DELRAY BEACH, Fla., Sept. 11, 2026 /PRNewswire/ — According to MarketsandMarkets™, 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%.
Browse 350 market data Tables and 70 Figures spread through 400 Pages and in-depth TOC on ‘Retail Analytics Market – Market Size, Share & Forecast to 2032’
Retail Analytics Market Size & Forecast:
- Market Size Available for Years: 2021–2032
- 2025 Market Size: USD 10.44 billion
- 2026 Market Size: USD 11.82 billion
- 2032 Projected Market Size: USD 23.21 billion
- CAGR (2026–2032): 11.9%
Retail Analytics Market Trends & Insights:
- 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.
- By offering, the solutions segment is estimated to account for the largest share of 75.5% in 2026.
- By analytics type, autonomous & agentic analytics are slated to grow the fastest between 2026 and 2032.
- By application, the enterprise decision intelligence segment is expected to witness the highest growth rate over the forecast period.
- By retail type, the beauty & personal care retail segment is expected to witness the fastest growth rate over the forecast period.
- The Asia Pacific region is poised to register the highest CAGR of 14.9% over the forecast period.
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The Retail Analytics Market is expanding rapidly as retailers increasingly adopt integrated platforms for data-driven decision-making. Growth is driven by investments in artificial intelligence, omnichannel commerce, inventory optimization, and customer intelligence. Retailers consolidate transaction, inventory, pricing, merchandising, loyalty, ecommerce, and supply chain data across connected environments. Predictive models improve demand forecasting, assortment planning, replenishment, pricing, and customer engagement across retail operations. Real-time analytics enables faster responses to demand shifts, stock imbalances, operational exceptions, and shopper behavior. Cloud platforms support scalable analytics while improving forecasting accuracy, inventory productivity, and operational decision-making across retailers.
Based on analytics type, AI-embedded & predictive analytics are positioned to dominate the market in 2026.
AI-embedded and predictive analytics are positioned to dominate in 2026 as retailers prioritize proactive decision-making capabilities. These solutions combine machine learning, historical data, and real-time signals to forecast demand and operational outcomes. Retailers use predictive models to optimize inventory, pricing, assortment, promotions, replenishment, and customer engagement decisions. Oracle applies machine learning within Retail AI Foundation to improve forecasting, segmentation, clustering, and inventory optimization. Predictive analytics also helps retailers identify demand changes earlier and reduce stockouts, overstocks, and avoidable markdowns. Embedded AI increasingly brings recommendations directly into merchandising, supply chain, customer, and store management workflows. NRF highlights predictive analytics for improving forecasting accuracy, optimizing inventory, reducing waste, and streamlining supply chains. These capabilities strengthen adoption as retailers seek faster, automated, and measurable decision support across operations.
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Based on retail type, beauty & personal care retail is set to register the fastest growth during the forecast period.
Beauty and personal care retail is expected to register the fastest growth during the forecast period. Beauty retailers increasingly combine physical stores, ecommerce, social commerce, loyalty programs, and personalized digital experiences. Frequent launches, short trend cycles, and individualized product preferences create strong requirements for advanced retail intelligence. L’Oréal increasingly applies artificial intelligence and proprietary beauty data to personalize recommendations and improve consumer experiences. Its Beauty Tech ecosystem combines millions of data points across products, consumers, routines, and engagement touchpoints. AI-powered services also help beauty retailers strengthen product discovery, conversion, loyalty, and personalized shopping journeys. Growing ecommerce penetration further increases requirements for assortment, pricing, inventory, promotion, and customer behavior analysis. These trends support faster analytics adoption across beauty and personal care retailers seeking differentiated omnichannel experiences.
By region, North America is estimated to account for the largest Retail Analytics Market in 2026.
North America is estimated to account for the largest Retail Analytics Market share in 2026. The region benefits from mature cloud infrastructure, high technology spending, and advanced omnichannel retail ecosystems. United States retailers generate extensive transaction, ecommerce, inventory, loyalty, merchandising, and fulfillment data requiring continuous analysis. Census Bureau data shows ecommerce represented 17.1% of total United States retail sales during second-quarter 2026. Retailers increasingly deploy predictive analytics, artificial intelligence, inventory optimization, personalization, and real-time operational intelligence capabilities. The region also hosts major cloud, enterprise software, analytics, and retail technology providers supporting adoption. NRF highlights continued investment in artificial intelligence, inventory management, supply chains, automation, and agentic retail technologies. Strong vendor ecosystems, sophisticated retailers, and continuous technology adoption reinforce North America’s leadership throughout the forecast period.
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Top Companies in Retail Analytics Market:
The Top Companies in Retail Analytics Market are Oracle Corporation (US), Salesforce, Inc. (US), Microsoft Corporation (US), SAP SE (Germany), Teradata Corporation (US), Adobe Inc. (US), Zebra Technologies Corporation (US), Shopify Inc. (Canada), Lightspeed Commerce Inc. (Canada), Manhattan Associates, Inc. (US), UiPath Inc. (US), NielsenIQ (NIQ) (US), Databricks, Inc. (US), and Infor, Inc. (US), among several others.
Retail Analytics Market – Investment & funding +Merger & Acquisition
Investment Funding Context
The Retail Analytics Market continues to attract investment, with capital shifting toward AI-native software, autonomous decisioning, real-time demand forecasting, and agentic merchandising suites. Funding remains concentrated among platforms that can optimize complex enterprise planning without creating data fragmentation. In May 2025, Impact Analytics raised USD 15 million in a Series D growth investment led by Blue Cloud Ventures, building upon previous backing from existing partners Sageview Capital and Vistara Growth. In January 2025, RetailNext announced a strategic majority growth investment from technology-focused investor Battery Ventures. The investment provides additional capital for product development, geographic expansion, acquisitions, and broader retail analytics innovation. CommerceIQ reports raising USD 200 million from venture investors including SoftBank, Insight Partners, and Madrona Venture Group. This capital injection will accelerate regional development across major international territories while scaling autonomous decisioning mechanisms across the entire retail value chain.
Revenue Shift Context
The global Retail Analytics Market is projected to grow from USD 11.82 billion in 2026 to USD 23.21 billion. At an 11.9% CAGR, revenue generation increasingly shifts toward AI-embedded, predictive, prescriptive, and agentic analytics capabilities. Platform revenues increasingly reflect demand for forecasting, merchandising, pricing, inventory optimization, customer intelligence, and decision automation. Services spending also expands as retailers require implementation, integration, model configuration, data engineering, and ongoing optimization support. Growing cloud adoption and unified planning investments are strengthening recurring software revenues across increasingly connected retail operations.
Mergers and Acquisitions
M&A activity from August 2025 through August 2026 shows growing buyer interest in AI-enabled retail analytics platforms. Strategic acquirers are using transactions to expand forecasting, inventory optimization, store intelligence, measurement, and decision capabilities. Key transactions included Instacart’s acquisition of Arpalus and RELEX Solutions’ acquisition of Ida. Circana also acquired Nielsen’s Marketing Mix Modeling business and NCSolutions to strengthen advanced measurement and shopper intelligence. Together, these transactions broaden vendor capabilities across retail planning, operations, customer intelligence, and analytics-led decision execution.
RETAIL ANALYTICS MARKET: MERGERS AND ACQUISITIONS, AUGUST 2025–AUGUST 2026
| Month & Year | Deal Type | Company 1 | Company 2 | Description |
| July 2026 | Acquisition | Instacart (US) | Arpalus Ltd. (Israel) | Instacart acquired Arpalus, a computer-vision company providing shelf intelligence technology specifically developed for grocery retailers. Arpalus strengthens real-time inventory visibility, shelf availability analytics, fulfillment accuracy, and AI-powered in-store retail intelligence capabilities. |
| December 2025 | Acquisition | RELEX Solutions (Finland) | Ida (France) | RELEX acquired Ida, an AI-native fresh replenishment and store-ordering optimization provider serving grocery retailers. The acquisition extends RELEX analytics into fresh forecasting, automated ordering, production planning, and store-level inventory optimization. |
| August 2025 | Acquisition | Circana LLC (US) | Nielsen Marketing Mix Modeling Business (US) | Circana completed its acquisition of Nielsen’s Marketing Mix Modeling business, expanding advanced statistical modeling and measurement capabilities. The acquisition strengthens predictive analysis of marketing investments, channel performance, optimization opportunities, and return on investment. |
Company Revenue Share Details
The total market share of the top five players is 23.4%, representing a fragmented market. This fragmentation indicates that no single vendor has established dominant control, leaving significant room for competition and consolidation in the years ahead. The top 10 key players, contributing to around 38.9% of the total market share, are Oracle Corporation (US), SAP SE (Germany), Salesforce, Inc. (US), Circana, LLC (US), NielsenIQ (NIQ) (US), Adobe Inc. (US), SAS Institute Inc. (US), Blue Yonder Group, Inc. (US), Microsoft Corporation (US), and Sensormatic Solutions LLC (US. The presence of both established enterprise technology providers such as Salesforce (US), Adobe (US), Oracle Corporation (US), Microsoft Corporation (US), and SAP SE (Germany), alongside specialized retail analytics vendors such as CommerceIQ, Inc. (US), RetailNext, Inc. (US), COMPETERA Inc. (US), Retalon, Inc. (Canada) and DataWeave Software Private Limited (US) reflects the market’s broad competitive landscape and suggests that continued investment, acquisitions, AI development, and retailer modernization should intensify competition across the market through 2032.
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