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TTAN — ServiceTitan News Story

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ServiceTitan Q1 revenue beats estimates on Max product expansion

ServiceTitan Q1 revenue beats estimates on Max product expansion


Overview

  • US trades software platform's fiscal Q1 revenue rose 25% yr/yr, beating analyst expectations

  • Company posted a GAAP net loss but improved operating margin from prior year

  • Non-GAAP income from operations more than doubled yr/yr, driven by growth initiatives


Outlook

  • ServiceTitan expects Q2 2027 revenue of $284 mln to $286 mln

  • Company sees full-year 2027 revenue between $1,130 mln and $1,140 mln

  • ServiceTitan expects Q2 2027 non-GAAP income from operations of $38 mln to $39 mln


Result Drivers

  • MAX PRODUCT EXPANSION - Co more than doubled the number of locations on Max in Q1 and expects to double again in Q2, per President Vahe Kuzoyan

  • PROCESS AUTOMATION - Co said it is optimizing internal processes and automating customer onboarding to improve efficiency

  • CUSTOMER MOMENTUM - Co said customers are off to a strong start in fiscal year 2027, per CEO Ara Mahdessian


Company press release: ID:nGNXbfWF1t


Key Details

Metric

Beat/Miss

Actual

Consensus Estimate

Q1 Revenue

Beat

$268.8 mln

$256.67 mln (17 Analysts)

Q1 Net Income

-$22.82 mln

Q1 Basic EPS

-$0.24

Q1 Gross Profit

$193.79 mln

Q1 Income from Operations

-$25.8 mln


Analyst Coverage

  • The current average analyst rating on the shares is "buy" and the breakdown of recommendations is 15 "strong buy" or "buy", 3 "hold" and no "sell" or "strong sell"

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

  • Wall Street's median 12-month price target for ServiceTitan Inc is $100.00, about 37.7% above its June 3 closing price of $72.63

  • The stock recently traded at 52 times the next 12-month earnings vs. a P/E of 66 three months ago


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