Appian Q3 revenue up 21%, beats expectations

Reuters
Nov 06, 2025
Appian Q3 revenue up 21%, beats expectations

Overview

  • Appian Q3 total revenue grows 21% yr/yr, beating analyst expectations

  • GAAP net income for Q3 was $7.8 mln, compared to a loss last year

  • Non-GAAP operating income rose to $29.8 mln from $8.3 mln last year

Outlook

  • Appian expects Q4 cloud subscriptions revenue between $115 mln and $117 mln

  • Company sees Q4 total revenue between $187 mln and $191 mln

  • Appian forecasts full-year cloud subscriptions revenue between $435 mln and $437 mln

  • Company expects full-year total revenue between $711 mln and $715 mln

Result Drivers

  • CLOUD SUBSCRIPTIONS - Cloud subscriptions revenue increased 21% yr/yr to $113.6 mln, driving overall revenue growth

  • PROFESSIONAL SERVICES - Professional services revenue rose 29% yr/yr to $39.8 mln, contributing to total revenue increase

  • OPERATING INCOME IMPROVEMENT - Transitioned from GAAP operating loss last year to GAAP operating income of $13.1 mln this year

Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q3 Revenue

Beat

$187.004 mln

$174.08 mln (6 Analysts)

Q3 Net Income

$7.83 mln

Q3 Gross Profit

$141.71 mln

Q3 Operating Expenses

$128.60 mln

Q3 Operating Profit

$13.11 mln

Q3 Pretax Profit

$9.20 mln

Analyst Coverage

  • The current average analyst rating on the shares is "hold" and the breakdown of recommendations is 1 "strong buy" or "buy", 6 "hold" and 1 "sell" or "strong sell"

  • The average consensus recommendation for the software peer group is "buy."

  • Wall Street's median 12-month price target for Appian Corp is $33.00, about 11.1% above its November 5 closing price of $29.33

  • The stock recently traded at 58 times the next 12-month earnings vs. a P/E of 76 three months ago

Press Release: ID:nGNX5H8sqc

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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