SaaS, Loops, and Aggregation: How Some Companies “Morph” and Unlock Access to New Billion Dollar Problems
Just as a caterpillar becomes a butterfly, some companies are capable of incredible transformation. At their start, they address a seemingly small or straightforward problem. But, in solving that problem, they unlock access to a greater one—building a more critical and profitable product in a bigger addressable market.
Companies that do this go through a type of metamorphosis.
Many companies grow and evolve over time, but only some of them are capable of undergoing a quick and dramatic transformation when certain requirements have been met. These companies — let’s call them “morph” companies — are particularly well positioned to unlock access to big hairy problems, many of which represent billion dollar opportunities.
Examples include Plaid (most recently valued at $13.4B) and Segment (acquired by Twilio for $3.2B). Many are found in SaaS, due to the complexity of the industries and the fact that many more niche opportunities exist (i.e., they don’t require the same scale that consumer businesses often do). Many of them are just getting started today.
What makes them different?
In tackling their first problem, morph companies establish a flywheel (or loop), where they aggregate suppliers and data. This loop establishes the foundation to address problems that were nearly unreachable previously. The transition is quick and dramatic, rather than a slow evolution.
Sequential Problem Solving
Companies that go through this metamorphosis get access to entirely new line(s) of business/revenue as an essential byproduct of solving their first problem. The core value proposition of the company may even change altogether because the next problem may be orders of magnitude more valuable than the original.
As a former industry analyst, I first observed this with Tealium. Tealium may not be a household name, but as of a few months ago it was valued at $1.2B.
Morph companies have something in common: they enable access to the next solution through aggregation (of suppliers and data), often in disjointed industries.
It should be no surprise that a growing number of these companies are data-focused or API-first, like Plaid:
Plaid provides the “connective tissue” between fintech services and banks. Apps like Betterment, Robinhood, and Coinbase don’t have to set up and maintain connections with hundreds of banks (an otherwise messy, fragmented industry) to let users quickly connect their bank accounts. By providing this critical fintech infrastructure, Plaid becomes a gatekeeper and gets a whole lot of data. Already, that has opened up additional revenue opportunities via expanded use cases like lending products. Plaid could also potentially sell analytics products in the future, similar to what Stripe has done. (Note: Stripe is not an example of a morph company; they went after the truly hard problem from the start.)
Financial services, Healthcare, Construction, Shipping, and other disjointed, sometimes regulated, frequently opaque industries are especially ripe for these kinds of businesses to have outsized impacts.
Keith Rabois has described something similar as a “formula for startup success”:
Packy McCormick has a great writeup on TrueWork, which has raised $45M to date:
“Starting with employment and income verification, Truework is building a digital-first credit bureau that makes it faster for consumers to apply to loans, apartments, jobs, and more, while maintaining privacy.”
“…employment and income verification is a wedge into a much bigger opportunity: to become the verified identity layer for the internet.”
Some morph companies, as TrueWork has the potential to be, use a wedge (i.e., a small entry point to an existing market with one or more incumbents). But companies using a wedge approach don’t necessarily end up morphing. Successful wedges lead to expansion, but they don’t necessarily lead to a rapid transformation. Also, not all morph companies go after established markets—some address relatively new problems in entirely new markets.
A wedge is sort of like a Trojan Horse: useful when you need to take a fortified city, but not necessarily in building a new one. Often morph companies have to be city-builders (or “worldbuilders”).
Loops Lay the Groundwork for Metamorphosis
I think it’s fair to say, as Kevin Kwok loves to do, that companies successful in the long run “can repeatedly find the next loop.”
Generally, “the next loop” for a company stems from a benefit of some previous loop, like an existing customer base, or a solution that is transferrable to another use case. Pursuing the next loop is then easier to some degree than it would have been otherwise.
As a point of distinction, the sequential loop for morph companies is only possible because of the previous loop. That is, if the first loop is successful, it allows the business to solve a different, previously unsolvable (or at least much more originally challenging) problem and the next loop is essentially a natural byproduct.
Today a single, effective, data-driven loop might look like this:
Each layer adds increasing value to the customer, makes the product itself better, reduces acquisition costs, and helps create a moat. But the real trick is when one loop naturally leads to the next, through the aggregation of suppliers, data, or both:
It’s effectively a bottom up approach: solving a simpler problem first unlocks access to the next one, which is otherwise (relatively) inaccessible.
Aggregation is Efficient
Let’s look at why aggregation is so important to morph companies.
First, some context. Aggregation Theory as a framework was created to characterize specific types of internet-age consumer businesses. While B2B does not have the same potential scale or zero-marginal-costs as B2C, the efficiencies can still be extremely large and therefore comparable. The core elements of aggregators apply: 1. direct relationships with customers, 2. modularized suppliers, and 3. minimal/decreasing acquisition costs.
In B2B, the aggregation of suppliers can create direct opportunities and/or indirect ones through associated data collection (as in the Tealium example above). Most solve a problem on the demand side first, but from there they may address the supply side next.
Cloud marketplaces like Salesforce AppExchange and AWS Marketplace have also become aggregators (and in a big way), but they backed into those based on ecosystems that were built around their own product after the fact. That’s an evolution (slow, reactionary), not a metamorphosis (fast, substantial).
One other key difference between morph companies and aggregators is that the former don’t have a direct route to become the latter. For aggregators, the focus is on the network from the outset, even if they do adopt a “come for the tool, stay for the network” approach. So while morph companies and aggregators aren’t synonymous, Aggregation Theory is helpful in framing their potential.
Mo SaaS, Mo Problems… Mo SaaS?
Let’s look at one relatively new area where we can see some examples of morph companies. The proliferation of SaaS companies (over 20,000 in Crunchbase) has introduced entirely new challenges. Many of those challenges are now being solved by… yet more SaaS companies (ooh, meta).
This cohort of “SaaS solving problems caused by so much SaaS” can be broken into two groups: one group serves SaaS vendors, while the second serves SaaS customers. It’s in the latter where we see several morph companies, some of which are still very young. Below are a few examples, most of which already integrate with hundreds or thousands of their respective “suppliers”:
Customer Data Platforms (CDPs)
A number of Customer Data Platforms started as solutions to manage and unify data from disjointed marketing tools (e.g., web analytics, retargeting, marketing automation, etc.). That laid the groundwork to get unified user/customer profiles and detailed insights into customer journeys, enabling much greater segmentation and personalization.
Examples: Segment, Tealium
SaaS Management Platforms (SMPs)
By providing a solution for IT to manage hundreds of SaaS vendors (license renewals, seat management, etc.), SMPs conveniently collect data about who uses which tools, how/when they’re used, which tools are complementary or redundant, and even which individual features are used. So while one initial value prop is minimizing excess spend by rightsizing contracts, the data also enables recommendations related to internal efficiency like, “which tools/features are being used by our top people in each department?” And that’s only on the demand side; on the supply side (SaaS vendors), data about product and specific feature usage can be invaluable.
Examples: Blissfully, Productiv
This isn’t exactly a category, but a growing and diverse set of needs with some interesting new vendors. In order to sell SaaS to enterprises there are a lot of requirements, which are significant time and resource drains — especially for smaller startups!
WorkOS lets their customers choose from multiple solutions in a variety of categories (SSO, identity provisioning, audit trail, legacy integrations, etc.) and quickly integrate them. As they enable more customers, they effectively build a database of enterprise-ready SaaS apps, which they could eventually turn into a marketplace. Large enterprises, according to CEO Michael Grinch, “will be able to rapidly adopt more cloud apps and take part in the resulting massive productivity gains. (Imagine the cascading impact this could have!)”
Secureframe is building tooling for security compliance. SOC 2, HIPAA, and other compliance certifications are expensive and hard to get. They require things like background checks, training, cloud scanning, etc. Secureframe integrates with 40+ (and growing) vendors to assess and manage risk, but compliance is just the first step. Having established their user base and understanding their needs, they can provide additional tools (e.g., for ongoing database backup and encryption). The company also plans to open up an integration marketplace, gaining more supplier integrations and making the process of setting up/maintaining them easier/cheaper. And, most significantly, by collecting data and best practices, SecureFrame is working toward building its own security standard.
Vendors: WorkOS, SecureFrame
Morph vs. “Regular” Companies
Better? Worse? Does it matter?
Morph companies have a two-for-one potential, so evaluating them should address this.
That impacts questions like:
- How valuable could this be?
- How difficult will this be? (easier to start small but win bigger)
- How much investment will be required?
In nature, there are different types of metamorphosis: “completely changing” or “half-changing.” The transformation for morph companies may similarly be more or less extensive: not every one will be a massive disruptor.
However, the potential to unlock access to much harder problems is obviously noteworthy. Because that extra potential is baked in from the start, and often is very significant, the value should certainly be accounted for differently (assuming the full opportunity is recognized from the start, of course).
For Investors, Founders, and Job Seekers
For founders and investors, it may be helpful to look backward from an end goal, and work backward to a simpler possible entry point. That may be especially viable in the case of fractured, disjointed industries.
Job seekers and investors may also want to think about how companies they evaluate may have more potential than just the problem/market they appear to be addressing at the outset. At times, that may be obvious… but not always!
What feedback do you have? What did I miss? I’d love to hear what other morph companies you can think of, and which industries could be affected (and the initial solution that might enable a sequential opportunity).