Arlo Technologies (ARLO) Research & Development (2017 - 2026)
Arlo Technologies (ARLO) recorded Research & Development of $23.66 million in Q2 2026, up 28.0% from $18.49 million a year earlier and up 3.7% from the prior quarter.
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Analysis
Arlo Technologies (ARLO) Research & Development (2017 - 2026) Analysis & Trends
On a TTM basis, Arlo Technologies' Research & Development came in at $85.47 million as of Jun 28, 2026, up 26.7% year-over-year; for FY2025, it came in at $73.65 million, up 0.6% from FY2024.
- Annual Research & Development has increased for four straight years, with a five-year compound annual growth rate of 4.1% (FY2020 to FY2025).
- Across earlier years, Research & Development came in at $73.18 million in FY2024 (+6.6%), $68.65 million in FY2023 (+6.1%), $64.71 million in FY2022 (+9.6%) and $59.06 million in FY2021 (-1.8%).
- The Q2 2026 figure is the highest quarterly Research & Development in data going back to Q2 2017.
- On a year-over-year basis, Research & Development has increased for four consecutive quarters, with growth averaging 9.8% over the last eight quarters.
- Peak year-over-year performance for Research & Development in the last five years was growth of 41.1% in Q1 2026, against a decline of 22.3% in Q1 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $22.81 million (Q1 2026), $20.85 million (Q4 2025) and $18.14 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 316.55 Bn | 301.63 Bn | 2.30 Bn | 779.00 Mn |
| 2 | CrowdStrike Holdings | 269.03 Bn | 249.47 Bn | 1.10 Bn | 444.20 Mn |
| 3 | Fortinet | 129.08 Bn | 115.01 Bn | 1.64 Bn | 225.00 Mn |
| 4 | Snowflake | 116.42 Bn | 103.73 Bn | 1.04 Bn | 567.48 Mn |
| 5 | Datadog | 96.40 Bn | 78.04 Bn | 881.34 Mn | 477.97 Mn |
| 6 | Okta | 34.24 Bn | 24.34 Bn | 641.00 Mn | 163.00 Mn |
| 7 | Axon Enterprise | 34.08 Bn | 28.61 Bn | 546.45 Mn | 208.69 Mn |
| 8 | Zscaler | 32.34 Bn | 18.46 Bn | - | - |
| 9 | Baidu | 29.50 Bn | -44.13 Bn | 1.47 Mn | 679.00 Mn |
| 10 | Arlo Technologies | 1.34 Bn | 850.50 Mn | 75.22 Mn | 23.66 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 23.66 Mn |
| Mar 29, 2026 | 22.81 Mn |
| Dec 31, 2025 | 20.85 Mn |
| Sep 28, 2025 | 18.14 Mn |
| Jun 29, 2025 | 18.49 Mn |
| Mar 30, 2025 | 16.17 Mn |
| Dec 31, 2024 | 15.27 Mn |
| Sep 29, 2024 | 17.56 Mn |
| Jun 30, 2024 | 19.56 Mn |
| Mar 31, 2024 | 20.79 Mn |
| Dec 31, 2023 | 16.45 Mn |
| Oct 1, 2023 | 16.83 Mn |
| Jul 2, 2023 | 17.62 Mn |
| Apr 2, 2023 | 17.75 Mn |
| Dec 31, 2022 | 14.46 Mn |
| Oct 2, 2022 | 16.47 Mn |
| Jul 3, 2022 | 17.40 Mn |
| Apr 3, 2022 | 16.38 Mn |
| Dec 31, 2021 | 13.64 Mn |
| Oct 3, 2021 | 14.38 Mn |
API Access
Arlo Technologies Research & Development 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=research-and-development&ticker=ARLO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "ticker": "ARLO", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=research-and-development&ticker=ARLO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();