Iron Mountain Q3 profit beats estimates on higher storage rental and service revenue

Reuters
Nov 05, 2025
Iron Mountain Q3 profit beats estimates on higher storage rental and service revenue

Overview

  • Iron Mountain Q3 revenue rises 12.6% yr/yr, meeting analyst expectations

  • Adjusted EPS for Q3 beats analyst expectations, reflecting strong performance

  • Company increases quarterly dividend by 10%, driven by AFFO growth

Outlook

  • Iron Mountain reiterates full-year 2025 guidance, with Q4 revenue expected to rise ~14%

  • Company expects Q4 2025 adjusted EBITDA to increase ~14%

Result Drivers

  • GROWTH BUSINESSES - Data center, digital, and ALM businesses collectively grew over 30% year-over-year, driving revenue growth

  • REVENUE INCREASE - Record revenue of $1.8 bln, driven by a 9.5% increase in storage rental revenue and a 15.3% increase in service revenue

  • ADJUSTED EBITDA GROWTH - Record Adjusted EBITDA of $660 mln, driven by increased revenue and improved operating leverage

Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q3 Revenue

Meet

$1.75 bln

$1.75 bln (8 Analysts)

Q3 Adjusted EPS

Beat

$0.54

$0.53 (6 Analysts)

Q3 EPS

$0.28

Q3 Net Income

$86 mln

Q3 Adjusted EBITDA

Beat

$660 mln

$639.80 mln (7 Analysts)

Q3 Adjusted EBITDA Margin

37.60%

Analyst Coverage

  • The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 10 "strong buy" or "buy", 1 "hold" and 1 "sell" or "strong sell"

  • The average consensus recommendation for the specialized reits peer group is "buy"

  • Wall Street's median 12-month price target for Iron Mountain Inc is $122.00, about 15.3% above its November 4 closing price of $103.32

  • The stock recently traded at 45 times the next 12-month earnings vs. a P/E of 45 three months ago

Press Release: ID:nBw6Sjp5pa

For questions concerning the data in this report, contact Estimates.Support@lseg.com. For any other questions or feedback, contact RefinitivNewsSupport@thomsonreuters.com.

(This story was created using Reuters automation and AI based on LSEG and company data. It was checked and edited by a Reuters journalist prior to publication.)

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