Historical Group Data

This version is now depreciated. We recommend to use public companies API v2.

Introduction

This endpoint returns historical monthly values (time series) for the specified aggregated group.

Similar to Current Group Data, you can select from the following groups:

Industries: 220+ segments, for example: IoT, Online Dating, DevOps
Themes: 40+ broad technology themes, for example: DeepTech, PetTech
Countries: all global countries in ISO3 format, for example: CAN, JPN, BRA
Regions: all global regions, for example: Northern Europe, Oceania

You can mix groups together, for example Online Dating comps in Europe.

You can create time-series for the last 10 years (120 months).

Groups

Interactive public comps table available here to quickly look up industries, themes and geos

Four available fields - industries, themes, regions, countries

Industries - look up the full list here

{
    "industries": [
        "Productivity Software",
        "Cloud Infrastructure"
    ]
}

Themes - look up the full list here

{
    "themes": [
        "B2B SaaS"
    ]
}

Regions - full list in the code snippet below

{
    "regions": [
        "Africa",,
        "Central Asia",
        "East Asia",
        "Eastern Europe",
        "Latin America",
        "Middle East",
        "North America",
        "Northern Europe",
        "Oceania",
        "South Asia",
        "South-East Asia",
        "Southern Europe",
        "Western Europe"
    ]
}

Countries - look up the full list here

{
    "countries": [
        "ARG",
        "AUS",
        "AUT",
        "BHR",
        "BGD",
        "BEL",
        "BIH",
        "BRA"
    ]
}

You can mix fields together to narrow down your call

{
    "industries": [
        "Productivity Software",
        "Cloud Infrastructure"
    ],
    "themes": [
        "B2B SaaS"
    ]
}

Set up

Single endpoint, returning data for the combined group specification, per specified time-frame

Endpoint

https://multiples.vc/api/v1/groups/time-series

Body example

{
    "industries": [
        "Cybersecurity"
    ],
    "fields": [
        "evRevenueLtm",
        "evRevenueNtm"
    ],
    "dateFrom": "2024-03",
    "dateTo": "2025-04"
}

Response

{
    "data": [
        {
            "period": "2024-03",
            "median": {
                "evRevenueLtm": 3.8185000000000002,
                "evRevenueNtm": 3.4845
            }
        },
        {
            "period": "2024-04",
            "median": {
                "evRevenueLtm": 3.5656,
                "evRevenueNtm": 3.208
            }
        },
        {
            "period": "2024-05",
            "median": {
                "evRevenueLtm": 3.5612500000000002,
                "evRevenueNtm": 3.3096
            }
        },
        {
            "period": "2024-06",
            "median": {
                "evRevenueLtm": 3.4457,
                "evRevenueNtm": 3.3219000000000003
            }
        },
        {
            "period": "2024-07",
            "median": {
                "evRevenueLtm": 3.6839000000000004,
                "evRevenueNtm": 3.4715
            }
        },
        {
            "period": "2024-08",
            "median": {
                "evRevenueLtm": 3.68515,
                "evRevenueNtm": 3.3573
            }
        },
        {
            "period": "2024-09",
            "median": {
                "evRevenueLtm": 3.8834,
                "evRevenueNtm": 3.5027
            }
        },
        {
            "period": "2024-10",
            "median": {
                "evRevenueLtm": 3.9536,
                "evRevenueNtm": 3.5189
            }
        },
        {
            "period": "2024-11",
            "median": {
                "evRevenueLtm": 4.2094,
                "evRevenueNtm": 3.7185
            }
        },
        {
            "period": "2024-12",
            "median": {
                "evRevenueLtm": 4.4341,
                "evRevenueNtm": 3.7665
            }
        },
        {
            "period": "2025-01",
            "median": {
                "evRevenueLtm": 4.5944,
                "evRevenueNtm": 4.0721
            }
        },
        {
            "period": "2025-02",
            "median": {
                "evRevenueLtm": 4.7118,
                "evRevenueNtm": 4.244
            }
        },
        {
            "period": "2025-03",
            "median": {
                "evRevenueLtm": 4.369949999999999,
                "evRevenueNtm": 3.88815
            }
        },
        {
            "period": "2025-04",
            "median": {
                "evRevenueLtm": 4.3994,
                "evRevenueNtm": 3.8611
            }
        }
    ],
    "meta": {
        "count": 14,
        "companies": 133
    }
}

Available fields

Raw Financials

`marketCap`	market capitalization in USD
`marketCapLcu`	market capitalization in local currency
`enterpriseValue`	enterprise value in USD
`enterpriseValueLcu`	enterprise value in local currency
`revenueLtm`	revenue - last 12 months
`revenueNtm`	revenue - next 12 months
`ebitdaLtm`	EBITDA - last 12 months
`ebitdaNtm`	EBITDA - next 12 months
`grossProfitLtm`	gross profit - last 12 months
`grossProfitNtm`	gross profit - next 12 months
`netIncomeLtm`	net income - last 12 months
`netIncomeNtm`	net income - next 12 months
`fcfLtm`	free cash flow - last 12 months
`fcfNtm`	free cash flow - next 12 months

EV Multiples

`evRevenueLtm`	EV / LTM Revenue - last 12 months
`evRevenueNtm`	EV / NTM Revenue - next 12 months
`evRevenueGrowthAdjNtmLtm`	EV / Growth-Adjusted NTM/LTM Revenue
`evEbitdaLtm`	EV / LTM EBITDA - last 12 months
`evEbitdaNtm`	EV / NTM EBITDA - next 12 months
`evEbitdaGrowthAdjNtmLtm`	EV / Growth-Adjusted NTM/LTM EBITDA
`evGrossProfitLtm`	EV / LTM Gross Profit - last 12 months
`evGrossProfitNtm`	EV / NTM Gross Profit - next 12 months
`evFcfLtm`	EV / LTM Free Cash Flow - last 12 months
`evFcfNtm`	EV / NTM Free Cash Flow - next 12 months

Growth rates

`revenueGrowthNtmLtm`	Revenue growth NTM/LTM
`ebitdaGrowthNtmLtm`	EBITDA growth NTM/LTM

Margins

`marginEbitdaLtm`	EBITDA margin - last 12 months
`marginEbitdaNtm`	EBITDA margin - next 12 months
`marginEbitLtm`	EBIT margin - last 12 months
`marginEbitNtm`	EBIT margin - next 12 months
`marginGrossLtm`	Gross margin - last 12 months
`marginGrossNtm`	Gross margin - next 12 months
`marginFcfLtm`	Free cash flow margin - last 12 months
`marginFcfNtm`	Free cash flow margin - next 12 months
`marginNetLtm`	Net margin - last 12 months
`marginNetNtm`	Net margin - next 12 months

Expenses as % of revenue

`expensesRevenuePercentageSmLtm`	LTM Sales & marketing as % of revenue - last 12 months
`expensesRevenuePercentageSmNtm`	NTM Sales & marketing as % of revenue - next 12 months
`expensesRevenuePercentageRdLtm`	LTM R&D as % of revenue - last 12 months
`expensesRevenuePercentageRdNtm`	NTM R&D as % of revenue - next 12 months
`expensesRevenuePercentageOpexLtm`	LTM Opex as % of revenue - last 12 months
`expensesRevenuePercentageOpexNtm`	NTM Opex as % of revenue - next 12 months
`expensesRevenuePercentageGaLtm`	LTM G&A as % of revenue - last 12 months
`expensesRevenuePercentageGaNtm`	NTM G&A as % of revenue

P/E ratios

`priceEarningsLtm`	LTM price-to-earnings - last 12 months
`priceEarningsNtm`	NTM price-to-earnings - next 12 months

SaaS ratios

`ruleOf40`	rule of 40
`ruleOfX`	Bessemer’s rule of X

Current Group Data

List of Companies