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Sprinklr CXM Professional services — Total Cost of Revenue

Other product segments

Subscription
$50.85M+20.5%

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Other financials

Income statement

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Revenue$219.5M+6.8%
Gross profit$143.0M+0.1%
Operating income$10.6M+705%
Net income$4.2M+367%
EPS (diluted)$0.02+300%

Balance sheet

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Cash & equivalents$171.9M+27.2%
Total debt$43.8M-13.9%
Total equity$488.5M-23.7%
Total assets$1.1B-10.7%

Cash flow

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Operating cash flow$70.4M-16.0%
CapEx$328.0K+13.5%
Free cash flow$70.0M-16.1%

Valuation

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Market cap$1.17B-43.5%
Enterprise value$1.05B-47.5%
P/E41×+22.0×
P/S1.4×-1.2×

Profitability

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Gross margin66.3%-4.7pp
Operating margin6%+4.0pp
Net margin3.3%-10.3pp
FCF margin16.6%+2.2pp

Returns & leverage

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Return on equity5.1%-12.4pp
Debt / equity0.1×0.0×
Current ratio1.4×-0.3×

Where this comes from

Reported directly by Sprinklr in its filing.

Tagged under the XBRL concept us-gaap:CostOfGoodsAndServicesSold.

The official record: Sprinklr’s 10-Q, filed June 4, 2026, on SEC EDGAR. View the filing →

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Questions, answered.

What is Sprinklr's professional services — total cost of revenue?
Sprinklr (CXM) reported professional services — total cost of revenue of $25.59M in Q1 2026.
How has Sprinklr's professional services — total cost of revenue changed year-over-year?
Sprinklr's professional services — total cost of revenue increased by 25.2% year-over-year, from $20.45M to $25.59M.
What is the long-term trend for Sprinklr's professional services — total cost of revenue?
Over 4 years (2022 to 2026), Sprinklr's professional services — total cost of revenue has grown at a 15.0% compound annual growth rate (CAGR), from $57.65M to $100.78M.
What does professional services — total cost of revenue mean?
This metric captures the direct costs associated with delivering professional services, such as personnel expenses for consultants, travel, and third-party contractor fees. Monitoring this figure helps assess the operational efficiency and gross margin profile of the services division. High costs relative to service revenue may indicate inefficiencies in delivery models or the need for improved automation in implementation processes.