VENIONAIRE DEALMATRIX MULTIPLES
Valuation Multiples for
Private Markets
Private market EV/Sales & EV/EBITDA multiples, tailored by sector, stage, and region.
TRACK RECORD OF LEADING COMPANIES & EVENTS
WHAT WE DO
Signal out the noise.
We turn noisy public multiples into a benchmark you can actually price a private company against.
The market swings. Your benchmark shouldn’t.
Our model estimates what the multiple should be, from 25 years of market data. What the market pays beyond that is noise and we quantify it.
Converting it to private market DealMatrix sectors.
To benchmark a private company against the right peers, each DealMatrix category is a weighted blend of the listed sub-industries that match the revenue model.
FinTech, for example, is 40 % payments, 30 % application software, 20 % systems software and 10 % data processing — the translation work an investor would otherwise do by hand.
Adapted for private markets.
Listed companies are priced by a deep market, every day, on published numbers. Private companies are not: they grow faster, their capital costs more, their shares cannot be sold at will and the market they raise in shapes the price far more than it does for a global index constituent.
The final step accounts for those differences. What comes out is a benchmark for how private companies are actually priced.
MULTIPLES COMPARISON
Our multiples, checked against real deals.
Privately held companies that disclosed both a funding valuation and revenue. Our range brackets the actual multiple without ever seeing the deal.
| Company | Industries (blend) | Region | Stage | Round | Valuation | Revenue | Actual EV/Sales | DealMatrix EV/Sales |
|---|---|---|---|---|---|---|---|---|
| Mercury | FinTech, SaaS, Payments, Financial Services | North America | Series C | Q1 2025 | $3.5B | $500M (FY24) | 7.0× | 6.7–7.9× |
| Mercury | FinTech, SaaS, Payments | North America | Series D | Q2 2026 | $5.2B | $650M (ann.) | 8.0× | 6.9–8.3× |
| KreditBee | FinTech, Lending, Payments | Asia-Pacific | Series D | Q1 2023 | $680M | ~$96M (FY23) | 7.1× | 6.8–8.0× |
| Enpal | CleanTech, Green Energy, Financing | Europe | Series D | Q1 2023 | €2.2B | €415M (FY22) | 5.3× | 4.6–5.5× |
| Olipop | Food and Beverage, Nutrition, Consumer Goods | North America | Series C | Q1 2025 | $1.85B | $400M (FY24) | 4.6× | 4.3–5.2× |
| Bending Spoons | Apps, SaaS, Artificial Intelligence | Europe | Series D | Q1 2024 | $2.55B | $392M (FY23) | 6.5× | 5.7–6.8× |
| Plata | FinTech, Lending, Payments | Latin America | Series C | Q2 2026 | $5.0B | $600M+ (ann.) | 8.3× | 7.3–8.6× |
| KreditBee | FinTech, Lending, Payments | Asia-Pacific | Series E | Q2 2026 | $1.5B | ~$315M (FY25) | 4.8× | 4.5–5.4× |
EV/Sales = enterprise value ÷ revenue. Actual = disclosed round valuation ÷ disclosed revenue (or annualized run-rate, marked “ann.”). The DealMatrix range reflects the possible weightings across the listed industries. Deal figures come from company announcements and filed accounts linked on each company name.
The Venionaire DealMatrix Multiples Model
DealMatrix multiples are derived through a six-step model combining public capital market comparables, proprietary VC/PE/M&A transaction data, and macroeconomic indicators.
The model produces three components: The reported public multiple, the model-predicted multiple, and the lower bound predicted multiple averaged into the DealMatrix Composite, then adjusted for region and funding stage. The methodology follows the IPEV Guidelines 2025.
- 15,000+ PE/VC multiples
- 140+ Industries
- EV/Sales & EV/EBITDA multiples
- 6 Regions & 7 Stages filter
- Up to 25 years of time series
- Individual sector weighting
- PDF export
- Up to 3 Workspaces
- 15,000+ PE/VC multiples
- 140+ Industries
- EV/Sales & EV/EBITDA multiples
- 6 Regions & 7 Stages filter
- Up to 25 years of time series
- Individual sector weighting
- PDF export
- Unlimited Workspaces
- Raw data export (CSV / Excel)
- Priority support
- Everything in Professional, plus:
- API Access
- Individual Branding
- Custom Reports
- Premium Support
- Individual Contingent
FAQ
The most asked questions answered here.
Where is the data coming from?
DealMatrix multiples start from roughly 200 GICS-classified public equity indices across six regions and 25 years of quarterly history. Several steps then turn this baseline into private-market multiples: a mixed linear model with eight macroeconomic factors, a regional adjustment, a mapping of the indices onto approximately 150 private-market startup categories (SaaS, marketplaces, AI infrastructure and more), and a funding-stage adjustment from Pre-Seed to Series E. The tool provides private-market multiples across 140+ sectors, each modelled independently by sector, stage and region, aligned with the IPEV Guidelines 2025.
How do you select and curate the data?
DealMatrix multiples are produced through a six-step econometric model:
- Data acquisition. Roughly 200 GICS-classified public equity indices per region and quarter form the observable baseline.
- Statistical cleaning. Unusable records are removed, observations are aggregated at subsector level, and extreme values are capped (300x for EV/EBITDA, 60x for EV/Sales).
- Econometric modelling. The panel is combined with eight quarterly macroeconomic indicators per region (GDP, interest rates, inflation, money supply); a mixed linear model separates macro, sector, time and region effects, and a reported multiple, a model-predicted fair value and a conservative lower bound are averaged into one stable figure.
- Regional adjustment. A coefficient normalised to North America reflects differences in market depth, investor appetite and valuation culture.
- Industry weighting. Because startups rarely map to a single listed sub-industry, each of roughly 150 DealMatrix categories is a weighted blend of the public sub-industries whose companies are most economically comparable.
- Stage adjustment. A stage factor from Pre-Seed to Series E adds an early-stage growth premium and a late-stage pre-IPO discount, producing true private-market multiples.
The methodology follows the IPEV Guidelines 2025.
How do you ensure data accuracy?
Accuracy is built in at every layer:
- Institutional-grade public equity and macroeconomic inputs.
- Cleaning and normalisation (removal of unusable records, subsector aggregation, outlier capping) to reduce statistical noise.
- A mixed linear model that separates macroeconomic, sector, time and region effects, then averages a reported multiple, a model-predicted fair value and a conservative lower bound into one stable figure.
- Every sector, stage and region combination modelled independently (around 49,000 data points), refreshed quarterly.
The output complies with the IPEV Guidelines 2025.
How wide is the coverage?
Coverage is granular and modelled independently for each combination:
- 140+ private-market sectors, mapped from roughly 200 GICS-classified public indices.
- 7 funding stages, Pre-Seed to Series E.
- 6 global regions (Europe, North America, APAC and more).
- 25 years of quarterly history, both EV/Sales and EV/EBITDA.
Around 49,000 sector-stage-region data points, updated each quarter.
Why use the Multiples App by Venionaire DealMatrix?
You get private-market multiples calibrated to how startups are valued at each funding stage, sector and region. Roughly 200 public equity indices are mapped onto approximately 150 private-market startup categories and adjusted by region and by funding stage (Pre-Seed to Series E), adding an early-stage growth premium and a late-stage pre-IPO discount. A six-step econometric model over 25 years of data, refreshed quarterly and aligned with the IPEV Guidelines 2025, delivers market-realistic private-market valuation ranges by sector, stage and region.