of construction materials, are bringing automation to the “low value-add” stages of the construction value chain. Field Materials empowers contractors and vendors to streamline every aspect of procurement, freeing up time for more valuable work while generating margin gains and cost savings.

Another example is OnSiteIQ, a construction intelligence platform that uses computer vision to monitor building progress, pinpoint issues, and enable collaboration with teammates. They are digitizing manual labor-based monitoring and supplying real-time insights to interested parties that can pinpoint issues upfront and prevent delays or workovers.

Personally, I believe that the people side of construction is the greatest white space opportunity for construction tech founders. I’d love to see more HR tech startups serving the construction end-market. HR tech, as it has done in other industries, can help deliver a superior experience to workers and employees, allowing employers to better compete for and retain the highest quality labor. HR tech can help automate the recruiting process (e.g. FactoryFix for manufacturing). Also, HR tech can help with onboarding, training, and upskilling. Think PluralSight, but for construction.

5. Grow your market; think about how your tech can serve both construction and real estate customers.

There is valuable data and knowledge generated during the construction phase that can carry over once a building is completed (e.g. ISO 19650). I expect to see a few companies pop up to help real estate owners glean insights from data and knowledge generated during design and construction so that they can manage, operate, and maintain their buildings better. For instance, Passive Logic is the developer of robust physics-based digital twins, which can be leveraged to better design, build (i.e. construction), operate, maintain, and manage our buildings (i.e. real estate).

I expect the line between construction tech and proptech to blur in 2024. Construction tech founders should think about how their products might be able to serve both construction and real estate customers.

Plenty to build on

Heading into 2024, there is a lot to be giddy about if you are a construction tech entrepreneur, buyer, user, or investor.

As a construction tech investor, this is what I’m looking for in founders and their products:

• An ambitious founder solving a big problem that impacts a sizable portion of the overall construction market

• A thoughtful product: This means the founder has a deep understanding of the way customers do business and has a clear vision for how multiple stakeholders can interact with and benefit from the product.

Disclaimer: Planera and PluralSight are Sorenson investments. 

Construction is the largest industry in the world economy, accounting for approximately 13% of the global GDP. Yet, productivity growth in the sector averaged just 1% over the past 20 years versus 2.8% for other industries. Our built environment is facing opportunities and challenges of an unprecedented scale: aging and deteriorating public infrastructure in most of the developed world, a chronic shortage of affordable housing (7.3 million in the U.S. alone), the dire need for climate change resilient infrastructure buildout, and explosive population and construction booms in parts of Asia and the Middle East. We cannot be successful in tackling these opportunities and challenges with just hammers and hoes. The $1.8 trillion construction industry in the U.S. ($15.5 trillion globally) is long overdue for a technological facelift.

Construction project management, in particular, needs an upgrade. For starters, most enterprises still plan and schedule construction projects using the Gantt chart, a project management tool that pre-dates the Great Depression.

Enter Planera, a visual scheduling and planning product that helps construction companies build, analyze, and optimize schedules designed for ease, collaboration, and dollar impact in mind. Sorenson recently led Planera’s $5.4 million seed round to supplant legacy systems that inhibit collaboration and waste valuable time during the bidding process. Prestigious customers, such as Shimmick Construction and Webcor, are already singing high praises about the efficiency and stakeholder alignment that Planera enables.

Planera’s core value prop, making teamwork less work, is critical for an industry in which poor collaboration could mean losing business—or going out of business altogether. Planera reminds us of the disruption we previously saw with Figma and Miro.

Time for a rebuild

Construction is highly complex. It is multi-stakeholder in nature, cyclical, project-based, and heavily regulated. Repeatable productivity gains are far from a sure thing.

This inefficiency extends to the pre-construction phase, when project managers, contractors, schedulers and others design and strategize ahead of the bidding process. Pre-construction requires as much teamwork and synergy as on-site operations. However, legacy planning and scheduling solutions, like Oracle Primavera P6, lack frictionless real-time collaboration, a feature that is table stakes in today’s cloud-centric enterprise software stack in other industries.

Seamless collaboration during pre-construction is crucial given all of the players and moving parts. One miscommunication, one false step in planning or estimation, can crater an entire project. Bid too high on a project, and you’ll scare clients away. Bid too low, and you’ll win more jobs but lose money in the grand scheme. Yet, most “collaboration” takes place over email, and the truth might be buried somewhere in the 26th message of a long email chain.

Aside from their collaborative pitfalls, legacy tools are also a pain to figure out. The complicated UX frustrates users across the pre-construction spectrum, leading to major project delays and erroneous estimations.

The construction tech renaissance is underway. Opportunity knocks.

Sounds like a Planera

AI-assisted design. Self-healing concrete. The hard hat? Hyperbolic as it may sound, Planera is well-poised to be one of construction’s most impactful innovations.

Think of Planera as a digital whiteboard on which collaborators can sketch out ideas, visualize workflows, and build optimal project schedules. The collaborative prowess of Google Docs or Figma, powered by a best-in-class CPM engine. Planera includes all of the bells and whistles of its legacy predecessors as well, such as critical path, float management, and resource usage graphs.

Before Planera, generating a resource-loaded schedule for a project took weeks. Now it takes hours because people with knowledge of the job can build their own schedule without relying on scheduling experts. Estimating the price for a project is no longer a toss-up. Costs like labor and equipment are effortlessly accounted for and inconsistencies easier to catch. Bids are accurate, expeditious, and won’t spike blood pressure levels.

Planera’s adaptability and accessibility unlock myriad possibilities down the road, possibilities that its founding team—rife with leadership experience and domain expertise—is more than capable of realizing.

A strong foundation

Planera’s founding team is quite the starting five.

Running point is CEO Nitin Bhandari, a 3X entrepreneur and one of the most impressive, thoughtful product-builders we have ever worked with. Nitin brings more than two decades of experience to the role, and both of the companies he previously co-founded (Zenlabs, Skyfire) were successfully acquired. Joining Nitin are Erik Swenson, a fellow co-founder of Skyfire with 50+ US patents to his name, and Head of Customer Success Noor Lodhi, formerly an executive at NetApp.

Planera’s other two co-founders, Saif Lodhi and Wahid Tadros, bring unparalleled domain expertise as seasoned insiders of the construction industry. Both hold senior positions at a well-regarded West Coast heavy construction contractor, and Saif was the lead contractor for the $350M iconic Bay Bridge reconstruction project in San Francisco.

Planera’s end-users—mostly general contractors who feel misunderstood by new technology offerings—won’t take a chance on a product if the people behind it are clueless about the industry. Ample domain expertise and seven decades of combined software experience, plus a deep bullpen of early, enthusiastic customers, isn’t a bad way to break the ice.

Skyscraper potential

Planera’s quest to bring the best of modern software tooling to construction planning and scheduling is exciting enough, but it could lead to facilitating other phases of the project lifecycle. On-site execution? Supply chain and procurement? Many other areas of construction would benefit from frictionless collaboration.

Another promising sign for Planera’s long-term prospects is the market. The construction management software market is expected to reach nearly $4 billion by 2030, growing at a CAGR of 9.43%.

With a supremely differentiated product, a formidable team behind the controls, and weathervanes pointing in all the right directions, Planera is primed for the long haul. We are honored to be along for the ride as the company helps transform a challenging yet critical industry.

In late November, I checked out Startup Week in Calgary, where Sorenson Capital hosted a breakfast session for Alberta-based founders. This experience, coupled with last week’s C100 Summit in Half Moon Bay, was incredibly energizing. It also presented a valuable opportunity to compare the experiences of founders, operators, executives, and investors from Canada versus the U.S.

I am incredibly bullish on the future of Canadian tech. That said, my recent trips back home provided new insights into why Canada’s tech scene leaves more to be desired and many Canadian founders continue to struggle with access to capital and scaling their ventures.

Here are my hot takes on some of the roadblocks keeping the Canadian tech scene from reaching its full potential.

1. Smaller outcomes, thin equity

When a Silicon Valley-based company exits, there is, typically, plenty of money to go around. Lucrative, life-changing wealth enables C-level executives and maybe the first 50 employees to branch out into other pursuits. The CEO might start another company. The CTO and VP of Sales might join another startup. Others become angel investors. The positive spillover is substantial.

We know that outcomes of this magnitude are still rare in Canada. Moreover, I recently spoke with a founder who’s hired team members in both Canada and the U.S. He explained that most Canadian employees don’t value equity as much as their American counterparts, who tend to actively seek and negotiate equity compensation.

As a result, equity is spread thin in Canadian startups. When a Canadian startup exits, the positive contagion described above is limited in scope - to the C-suite and maybe the first few employees. The lack of understanding and deprioritization of equity among employees is the culprit. 

2. A different breed of angels

Quality angel investors aren’t an endangered species in Canada. I’ve met plenty. But Canada doesn’t churn them out like Silicon Valley.

Most of the angels I know in the U.S. work or have previously built businesses in tech. They’ve battled in the startup trenches, understand the difficulty of getting a company off the ground, and are familiar with the high-risk, high-return nature of early-stage investments.

Given that Canada’s tech scene is somewhat infantile relative to Silicon Valley, many of its angel investors bring experience from cash-flow-oriented industries such as real estate, financial services, or natural resources - industries where wealth was traditionally created in Canada. Not to say these angels can’t offer general entrepreneurial wisdom, but the value-add for tech founders won’t be the same.

An angel with little to no experience in tech may also lack the requisite level of discernment. I’ve heard from Canadian founders stories of angels passing on pre-seed or seed investments, because “you don’t have product-market fit yet”. Silicon Valley angels, on the other hand, have a higher appetite for risk. They invest because they might personally know the founder, desire to see a different future state as a result of the product they are investing in, support the ecosystem, or simply pay it forward. They have a higher willingness to invest in outlandish visions or contrarian ventures, some of which turn out to be home runs.

3. Homogeneity precludes ingenuity

There is no shortage of success stories in Silicon Valley, nor is there a one-size-fits-all formula for how those startups got there. Around these parts, ask 10 people for startup advice and you’ll hear 10 different answers.

Canada’s smaller tech scene has fewer success stories under its belt. Advisors and investors are less experienced. (This will naturally get better over time.) With fewer battle-hardened founders or successful playbooks to look up to—at least compared to Silicon Valley—ask 10 people for startup advice and you might hear only 2 or 3 different answers. There are multiple paths to success. More creativity, heterogeneity of thought, and “deviances from the known path” in Canada’s tech scene will translate into more success.

4. Taking the “fun” out of government funding

On the surface, free government funding for startups sounds amazing, almost too good to be true. Canada, indeed, offers a plethora of grants and tax credits to founders in an effort to support its tech scene. The free, however, is a bit of a misnomer.

Countless hours spent filling out paperwork, opaque selection processes, and needing to demonstrate proper use of funds—even the less competitive grants are a chore.

Much of the government’s support is directed at R&D and deep tech. However, in my opinion, support, and funding for turning this R&D into a product and scaling it is just as important and impactful for the overall ecosystem.

Some entrepreneurs have solved the government grant Rubik's cube. That’s great! Accessibility and how well it is working is still a question mark.

5. Policymakers can’t keep up

The mega-merger sweepstakes are off and running in The Great North: Rogers acquired Shaw, RBC acquired HSBC, and WestJet is vying to buy Sunwing Airlines. This consolidation trend, which has accelerated over the past decade, doesn’t bode well for startup entrepreneurs. Instead of leveling the playground so that startups with disruptive technology can compete with incumbents, policymakers are allowing large companies to get larger and accrue unfair advantages.

Canadian universities generate valuable research and IP, but officials from these universities regularly travel down to Silicon Valley, pleading that all they need is founders willing to take the risk and spin this IP into successful ventures. With consolidation swinging the odds clearly in favor of the behemoths, you can’t blame doctorate fellows and startup founders for wanting to play it safe and lacking motivation. Swimming with elephants is hard.

Instead of launching their own companies, many Canadian PhDs and professors are leaving to join AI startups in the U.S. In the yearly State of AI Report by Nathan Benaich of Air Street Capital, the University of Toronto is, unsurprisingly, listed near the top of leading Brain Drain institutions.

6. A deceptively small market

Canada takes up a lot of space on the map, but this isn’t commensurate with the size of its economy. Except for a handful of consumer plays (e.g. Neo, Borrowell), Canada’s domestic market isn’t large enough to single-handedly and repeatedly churn out unicorns.

Most global VC firms group Canada into the “North America” category, so there isn’t a fixed and enduring allocation to Canadian, versus U.S., startups at these funds. (If you find one, let me know!) The same firms usually have a fixed allocation, hence dedication, to other major ecosystems, like Israel or the Nordic region. While many U.S. VCs travel to Canada regularly, the Canadian tech scene is still chronically underserviced.

It makes sense for Canadian startups to seek out customers across the border, but landing U.S. customers isn’t a sure thing. For instance, take a Canadian SaaS startup that sells to supermarket chains and retailers, like The Bay, Loblaw’s, and Aldo. These are blue-chip Canadian customers, but Nordstrom and Kroger don’t really see these Canadian counterparts as being “market-leading” or referenceable. Go-to-market (GTM) success in Canada doesn’t translate frictionlessly state-side; bagging your first referenceable U.S. customer is always a tough challenge, regardless of how physically close Canada and the U.S. are.

Belabored as this example may be, Israel exemplifies the small country punching well above its entrepreneurial weight. As soon as their ventures show promise, Israeli founders relocate or set up an office in the U.S. These companies look and feel local to U.S. customers. Israeli founders have shrewd GTM playbooks and instincts. This is something to aspire to for the Canadian tech scene.

7. Risky business

Canadians, specifically Canadian entrepreneurs, have traditionally been deemed more risk-averse than their international counterparts.

While it’s theoretical to peg risk aversion as a contributing factor in Canada’s tech scene still being far away from reaching its full potential, my conversations with Canadian founders support this claim. Many of these founders are building toward $50 million, $100 million outcomes—highly conservative compared to U.S. founders. Meaningful wealth for founders, sure, but it doesn’t excite venture investors.

Speaking of venture, it seems Canada’s risk-averse culture extends to VCs as well. If founders and VCs are both afraid to push their chips in deep, this only exacerbates matters. 

8. Most Canadian wealth flows out of Canada

Most of Canada’s wealth is tied up in pension funds, such as Canada Pension Plan (CPP), Ontario Teachers’, PSP, and AIMCo. Very few of these funds (not counting Sorenson Ventures’ neighbor OMERS) have an active direct investment program focused on early-stage Canadian startups as an asset class. This contrasts sharply with their hyperactive direct investment programs in the private equity asset class. Funds they do allocate to VC merely flow through funds of funds (FoFs), which funnel the capital to brand name firms in Silicon Valley or abroad rather than the Canadian tech scene.

Imagine if a small fraction of all the Canadian wealth tied up in pension funds can go towards supporting the future of Canadian tech. It would easily yield 10x the benefits of any tax credit or grant program. I want to see the large Canadian pension funds do more to support homegrown founders.

Worry not, Canadians

Despite the concerns listed above, I am extremely bullish as they come on the future of Canada’s tech. I’m Korean by birth and Canadian by choice. I am forever humbled by the zeal and hard work put in by Canada’s talented entrepreneurs in or outside tech.

Consider these challenges potholes, not sinkholes. Nothing that can’t be smoothed out with some time and maturity. Becoming a tech “ecosystem” doesn’t happen overnight: Silicon Valley’s history dates back more than a hundred years.

Growing up in Toronto, it was rare to know anyone who worked in tech. My friends’ parents worked in real estate, financial services, or mining. The closest I had to tech was my friend’s dad who worked in IT at TD. In retrospect, it’s encouraging that Canada’s tech scene has developed exponentially over such a short span. Canada now boasts multibillion-dollar tech companies like Shopify, Neo, 1Password, and Sorenson portfolio company Visier among many others, plus well-attended conferences like Collision, and Superclusters.

I love bumping into Canadian founders in the Bay Area, but can’t help but think, “Why did they have to leave?”

My long-term goal is to make Sorenson a household name for early-stage software entrepreneurs in Canada, doing more to support talented founders, and adding to our existing slate of Canadian investments that includes Visier, Owl.co, Expeto and Boost. (This would also give me an excuse to spend more time in my hometowns of Toronto and Calgary.)

If Canada can button up even just a few of these “potholes,” the momentum will be palpable. And all of those naysayers? They’ll come around, too.

“How can I show traction beyond revenue?”

I frequently get this question from founders of pre-revenue startups. Absent the obvious measure of traction (i.e. revenue), how can I demonstrate that my startup is heading in the right direction and making progress?

Today, this is topical for pre-revenue and post-revenue founders alike. Corporate budgets are being slashed. Software buyers are increasingly risk-averse and reluctant to make drastic purchase decisions for non-mission critical software. Sales cycles are lengthening.

If your time to first revenue is being pushed out, or your revenue projections are coming down, are there non-revenue metrics of traction that you can point to?

Sorenson Ventures was launched in 2017 as a way to address the funding gap that many early-stage founders and startups face as they try to validate product-market fit and define scalable and repeatable growth models. Approximately a third of the companies that we invest in are pre-revenue (at the time of first check). Even post-revenue, growth can be lumpy. As investors, we underwrite our investments on a multitude of data points and evidence, not one metric.

For Revenue-Generating Startups

Data plays an essential role in the decision-making processes for VCs.

For revenue-generating businesses, we typically look at a variety of metrics, including ARR, ARR growth (including new logo, expansion, churn downsell), gross margin, CAC payback, LTV, ACV (average contract value), sales efficiency, sales pipeline statistics and NPS score.

Through these metrics, we are trying to validate:

• Whether your product is solving a real challenge in the world; and

• The extent to which your target customers love and care about the product you are building

For revenue-generating startups, there is typically no shortage of data. However, for many, non-revenue data points, which will be highlighted in the next section, could still be relevant and helpful.

For Pre-Revenue Startups

Non-revenue data points for pre-revenue companies can include:

1. Partnerships or other powerful relationships that can open doors to customers

   “We just signed a MSP that works with Forbes 2000 companies x, y and z. It will take time to figure out how to work together, but we expect this relationship to generate approximately $m million of value in 2024 and $n million of value in 2025”.

2. Design partners

   “We are working with Company x as our design partner. They struggle with Problem y, which costs them up to $z million every year. They evaluated and tried many alternative solutions, but nothing worked. They love what we are working on, and expressed a strong interest in converting to a paying customer once our product is ready for commercial launch".

3. Letters of interest or intent

   Many letters of interest or intent eventually turn into nothing, but it always impresses me when a large company is willing to pick up the pen, and explain why this is a problem and how excited they are about this new product”.

4. Waitlist and pre-orders

   I am #118,692 on the waitlist for Notion AI.

   While not everyone on the waitlist ends up buying, it is a great indicator for the general level of interest in your product.

5. Angel investments from renowned executives

   Are you building a DevOps startup, and the founders of GitHub, Harness and CircleCI are investing? I am excited about the wisdom that these individuals can impart and the doors they can open for you.

   The relevance of the angel investor to your startup and his / her level of engagement are more important than fame and the number of Twitter followers.

6. GitHub stars

   GitHub stars are a useful heuristic for “interest”.

   However, GitHub stars can be gamed. Stars can be bought. Media coverage can temporarily induce spikes of stars that might be dislocated from the actual value or substance of the project.

7. Public attention

   Coverage on TechCrunch or Hacker News is great, but I enjoy reading about what products and open source projects developers are talking about on Reddit, Discord and Slack channels. Are your customers loving and passionately advocating your product?

8. Is your community thriving?

   Nowadays, every software startup has a Slack community. Only a fraction of them thrive.

   If you happen to have a thriving community of customers and champions, or if people are coming to your Slack channel to discuss their challenges, collaborate and do interesting things (ideally involving your product), this is an important data point for investors.

   I recently came across an early-stage startup that has an impressive, thriving Slack community. They have invested a ton in developing content and educational materials, which made them a central destination for developers interested in this topic. Bravo!

   On a related note, I recently listened to Tristan Handy (CEO of dbt Labs) on a podcast, elegantly outlining his thoughts on building a community. It is long but worth quoting in entirety:

I think of this as, you know, the best way to see stars in the night sky is to not look directly at them because it turns out that the edges of your eyesight are much more low light sensitive. And I think one of the best ways to start a community is to not try to start a community.

Sometimes I field questions from software founders who have gotten from zero to one, and now they’re thinking about scalable marketing channels to continue to grow. And they say, “Ah, I want to start a community.” It’s like, I, that’s not generally how that goes.

For us, we were practitioners, we were trying to solve real problems. We were using dbt as a tool in solving those problems, but we were not really just talking about dbt, we were talking about the problems that we were facing in the context of doing the kinds of analytics that digital native businesses do. And so we had a Slack group, and the Slack group was like for our little network of people to kind of collaborate.

And three months in, we ended up working with a company called Casper. They were really very central in the New York tech community in 2016. Their data team was like a dozen people. And they hosted meetups and all this stuff. And as a result of this project that we worked on together, they adopted dbt, and they became this kind of central locus.

They brought other folks from the New York tech community and told them about this new tool that they were using. And things have kind of spread from there. And Drew and I, who don’t live in New York, we were kind of observing all this from afar. We just continued to be helpful on Slack, and people were trying to get set up and running, and people were trying to absorb the things that dbt kind of assumed about how you were going to work.

We just worked with people without any expectation of an immediate payoff there. So if I were going to kind of summarize all that — create some focus that people can kind of organize around and then just provide value. But then do it for a very long period of time. I mean, it was years and years before there were a real meaningful number of people in there.

Ending Thoughts

While fundraising is a high-stakes circumstance for founders and there is a lot of pressure to paint a rosy picture, you don’t necessarily need to hit top quartile metrics across the board. Very few companies look like that.

If your ARR predictably T2D3, you will have a relatively straight-forward fundraising process. If it doesn’t, be sure to point to other metrics and data points that will demonstrate to investors that you are working on an important problem that your customers care about.

You are running an early-stage startup. It is completely normal not to have the answers to all the questions. It would be abnormal not to have kinks and bottlenecks. In fact, I really enjoy collaborating with founders who are trustworthy and honest, and believe that is where I can add the most value.

I remember installing on my MS-DOS computer software or games that were shipped on a pack of 20 floppy disks.

As we transitioned from on-prem to the cloud, the “transfer of value” changed from one-time to continuous. Similarly, we transitioned from perpetual licenses (bye bye lumpy one-time revenue) to subscriptions (hello recurring revenue). The way we “consume” software continues to evolve.

Today’s grand transition is towards usage-based pricing (UBP).

Usage-based pricing makes sense

Intuitively, it makes a lot of sense that you should charge customers based on the value you create for them. One area where value-based pricing is fairly popular? Health care.

At an extremely high level, value-based care is a system where healthcare providers are paid based on the quality of the care outcome they deliver rather than the number of healthcare services provided or the number of patients seen.

Unfortunately whether it is health care or software, 1) figuring out the ROI of a product is not straight-forward, and 2) getting started with value-based pricing requires thoughtful preparation and implementation.

Usage-based pricing (UBP) in software simply approximates value-based pricing.

Benefits of UBP

In today’s economic environment where there is a lot of budget reductions and scrutiny on new purchases, it is a competitive advantage to make it as easy as possible for your customers to get started.

1. UBP allows customers to start at a low cost, minimizing friction to initial adoption.

A snippet from the Acquired podcast episode on AWS:

“Every month, I get a bill from AWS for 71 cents, and I have no idea what old project it was for. It's one of these things where it's priced so dynamically. If it was a big successful project holding a lot of data, then it would be expensive.” - Ben Gilbert

Part of AWS’s success is that they made it super easy for anyone - single practitioners, SMBs and large enterprises - to get started with a credit card. You are charged next to nothing for your small project.

2. In turn, your revenue scales with your customer’s growth and success.

3. Because UBP is fundamentally a volumetric approach to pricing, you are afforded greater flexibility in pricing and packaging your product especially if your product serves a heterogenous set of customers, greatly varying in size and usage (e.g. SMBs as well as large enterprises).

4. You can incentivize higher consumption with volume-based discounts.

   When you charge $10 for the first 100 events and $5 for the next 100 events, $5 feels like a bargain.

5. UBP aligns pricing to the value delivered to customers.

   I was surprised by how many buy decision-makers that I interviewed mentioned “fairness” as a key benefit of UBP.

   If your product delivers tremendous value and everyone uses it a ton, you will be paid more. If your product is a bummer, usage will trend down, you will make less.

6. Simplify process to upgrade / downgrade without manually changing plans.

   Because nobody likes having to talk to an account manager to add the 101st user.

Why has UBP been gaining momentum?

I will highlight three, out of many, trends fueling the momentum for UBP.

1. Product-led growth (PLG)

   Gone are the days of universal top-down buy decisions. End users are trialing products, buying them with their credit card, and telling their colleagues and managers to buy.

   PLG SaaS companies rely on their product as the main vehicle to attract, acquire, activate and retain customers. Typically customers start small and grow over time.

   UBP lowers the barrier to trial, as customers can start as small as it makes sense. In turn, UBP allows SaaS companies to benefit from the upside as customers grow with them.

2. Show me your value

   Customer success, customer success, CUSTOMER SUCCESS!

   In an era where software buyers are increasingly bombarded with products that claim to make their life incrementally better, proving your product’s value needs to come before closing a sale.

   UBP lowers the barrier to trial, and allows customers to experience the value of your product on a smaller scale before ramping up usage.

3. Proliferation

   We already crossed the chasm for UBP. The 800LB gorillas that drove this? AWS, Azure and GCP.

   Cloud service providers typically charge based on the resources that you consume. While UBP has been embedded in our life for a long time (e.g. utilities), the hyperscalers really made UBP the norm in tech.

   In addition, I recently noticed that all of the large language and AI models charge based on usage.

Is your company UBP-ready?

While the benefits of UBP are compelling, not every product makes sense to be charged based on consumption, for example, if availability or “streaming” is an important feature. Taking “streaming” quite literally, what would happen if Netflix were to start charging based on each show you watch? (For one, I would be racking up a big tab.)

Even if your product is a great candidate for UBP, not every company is ready for UBP. Enterprise-wide buy-in of the UBP business model needs to happen before UBP can be implemented successfully.

To demonstrate how this impacts everyone in the enterprise:

• Pricing is one of the most important business decisions that leadership teams and product managers make.

• Engineering needs to build and maintain, or buy metering and billing infrastructure. In addition, you need a dashboard that shows real-time usage data to both customers (so that they can understand and plan their consumption) and internal stakeholders (who need this data to interact with customers).

• Accounting needs to understand the financial impact of introducing or altogether switching your pricing to UBP. They will also need to handle any changes to billing and payments.

• Customer success needs to communicate with existing customers, help them understand how UBP would affect them, and equip them with appropriate tools — so that they have real-time, high-fidelity visibility into their consumption. This is important for “trust”.

• Sales needs to consider new pricing and rewrite parts of their playbook.

A quick aside on sales: typically, software sales teams are financially incentivized to eke out as large an upfront committed spend as possible.

As you transition towards UBP, sales compensation structure needs to be updated and tied to actual billable consumption in some way. This might mean that the potential of large one-time payouts from signing up large deals is being diminished.

Changing your sales compensation structure is a huge undertaking. If handled poorly, it can result in costly consequences of talent attrition.

Challenges of UBP

1. As mentioned earlier, it lends better to some products versus others, for example:

   • If your product is sticky after initial adoption and usage generally trends up over time

   • If the consumption of your product is “event-driven”

   When you charge per seat, there is no upper bound for how much customers can interact with your product prior to paying more. A common concern for UBP is that it makes customers hyper-conscious of their consumption and limit their interactions with your product.

2. As highlighted above, UBP implementation needs to be an extremely deliberate process.

3. While preparing for this post, I spoke with the VP Product of a software start-up who said:

   “99% of my customers don’t have any problems with what we bill, but 1% of do. These people waste all my time. There’s nothing in-house I can use to investigate and fight these disputes. So I end up just letting these customers have it their way every time.”

Your metering and billing services need to hold up. Otherwise, UBP can be a headache to manage.

4. Customer success becomes high stakes. If your product sucks and customers use it less and less, there is no “fixed price subscription” that shields you (temporarily) from the financial blow.

5. Some customers still demand the predictability of fixed price subscriptions.

   In other words, “how much should I put into next year’s budget for this?”

   For existing customers, you already sit on a lot of historical data, and can drive an intelligent conversation around planning their consumption.

   For new opportunities, it can be trickier, but might not be as complex as one imagines. Customer case studies can set expectations for what a customer’s consumption could look like over time.

   Fundamentally, UBP is an opportunity offer more flexibility to customers, and can be a win-win. Can you design something where there might be 20% less predictability but perhaps 50% more exposure to share the upside? Wouldn’t this be exciting?

6. Your finance team might not love it initially. It might become more challenging to predict your revenues and cash inflows / outflows.

UBP Innovations

Some of the challenges of UBP highlighted above can be addressed through creative innovations and hybrids.

• Larger upfront commitment = larger discount

  Would you benefit from having some predictability in customers’ consumption for reasons, such as planning out your own infrastructure needs, or cash flow management? Do some customers still demand the predictability of fixed price subscriptions?

  Customers can pre-commit to an upfront spend level in return for better pricing. Any consumption above this threshold can be billed based on usage metrics.

• Usage draw-down is similar to pre-commits. The key difference is that customers choose between a monthly usage subscription or an annual allotment that can be used flexibly. With the latter, customers can protect themselves from any seasonal spikes in their usage, knowing that it will be offset by slower months.

• Commit now, pay later

  Customers have the flexibility to pre-pay or pay as you go. They receive discounts for any prepaid “credit”. Customers can choose to partially pay upfront for “credit” and pay for any overage as they go, or entirely pay in arrears.

• Credits and tokens

  In addition to standard recurring subscriptions, Autodesk offers a “Flex” pricing plan where you use pre-paid tokens to access a variety of products. Tokens can be used to access any product for 24 hours at a time, giving flexibility to SMBs and low-frequency users.

  Back in 2014, WalmartLabs was Slack’s largest single customer. A closer look of that account unveiled that of the 800 users signed up, half were inactive. In other words, WalmartLabs would have to either pay for these 400 people not using Slack, or manually deactivate them one-by-one.

  Today, Slack is well-known for its “fair billing policy” where they make pro-rated refunds for all inactive accounts.

  Not only does this enforce the notion of “fairness” that I have discovered software buyers really value, it lowers the barrier to initial adoption, because:

  “I hate buying software nobody is going to use”

How to get started with UBP?

Step 1 - Make sure UBP is right for your company, product and customers.

As highlighted above, UBP might not be right for every company, product and customers. Some guiding questions include:

• How does my competition charge? Has anyone pivoted to UBP?

• Would customers value greater flexibility?

• How sticky is my product? Does consumption grow over time?

• Is my team ready for this shift?

Step 2 - “You don’t know what you don’t measure”

Before implementing UBP, start measuring everything. Then assess which metrics track your customers’ consumption best and if these are well-aligned with the value created by your product and the costs incurring in delivering it. (You have a problem when costs scale faster than revenue!)

This might be a good time to start building your own metering and billing infrastructure, or buy from third parties (e.g. Amberflo, Octane, Metronome).

Aside: Interestingly, these UBP metering and billing companies charge all differently. Amberflo does UBP ($0.01 for 1,000 metering events). Octane charges basis points off your billing volume (like Stripe). Metronome sizes you up and charges a fixed subscription price.

Step 3 - Analytics

Make available analytics capabilities, dashboarding and usage forecasting tools to internal stakeholders and customers. UBP doesn’t work without trust, visibility and planning.

Step 4 - Pricing

Design a program that supports fair, transparent and attractive pricing.

Concluding Thoughts

I have been pondering UBP for the last 12 months, and interviewed over 10 startup executives and engineering leaders on this topic.

Over this time period, more companies have launched UBP. The level of interest in UBP among our portfolio companies has increased.

Pricing is one of the most visible parts of the customer experience. Today’s economic downturn is making pricing topical. It is pushing companies to think deeply about “how can we lower the barrier to adoption?”, “how can we make the buy decision as risk-free as possible?”, and “how can we become more customer-centric?”.

I learned through these interviews that implementation matters a lot. There is a large standard deviation on the good and bad stories about UBP implementation.

Just as a data point, apparently Twilio has over 40 engineers working on metering and billing alone.

I am encouraged by the promise of UBP as a source of competitive advantage for SaaS companies (with the right implementation and tooling), and have no doubt that 12 months from now, the software industry will look a little different because of it.

Disclaimer: I am an immigrant myself - twice over.

Let’s explore why immigrants make great founders.

Network

Who has the most valuable network in the diagram above? Jenny has the highest number of connections (five). To me, Mary is the most exciting person. She has four connections and serves as a bridge between the yellow and blue networks.

Being a bridge between two networks opens up unique possibilities. Immigrant founders often open secondary offices in the country they come from (e.g. Egypt, India, Israel, Turkey), unlocking access to a new pool of talent and lower labor costs outside the U.S.

In addition, immigrant founders can capitalize on their relationships abroad and expand customer bases across borders more seamlessly. With the cross-cultural context and understanding, they are well-equipped to balance the resource-intensive initiatives and patience to expand to new regions with the successes and immediacy of the U.S. market.

Resilience

Resilience is the capacity to recover from difficulties. Many types of life experiences can help build resilience, for example, migration. Leaving family and friends, selling your prized possessions, and moving across the world to a place where nobody knows or cares about you is a traumatic experience.

You learn to be resourceful and self-reliant in contexts characterized by many obstacles and struggles, including finding a job, learning a new language, coping with bias / discrimination, or the simple tragedy of spending Christmas alone.

In this study, migrants showed higher resilience capacity than non-migrants. Interestingly, although migrants experienced more traumatic events, the impact of trauma on mental health outcomes was greater in non-migrants. Immigrant founders are well-equipped to handle the ups and downs of building a startup (and likely to be less scarred by them).

Perspective and inspiration

While Zoom, with its $30B enterprise value today, is an obvious success story, it didn’t seem like that at first. People wouldn’t even take meetings with Eric Yuan (CEO of Zoom). Santi Subotovsky who led Zoom’s Series C and is an immigrant from Argentina said in a podcast interview,

“I had a real need. I wanted to stay in touch with my friends and family in Argentina, and I couldn’t find any technology that allowed me to have a conversation”.

Immigrants can recognize opportunities, which might not be salient to others. They have unique needs and are keen observers of their environment.

They can also import ideas from their native environment to their host environment (e.g. livestream shopping from China to the U.S.), and vice versa (e.g. Uber in the U.S. ⇒ Grab in SE Asia)

Chutzpah

Back in 2018, Daniel Schreiber (CEO of Lemonade) spoke with a group of us taking a course at Tel Aviv University.

Before founding Lemonade, Daniel looked at a bunch of industries where customer experience was terrible and chose insurance. Insurance is “such a vast industry, unloved by consumers, but used by all of them”. With no previous experience in insurance, he started with a blank slate and designed a technology-forward and customer-first insurance company, the way it should be.

From time to time again, immigrants take on challenges that others shy away from because “it is too difficult” or “it would take too long”. Sometimes you need the audacity of an outsider to do something huge.

Closing Thoughts

When I first moved to the U.S., I noticed a popular conversation starter - “Where did you go to college?”

Over time, I realized that in a country with over 300 million people, college affiliation is an easy way to dissect social networks. (e.g. “You went to MIT too? My sister-in-law was in the Class of 2005!”) and build affinity with strangers.

Many immigrants don’t come with these natural affiliations or networks that might open up doors to your first customers or partnerships. The lack of familiarity with culture, language and social cues can compound to make building a startup an especially frustrating experience for newcomers.

I believe that talent is evenly distributed around the world and opportunities aren’t. The fact that the U.S. holds cultural leadership globally and many of the brightest minds around the world aspire to come here might be the single most important competitive advantage of this country’s tech ecosystem.

Talent comes in all sorts of shapes and colors. I hope to go beyond these shapes and colors and see founders and their ideas for what they are.

I am excited to continue partnering with immigrant founders.

As investors try to differentiate their merit beyond capital, “value add” as a term gets thrown around. In this post, I break down the sources of investor value add and how founders can match themselves to the right investors.

Sources of Investor Value Add

1. Sector (or stage) expertise

These investors have a clear line in the sand delineating where they play and where they don’t. For example, Sorenson Ventures invests in early-stage (typically seed and Series A) enterprise software and security only. AutoTech Ventures specializes in the future of mobility and transport. First Round Capital focuses on seed stage funding.

These investors tend to have a sophisticated and nuanced understanding of the opportunities and challenges in their target areas. This focus allows them to deliver advice and insights highly relevant to the founders they partner with.

2. Prestige

Simply being an a16z portfolio company can unlock lots of doors. It can de-risk a company in the minds of potential hires and customers. Having a Marc Andreesen or Peter Thiel on the cap table sends a quality signal to the market, provides validation, and can help a founder sleep better at night.

3. Capabilities and resources

Some investors sweeten up the deal by offering access to specific capabilities or resources. Examples include:

• Recruiting services

• PR

• Business development

• Expert network

I have seen a couple of creative examples recently, including a firm that commits 1 percent on top of every check for “founder development services” and a firm that gives its portfolio companies access to a network of thousands of PMs and “a playbook to turn them into customers”.

How do you pick the investors with the “best value add”?

1. Sector (or stage) expertise triumphs everything.

There is no universal right or wrong answer to most questions in the world. In this case, I firmly believe that sector (or stage) expertise should come first.

Yet surprisingly, Forward Partners’ More Than Money Report discovered that 47% of surveyed founders believed their investors had little to no knowledge of the sectors they are investing in.

The investor will sit on your board and have a say in the most important decisions of your company. You want someone who is thoughtful, understands the opportunities and challenges in your market, and can share with you relevant and distilled strategic insight. Otherwise, it can be an extremely frustrating experience.

The most valuable asset that sophisticated investors bring is “pattern recognition”. Even experienced founders might have only seen something once or twice. An investor has accumulated patterns across dozens or even hundreds of companies. Working with an investor with deep sector (or stage) expertise means that you will have access to the most relevant patterns and case studies.

2. Will you pick up my call when I need you?

According to Forward Partners' More Than Money Report, three-fifths of founders described their value-add experience as “negative” compared to what their investors claimed to offer. A third (33%) feel that value-add is “over promised and under delivered”.

Investors tend to be a self-promotional breed. They will show up in the fanciest Patagonia sweater to win your heart... but will they pick up your call when you need them?

Based on what I see, most founders could do way more due diligence on their investors before signing on the dotted line. The firm’s structure, investment strategy, and portfolio construction, for example, can significantly impact your experience working with the investor.

Does your investor make 30+ investments in one fund (a.k.a. spray and pray), and have a tiny team? They might not have enough resources to allocate among portfolio companies.

Are you working with a high-profile investor that already sits on 12 boards? Have realistic expectations about how much time they can devote to you.

Borrowing Fred Wilson here:

Encourage the entrepreneur to get feedback on you and your firm. Instead of references, I like to give a list of every entrepreneur I’ve ever worked with and an email address. I tell them “throw a dart at that list and talk to four or five of them randomly. you’ll hear the same thing from everyone.”

3. First-level thinking founders overvalue prestige.

Sophisticated founders know how to decouple investor value add from prestige.

There is a strong breed of VCs not as glamorous from the outside as a Sequoia, but they are a great, trustworthy, sharp group of people. They are thoughtful about whom they partner with and invest heavily into setting their portfolio companies up for success. When I am thinking about co-investors and doing introductions for my founders, these are the people that come to my mind.

Founders should think honestly about what value add would benefit them most, and pick their investors accordingly.

Concluding Thoughts

I read through the websites of many VCs that I know in real life and some that I don’t while preparing this post. Although capital is abundant, I still see a high heterogeneity in how different VCs define their value add.

Because investors promise different types of value add, they allocate their time differently, too. There are some who are focused on building thought leadership and brand. There are others who spend their day bending over backwards responding to fire drills in their portfolio companies.

Founders should self-select and work with investors based on what they value.

On a related note…

I am unbelievably excited to embark on a new adventure and join the all-star team at Sorenson Ventures. What especially impresses me about this team is the depth of knowledge and experience, and the relentless focus on forging a meaningful, long-term partnership with founders.

When Sorenson invests its capital, we are also investing our commitment, dedication, and energy. We are serious about our work. We spend a lot of time discussing what kind of partner we want to be and executing on these aspirations.

All investors claim that they are looking for founders working on “original” or “disruptive” ideas, but when the time comes to write a check, many sit on the sidelines. My colleagues Ken Elefant and Rob Rueckert created Sorenson Ventures to address the funding gap that many early-stage founders and startups face as they try to validate product/market fit and define scalable and repeatable growth models. I firmly share their ambition in enabling early-stage entrepreneurs working on the most innovative and disruptive ideas.

I will continue to focus on early-stage enterprise software and security in my new role. I also want to make it a priority to partner with founders who are working on disruptive ideas and/or often don’t fit the Silicon Valley mold.

Disclaimer: The views expressed herein are the author's alone and do not represent views of any organization or employer the author is currently or was previously associated with.

Exhibit A: GitLab's share price performance

Source: CapitalIQ

I dive into GitLab's S-1 with a customer analytics lens.

Disclaimer: The following work is created and authored by me and is published and provided for informational and entertainment purposes only. The information below constitutes my own opinions. None of the information below constitutes a recommendation for any particular security.

Exhibit B: GitLab's Top Line Growth

Source: GitLab S-1

GitLab's top line growth has been impressive - a 15% CAGR in the last five quarters. However, this particular chart doesn't reveal anything about underlying cohort behavior.

Exhibit C: Cohort ARR

Source: GitLab S-1

Note: The cohort for a given year represents customers that made their initial subscription purchase in that year. GitLab's fiscal year ends on January 31. For example, the 2018 cohort represents all customers that bought their initial subscription between February 1, 2017 and January 31, 2018.

This is my favorite chart in GitLab's S-1. GitLab's 2015 customer cohort, which started with a minuscule revenue, generates over $25M of ARR currently. This is partly the power of the land-and-expand model. GitLab explains in its S-1,

"We employ a “land and expand” business strategy that focuses on efficiently acquiring new customers and growing our relationships with existing customers over time. We believe that as our customers realize the benefits of a single application approach, they will increase the use of The DevOps Platform, enhancing our ability to expand revenue generation within our existing customers over time. As a result of our approach, our Dollar-Based Net Retention Rate was 179% and 148% for fiscal 2020 and fiscal 2021, respectively. As of July 31, 2020 and 2021, our Dollar-Based Net Retention Rate was 153% and 152%, respectively."

GitLab offers a free tier, which encourages initial adoption of its product by developers. After overcoming the initial hurdle of adoption by perhaps an individual or several members of an organization, usage expands across teams and up to managers and executives who want additional features and therefore buy GitLab's paid Premium and Ultimate tier packages. It is also worth noting that GitLab was founded only 7 years ago and continuously adding new features to its plat in addition to geographic expansion, leading to more revenue opportunities.

At a first glance, GitLab's customer cohorts are doubling and quadrupling revenue every year before moderating to a stable growth rate seen in the 2015 cohort for example. My first hunch is that 1) GitLab likely has a long-ish CAC payback period 2) but that is okay, because each cohort stays with you a long time, generating a long, fat tail of cash flows.

Let's put GitLab's retention rates in context.

Exhibit D: Gross Retention Rates

Source: Sammy Abdullah at Blossom Street Ventures

Dollar-based gross retention represents how much revenue you lost to churn or downgrades. In GitLab's case, 97% of ARR on January 31, 2019 remained a year later on January 31, 2020. Impressive that only 3% of ARR was lost to churn and downgrade.

I like gross retention, because it shows how sticky your business is in raw terms. While most publicly traded SaaS companies report net retention, far fewer companies disclose gross retention. Presumably, companies opt not to disclose these numbers, unless they make them look good. Even benchmarked against these companies that opt in to disclose it, GibLab's retention appears competitive. GitLab's 97% gross retention benchmarks favorably to the peer group average of 95%.

Let's look at this a different way: net retention. Net retention is starting ARR + upgrades - downgrades - churn. This is a key metric for valuing SaaS companies.

Exhibit E: Net Retention Rates

Source: Sammy Abdullah at Blossom Street Ventures

Based on the above, a top quartile company's net retention at IPO is 120+%, with the median being 111%. GitLab's 12-month retention as of January 31, 2021 was 148%. GitLab continues to look great relative to peers.

While my favorite chart (Exhibit C) was helpful in drawing early insights, I'd like to work with numbers. Let's rely on the old art of pixel counting and recreate Exhibit C.

Exhibit F: My Favorite Chart Reproduced

Pretty close, right?

Acknowledging the imprecision introduced from pixel counting, the total ARR in 2020 is $101.5M. The total ARR from customers acquired in 2020 and before is $152.5M in 2021. The % increase is 50%, which roughly goes around with the S-1's quoted dollar-based net retention being 148%. The two percent difference is the margin of error from counting pixels.

Similarly, the total ARR in 2019 is $48.0MM. The total ARR from customers acquired in 2019 and before is $85.5M in 2020. The % increase is 78%, which roughly goes around with the S-1's quoted dollar-based net retention being 179% for this period. The one percent difference is my margin of error from counting pixels.

Now we know the numbers from pixel-counting are somewhat reliable, let's change the stacked area chart into a line graph by left-shifting each cohort.

Exhibit G: Cohort ARR

Except for the year 2017, every cohort's ARR line starts above the preceding year's cohort (except 2017). Also every line has a positive slope.

This growth pattern becomes more evident when each cohort's ARR is indexed to its first year.

Exhibit H: Cohort ARR Growth Over Time Indexed to the First Year

This shows the ARR growth of each annual cohort indexed to 1x. Since the 2015 cohort, which started at $1M and has grown to $37M by 2021, is going to the moon, I take the grey line off to observe the other years better.

Exhibit I: Cohort ARR Growth Over Time Indexed to the First Year (excluding 2015)

While the size of each ARR cohort is increasing, the growth of each successive cohort is also moderating, as shown in the decreasing slope from 2017 to 2019.

GitLab acquired its first $100,00 ARR customer in 2017 and its first $1M ARR customer in 2019. In 2020, the company formed its enterprise sales team and established partnerships with AWS and GCP in addition to key national system integrators and resellers. It is easier for caterpillars to double in size than whales. It makes sense that the growth profile (in multiple or percentage terms) of each successive cohort is moderating while presumably the average ARR per acquired customer trends up.

Exhibit J: Account Size

GitLab does not disclose the total number of customers. It only discloses "Base Customers", defined as customers generating $5,000 or more in ARR. This is understandable, given GitLab offers a free tier, which probably produces a long left tail of customers. The number of Base Customers is only available for the fiscal years 2020 and 2021. I divide ARR by the number of Base Customers for each year, resulting in approximately $61,000 and $64,000 for the fiscal years 2020 and 2021 respectively. Remember that this is overstated, given the denominator excludes customers generating less than $5,000 in ARR.

As shown below in Exhibit K, a Premium user pays $228 per year, and an Ultimate user pays $1,188 per year. S-1 doesn't provide information to allocate the $64,000 ARR per customer among Premium and Ultimate users. In other words, I'm not sure if an average account is comprised of, for example, 53 Ultimate users, or 30 Ultimate users plus 124 Premium users.

Exhibit K: GitLab Pricing

Exhibit L: Customer Acquisition

GitLab acquired its first $1.0M ARR customer two years ago in 2019. It currently has 27 customers generating $1.0M or more in ARR. As customers in the free tier convert to paid subscriptions and GitLab invests more resources in enterprise sales, I expect the average revenue per customer to continue trending up.

Exhibit M: Customer Base Breakdown

As shown in Exhibit M, GitLab's overall customer base is comprised of lots of small accounts (generating ARR below $100,000).

Overall, I am very impressed by GitLab's ARR growth, but how profitable is this?

Because we don't have all the numbers that we need from public disclosure, here are a few simplifying assumptions to facilitate some math:

• 100% of GitLab's sales and marketing costs are to acquire paying customers. In fact, some of the sales and marketing would target customers in the free tier and existing customers. This would result in a somewhat punitive CAC.

• All of GitLab's customers are Base Customers ($5,000 or more in ARR).

• 85% customer retention rate

GitLab spent $154M in sales and marketing expenses for the fiscal year ending January 31, 2021. Given these assumptions, GitLab's customer acquisition cost for the year was approximately $115,680. The sensitivity table below shows how GitLab's CAC could change if we tweak assumptions on sales and marketing costs and retention.

Exhibit N: GitLab's Approximate CAC

From the stacked area chat that I reproduced (Exhibit F), we know that the customers acquired between January 2020 and January 2021 were generating approximately $23M of ARR at the end of January 2021.

I extrapolate the ARR of the 2020 cohort forward a couple of years using preceding cohorts' ARR growth rates. Applying GitLab's healthy contribution margin of 88%, the contribution margin from the first three years of the 2020 cohort add up to $140M. Given GitLab's sales and marketing spend of $154M for the fiscal year 2021, the CAC payback is slightly over three years.

A three-year CAC payback is a disappointing number on its own. Does this mean that GitLab's growth is less than profitable?

The short answer is no. Although CAC payback seems slow, GitLab shows such a stellar dollar net retention. Continued growth from maturing cohorts generate strong cash flow.

Exhibit O: My Favorite Chart Again

How profitable? I make a couple of assumptions to calculate LTV / CAC:

• The 2020 cohort's spend increases at the same pace as the 2016 cohort, before moderating to YoY growth of 20% or less in the long term.

• 88% contribution margin

Exhibit P: Profitability (truncated)

IRR is a whooping 57%! This is far above GitLab's cost of capital. This has to be a high number to cover GitLab's fixed costs and overhead, and it is. LTV-to-CAC is a healthy 4.3x. A healthy LTV-to-CAC ratio is usually around 3x to 5x.

Concluding Thoughts

Without more disclosure, it would be impossible to perform a comprehensive and accurate customer-based corporate valuation. Especially with these assumptions that I make for simplicity or to facilitate calculations, the numbers in my analysis are meant to guide insights not precision.

Nonetheless, the key takeaway stands. GitLab's land-and-expand sales strategy and strong customer retention feed a flywheel that harvests profitable economics from existing customers, which in turn are re-invested in acquiring new customers. As a result, here is a company that doesn't look great on net income given large sales and marketing spend. However, in the long term, customer economics are very profitable.

TLDR

• SPACs are highly idiosyncratic

• It is an incredibly expensive way to go public (AND I'LL SHOW YOU THE MATH on the Social Capital - Opendoor transaction)

Introduction

Special Purpose Acquisition Companies (SPACs) are flooding the headlines in recent months, as a record high number of these “blank check” companies have raised capital and publicly listed their shares. For companies wanting to go public, SPACs have emerged as a popular alternative to traditional IPOs and direct listings.

[Exhibit] SPACs are the talk of the town

Why are these companies going public via SPAC mergers, versus IPOs?

There is a plenty of great literature on the mechanics of SPACs. If you want to get up to speed on this topic, here is a couple of great sources to check out:

https://techcrunch.com/2020/08/21/almost-everything-you-need-to-know-about-spacs/

http://abovethecrowd.com/2020/08/23/going-public-circa-2020-door-3-the-spac/

Perhaps Bill Gurley of Benchmark Capital is the most vocal critic of IPOs in Silicon Valley.

“The traditional way of going public is systematically broken and is robbing Silicon Valley founders, employees, and investors of billions of dollars each year.” – Bill Gurley, Benchmark Capital

The public misleadingly perceives the “pop” on the first day of trading after an IPO as a positive. On the contrary, this represents an underpricing, which comes at a cost to the company and existing shareholders. Rewards, which should have rightfully gone to founders, employees and existing investors who built the company and stuck through all the ups and downs for years, are being transferred to investors who just bought the stock through the IPO a day ago. No homeowner should sell his or her house 31% below market. Companies shouldn't either.

[Exhibit] IPO “pops” come at a cost to the company and existing investors

According to the research of Jay Ritter at the University of Florida, an average company that went public in the first half of 2020 was underpriced by 31%. Given that offering expenses range around 5% to 7% of the IPO size, the cost of capital from IPOs equates to over 36% (5% + 31%).

Bill Gurley argues that the traditional IPO process, which involves one-on-one meetings between the management team and select institutional investors and a manual allocation process by the underwriters’ ECM desks, robs value that should have gone to the company's founders, employees and existing investors. For this reason, Bill Gurley asserts that companies should consider direct listings and SPAC mergers as an alternative to traditional IPOs as a more efficient route to achieve liquidity.

How does a company go public via a SPAC?

The target company, which merges with a SPAC to go public, essentially negotiates a merger transaction with the SPAC’s management team. This could mean a greater certainty on proceeds and timing than a traditional IPO where the pricing happens hours before a company lists on the exchange, and the offering can be pulled or postponed anytime if market conditions were to deteriorate.

While many of Bill Gurley’s criticisms are well-founded, I would hesitate writing off traditional IPOs entirely as being “broken”. This sentiment is concurred by Josh Kopelman at First Round Capital.

“I'm not sure I'd argue that … (IPOs are) broken. I actually think that you are seeing far more companies exit, and we have seen a real acceleration in both the number of exits and the size of those exits, which I think is a promising thing. I think there is a benefit to the transparency the public market shines on a company, because that's how you could truly lock in a value. We've all seen companies that have garnered valuation x in the private markets only to find out it's not a true representation of the company's ultimate value when it was fully transparent in the public markets. So I think the IPO process is a healthy process in general and over the last two years we have seen an incredible acceleration.” – Josh Kopelman, First Round Capital

In response to the market’s increasing interest in alternatives to traditional IPOs, the SEC recently approved a new type of direct listings on the NYSE. It will allow companies to issue new stock (known as a “primary offering”). Historically the NYSE had allowed existing investors to sell shares in a direct listing (known as a “secondary offering”), but companies could not raise new capital.

Is going public via a SPAC truly cheaper than an IPO?

The short answer is that “it depends”. In any case, going public via a SPAC can be deceptively costly. Let me demonstrate this point using the Social Capital Hedosophia II – Opendoor transaction as a case study.

Social Capital Hedosophia II (“IPOB”), one of numerous blank-check companies associated with investor Chamath Palihapitiya, announced that it will merge with Opendoor, taking the private real estate startup public in the process.

[Exhibit] Social Capital Hedosophia II Trading History

IPOB’s IPO was completed on April 30, 2020 at $10/unit. Each unit was comprised of one common share plus one-third of a warrant exercisable at $11.50/sh.

The merger between IPOB and Opendoor was announced on Spetember 14. The news was favorably received, with IPOB’s share price popping and closing at $17.58/sh on September 15, approximately 62% higher than IPOB’s average closing price of $10.88/sh during the month of August. The stock has traded up since, and closed at $26.48/sh today (as of October 14, 2020).

The economics of the deal were fixed prior to announcement, pinning the value of Opendoor at $5.0B, which equated to approximately 500MM IPOB shares being issued to Opendoor investors. The share price appreciation since merger announcement benefits Opendoor shareholders who will be allowed to sell their shares in 6 months (probably sooner).

[Exhibit] Promote to Social Capital and related parties

Social Capital and its related parties (“the sponsor”) owned 20% of the pre-merger IPOB, having paid $0.0024 per share. This contrasts with $10 per unit (including a fractional warrant) that public shareholders paid in the IPO. I see the lack of paid-in capital by the sponsor as a potential source of misalignment between the sponsor and third-party investors. In the end, Social Capital’s ownership percentage was diluted down by 500MM IPOB shares being issued to Opendoor investors. Nonetheless, the sponsor was able to capture a whopping $621MM in gains.

Sponsor promote is not the only source of "leakage". Prior to public announcement of the merger with Opendoor, Social Capital approached select institutional investors who under NDA became privy to the details of the transaction and were offered an exclusive opportunity to buy IPOB shares at $10/sh. This is generally referred to as a PIPE transaction (private investment in public equity). These PIPE investors were able to buy IPOB shares with the knowledge of the Opendoor transaction significantly below the merger announcement-affected share price ($17.58/sh on September 15).

[Exhibit] Underpriced PIPE

[Exhibit] Total Leakage

Aggregating these figures, the total “leakage” that comes at a cost to Opendoor shareholders from transaction fees, management promote and PIPE underpricing was $1.3B, or 9% of IPOB-Opendoor’s pro-forma enterprise value.

While this 9% leakage from the mechanics of going public via a SPAC is smaller than the typical IPO underpricing quoted in Jay Ritter’s research, the dollar figure ($1.3B) makes me scratch my head.

Other Concerns

Usually the management team of a SPAC has two years to find and transact with a target company. Given the latest explosion in SPAC IPOs, there is a lot of capital chasing acquisition targets. Anecdotally, A LOT of growth stage companies that I spoke with over the last couple of months mentioned being in merger discussions with SPACs. In some cases, this made sense. In many cases, I was deeply skeptical about their investment worthiness and preparedness as a publicly traded entity.

There is a tangible risk that some SPACs might not be able to consummate an acquisition and would be dissolved after two years. Worse yet, it might create perverse incentives for the management teams of SPACs to pay an unjustifiably high price to consummate a transaction, or accelerate the acquisition process without proper due diligence.

This concern is perhaps embodied in the following example. Nikola Corporation is under investigation by the Department of Justice and SEC after a well-known short seller Hindenberg publicized potential fraud allegations (link). Based on its SEC filings, VectoIQ Acquisition Corp., the SPAC that merged with Nikola Corporation, went from a first meeting (November 25, 2019) to the signing of transaction documents (March 2, 2020) in three months, an exceptionally short timeframe of due diligence for a transaction of this size. The merger proposal was publicly announced on March 3, 2020. Back in my days in investment banking, a deal of this scale usually involved four to six months of intense due diligence and negotiations. VectoIQ Acquisition Corp. went public in May 2018, and was due to be dissolved in May 2020. Could VectoIQ have cut corners in fulfilling its fiduciary duty under time pressure?

[Photo] Troubled former Nikola executive chairman Trevor Milton stands next to a truck at Nikola World 2019

(Photo Source: CNN)

A few years back, SPACs had the reputation of being run by sub-par quality management teams. It also remains to be seen whether some of the individuals who have been successful in raising SPACs are sufficiently qualified and experienced to deliver a satisfactory outcome to shareholders. I believe that this is one of the reasons why the market has recently seen a few SPAC IPOs, which were downsized or are subsequently trading below IPO prices in the markets.

Concluding Thoughts

I am always excited to see more options being made available to companies that want to go public. While the SPAC vehicle is not a new invention in any way, I see the rising popularity of SPACs as a generally positive development in capital markets. However, SPACs are far from being a perfect solution. In fact, they usually come with a complex list of governance challenges and deal leakage.

[Photo] Bill Ackman is hunting for a "mature unicorn" after launching his SPAC, Pershing Square Tontine Holdings

(Photo Source: Bloomberg)

These concerns are not lost on the SPAC community. Pershing Square Capital Management founder Bill Ackman is trying to build the "most investor friendly SPAC in the world" through the newly launched Pershing Square Tontine Holdings. No, he is not buying a bunch of founder shares pre-IPO at $0.0024 each. Pershing Square Funds are in fact purchasing at minimum an aggregate of $1B of units at $20/unit, the same price that the public paid in the IPO. The performance of Pershing Square Tontine Holdings remains to be seen. Nonetheless, I view these experiments and innovations as being essential to the continued proliferation of the SPAC market.

As an investor, I would be encouraging the companies that I am involved with and are thinking about going public to consider all the options (e.g. IPO, direct listing, SPAC merger) on the table before deciding on an optimal path forward.

Views expressed in this post are of my own. These do not represent views of any organization or employer I am currently or was previously associated with. The math presented in this post is for illustrative purposes only and subject to reasonable but simplifying assumptions.

Continuing from Part 1, here I share my personal outlook on the future of telehealth.

Outlook

1) Telehealth is here to stay

There were temporary measures put in place by Centers for Medicare & Medicaid Services (CMS) and other payers to make it easier for providers and patients to use telehealth. How many of these become permanent would influence how much of telehealth sticks around post-COVID-19. It is generally difficult to take something away from people. Patients have now experienced the convenience of telehealth, and will continue to demand it. For this reason, I believe that a fundamental behavioral shift has already taken place. Telehealth is here to stay.

Exhibit A. The share of telehealth visits at Duke Health has increased from <1% of total visits to 70% of total visits

(Source: Journal of the American Medical Informatics Association, 27(6), 2020, 957–962)

2) There is room for multiple winners

Health care spending is almost 18% of the U.S. GDP. Given the size of the market and the heterogeneity of needs and problems in this space, I believe that there is room for multiple telehealth companies to succeed. Not a winner-takes-it-all market. For example, Ro is a telehealth start-up that powers Rory for women's health and Roman for men's health. Ro’s monetization model is based on its proprietary drug catalogue, online pharmacy services and tech-savvy UX/UI. Ro’s services, products and medication are not covered by insurance. This would attract and serve a different segment of the population from the likes of Amwell or Teladoc.

3) Amwell is well-positioned for success

Amwell, an LG Technology Ventures portfolio company, is and will continue to be a leader in health care innovation. There are many aspects of Amwell’s strategy that comes across as being extremely thoughtful. One is that Amwell has focused on building an ecosystem. Any health care innovation depends on the cooperation of multiple stakeholders, including patients, insurers, employers, providers, physicians, medical device companies and pharmacies.

4) Greater roles for technology in health care

A primary care physician once told me that on a typical winter day, his interactions with the majority of patients are surprisingly uniform. They have some combination of flu symptoms, and he prescribes the same set of medications. Of course there is a lot of complexity to the science of medicine being over-simplified here. However, given the looming physician shortage and the trend of the increasingly aging (and sicker) population in the U.S., technology can play a greater role in providing care at scale.

For example, there can be a greater use of algorithmic triage or AI. Before a patient sees the doctor, she fills out a questionnaire where the AI dynamically adjusts questions to dig deeper into the answers being provided. In return, the AI suggests a certain diagnosis to the physician who can confirm or reject it through one-on-one interaction with the patient.

Exhibit B. Technology, especially AI, will continue to play greater roles in health care

(Image Source: Bruno Mangyoku)

Conclusion

COVID-19 has affected our society, economy, community and health care system in fundamental ways. While the scars of COVID-19 are far from being the past and history is being written as we speak, I am amazed by the strength of the human spirit – the adaptability of people who are persevering. It includes health care workers sweating in multiple layers of protective equipment day and night, drive-through testing centers popping up, gig-workers delivering groceries to people’s doors, and the small nail saloon down the street from my home that set up tables outside. It is times like this where the humankind tries new solutions, accelerating the pace of innovation. Telehealth is one of the most important “experiments” in health care underway.

Views expressed in this post are of my own. These do not represent views of any organization or employer I am currently or was previously associated with.

(Source: iStock)

My first encounter with health care dates back to high school when I volunteered in the Pediatric Urgent Care unit of Trillium Health Centre. While I was very impressed by the standard of care at Trillium, there were a few problems that bewildered me. Working parents rushed home to bring their sick kids to the general hospital, because there was limited urgent care available outside 9 to 5. Patients of varying ages, infants to teenagers, with coughs, a suspected ear infection or fever sat in the waiting area for 2 to 3 hours to see a doctor.

Over the years, I continued to have more meaningful interactions with health care. I attempted my own telemental health start-up, worked at a medical device start-up at the Perelman School of Medicine, and currently study health care as a venture capital investor. I have met many people working on noble aspirations and innovating health care. Especially, I am excited that many problems in health care are being solved by telehealth, and my team at LG Technology Ventures participated in Amwell’s recent $194MM funding round (press release).

Here, I would like to share what excites me about telehealth.

Why does telehealth make sense?

"Telehealth is the use of digital information and communication technologies, such as computers and mobile devices, to access health care services remotely and manage your health care. These may be technologies you use from home or that your doctor uses to improve or support health care services" – Mayo Clinic

1) Accessibility

Telehealth helps address accessibility issues. On the recent Freakonomics Radio episode on telehealth (link), Dr. Ellimoottil at Michigan Medicine explains:

“We’re seeing patients from all over the state who sometimes travel four hours just to have a 15-minute consultation about their kidney stone. And to be honest, I probably knew the answer about how I was going to manage that patient when I looked at their C.T. scan”.

Telehealth enables rural patients to interact with their care providers without spending hours traveling to and from the doctor's physical location. This is important for patients in a variety of circumstances: low-income patients who might be sacrificing a day’s worth of wages to travel for a doctor’s visit, elderly patients who might depend on others for transportation, or patients who have to put themselves at great danger traveling during challenging weather conditions (perhaps I feel compelled to add this due to my experience living through blizzards in Canada).

Convenience and accessibility are also highly valued by urban patients. Many of my friends, otherwise healthy in their 30s and 40s, postpone trips to the doctor because of the inconvenience of traveling or taking time off work. These conditions, which might have been mild at the start, often worsen over time in the absence of timely medical attention.

Exhibit A: Patient attitude towards telehealth by age group

(Source: Amwell, Barclays)

2) Reducing Disease Spread

Telehealth can help keep immunocompromised patients out of hospitals or clinics where they might contract other illnesses or diseases. Conversely, patients with infectious diseases can be kept out of hospitals or clinics to control cross infection while still being cared for. In U.S. hospitals, cross infection affects approximately 5% to 10% of patients, costing over $4.5 billion.

3) More Efficient Delivery of Care

Health care is the ultimate operations problem, and telehealth is the perfect opportunity for pooling. How do you staff enough physicians in every population center, big and small, around the country and ensure a certain service level at all times? If there are fewer sick patients in San Francisco and more in San Diego in a given day, some San Francisco physicians can see San Diego patients via telehealth. Using pooling and the flexibility afforded by telehealth, you can ensure a higher service level (e.g. shorter patient wait times) with the same or fewer resources in the overall system.

Exhibit B: Much like the manufacturing example below, flexibility afforded by telehealth can enable optimization of physician resources (or "utilization") and more patients served (or "sales")

(Source: Professor Hummy Song, Wharton School)

Risks and Challenges

1) Care

Since the interaction is virtual, there is a limit on the types of care that can be provided through telehealth. The doctor cannot listen to your lungs or perform an ultrasound virtually (yet). Nonetheless, telehealth is still valuable as a triage process to determine which patients need to be seen in-person. Consults and routine follow-ups that happen to be almost entirely verbal in nature are most conducive to being converted to telehealth.

2) Physician Reimbursement

Dr. Daniel Horn, a primary care physician at Massachusetts General Hospital explains the importance of telehealth interactions with patients:

"I made 30 such calls last week to people living alone, struggling with food insecurity or grappling with mental health issues. These were some of the most meaningful conversations of my career. Our primary-care teams have undoubtedly saved many lives with the telephone surveillance, which takes about 30 percent of our doctors’ time and nearly all of our nurses’ time" (link).

Unfortunately, physicians are not necessarily being reimbursed by payers for this big chunk of time spent on follow-up telehealth calls. Physicians need to earn a living and cover many costs, depending on the structure of their practice, such as wages for nurses and other staff, equipment, and rent. A national survey of over 2,600 primary care physicians conducted in April by the Primary Care Collaborative found that “financial strain on primary care practices is impacting their ability to keep staff employed and doors open” (link). We have to find a financial model that works for everyone.

3) Regulation

Centers for Medicare & Medicaid Services (CMS), the largest payer for health care in the U.S., has expanded telehealth coverage on a temporary basis, including cutting back on HIPAA enforcement, reimbursing telehealth services at parity with in-person visits, and letting physicians practice across the country, versus state-by-state. Regulation changes after COVID-19 will affect the shape and form in which telehealth exists going forward.

According to NCBI, the length of an average in-person doctor’s visit was 17.4 minutes. I have encountered telehealth start-ups that claim to take inefficient time out of a physician-patient interaction using technology, resulting in an average visit being only 2 minutes. This is probably not an apples-to-apples comparison. Nonetheless, if the average length of a telehealth visit is indeed shorter and there are fewer “services” performed (e.g. a physician cannot use the otoscope to look inside your ear in a telehealth visit), is there an argument for reducing the reimbursement level for telehealth visits? Alternatively do we need a different reimbursement model altogether in light of the financial strain on primary care practices discussed earlier?

Coming Soon

In Part 2, I will share my outlook on the future of telehealth. Please stay tuned.

Views expressed in this post are of my own. These do not represent views of any organization or employer I am currently or was previously associated with.