Similarweb Ltd (SMWB) Fair Value & Analysis
Technology · US · Market cap $449M
Fair value as of: Jun 24, 2026
Analysis
Similarweb Ltd (SMWB) currently trades at $4.97, while our model-based Fair Value estimate is $0.8000 — implying the stock looks roughly 83.9% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: medium).
About the company
Similarweb Ltd. provides digital data and analytics for power critical business decisions in the United States, Europe, the Asia Pacific, the United Kingdom, Israel, and internationally. The company offers web intelligence solutions for its customers to benchmark performance against competitors, analyze trends in the market, conduct deeper research into specific companies, and analyze audience behavior; and solutions for its customers to understand their competitors' digital acquisition strategies on various marketing channel, and optimize their own strategies. It also provides app intelligence that allows its customers to identify trends and monitor usage and performance for mobile apps, as well as to benchmark performance against competitors across the funnel from app store downloads to usage and stickiness; sales intelligence solutions for its customers to access relevant buying signals and digital insights of their customers to generate leads quickly; and retail intelligence sol…
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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.