Functional Brands (MEHA) Price to Book (2025)
Functional Brands' (MEHA) Price to Book came in at 1.02 for Q4 2025.
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Analysis
Functional Brands (MEHA) Price to Book (2025) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Procter & Gamble | 336.76 Bn | 292.75 Bn | 10.28 Bn |
| 2 | Colgate Palmolive | 67.18 Bn | 62.24 Bn | 3.30 Bn |
| 3 | Estee Lauder Companies | 33.32 Bn | 21.40 Bn | 2.74 Bn |
| 4 | Kenvue | 33.09 Bn | 28.70 Bn | 2.30 Bn |
| 5 | Kimberly Clark | 31.38 Bn | 28.71 Bn | 1.60 Bn |
| 6 | Church & Dwight | 22.37 Bn | 20.90 Bn | 693.90 Mn |
| 7 | Clorox | 9.72 Bn | 8.16 Bn | 804.00 Mn |
| 8 | e.l.f. Beauty | 6.17 Bn | 5.15 Bn | 398.84 Mn |
| 9 | Reynolds Consumer Products | 4.71 Bn | 4.37 Bn | 245.00 Mn |
| 10 | Functional Brands | 426,716.59 | 426,716.59 | 1.12 Mn |
API Access
Functional Brands Price to Book API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=price-to-book&ticker=MEHA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-book", "ticker": "MEHA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=price-to-book&ticker=MEHA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();