SPS Commerce, Inc (SPSC) Fair Value & Analysis
Technology · US · Market cap $2.1B
Analysis
SPS Commerce, Inc (SPSC) currently trades at $54.78, while our model-based Fair Value estimate is $50.85 — implying the stock looks roughly 7.2% 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: high).
About the company
SPS Commerce, Inc. provides cloud-based supply chain management solutions in the United States. It offers solutions through SPS Commerce, a cloud-based platform that connects retailers, brands, distributors, manufacturers, and logistics providers, handling the complexity of modern commerce operations. The company also provides Fulfillment, a comprehensive solution designed to streamline supply chain operation that sends and receives order data, ensuring accurate execution of required processes from order to invoicing and revenue recovery through fully automated operations; and Analytics product that simplifies managing sell-through data from customers business partners that handle data acquisition, cleansing, normalization, and delivery. In addition, it offers various complimentary products, such as assortment product, which simplifies the communication of robust, accurate item data by automatically translating item attributes, and hierarchies through single connection across all sa…
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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.