Ulta Beauty (NASDAQ:ULTA) reported better-than-expected earnings and revenue for the fiscal Q4 2023 and revised guidance for the full-year operating margin and capital expenditure.
The company’s shares fell over 3% in after-hours trading Thursday.
For Q4 2023, the American chain of beauty stores reported earnings per share (EPS) of $8.08, outshining the analysts' prediction of $7.52.
Quarterly revenues stood at $3.6 billion, topping the anticipated $3.53 billion.
Comparable sales grew by 2.5%, a significant drop from the previous year's 15.6% but slightly ahead of the 2.23% forecast.
The company maintained a steady gross margin of 37.7%, marginally better than the prior year's 37.6% and above the expected 37.3%.
Looking forward to the year, Ulta Beauty has adjusted its financial forecasts.
The company now projects its earnings per share to be in the range of $26.20 to $27, an increase from the previously forecasted range of $25.20 to $25.60.
Net sales are anticipated to reach between $11.7 billion and $11.8 billion.
The forecast for comparable sales growth has also been slightly revised, now expected to be between 4% and 5%, a slight decrease from the previously projected range of 5% to 5.5%.
Moreover, Ulta Beauty plans to increase its capital expenditures to between $415 million and $490 million, up from the earlier estimate of $400 million to $425 million.
However, the company has slightly reduced its operating margin outlook, now foreseeing margins between 14% and 14.3%, compared to the previously expected range of 14.6% to 14.8%.
The retailer also approved a $2 billion buyback program.
“We closed out a strong 2023 with better-than-expected fourth quarter financial performance. Our compelling holiday plans and thoughtfully curated assortment resonated with our guests and delivered healthy traffic, record brand awareness, and strong member growth,” said CEO Dave Kimbell.
“We enter 2024 well-positioned to drive strong top and bottom-line growth, build on our foundational capabilities, and unlock further advantages of our differentiated model.