Ibotta (IBTA) Operating Expenses (2023 - 2026)
Ibotta's Operating Expenses was $71.6 million in Q2 2026, up 7.1% from $66.87 million a year earlier but down 3.1% from the prior quarter.
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Analysis
Ibotta (IBTA) Operating Expenses (2023 - 2026) Analysis & Trends
On a trailing twelve-month basis, Ibotta's Operating Expenses was $280.49 million through Jun 30, 2026, up 2.7% year-over-year; for FY2025, it was $272.18 million, down 5.9% from FY2024.
- Operating Expenses shows a three-year compound annual growth rate of 9.9% (FY2022 to FY2025).
- In earlier years, Operating Expenses was $289.21 million in FY2024 (+31.4%), $220.05 million in FY2023 (+7.4%) and $204.84 million in FY2022.
- Quarterly Operating Expenses has moved between $47.38 million (Q1 2023) and $97.3 million (Q2 2024) over five years.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 2.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q2 2024 (growth of 103.0%); the worst was Q2 2025 (a decline of 31.3%).
- Per Business Quant data, IBTA's Operating Expenses in the three quarters before Q2 2026 was $73.87 million (Q1 2026), $71.27 million (Q4 2025) and $63.75 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | -5.39 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 429.41 Mn |
| 10 | Ibotta | 929.36 Mn | 206.69 Mn | 69.72 Mn | 71.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 71.60 Mn |
| Mar 31, 2026 | 73.87 Mn |
| Dec 31, 2025 | 71.27 Mn |
| Sep 30, 2025 | 63.75 Mn |
| Jun 30, 2025 | 66.87 Mn |
| Mar 31, 2025 | 70.29 Mn |
| Dec 31, 2024 | 70.26 Mn |
| Sep 30, 2024 | 65.74 Mn |
| Jun 30, 2024 | 97.30 Mn |
| Mar 31, 2024 | 55.91 Mn |
| Dec 31, 2023 | 61.10 Mn |
| Sep 30, 2023 | 63.64 Mn |
| Jun 30, 2023 | 47.93 Mn |
| Mar 31, 2023 | 47.38 Mn |
API Access
Ibotta Operating Expenses 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=operating-expenses&ticker=IBTA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IBTA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=IBTA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();