Particular Audience Unveils AI Tools To Power Retail Media Networks

Retail media networks are entering a new phase as retailers look for greater flexibility, stronger performance, and faster innovation without overhauling their existing technology stacks. This shift matters to the MarTech ecosystem because retail media is now one of the fastest growing digital revenue channels, and the tools that power it are rapidly evolving.

Particular Audience has announced the launch of a new suite of AI tools for retail media networks, designed to help retailers enhance monetisation and personalisation without replacing their incumbent adtech platforms. The new offering introduces a modular retail media approach that allows RMN operators to plug advanced capabilities into their current systems feature by feature.

The release is built around the idea that retail media should no longer be constrained by single, closed platforms. Instead, retailers can deploy specific modules that address clear objectives such as personalisation, reporting, basket building, and awareness, while maintaining a seamless customer experience. The tools are available through Particular Audience DiscoveryOS platform and can be adopted either as a complete solution or as individual API first components within an existing stack.

James Taylor, chief executive officer of Particular Audience, said, “The era of monolithic retail media is ending.” He added, “Modular retail media introduces a new way for retailers to build and scale commerce monetisation, feature by feature, rather than by adopting a single closed platform.”

The modular retail media solution includes 13 modules, each aligned to a distinct commercial or operational goal. Within those modules are 74 individual components that retailers can activate as needed. This structure allows RMN operators to scale capabilities gradually, matching investment to maturity and demand rather than committing to a single all or nothing deployment.

According to Taylor, retail media must integrate more closely with the wider commerce experience. “Retail media shouldn’t operate in a silo,” he said. “It should be composable, transparent and interoperable, and that’s what this modular system delivers.”

Early campaign results illustrate the commercial impact of this approach. In a campaign for LEGO, Particular Audience reported a 142 percent uplift in share of revenue during the first two weeks. After additional modules were introduced and optimised, that uplift increased to 334 percent. The company also cited stronger performance from sponsored placements on product detail pages, with clickthrough rates more than double those of sponsored search in comparable conditions.

The technology is designed to support a wide range of retail media use cases, from AI driven search automation and semantic targeting to intelligent product bundles that respond to basket patterns and inventory signals. Retailers can license modules using flexible commercial models, including performance based, impression based, tenancy based, or subscription pricing.

Trusted by retailers and brands such as Target, Sony, and Royal Canin, Particular Audience positions its modular system as a way to unlock previously overlooked monetisation points across the funnel.

As retail media continues to mature, the launch signals a broader industry move toward flexible, AI driven architectures that prioritise outcomes over formats. By giving retailers control over how and where innovation is applied, Particular Audience AI tools for retail media networks aim to deliver both stronger commercial results and better shopper experiences.