Top Retail Analytics Companies

The retail analytics market is projected to grow from USD 11.82 billion in 2026 to USD 23.21 billion by 2032, at a CAGR of 11.9%. The retail analytics market is witnessing significant growth as retailers increasingly use data, AI, and machine learning to improve decision-making across merchandising, supply chain, store operations, and customer engagement. Retailers are deploying predictive demand forecasting, inventory analytics, assortment optimization, customer segmentation, pricing analytics, and real-time performance monitoring to improve operational efficiency and profitability. Growth is supported by expanding omnichannel retail, rising e-commerce activity, increasing volumes of transaction and customer data, and greater requirements for real-time inventory visibility. Retailers are also integrating data from stores, digital channels, supply chains, loyalty programs, and external signals to create more unified analytical environments. AI adoption is strengthening analytics capabilities by enabling demand prediction, personalized recommendations, automated planning, and proactive supply chain decisions. Vendors are consequently enhancing retail analytics platforms with generative AI, machine learning, cloud data architectures, real-time intelligence, and automated decision-support capabilities.

Vendors in the market, such as Oracle Corporation (US), Salesforce (US), SAP (Germany), Teradata Corporation (US), Microsoft (US), and Adobe Inc. (US), are accelerating growth through product innovation, AI integration, cloud expansion, and ecosystem partnerships. Organic initiatives increasingly focus on predictive forecasting, inventory optimization, merchandising intelligence, pricing optimization, customer analytics, and supply chain planning. Microsoft is expanding AI-enabled retail capabilities across assortment optimization, demand forecasting, pricing, promotions, inventory planning, and real-time supply chain visibility. Oracle combines descriptive, predictive, and prescriptive analytics across merchandising, customer insights, demand forecasting, assortment, pricing, and inventory optimization. SAP is strengthening AI-driven retail planning, forecasting, customer intelligence, inventory management, and supply chain analytics capabilities. These developments expand retailers' ability to turn high-volume operational and customer data into faster, more automated, and actionable business decisions.

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In July 2026, Oracle expanded its commercial engagement with Bealls by adopting Oracle Retail Lifecycle Pricing Optimization technology. The solution analyzes real-time demand, inventory, regional factors, and projected margins to optimize markdown decisions. Oracle reported that Bealls increased clearance sales dollars by 25% within one year of implementation. The deployment replaces fixed discount schedules with AI-driven recommendations tailored to item-level performance and inventory conditions. This expansion strengthens Bealls’ pricing analytics capabilities while supporting profitability, sell-through, and more responsive clearance management.

In January 2026, Salesforce expanded its Google partnership by supporting Universal Commerce Protocol within Agentforce Commerce. The integration enables merchants to connect products and checkout experiences across Google’s emerging AI-driven shopping surfaces. Native protocol support extends conversational commerce into Google Search AI Mode and the Gemini application. The collaboration helps retailers expose product information through standardized interfaces supporting discovery, personalization, and transaction completion. This partnership strengthens Salesforce’s retail commerce ecosystem while expanding data-driven interactions across agentic customer journeys.

Oracle is strongly positioned in retail analytics through its integrated Retail Analytics and Planning solution portfolio. The platform supports descriptive, predictive, and prescriptive analytics across merchandising, customers, demand, assortment, pricing, and inventory. Retail AI Foundation applies machine learning to forecasting, segmentation, clustering, inventory placement, offers, and pricing decisions. Oracle Retail Insights delivers merchandise, customer, and consumer insights through centralized retail data and analytical dashboards. These capabilities help retailers turn operational data into actionable decisions that support profitability, availability, and customer engagement.

Salesforce is well positioned in retail analytics through Tableau, Data 360, Commerce Intelligence, and retail applications. Commerce Intelligence provides merchant dashboards and AI insights to evaluate performance and optimize commercial decisions. Data 360 unifies commerce information, while Tableau supports visual analytics, monitoring, predictions, and conversational exploration. Agentforce Merchant Agent uses real-time data to recommend actions supporting merchandising, inventory movement, and conversions. Together, these capabilities strengthen data-driven retail decision-making across commerce, customer engagement, merchandising, and operational workflows.

Market Ranking Analysis

Oracle Corporation, Salesforce, Inc., Microsoft Corporation, SAP SE, Teradata Corporation, Adobe Inc., Zebra Technologies Corporation, Shopify Inc., Lightspeed Commerce Inc., and Manhattan Associates, Inc. are among the prominent players in the retail analytics market. Oracle strengthens its market position through Oracle Retail AI Foundation, Retail Insights, Lifecycle Pricing Optimization, Inventory Planning Optimization, and assortment analytics capabilities. These solutions support retailers across customer segmentation, demand forecasting, pricing, promotions, inventory placement, merchandising, and operational decision-making. Salesforce strengthens its position through Commerce Intelligence, Data 360, Tableau, and Agentforce capabilities supporting merchant dashboards, customer intelligence, merchandising insights, and real-time recommendations. Microsoft differentiates through AI-enabled retail solutions supporting consumer insights, assortment optimization, predictive demand forecasting, store analytics, and supply chain intelligence. SAP extends its retail analytics capabilities with demand forecasting, predictive analytics, shopper insights, and planning applications that support merchandise and inventory decisions. Teradata supports retailers through integrated cloud analytics, AI/ML, pricing, category management, customer personalization, supply chain forecasting, and profitability analytics. Adobe strengthens customer-focused retail analytics through Customer Journey Analytics, enabling cross-channel analysis across digital, in-store, POS, campaign, and customer interaction data. Zebra Technologies focuses on actionable retail intelligence supporting inventory anomaly detection, shrink reduction, store operations, and inventory accuracy. Shopify and Lightspeed Commerce provide embedded analytics covering sales, inventory, customers, store performance, profitability, and merchandising decisions. Manhattan Associates strengthens its position through real-time sales, fulfillment, inventory, customer behavior, and store-performance insights integrated within omnichannel retail operations. Together, these companies continue strengthening their market positions through AI integration, unified retail data, predictive intelligence, automation, and increasingly real-time analytics.

Related Reports:

Retail Analytics Market by Solution (Enterprise Suite, Customer Intelligence, Planning & Decision Intelligence, AI Suite), Application (Sales, Merchandising, Marketing, Supply Chain, Inventory), Retail Type, Region - Market Size, Share & Forecast to 2032

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