Artificial Intelligence (AI)-Driven Retail Media Attribution Market Report 2025

The artificial intelligence (AI)-driven retail media attribution market size has grown exponentially in recent years. It will grow from $1.62 billion in 2024 to $1.99 billion in 2025 at a compound annual growth rate (CAGR) of 23%. The growth observed during the historic period can be linked to the rising demand for customized manufacturing, the pursuit of cost-efficient production methods, the shortcomings of conventional manufacturing techniques, the increasing adoption of additive manufacturing, and the expansion of industries that require complex structures.

The artificial intelligence (AI)-driven retail media attribution market size is expected to see exponential growth in the next few years. It will grow to $4.51 billion in 2029 at a compound annual growth rate (CAGR) of 22.7%. The projected growth in the forecast period is expected to be driven by growing demand for sustainable and environmentally friendly manufacturing, expansion in construction and infrastructure projects, the need for faster prototyping and tooling, greater adoption of automation in production, and the rising requirement for on-site manufacturing capabilities. Key trends anticipated in this period include the integration of AI and machine learning for process optimization, the creation of new materials for three-dimensional (3D) printing, the broadening of 3D printing applications in aerospace and automotive sectors, the increased use of 3D printing in construction, and advancements in multi-material printing technologies.

The increasing growth of e-commerce sales is playing a significant role in driving the artificial intelligence (AI)-driven retail media attribution market. E-commerce refers to the digital buying and selling of goods and services via websites, mobile applications, and other online platforms, offering consumers the convenience of shopping without visiting physical stores. This surge in e-commerce activity is primarily fueled by the widespread availability of the internet and smartphones, giving more people easy access to digital shopping channels. AI-driven retail media attribution supports this growth by enabling businesses to track consumer behavior across different platforms, optimize marketing campaigns in real time, and offer personalized shopping experiences that improve conversion rates. For example, in May 2025, the U.S. Census Bureau reported that e-commerce sales grew by 8.5% (±1.1%) in the first quarter of 2024 compared to the same period in 2023, while total retail sales rose by 2.8% (±0.5%). During this time, e-commerce made up 15.6% of all retail sales. As a result, the expansion of e-commerce is contributing significantly to the growth of the AI-driven retail media attribution market.

Leading companies in the AI-driven retail media attribution sector are developing advanced solutions such as deterministic attribution models to more accurately link advertising efforts to actual sales results. These models use verified first-party data to connect customer actions directly to marketing touchpoints, giving brands a more accurate understanding of return on investment and the customer journey. For instance, in July 2025, AiOpti Media LLC, a U.S.-based company specializing in data, media, and analytics, introduced an AI-powered attribution and measurement platform. This platform combines data, media, and analytics to offer comprehensive insights into marketing performance. It includes features such as OptiRevea, which identifies under-targeted audience segments, and a Super AIdentity Graph that converts anonymous website visitors into verified identities without relying on cookies. It also enables omnichannel ad delivery across platforms such as connected TV, audio, video, display, and out-of-home media using deterministic signals. Furthermore, it supports offline attribution by utilizing real-time location and purchase data to track in-store engagement, along with customer journey analytics to refine every stage of the buying process. Built with a privacy-centric framework, the solution allows brands, agencies, and multi-location businesses to turn first-party data into actionable insights that enhance growth, customer relationships, and media return on investment.

In March 2022, Nielsen Consumer LLC, a U.S.-based consumer intelligence firm, acquired ciValue Ltd. for an undisclosed amount. Through this acquisition, NielsenIQ aimed to improve its retail media offerings by integrating ciValue’s AI-based personalization and audience insight capabilities into its Connect platform. This integration allows retailers to make smarter, data-driven decisions, generate new revenue streams, boost sales, and increase customer engagement through targeted, scalable retail media strategies. ciValue Ltd., based in Israel, provides a SaaS platform that specializes in AI-powered retail media attribution and personalized marketing solutions.

Major players in the artificial intelligence (ai)-driven retail media attribution market are Walmart Inc., Amazon.com Inc., Google LLC, Microsoft Corporation, Meta Platforms Inc., Eagle Eye Solutions Group, Oracle Corporation, Salesforce Inc., Tata Consultancy Services Limited, Adobe Inc., Omnicom Media Group, Dentsu Group Inc., NielsenIQ Holdings LLC, Epsilon Data Management LLC, The Trade Desk Inc., Criteo SA, Zeta Global Holdings Corp., LiveRamp Holdings Inc., Tinuiti Inc., Skai Holdings Inc., and Measured Inc.

North America was the largest region in the artificial intelligence (AI)-driven retail media attribution market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in artificial intelligence (AI)-driven retail media attribution report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa. The countries covered in the artificial intelligence (AI)-driven retail media attribution market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report’s Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the retail and wholesale sector, particularly in sourcing, inventory management, and pricing strategies. Higher duties on imported consumer goods including electronics, apparel, furniture, and packaged foods have raised procurement costs for retailers and wholesalers, compelling many to either increase prices for end consumers or absorb losses. Small and mid-sized businesses with limited pricing power are especially vulnerable, often facing squeezed margins and reduced competitiveness. Inventory cycles are also disrupted as firms grapple with delays and uncertainty in international supply chains. Additionally, retaliatory tariffs in foreign markets have curtailed export opportunities for U.S. brands, limiting revenue growth. In response, companies are shifting toward domestic and regional suppliers, investing in supply chain resilience, and adopting data-driven demand forecasting to navigate cost volatility and maintain customer satisfaction.

AI-driven retail media attribution refers to the application of artificial intelligence to monitor and evaluate how retail media campaigns influence consumer purchasing decisions. By using machine learning and data analytics, it determines which marketing touchpoints have the strongest impact on sales and conversions. This method allows for more precise assessment of campaign effectiveness and real-time optimization of marketing strategies.

The core elements of AI-driven retail media attribution are software and services. Software acts as a digital tool that applies AI and analytics to monitor, assess, and enhance marketing performance across different touchpoints. It incorporates various attribution models, such as single-touch, multi-touch, and algorithmic attribution, and can be implemented through cloud-based or on-premises systems. These solutions are used in e-commerce, physical retail, and omnichannel environments, serving retailers, brands, agencies, and other stakeholders.

The artificial intelligence (AI)-driven retail media attribution market research report is one of a series of new reports that provides artificial intelligence (AI)-driven retail media attribution market statistics, including artificial intelligence (AI)-driven retail media attribution industry global market size, regional shares, competitors with the artificial intelligence (AI)-driven retail media attribution market share, artificial intelligence (AI)-driven retail media attribution market segments, market trends, and opportunities, and any further data you may need to thrive in the artificial intelligence (AI)-driven retail media attribution industry. This artificial intelligence (AI)-driven retail media attribution market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The artificial intelligence (AI)-driven retail media attribution market consists of revenues earned by entities by providing services such as attribution modeling, marketing analytics and insights, campaign performance measurement, and reporting and visualization services. The market value includes the value of related goods sold by the service provider or included within the service offering. Only goods and services traded between entities or sold to end consumers are included.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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