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This grid compares the metrics disclosed and guided by ten leading marketplace companies.
The comparison highlights similarities and differences in their reporting practices, reflecting their individual business models and investor focus.
Legend:
One checkmark (✓): Company discloses this metric
Two checkmarks (✓✓): Company both discloses and provides guidance on this metric
Blank: Company neither discloses nor guides on this metric
Key Observations:
Revenue and GMV: All companies prioritize revenue reporting, with most also disclosing Gross Bookings or Gross Merchandise Value (GMV) to show the total value flowing through their platforms.
Take Rate: Most marketplace companies disclose their take rate, showing the percentage of GMV they capture as revenue. This is crucial for understanding their monetization strategy.
Profitability Metrics: Adjusted EBITDA and Non-GAAP Net Income are universally reported and guided, reflecting the focus on demonstrating a path to profitability for these often high-growth, but historically unprofitable companies.
User Metrics: All companies report on their user base, though the specific metrics vary (e.g., Monthly Active Users, Active Riders, Active Hosts) based on their business model.
Transaction Metrics: Companies like Uber, Airbnb, DoorDash, and Instacart report on transaction volumes (Trips, Nights, Orders) to show platform activity.
Unit Economics: Metrics like Average Order Value and Contribution Margin are key for companies to demonstrate improving efficiency and profitability at the transaction level.
Cash Flow: Free Cash Flow is widely reported, with some companies providing guidance, indicating a growing focus on sustainable cash generation.
Company-Specific Focus:
Uber and Lyft emphasize similar metrics, focusing on rides and driver engagement.
Airbnb highlights nights booked and host metrics.
DoorDash and Instacart focus on order volumes and marketplace efficiency.
eBay and Etsy, as more mature marketplaces, emphasize GMV and take rates.
Zillow's metrics reflect its focus on the real estate market, with less emphasis on traditional marketplace metrics.
CarGurus, as an auto marketplace, has a unique set of metrics focused on dealer relationships and lead generation.
Upwork's metrics highlight its focus on freelancer engagement and client spend.
Guidance Practices: Most companies provide guidance on top-line metrics (Revenue, GMV) and key profitability measures (Adjusted EBITDA, Non-GAAP Net Income). Operational metrics are typically disclosed but not guided.
Variations in Guidance: While most companies disclose similar metrics, there's variation in which metrics they provide forward-looking guidance on, likely reflecting what each company believes is most relevant to its investors and business model (and most importantly, what they feel they can forecast predictably).

TL;DR: Multiples are DOWN week-over-week.
Top 10 Medians:
EV / NTM Revenue = 16.1x (DOWN 0.9x w/w)
CAC Payback = 27 months
Rule of 40 = 53%
Revenue per Employee = $391K
Source: Koyfin

Figures for each index are measured at the Median
Median and Top 10 Median are measured across the entire data set, where n = 110
Population Sizes:
Security: 17
Database and Infra: 14
Backoffice: 16
Marcom: 16
Marketplace: 15
Fintech: 16
Vertical SaaS: 16
Revenue Multiples
Revenue multiples are a shortcut to compare valuations across the technology landscape, where companies may not yet be profitable. The most standard timeframe for revenue multiple comparison is on a “Next Twelve Months” (NTM Revenue) basis.
NTM is a generous cut, as it gives a company “credit” for a full “rolling” future year. It also puts all companies on equal footing, regardless of their fiscal year end and quarterly seasonality.

However, not all technology sectors or monetization strategies receive the same “credit” on their forward revenue, which operators should be aware of when they create comp sets for their own companies. That is why I break them out as separate “indexes”.
Reasons may include:
Recurring mix of revenue
Stickiness of revenue
Average contract size
Cost of revenue delivery
Criticality of solution
Total Addressable Market potential
From a macro perspective, multiples trend higher in low interest environments, and vice versa.
Multiples shown are calculated by taking the Enterprise Value / NTM revenue.
Enterprise Value is calculated as: Market Capitalization + Total Debt - Cash
Market Cap fluctuates with share price day to day, while Total Debt and Cash are taken from the most recent quarterly financial statements available. That’s why we share this report each week - to keep up with changes in the stock market, and to update for quarterly earnings reports when they drop.
Historically, a 10x NTM Revenue multiple has been viewed as a “premium” valuation reserved for the best of the best companies.
Efficiency Benchmarks
Companies that can do more with less tend to earn higher valuations.

Three of the most common and consistently publicly available metrics to measure efficiency include:
CAC Payback Period: How many months does it take to recoup the cost of acquiring a customer?
CAC Payback Period is measured as Sales and Marketing costs divided by Revenue Additions, and adjusted by Gross Margin.
Here’s how I do it:
Sales and Marketing costs are measured on a TTM basis, but lagged by one quarter (so you skip a quarter, then sum the trailing four quarters of costs). This timeframe smooths for seasonality and recognizes the lead time required to generate pipeline.
Revenue is measured as the year-on-year change in the most recent quarter’s sales (so for Q2 of 2024 you’d subtract out Q2 of 2023’s revenue to get the increase), and then multiplied by four to arrive at an annualized revenue increase (e.g., ARR Additions).
Gross margin is taken as a % from the most recent quarter (e.g., 82%) to represent the current cost to serve a customer
Revenue per Employee: On a per head basis, how much in sales does the company generate each year? The rule of thumb is public companies should be doing north of $450k per employee at scale. This is simple division. And I believe it cuts through all the noise - there’s nowhere to hide.
Revenue per Employee is calculated as: (TTM Revenue / Total Current Employees)
Rule of 40: How does a company balance topline growth with bottom line efficiency? It’s the sum of the company’s revenue growth rate and EBITDA Margin. Netting the two should get you above 40 to pass the test.
Rule of 40 is calculated as: TTM Revenue Growth % + TTM Adjusted EBITDA Margin %
A few other notes on efficiency metrics:
Net Dollar Retention is another great measure of efficiency, but many companies have stopped quoting it as an exact number, choosing instead to disclose if it’s above or below a threshold once a year. It’s also uncommon for some types of companies, like marketplaces, to report it at all.
Most public companies don’t report net new ARR, and not all revenue is “recurring”, so I’m doing my best to approximate using changes in reported GAAP revenue. I admit this is a “stricter” view, as it is measuring change in net revenue.
Operating Expenditures
Decreasing your OPEX relative to revenue demonstrates Operating Leverage, and leaves more dollars to drop to the bottom line, as companies strive to achieve +25% profitability at scale.

The most common buckets companies put their operating costs into are:
Cost of Goods Sold: Customer Support employees, infrastructure to host your business in the cloud, API tolls, and banking fees if you are a FinTech.
Sales & Marketing: Sales and Marketing employees, advertising spend, demand gen spend, events, conferences, tools.
Research & Development: Product and Engineering employees, development expenses, tools.
General & Administrative: Finance, HR, and IT employees… and everything else. Or as I like to call myself “Strategic Backoffice Overhead.”
All of these are taken on a Gaap basis and therefore INCLUDE stock based comp, a non cash expense.
You know who doesn't report enough useful metrics but it should? Adobe. They should break down the total users for each app and user type. Also the overlapp of users between apps. Makes it harder to analyze their apps vs competitors. Have to use website traffic or app downloads etc as a proxy.