There is a specific moment in every pre-IPO roadmap where the energy in the boardroom shifts from "innovation" to "validation."
For the first five years of a startup's life, the goal is disruption. You want to be the outlier. You want to break things. But when you start preparing the S-1 filing for the SEC, "breaking things" becomes a liability. Institutional investors—the pension funds and sovereign wealth managers who will actually buy your stock—do not like disruption. They like durability.
They need to know that your revenue isn't just a flash in the pan. They need to know that the market you serve is real, quantifiable, and growing.
This is where the disconnect happens. Most technical founders believe their code speaks for itself. They believe that if they build the best mousetrap, the bankers will value it accordingly. I have spent years advising C-level leaders, and I can tell you: bankers do not audit code. They audit risk.
And the primary mechanism for de-risking a SaaS company's valuation is not the sales team. It is the Analyst Relations (AR) function.
The Economics of Trust
To understand why AR correlates so strongly with IPO success, we have to look at the psychology of the "Lagging 70%."
Early adopters buy software because it is cool. The mainstream market—the Fortune 500 enterprises that provide the "durable revenue" public investors crave—buy software because it is safe. These buyers do not make decisions in a vacuum. They rely on third-party validation to protect their careers. If a CIO buys a solution that fails, they can get fired. If they buy a solution recommended by a major analyst firm and it fails, they can blame the analysts.
This dynamic creates a chain of custody for trust:
- The CIO trusts the Analyst.
- The Banker trusts the CIO's budget.
- The Investor trusts the Banker's book.
If you remove the Analyst from that chain, the trust evaporates. Without a mature AR function, a pre-IPO company is effectively asking Wall Street to trust its own marketing materials. That results in a "risk discount" on the share price.
Case Study 1: Snowflake and the $84 Billion TAM
Let’s look at the Snowflake IPO from September 2020. It was one of the most successful software listings in history. While their technology was undeniably great, their S-1 filing reveals a masterclass in Analyst Relations strategy.
Snowflake had a problem: If they were categorized simply as a "Data Warehouse," they would be valued like a commodity storage provider. The market for "Data Warehouses" is large but finite, and heavily commoditized by players like Amazon and Microsoft.
Snowflake needed to convince investors that they were not just selling storage—they were selling a "Cloud Data Platform." But you cannot just invent a category and expect the SEC and investors to believe you. You need a neutral third party to do the math.
"The pattern repeats across the SaaS IPO landscape,the broader principle—that independent analyst credibility drives IPO success—extends far beyond any single vendor's reports. A comprehensive study would reveal dozens of examples where companies leveraged third-party analyst validation to de-risk their valuations ahead of going public.
CrowdStrike exemplifies this perfectly: the company spent years building "Leader" status with multiple analyst firms before their June 2019 IPO, which resulted in a remarkable 71% first-day pop.
Similarly, Datadog, ServiceNow, and ServiceTitan all demonstrated the value of analyst-backed market sizing and competitive positioning in the years leading up to their successful NASDAQ listings. The common thread isn't any single analyst report or framework—it's the strategic, long-term investment in third-party credibility that makes institutional investors comfortable betting on unproven companies. For pre-IPO companies evaluating their analyst relations strategy, the takeaway is clear: the analysts you engage with today become the validators institutional investors call tomorrow. While these companies followed similar patterns, the depth of pre-IPO AR strategy may vary
In their S-1 filing, Snowflake did not cite their own internal market research. They cited a custom calculation based on data from a global market intelligence firm. The filing explicitly stated that the market for "Analytics Data Management" plus "Integration Platforms" and "BI Tools" would reach a combined value of $84 billion.
This was not an accident. This was an engineered narrative. Snowflake’s AR team worked with the analysts long before the IPO to ensure that their product was seen as bridging these distinct categories. By getting analysts to validate this convergence, Snowflake effectively unlocked a Total Addressable Market (TAM) that was 3x or 4x larger than a standard database play.
The Business Value: That validated $84 billion number became the anchor for their valuation. It allowed bankers to sell the stock not based on what Snowflake was earning today, but on the "verified" ceiling of what they could earn tomorrow.
Case Study 2: UiPath and the "Leader" Shield
UiPath, the robotic process automation (RPA) giant, faced a different challenge during their April 2021 IPO. The market knew RPA was a big trend, but it was crowded. Investors were worried about commoditization. Why would a customer buy UiPath over a cheaper competitor?
UiPath needed to prove Market Leadership. They needed to prove they were the "Category King."
In their S-1 and roadshow deck, UiPath heavily leveraged their positioning in the major vendor evaluation matrices (the famous "Quadrants" and "Waves" produced by legacy firms). They didn't just mention they were in the market; they showcased that they were the top-ranked "Leader" in both major analyst reports immediately prior to the listing.
This is where the timeline matters. Achieving a "Leader" position in these reports takes 12 to 24 months of briefing, inquiry, and strategy. You cannot buy your way in a month before the IPO. UiPath’s AR team had to be executing a "Leader" strategy two years prior to the bell ringing.
The Business Value: By plastering those "Leader" badges on their investor presentation, UiPath de-risked the technology for institutional investors. A portfolio manager doesn't know how to evaluate RPA code, but they know how to read a graph. If the dot is in the top right, the asset is "safe."
The Hidden Mechanics of S-1 Validation
When I advise companies on this transition, I often explain that the S-1 is the final exam, but the AR team does the homework. Here is how the mechanics actually work behind the scenes:
1. The Narrative Test
Long before the S-1 is drafted, the AR team tests the company's "equity story" with analysts. If you tell an analyst, "We are an AI company," and they roll their eyes, you know the bankers will do the same. AR provides a safe sandbox to refine the pitch until it resonates with a skeptical, technical audience.
2. The Reference Check
During the "quiet period" of an IPO, company executives are legally restricted from hyping the stock. However, analysts are not. Investors will call the major firms and ask, "What do you really think of Company X?"
If your AR team has done its job, the analyst will say, "They are the real deal. We hear great things from clients." If you have ignored AR, the analyst will say, "They have good tech, but we don't see them much in enterprise deals." That single sentence can shave millions off the valuation.
3. The Post-IPO Buffer
The correlation continues after the listing. Public companies miss earnings estimates. It happens. When a stock dips, you need defenders. Industry analysts who understand your long-term roadmap can publish notes saying, "The market overreacted; the fundamentals are strong." Without that air cover, a missed quarter turns into a rout.
Conclusion: It’s About Maturity, Not Marketing
We need to stop thinking of Analyst Relations as "pay-to-play" marketing. In the context of an IPO, it is a governance function.
A company that has successfully navigated the scrutiny of major analyst firms has demonstrated a level of operational maturity that startups lack. They have shown they can respond to inquiry, they can back up their claims with data, and they can hold their own against competitors in a neutral evaluation.
The correlation is clear: Companies that treat AR as a strategic partner 24 months out tend to control their own narrative on listing day. Companies that ignore AR until the roadshow find themselves priced by their competitors' narratives.
Is your narrative ready for the scrutiny of the public markets?
If you are looking at an exit in the next 18 to 24 months, ask yourself: If an institutional investor called a major analyst today
Disclaimer: This blog post reflects my personal views only. AI tools may have been used for brevity, structure, or research support. Please independently verify any information before relying on it. This content does not represent the views of my employer, Infotech.com.
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