TMT Comparable Company Analysis: Selecting the Right Peers

Dual-class shares are a defining feature of TMT, used by many of the largest technology companies: Alphabet (Class A: 1 vote, Class B: 10 votes, Class C: 0 votes), Meta (Zuckerberg controls approximately 61% of votes with approximately 13% economic ownership), Snap (public Class A shares have zero voting rights).

How they work: Founders and insiders hold super-voting shares (typically 10 votes per share) while public investors hold single-vote shares. This allows founders to maintain control despite being minority economic owners.

Governance implications:

1. Insulation from activist pressure. Founders can pursue long-term strategies without interference from short-term investors. This enabled Meta's pivot to Reality Labs (spending over $15 billion annually) despite investor objections.

2. Reduced accountability. If management performs poorly, public shareholders have limited recourse. They cannot force board changes or strategic shifts through proxy votes.

3. M&A impact. Dual-class companies are effectively immune to hostile takeovers, reducing the "takeover premium" embedded in the stock price. Any acquisition requires founder consent.

Valuation implications:

1. Governance discount. Some investors apply a 5-10% governance discount to dual-class companies, particularly when control is concentrated in a single individual.

2. Index inclusion. S&P reversed its 2017 ban on dual-class companies in its indices, removing a previous overhang. Most major indices now include dual-class companies.

3. Sunset provisions. Some companies include sunset clauses that convert dual-class to single-class after a period (typically 7-10 years) or when the founder's ownership drops below a threshold. These provisions partially mitigate the governance discount.

For TMT bankers, dual-class structures affect the EV-to-equity bridge (different share classes may have different market prices), proxy analysis, and M&A feasibility assessment.

Six adjustments are critical for meaningful SaaS comps.

1. Growth rate adjustment. The most important factor. Normalize by plotting EV/Revenue against growth rate for the peer set. Companies above the regression line are expensive; below are cheap.

2. Gross margin normalization. Compare on EV/Gross Profit rather than EV/Revenue when margin profiles differ significantly (especially when comparing AI-native with traditional SaaS).

3. SBC treatment. Some companies report "adjusted" EBITDA that adds back SBC. For companies where SBC is 20%+ of revenue, using adjusted metrics overstates profitability. Use GAAP-based metrics or explicitly adjust for SBC.

4. Free vs. paid revenue mix. Companies with significant professional services revenue alongside SaaS subscriptions should be compared on subscription revenue multiples, not total revenue, for purity.

5. NRR adjustment. Companies with 130% NRR have fundamentally better economics than those at 100% NRR. Adjust the expected multiple upward for higher NRR.

6. Market cap size. Larger SaaS companies (over $10 billion market cap) tend to trade at slight premiums to smaller peers due to liquidity and index inclusion effects.