eClerx Services Limited (ECLERX) Fair Value & Analysis
Technology · IN · Market cap ₹129B
Fair value as of: Jun 29, 2026
Analysis
eClerx Services Limited (ECLERX) currently trades at ₹1,405, while our model-based Fair Value estimate is ₹1,524 — implying the stock looks roughly 8.5% undervalued today. We read business quality at 97/100 (high quality), in the Technology sector. Bull case: trading below our estimate, it may offer upside if the fundamentals hold. Bear case: a low price can be a value trap when quality is weak or the data is thin (evidence: high) — always confirm before acting.
About the company
eClerx Services Limited provides business process management, change management, data-driven insights, and advanced analytics services in India, the United States, the United Kingdom, Europe, and the Asia Pacific. It offers omnichannel customer support services, customer care journey mapping and insights, automated quality monitoring, workforce management, and field technical operations; digital marketing services, including omnichannel campaigns, creative production, MarTech enablement, search and media operations, and content and commerce services; and creative and content productions, such as photo/video, post-production, 3D CGI, VR/AR, digital workflows, and omnichannel delivery. The company also provides market intelligence services which include digital shelf analytics, competitor intelligence, pricing intelligence, assortment optimization, product launch, revenue and yield management, and bid management; anti-money laundering, anti-bribery and compliance, fraud detection and …
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.