How to Assess Early-Stage Markets?

Some First Principles for Making Sense of Inchoate Market Opportunities

Every so often, we come across a new startup or idea and wonder if it makes any sense. Is there a market for this product?

Professional venture investors meet thousands of seed stage startups every year and ask themselves a similar question: What exactly is this product trying to do? What is the total addressable market?

While these are good questions to ask, they can also be misleading in isolation without customer context.

Trying to make sense of products or markets at early stages —where there are no or few dependable metrics—can be an uncertain and vexing exercise [1]. Apparent new dawns can peter out as mirages, while presumed duds turn out to be stars in disguise. Famous VC passes that became massive misses remind us how foggy investing can be. False negatives hurt the most in an industry dominated by the power law.

So how should we think about the formation of new markets? How can we see something not for what it is now but what it can potentially become? It is easy to connect the dots in hindsight but how do we project them forward in a probabilistic and uncertain future?

Let us do a thought experiment to travel back to the times when some of the most successful companies of today were fledglings— Salesforce in 2001, Shopify in 2008, and Whatsapp in 2009. In their formative years, the broad consensus was that these companies would go nowhere, let alone deliver outsize outcomes and gain global adoption. Why did so many miss or dismiss these trends and what can we learn from it?

Salesforce in 2001

In early 2001, the CRM market was exploding. It was dominated by Siebel Systems that sold on-premise software to large enterprises. The customer typically paid software license fees upfront, maintenance of 20% per year, and 2-5 times the license fees to deploy the software. It was not uncommon to see a large telecom or banking company pay $30+M upfront in license fees to Siebel for an enterprise-wide deal and another $120+M in implementation costs (over a few years) to a systems integrator like IBM or Accenture.

In 2001, Salesforce was a small player who had built just one module of CRM (sales force automation), and that too with minimal features that would work only for small businesses with simple needs. But the software was available “on demand”; the customer paid no maintenance, no implementation fees, and there were no license fees. Instead, the first 5 users were free, and there was a $50 per user per month for every additional user.

At that time, skepticism was the default: Small businesses are not a big market! The functionality is too basic! No decent sized company wants their pipeline on the cloud! This can never be profitable!

To visualize Salesforce as an early version of a massive company needed a lens that would reflect reality as it was and without distortions.

• The truth was that the on-premise CRM model was a lop-sided bargain that solved for the vendor first; the typical customer was often screwed over by the vendor and its ecosystem; it looked like a great deal only because there were no better alternatives.

• The size and timing of the customer’s cash outflows were not aligned with the value created for the customer.

• The systems integrators were fleecing the customer. It was expensive to implement, integrate, and upgrade, difficult to use, and it all added up. The total cost of ownership for the customer including software, services, maintenance, servers, databases, systems software, personnel, impact of downtimes, etc. was way too high.

But most people could not take off the colored glasses. And too many incumbents, smitten with their own business models and biases, lost sight of the customer, leaving the door open to a new and disruptive model. Several investors who missed the boat on the first wave of SaaS companies focused on the wrong metrics around Capex, EBITDA, and relative gross margins in SaaS vs. licensed software than ask if this would change the customer’s experience and economics for the better.

Key Takeaways:

1. Always seek a clear-eyed view of the status quo from the customer’s perspective, not the incumbents’. What is the job to be done, what does success mean, and how can it get better?

2. Seek to understand on the customer’s behalf, and not just what they say. Customers always want something better even if they do not realize it yet. They can seem satisfied when there are no better options.

3. If a new product seeks to make the customer’s economics or experience substantially better at least on one vector that a sufficient number of customers prioritize, it has promise, irrespective of the lack of parity on other vectors.

4. What value means to the customer is at the heart of assessing new shifts. Any new thing wanting to succeed has to re-align the “value created” to “value captured” [2] equation in the customer’s favor, not only in aggregate but also on a temporal basis. [3]

5. Business models that solve for trust and mutual success are more sustainable over the long-term for all parties. Comparing the financial metrics of new and disruptive business models with priors at early stages miss the fundamental trade-offs in question.

As we see in so many situations where the new tool does the job substantively better than the old one, the change in spending and market share from the old to the new can be slow and gradual at first, but then turn into an exponential torrent. Salesforce is now valued higher than SAP and Oracle and in excess of $200B. There are many other fascinating aspects to the Salesforce growth story, especially in terms of a) the enabling platform and b) the network effects with developers and customers. I hope to discuss these at another time.

In Part 2 of this series, I will discuss Shopify and Whatsapp, their uncertain beginnings, the conventional wisdom that has been proven wrong, and the key learnings that follow.

Foot Notes:

[1] This piece does not delve into the team and product aspects of assessing a new startup opportunity. Of course, these are as important as understanding the under-served customer need and the biases that can limit that perception.

[2] Value created is the monetary equivalent of the benefits realized by the customer. This differs by context and can include improved productivity, higher revenue, increased savings, etc. Value captured is the price charged by the vendor for their products and services.

[3] Implies matching the timing of cash outflows to vendors with value realized. Many SaaS vendors now also provide usage based pricing so customers pay only for what they consume.

Photo by Francesco Gallarotti on Unsplash