J.Jill (JILL) Operating Expenses (2016 - 2026)
J.Jill's Operating Expenses was $94.65 million in fiscal Q2 2027 (quarter ended Aug 1, 2026), up 6.9% from $88.57 million a year earlier and up 5.5% from the prior quarter.
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Analysis
J.Jill (JILL) Operating Expenses (2016 - 2026) Analysis & Trends
On a trailing twelve-month basis, J.Jill's Operating Expenses was $363.16 million through Aug 1, 2026, up 1.6% year-over-year; for FY2026 (ended Jan 31, 2026), it was $374.95 million, down 2.8% from FY2025.
- Operating Expenses shows a five-year compound annual growth rate of 0.4% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $385.58 million in FY2025 (+6.9%), $360.54 million in FY2024 (-0.8%), $363.36 million in FY2023 (+1.9%) and $356.72 million in FY2022 (-3.1%).
- The fiscal Q2 2027 figure marks the highest quarterly Operating Expenses since fiscal Q4 2020.
- Compared with a year earlier, Operating Expenses was higher in five of the last eight quarters, with growth averaging 1.5%.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q1 2023 (growth of 8.1%); the worst was fiscal Q3 2022 (a decline of 7.2%).
- Per Business Quant data, JILL's Operating Expenses in the three fiscal quarters before Q2 2027 was $89.72 million (Q1 2027), $86.99 million (Q4 2026) and $91.8 million (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,686.58 Bn | 2,203.28 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 283.87 Bn | 277.11 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 145.82 Bn | 123.36 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 103.43 Bn | 96.39 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.61 Bn | 57.54 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.16 Bn | 65.74 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 69.71 Bn | 68.80 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 68.78 Bn | 60.38 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.23 Bn | 45.13 Bn | 2.52 Bn | 1.60 Bn |
| 10 | J.Jill | 363.01 Mn | 150.43 Mn | 118.98 Mn | 94.65 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 94.65 Mn |
| May 2, 2026 | 89.72 Mn |
| Jan 31, 2026 | 86.99 Mn |
| Nov 1, 2025 | 91.80 Mn |
| Aug 2, 2025 | 88.57 Mn |
| May 3, 2025 | 91.09 Mn |
| Feb 1, 2025 | 89.31 Mn |
| Nov 2, 2024 | 88.65 Mn |
| Aug 3, 2024 | 86.31 Mn |
| May 4, 2024 | 89.11 Mn |
| Feb 3, 2024 | 90.84 Mn |
| Oct 28, 2023 | 86.45 Mn |
| Jul 29, 2023 | 84.28 Mn |
| Apr 29, 2023 | 82.97 Mn |
| Jan 28, 2023 | 90.54 Mn |
| Oct 29, 2022 | 84.87 Mn |
| Jul 30, 2022 | 84.28 Mn |
| Apr 30, 2022 | 85.58 Mn |
| Jan 29, 2022 | 85.20 Mn |
| Oct 30, 2021 | 85.53 Mn |
API Access
J.Jill 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=JILL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "JILL", "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=JILL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();