Public market valuations reflect real-time information and have high data integrity because they include a wide array of companies and are based on audited financial statements. Public valuation data is the primary starting point for valuation analysis by both buyers and sellers. One key valuation index is one developed by SaaS Capital – aptly called The SaaS Capital Index. The index represents pure B2B SaaS companies, and specifically excludes companies like LinkedIn (when public), PayPal, Carbonite, and Dropbox. The index also excludes legacy and conglomerate software vendors such as Microsoft and Oracle, who have a mix of perpetual and SaaS revenue.
Similar to public companies (albeit with less integrity to the data) the basic valuation formula for private SaaS businesses (which is a proxy for the net present value of future cash flows) can be reduced to a shorthand formula based on a multiple of the company’s annualized revenue. Annualized Revenue x Revenue Multiple = Company Valuation. For SaaS businesses, the best proxy of future cash flows in most instances for well-run businesses that can achieve scale is recurring revenue, and so they trade based on a multiple of that metric. Understandably, anything that affects the projected size, timing, and predictability of future cash flows impacts the revenue multiple. Those factors include company-specific drivers such as absolute size, growth rate, gross margins, retention, etc. and external or macro factors such as economic growth expectations, fear of exogenous shocks, tax policy, etc. Said differently, the current public market valuation multiples incorporate all known macroeconomic uncertainty, and the company-specific factors adjust it from there.
In short and said otherwise, the private “discount” of multiples to public multiples has increased from approximately 25% to 50% or so. For SaaS businesses, operators and owners can better optimize outcomes if they know their market value. The recent widening of the private-company discount to public market multiples has meaningful implications: