Physicswallah / Q3-FY26

PWL Q3 FY26 earnings call.

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Revenue

₹1,082 Cr

verified against source

Revenue YoY

34%

reported change

EBITDA

₹218 Cr

latest reported figure

Source

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Actual signal trajectory

Where this quarter sits.

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EBITDA (₹ Cr)PositiveWatchNegative
2 actual records
Actual quarterly EBITDA (₹ Cr) trajectoryReported values plotted by quarter. Hover or focus a point for its quarter, value, and source sentiment.Q3 FY26: 218 · Positive source sentimentQ3 FY26Q4 FY26: 9 · Positive source sentimentQ4 FY262189
Values are taken from the available verified source records; sentiment color is a separate source-read indicator.

Quarter read

What the record says.

Physicswallah delivered a strong Q3 FY26 with ₹1,082 crore revenue (+34% YoY) and ₹218 crore EBITDA (20.2% margin), growing PAT to ₹102 crore despite ₹23 crore one-time charges from IPO and labor code changes. Online contributes 51% of revenue at 31% growth; offline is 46% at 26% growth. The company raised full-year revenue guidance to 32-35% growth, with 9-month revenue of ₹2,980 crore already surpassing prior-year full-year ₹2,886 crore. K12 expansion is the strategic pivot—₹400 crore allocated to school management, 70 new offline centers planned at ₹200 crore capex. New categories (CLAT, NEPG, IIT JAM) contributed ₹32 crore in 9 months; state boards scaled to 175,000 paid learners (₹22 crore); vernacular reached 94,000 paid students (₹24 crore). AI initiatives (Arbutus, PW Talks) are bearing fruit with in-house proprietary data. Risk: K12 currently contributes less than 1% of revenue with payback cycles of 12+ years, and J/NEET growth has slowed to low-single digits in penetrated markets.

Colored figures show movement against the previous available record.

Guidance to track

  • Management guided full-year FY26 revenue growth in the range of 32% to 35%, driven by strong performance in both online and offline segments with continued momentum expected in Q4.
  • Full-year marketing spends will be significantly lower than last year's 9.6%, at 8-8.5% of revenue, as Q1/Q2 investments generated higher ROI and marketing leverage will emerge in Q4.
  • Company plans to open 70 offline learning centers next year with an outlay of ₹200 crore, continuing the asset-light built-to-suit model for expansion.
  • Management anticipates K12 will become a larger business than test prep within 5 years (by FY30), benchmarking against China education companies where K12 is 40% of revenue vs test prep at 30%.

Risks flagged

  • JEE/NEET enrollment growth has slowed to low-single digits (3-4%) because the denominator is large and penetration is very high in North India. Analysts questioned whether this pattern will replicate in other categories as they mature.
  • K12 currently contributes less than 1% of revenue with payback cycles exceeding 12 years as students stay enrolled from grade 1 to 12. Capital allocation of ₹400 crore (and potentially more) is a long-duration bet with uncertain near-term returns.
  • Tech and product team costs increased 40% year-over-year despite overall tech spend as percentage of revenue declining due to scale. AI talent competition could pressure margins as the company invests in AI initiatives.
  • Management deflected specific questions about K12 school unit economics, margins, and capital requirements beyond the initial ₹400 crore allocation, citing it as a 'long-term story' without providing detailed financial roadmap.

Key quotes

  • K12 will become larger than a test prep business down the line 5 years is what I imagine and if you benchmark any company in China—New Oriental, TAL Edu—all are listed, their K12 business is larger than their test business.
  • We generally acquire profitable entities and the range of the multiple we give to these companies is anywhere between 8 to 12 and we believe in earn-out structure where we don't take a short majority. We take anywhere between 25 to 50% equity as the first go and up to a 3-4 year earnout structure for the founders.
  • Our AI grader tools are completely designed for Indian test prep kids, completely designed by our own in-house proprietary data, millions of students' daily learning behavior patterns, data points or RAG layer as well. Our small language model operates better than Gemini or GPT-4.

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