Info Edge shares in focus as Q4 net profit jumps 22% to Rs 566 crore, revenue rises 16%

Shares of Info Edge will be in focus heading into trade on Monday after it reported a consolidated net profit of Rs 566 crore for the quarter ended March 2026, marking a 22% increase from Rs 463 crore recorded in the same period last year.

The operator of Naukri and Jeevansathi posted consolidated revenue of Rs 869 crore in Q4FY26, up 16% from Rs 750 crore in the corresponding quarter of the previous financial year.

The company’s board recommended a final dividend of Rs 3.60 per equity share for FY26. The proposal is subject to shareholder approval at the 31st Annual General Meeting scheduled for August 25, 2026. Info Edge has fixed July 24, 2026, as the record date to determine eligible shareholders.

On a standalone basis, revenue from operations rose 17.2% year-on-year to Rs 805 crore during the March quarter. Operating profit climbed 39.4% to Rs 323 crore, while operating profit margin stood at 40% of revenue in Q4FY26.

The standalone business generated cash from operations, before taxes, of Rs 621.1 crore during the quarter.

For the full year FY26, standalone revenue from operations increased 15% year-on-year to Rs 3,052 crore, while operating profit grew 16.9% to Rs 1,138 crore.

Cash generated from operations before taxes for the full year stood at Rs 1,469 crore. Revenue from the recruitment business rose 13.8% year-on-year, while combined revenue from non-recruitment businesses grew 18.6% during FY26.

Commenting on the performance, Managing Director and Chief Executive Officer Hitesh Oberoi said FY26 was a steady year for the company. He noted that revenue growth remained measured while operating margins improved through the year, particularly in the recruitment business. He also said that 99acres and Jeevansathi continued to strengthen their market positions and gain market share.

Oberoi added that the company made significant progress in deploying artificial intelligence across its businesses, increasing its use in matching and recommendation engines while also developing new AI-native products and features aimed at improving user and customer experience.