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Multiples

Introduction

This Deep Dive is the starting point to explore Deal Multiples on Dealroom. We provide three types of valuation multiples:

  • Public companies
  • VC rounds
  • Exit rounds

Each of these three is explored below.

You will find multiples by stage, sector, country, deal size and more.

This article also contains deep links to the platform giving you access to the underlying data.

Methodology and more detailed explanations are at the end.

Public valuation multiples

The full public valuation tool is accessible via app.dealroom.co/multiples and is powered by Flow Partners.

Coverage: all tech companies globally, with a market cap of $100m+ (including their key tech-adjacent comparables, such as BMW for Tesla). This includes 2,000 companies across 15 top level sectors, and 104 sub-sectors, detailed below. Biotech is not yet included but will be added later in 2024.

Top level sectors

Software

Growth drives software multiples

As shown above, multiples vary widely per company and per sector. The two main drivers are growth and profitability.

Bessmer's Rule of X provides a neat way to see how important each of these two factors are. It’s also a reference point for valuing companies.

The below chart shows the Rule of X where X = 3. The R-square is 0.75, which means that 3x growth and 1x EBITDA margins explain 75% of the valuation multiple.

Let's imagine if your revenue growth rate is 20% (x3 = 60%) and your margin is 40% you are at 100% which means your revenue multiple is about 15x.

The bubble chart above also allows you to compare multiples by location. It shows that Europe and Israel are only slightly undervalued, but not significantly when adjusting for growth.

Some Asian stocks are heavily undervalued, due to geopolitical risk.

Marketplaces and eCommerce

Marketplaces & eCommerce are valued very differently than SaaS companies and there's a huge range between sub-sectors.

Rule of 40 drives marketplace multiples

For Software, X=3, but for marketplaces X=1 (or closer to 1), which means the traditional Rule of 40 applies. It's called the Rule of 40 because as a rule of thumb, Revenue growth + margin should be above 40.

As shown below, Amazon does not quite meet the Rule of 40 and they're not doing too shabby.

In this context, the 40 isn't the most relevant; it's the line.

If you're a Marketplace or eCommerce company, see where you find yourself on this line to get an idea where you might be valued.

Prosus and Naspers are not shown here since they don't trade as marketplace stocks. Their stake in Tencent is the majority of the value. They trade more on a sum-of-the-parts basis.

Deep tech

In this context (public multiples) we define Deep Tech a bit more generously than we normally would for private companies, including industrial technology and hardware focused sectors. Deep tech multiples very widely. For instance, Nvidia trades way above the top quartile.

Climate tech

There are several public companies in the sustainability space, in renewable energy, climate tech itself, plant-based food, solar and electric vehicles.

Climate tech includes both manufacturing, marketplaces and SaaS. More representative multiples can be drawn looking at subcategories like software for energy management.

VC round multiples

We have been collecting revenues, valuations and multiples relating to thousands of VC rounds across the globe.

Valuations and revenues are based on public information (press releases, financial statements and occasionally public leaks).

By stage

The earlier the stage, the higher the multiples.

This is the result of two opposing forces: earlier stage investments have almost unlimited upside (could be the next Google) and revenues are still tiny and therefore less meaningful in the valuation process.

Later stage investments are further de-risked but multiples come down as the true revenue trajectory becomes more clear.

In the early stages, the upside clearly wins, at least for the top quartile.

SaaS
Representing 41% of all multiples rounds

Marketplaces and eCommerce
Representing 27% of all multiples rounds

By year

Multiples peaked in 2022 and have come back down.

The below chart does a good job of showing that trend. Of course, the multiples by stage continue to vary widely as shown above.

By industry

The below chart shows VC round multiples by main industry.

Some industries show very high spread/variability. This is often due to different models. Energy, for instance, includes software for smart grid and home energy efficiency as SaaS models, alongside battery manufacturing.

The Dealroom platform allows you to select sectors in more granular detail, to get more meaningful comparables.

Semiconductors are excluded from the above chart as their VC round multiples are off the scale.

Often Deep Tech companies are pre revenues when raising bigger rounds. Semiconductor multiples are:

  • Bottom quartile 28.1x
  • Median 164.5x
  • Top quartile 718.5x

Exit Multiples

By deal size

The bigger the deal, the higher the multiple. Interestingly, this is the reverse trend versus multiples on VC rounds.

This makes sense because high value exits tend to be more contested, high quality deals.

By year

By industry

 

Methodology

What are multiples?

Multiples are for companies what "price per square foot" is for properties. It's the universal metric by which a company's valuation is measured.

Types of multiples data: Private & Public

Advantages Disadvantages
Public Multiples
  • Lots of publicly available data
  • Always real-time
  • Less relevant for private transactions (e.g. illiquidity discount, strategic premium, early stage premium)
Private Multiples
  • More comparable when used for VC rounds or Exits
  • Data is very scarce
  • Not real-time

Public multiples methodology

This guide focuses on revenue multiples, because those tend to be most relevant and more widely available for (early stage) startups.

However, the platform also has EBITDA multiples, profit multiples, as well as growth metrics so growth adjusted multiples are possible.

Stock market data from providers is thoroughly scrubbed and checked to correct for identified issues (e.g. missing enterprise values estimated as market cap + net debt, missing FY year ends manually entered).

Enhanced manually with company information such as tech-specific verticals/tagging, shortnames, logos, websites and founded/IPO dates which are layered onto the exported data before each upload.

Data points are calendarised to December where relevant: retrieved data on financial year ends (e.g. FY, FY+1 etc.) are mapped to calendar years (2023A, 2024E etc.) before the appropriate month weights are then applied to prior/future fundamentals.

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