Technology Private Equity Advisory

Why SIC Codes Fail for Technology

Standard industry classifications can't distinguish vertical SaaS from horizontal tools, and that distinction drives a 3-5x difference in valuation.

The fundamental problem with technology deal sourcing is classification. SIC code 7372 ("Prepackaged Software") contains everything from a $500M enterprise platform to a two-person app. NAICS 511210 is equally useless. These codes were designed for an economy where software was shrink-wrapped. They can't tell you whether a company does vertical SaaS for auto dealerships or horizontal project management. And that matters, because those are entirely different businesses at entirely different multiples.

A $20M ARR vertical SaaS platform serving a specific industry (dental practice management, property management, construction project management) with 120%+ net revenue retention trades at 8-12x ARR. A $20M ARR horizontal SaaS tool in a crowded category with 95% net retention and heavy sales and marketing spend trades at 3-5x ARR. Commercial databases group them together. Our origination platform separates them.

We classify technology companies by their actual product capabilities, customer segments, technology stack, and competitive positioning. We use product-level data from software review platforms, integration ecosystem analysis, job posting data (which reveals tech stack and growth trajectory), patent filings, and developer community signals. The result is a technology target universe that a PE buyer can actually act on, not a list of 50,000 "software companies" sorted by estimated revenue.

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The Metrics That Drive Technology Valuations

ARR, net revenue retention, CAC payback, and gross margin aren't just financial metrics. They're the operating system of technology PE underwriting.

Technology PE underwriting runs on metrics that don't exist in standard financial databases. You won't find net revenue retention in a Dun & Bradstreet file.

Annual recurring revenue (ARR) is the baseline, but it's also the easiest metric to game. A company can inflate ARR through multi-year contract bookings, usage-based billing that hasn't been collected, or aggressive recognition of implementation fees as recurring. Sophisticated buyers look at ARR quality: what percentage is truly recurring (subscription) vs. transactional? What's the contract duration mix? How much comes from the top 10 customers?

Net revenue retention (NRR) is the single most important SaaS metric for PE buyers. NRR above 110% means the existing customer base grows without acquiring a single new customer. Above 120% is exceptional. Below 100% means you're on a treadmill. Public SaaS companies with NRR above 120% trade at roughly 2x the multiple of those below 110%. The same dynamic plays out in private transactions.

CAC payback period determines capital efficiency. A SaaS business that recovers customer acquisition costs in 12 months can grow with moderate capital. One that takes 24+ months needs perpetual fundraising. For PE buyers who are paying for the business (not subsidizing growth with venture dollars), CAC payback under 18 months is typically a minimum threshold.

Gross margin separates software from services. True SaaS (80%+ gross margin) gets software multiples. Managed services or heavily customized implementations (50-65% gross margin) get services multiples. The gap between those two categories is 3-5x. Many "SaaS" companies hide services revenue in their subscription line. The diligence work to untangle that starts at origination, not post-LOI.

Sub-Verticals: Vertical SaaS, Infrastructure, Cybersecurity, and IT Services

Each technology niche has distinct unit economics, competitive dynamics, and buyer appetite.

Vertical SaaS is PE's favorite technology thesis right now. And for good reason.

A vertical SaaS platform that becomes the system of record for a specific industry creates switching costs that horizontal tools can't match. The dental practice management system, the auto dealership DMS, the construction project management platform, the property management system. Once embedded, they don't get ripped out. That stickiness drives NRR above 110% and churn below 5% annually. PE firms have acquired vertical SaaS platforms across dozens of industries, and the playbook (acquire the platform, add adjacent modules, expand into adjacent verticals) keeps working.

Infrastructure software (DevOps, data management, cloud operations, monitoring) serves technical buyers and benefits from the complexity of modern IT environments. These businesses often have strong NRR because they become more embedded as customers' infrastructure grows. The challenge is identifying infrastructure software companies that have transitioned from open-source projects to commercial businesses, which requires mapping the developer ecosystem rather than scanning financial databases.

Cybersecurity remains one of the fastest-growing technology PE sub-verticals. Managed detection and response (MDR), identity and access management, compliance automation, and security operations platforms all attract PE capital. The tailwind is obvious: every data breach makes the budget conversation easier. Cybersecurity businesses with high-quality recurring revenue trade at 10-15x ARR.

IT services and managed services providers (MSPs) represent the volume end of technology PE. There are over 40,000 MSPs in the U.S. Most are sub-$10M in revenue. Platform-and-build strategies in IT services mirror the industrial services playbook: acquire a $20M+ platform, bolt on smaller MSPs in adjacent geographies, consolidate vendor relationships and back-office functions. MSPs trade at 6-10x EBITDA depending on recurring revenue mix and customer concentration.

Product-Level Origination: How We Find Technology Targets

Software review platforms, integration ecosystems, job postings, and developer community data reveal targets that financial databases miss.

Technology deal origination should start with the product, not the financial profile.

Software review platforms (G2, Capterra, TrustRadius) contain product-level intelligence on tens of thousands of software companies. Review counts indicate market traction. Feature comparisons reveal competitive positioning. Customer segments (identified through reviewer profiles) show who actually uses the product. A vertical SaaS company with 500+ G2 reviews and a 4.5-star rating in a specific category is a validated product. One with 12 reviews is an early-stage experiment.

Integration ecosystem data tells you how deeply a product is embedded in customer workflows. A SaaS company with 50+ native integrations to other business tools has created switching costs that go beyond its own functionality. App store and marketplace data (Salesforce AppExchange, Shopify App Store, HubSpot marketplace) reveals distribution partnerships and adoption.

Job posting analysis reveals growth trajectory and technology stack without asking the company for anything. A SaaS company that's hired 15 engineers in the last 6 months is investing in product. One that's hired 10 SDRs is investing in sales. One that's hired a VP of Finance and a Controller is getting ready for a transaction. We monitor job postings across 40,000+ technology companies to identify these signals.

Patent filings, GitHub contribution patterns, and developer conference participation add further signal for companies building technical infrastructure. These data sources capture companies that are invisible to financial databases because they're engineering-led, haven't raised institutional capital, and don't have a sales team generating the noise that makes them visible to traditional sourcing.

Fundraising for Technology PE Funds

Every LP wants tech exposure. Differentiation comes from thesis specificity and proving you can source bootstrapped founders who've never spoken to a banker.

Technology is the most competitive category in PE fundraising. Every institutional investor wants tech allocation. And they already have it. Most large LPs have 3-5 existing technology GP relationships. Getting commitment number 6 requires clear differentiation.

The managers who raise successfully in technology PE do two things differently. First, they define their thesis narrowly enough that LPs can see genuine differentiation. "We buy SaaS companies" is not a thesis. "We acquire vertical SaaS platforms in fragmented professional services industries, add workflow automation modules, and expand into adjacent verticals" is. Second, they demonstrate sourcing capability beyond the intermediary channel. In technology PE, the best deals are bootstrapped founders who've built $10-30M ARR businesses without institutional capital and are considering their first capital event. These founders don't show up in GP deal sourcing through traditional channels.

We target LPs based on their existing technology allocation and identified gaps. An endowment with exposure to growth-stage enterprise SaaS might be better suited for a vertical SaaS or IT services strategy. A family office whose principal built and sold a software company has different evaluation criteria than a pension fund. The matching matters because technology LP allocation is the most competitive in PE. You're not educating. You're displacing.

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