How retailers are finally solving the audience targeting puzzle

IAB Australia released a strategic blueprint on December 10, 2025, outlining systematic audience segmentation approaches that retail media networks must implement to transform first-party data into measurable advertising performance. The document provides explicit frameworks for 16 distinct segmentation types, ranging from foundational RFM analysis to advanced predictive customer lifetime value modeling, addressing persistent fragmentation that has limited retail media adoption across advertisers, agencies, and retailers.

The blueprint emerged from IAB Australia's Retail Media Council and arrives as retail media networks position themselves to capture 20% of global advertising revenue by 2030. The publication establishes specific technical requirements, measurement standards, and stakeholder responsibilities across the retail media ecosystem, moving beyond conceptual frameworks toward operational implementation guidance.

Three-stage maturity framework defines retail media capability

The blueprint categorizes retail media networks across three development stages, each requiring distinct data infrastructure and operational capabilities. Foundational networks rely on demographic and basic transactional data, offering limited targeting focused mainly on broad awareness campaigns. These networks face siloed systems and inconsistent identifiers as their primary challenge.

Developing networks introduce RFM analysis, basic lifecycle models, and mission-based targeting while implementing improved data unification across online and offline sources. Segments become increasingly actionable across multiple advertising formats as retailers progress through this maturity stage.

Advanced networks deploy propensity modeling, predictive CLV, real-time eligibility checks, and mission-context overlays. These segments activate seamlessly across on-site, in-store, and off-site channels while integrating clean room technology and incrementality testing as standard measurement practices.

Data readiness serves as the critical enabler across all stages. Retailers must invest in unified customer views, robust taxonomies, and operational infrastructure to progress along the maturity curve, the document states. Without these investments, advanced segmentation types remain aspirational rather than actionable.

The blueprint emphasizes that real-time triggers enable highly personalized response methodologies inside buying windows. Advanced data pipelines supporting event-based workflows allow integration from live customer interactions to message emitters, creating immediate advertising responses to consumer behavior signals.

Sixteen segmentation methods create multidimensional targeting

The toolkit section presents 16 distinct segmentation approaches that can be combined to create sophisticated audience strategies. Each method includes specific applications, required data inputs, and implementation warnings.

RFM segmentation categorizes customers by recency, frequency, and monetary value for CLV modeling, loyalty programs, and retention campaigns. The method requires transactional history but carries the limitation of being static and backward-looking, potentially overvaluing one-off bulk buyers rather than sustainable customer relationships.

Shopper missions contextualize purchase occasions, distinguishing between weekly shopping trips, convenience purchases, and distress shopping patterns. This segmentation draws from basket patterns and survey data but requires substantial resources and faces misclassification risks when relying solely on behavioral data.

Propensity and next-best-action models predict trial likelihood, upsell opportunities, and churn prevention through analysis of purchase patterns, browsing behavior, and price sensitivity. These models require validation to avoid over-targeting specific customer segments.

New-to-brand and new-to-category segmentation identifies customers engaging with products for the first time, supporting launches and category expansion initiatives. Multi-year purchase data feeds these segments, but retailers must ensure clean data and consistent definitions across systems.

Price sensitivity and promotion responsiveness segments optimize promotional campaigns through margin-aware targeting. Analysis of promotional exposure versus redemption patterns reveals which customers respond to discounts, though the blueprint warns against over-subsidizing habitual deal-seekers who would purchase regardless of promotional offers.

Affinity and market-basket associations enable cross-sell and basket expansion by identifying products commonly purchased together. SKU-level basket data and time stamps inform these segments, with the recommendation to keep product recommendations contextual rather than intrusive.

Customer lifecycle segmentation maps individuals through acquisition, growth, maturity, and lapse stages, enabling always-on CRM and media orchestration. Engagement history and tenure data drive these classifications, requiring aligned KPIs across organizational teams.

Churn-risk and retention-uplift segments predict customers likely to stop purchasing and design interventions to retain them. This approach primarily serves retailer-led retention efforts rather than advertiser objectives and requires uplift modeling to prove effectiveness.

Channel and fulfillment preferences identify how customers prefer to shop and receive products, whether through online ordering, in-store pickup, or home delivery. Order method, location, and delivery preference data inform creative and format alignment, requiring standardized reporting across different shopping channels.

Attention and media responsiveness segments classify audiences based on engagement levels with specific media channels, optimizing media mix by channel. Past channel performance provides the input data, though this requires normalized metrics for effective comparison.

Occasion and temporal segmentation targets customers around specific moments such as payday, seasonal events, or weather-driven demand. Timestamped purchase data, event calendars, and weather information feed these segments, which should coordinate with above-the-line campaigns for maximum impact.

Geographic and catchment clusters group audiences for localized campaigns and in-store activations. Store data and postcode catchments inform targeting, with the blueprint recommending matched-market experiments to test effectiveness.

Consent and privacy-tiered segmentation divides customers based on consent levels and privacy preferences, ensuring compliant targeting and flexible activation. Consent records and preference center data drive these segments, which should adapt to regulatory changes.

Eligibility and stock-aware targeting suppresses advertising to customers where products are unavailable, minimizing wasted impressions. Real-time stock data and fulfillment service-level agreements feed these segments, requiring robust operational integration between advertising systems and inventory management.

Predictive CLV models forecast customer future value using statistical approaches including Pareto/NBD and Gamma-Gamma models. Longitudinal purchase data provides the foundation, though these models need explainability for stakeholder buy-in.

Creative-messaging personas create human-centric audience groupings for creative testing and message tailoring. Mission proxies and category affinities inform these segments, with validation through A/B testing to ensure causality rather than correlation.

Stakeholder responsibilities span three organizational layers

The blueprint establishes distinct responsibilities for advertisers, agencies, and retailers, recognizing that effective retail media requires coordinated action across all three groups.

Advertisers must break down silos between brand, shopper, and performance teams while leveraging first-party and retailer data for intent-driven segmentation. Organizations should align KPIs to shared outcomes including incrementality and lifetime value rather than isolated channel metrics. Collaboration via clean rooms enables secure data integration, while advertisers must demand transparency and ethical data practices from retail media partners.

Agencies should develop retail media centers of excellence with standardized playbooks, acting as bridges between siloed advertiser teams and multiple retail media networks. The blueprint directs agencies to push for common metrics, transparent reporting, and adoption of IAB measurement standards across retail networks. Campaign design should incorporate incrementality testing from the outset, with agencies championing brand safety, data ethics, and long-term strategic value over short-term performance metrics.

Retailers must invest in data readiness, unifying online and offline sources while driving cultural change to secure cross-functional buy-in. Networks should provide transparent, standardized metrics and consistent reporting while diversifying offerings across on-site, in-store, and off-site channels. Clean room measurement capabilities and holdout testing enable closed-loop measurement, with retailers treating data ethics and privacy as competitive differentiators.

The document assigns specific ownership of churn-risk and retention-uplift segmentation to retailers, ensuring advertisers have access to stable, engaged audiences rather than declining customer segments.

Measurement standards emphasize incrementality over attribution

The blueprint establishes five core measurement principles that supersede traditional retail media metrics focused primarily on return on ad spend.

Incrementality testing through geo-holdouts, A/B tests, and control groups proves causal impact rather than correlative relationships between advertising exposure and sales outcomes. This methodology addresses the fundamental attribution challenge in retail environments where customers may have purchased regardless of advertising exposure.

Standardized reporting across retail media networks enables comparability, allowing advertisers to evaluate performance across different retailers using consistent methodologies and definitions. The lack of standardization currently affects 53% of retail media stakeholders, according to previous IAB research cited in related materials.

Reporting should extend beyond ROAS to include CLV growth, basket expansion metrics, and new-to-brand customer acquisition. These comprehensive metrics capture full-funnel value rather than last-click attribution that may misrepresent advertising effectiveness.

Creative best practices require segment-driven creative validated through robust testing. Different audience segments respond to different messaging approaches, necessitating systematic creative experimentation rather than one-size-fits-all advertisements.

Privacy-by-design principles must be embedded in all segmentation approaches from initial conception rather than added as afterthoughts. The document positions privacy protection as foundational to sustainable retail media growth.

Seven use cases demonstrate practical segmentation application

An appendix maps specific marketing objectives to recommended segmentation approaches, data inputs, activation tactics, and measurement frameworks.

Launching new products requires new-to-brand segmentation, propensity modeling, and creative personas fed by multi-year purchase history, browsing behavior, and affinity data. Activation occurs through off-site prospecting and inspirational content, measured by new-to-brand sales, trial rates, and incrementality analysis.

Growing basket size leverages affinity analysis, mission-based targeting, and RFM segmentation using basket-level data and SKU associations. Contextual cross-sell offers and in-store prompts drive activation, with measurement focused on average order value uplift and incremental basket items.

Winning back lapsed customers combines lifecycle segmentation, RFM analysis, and propensity modeling using recency data, frequency patterns, and engagement drop-off signals. Personalized win-back offers, email campaigns, and off-site retargeting activate these segments, measured through re-purchase rates and retention lift versus control groups.

Increasing customer lifetime value requires RFM segmentation, predictive CLV models, and lifecycle analysis based on longitudinal purchase data. Loyalty rewards, exclusive offers, and expanded category promotions drive activation, measured by CLV growth and migration across value tiers.

Protecting margins deploys price sensitivity analysis, eligibility checks, and stock-aware targeting using promotional redemption data and inventory levels. Tiered offers, out-of-stock suppression, and margin-aware pricing activate these segments, measured through promotional ROI and incremental sales net of subsidies.

Brand building utilizes mission segmentation, occasion targeting, and persona development from shopper journey and seasonal data. Full-funnel creative campaigns and thematic activations drive awareness, measured through perception studies and reach quality metrics rather than direct response.

Retailer-focused retention efforts employ churn-risk analysis and retention-uplift modeling based on frequency decay and declining basket size patterns. Loyalty communications and personalized retention campaigns activate these segments, measured through retention rates and incremental customer saves versus control groups.

Global retail media context accelerates implementation urgency

The IAB Australia blueprint arrives during significant retail media infrastructure development worldwide. European retail media spending grew 22.1% in 2024 compared to 6.1% growth for the broader advertising market, demonstrating the channel's transition from experimental category to strategic advertising infrastructure.

Programmatic real-time bidding capabilities have emerged for retail media sponsored products, addressing fragmentation challenges through standardized inventory access. Pentaleap and Teads announced RTB integration on July 24, 2025, enabling advertisers to activate sponsored product inventory across multiple retail networks through unified platforms.

Major platforms have consolidated retail media access, with Criteo becoming Google's first onsite retail media partner through Search Ads 360 integration announced September 10, 2025. The collaboration enables advertisers to create, launch, and optimize campaigns across Criteo's network of over 200 retailers directly within Google's advertising interface.

Payment networks have entered commerce media, with Mastercard launching its commerce media network on October 1, 2025. The platform leverages permissioned transaction data from more than 160 billion annual payments processed in 2024, reaching 500 million enrolled consumers across owned channels, bank outlets, and publishing partners.

Retail media and connected television are converging, with retail media advertising spend on CTV projected to grow three times faster than retail media search. This convergence enables brands to leverage first-party data including purchase history and browsing behavior for highly personalized advertisements in streaming environments.

The competitive dynamics extend beyond traditional retailers, with device manufacturers launching advertising businesses. HP announced its Media Network on July 16, 2025, targeting 160 million monthly U.S. users across 19 million devices, positioning hardware manufacturers as retail media competitors.

Implementation challenges require cross-functional coordination

The blueprint acknowledges significant operational challenges that retail media networks must address regardless of segmentation sophistication.

Data unification across online and offline sources remains technically complex, requiring integration of point-of-sale systems, e-commerce platforms, mobile applications, and loyalty program databases. Many retailers maintain separate data warehouses for different business units, creating inconsistent customer identifiers that prevent accurate segmentation.

Cultural change represents a substantial barrier as retail organizations traditionally focused on merchandise optimization must develop advertising technology capabilities. Cross-functional buy-in requires demonstrating value to merchandising, marketing, technology, and finance stakeholders who may perceive retail media as competing for resources.

Privacy compliance varies across jurisdictions, with different regulatory requirements in Australia compared to European GDPR frameworks or California's consumer privacy regulations. Segmentation approaches must adapt to local privacy requirements while maintaining consistent targeting capabilities across markets.

Measurement standardization faces technical and political challenges as retailers compete for advertising budgets while simultaneously needing industry-wide standards to attract advertiser investment. Individual retailers may resist transparency that enables cross-network performance comparison.

Platform integration complexity increases as advertisers demand unified campaign management across multiple retail networks. Current fragmentation requires separate creative assets, reporting formats, and optimization approaches for each retailer, limiting advertiser adoption beyond the largest networks.

Industry trajectory points toward audience intelligence standard

The blueprint positions audience segmentation as the foundation for retail media's transition from tactical sales channel to strategic growth engine. The document states that segmentation is no longer about broad descriptors but about intelligence combining value, context, behavior, and ethics.

Adopting robust segmentation toolkits while aligning stakeholders and adhering to IAB best practices enables advertisers, agencies, and retailers to unlock sustainable growth flywheels. Retail media will then serve not only as an advertising channel but as strategic infrastructure delivering measurable value across entire customer journeys.

The framework's emphasis on data readiness, measurement rigor, and privacy-first design reflects broader industry shifts toward first-party data activation as third-party cookie deprecation continues. Over 90% of advertisers now partner with retailers to access first-party data, with brands working with 4-6 retail media networks doubling in 2025.

Market projections indicate retail media networks will exceed $300 billion by 2030, representing fundamental transformation in how advertisers allocate budgets across digital channels. This growth trajectory depends on retail media networks implementing sophisticated audience segmentation that delivers superior performance compared to traditional advertising channels.

The Australian market context differs from larger economies due to geographic concentration and retailer market power, potentially accelerating standardization adoption as major networks compete for limited advertiser budgets. The blueprint's prescriptive approach may provide competitive advantages for early implementers who establish technical capabilities ahead of market standards.

Technical glossary defines operational terminology

The blueprint includes comprehensive terminology definitions spanning core concepts, segmentation techniques, and supporting infrastructure. The glossary establishes shared language for cross-functional teams implementing retail media programs.

Audience segmentation divides broad consumer audiences into smaller groups based on shared behaviors, needs, or characteristics, enabling targeted advertising using first-party data to maximize relevance and measurable impact.

Unified customer view integrates customer data across all touchpoints including online, in-store, and mobile interactions, supporting consistent targeting and measurement. This single representation enables retailers to recognize customers regardless of interaction channel.

Clean rooms provide privacy-safe data environments enabling advertisers and retailers to match, analyze, and activate overlapping data without sharing raw identifiers. These secure collaboration platforms have become essential infrastructure as privacy regulations restrict traditional data sharing.

Incrementality testing isolates causal campaign impact using A/B tests or geo-holdouts, moving beyond proxy metrics like return on ad spend to prove actual sales lift attributable to advertising exposure.

Closed-loop measurement connects media exposure to actual sales or behavioral outcomes, ensuring accountability for retail media performance rather than relying on intermediate engagement metrics.

Operational infrastructure encompasses systems and workflows needed to transform data insights into actionable audience segments and campaigns, including data pipelines, activation platforms, and measurement frameworks.

The comprehensive glossary reflects the blueprint's focus on operational implementation rather than conceptual frameworks, providing terminology that technical teams need for system development and integration.

Timeline

• July 2025: Pentaleap and Teads announce first RTB integration for sponsored products across retail networks
• July 2025: Innovid releases retail media features targeting fastest-growing advertising category
• September 2025: Criteo becomes Google's first onsite retail media partner through Search Ads 360 integration
• September 2025: MediaMarktSaturn launches offsite retail media program with Unlimitail partnership
• September 2025: Omdia projects retail media networks will exceed $300 billion by 2030
• October 2025: Mastercard launches commerce media network with $100 billion market potential
• October 2025: LiveRamp enables retail media networks to measure Meta campaigns
• November 2025: Retail media and CTV converge as shopping shifts to streaming platforms
• December 4, 2025: IAB Ireland releases retail media report for brands and agencies
• December 10, 2025: IAB Australia releases audience segmentation blueprint for retail media

Summary

Who: IAB Australia's Retail Media Council developed the strategic blueprint for advertisers, agencies, and retailers operating retail media networks. The framework targets stakeholders across the retail media ecosystem requiring standardized audience segmentation approaches.

What: A comprehensive strategic blueprint outlining 16 distinct audience segmentation methods, three-stage maturity framework, stakeholder-specific responsibilities, measurement standards emphasizing incrementality testing, and seven use-case applications. The document provides operational implementation guidance including technical requirements, data inputs, activation tactics, and measurement frameworks for each segmentation approach.

When: Released on December 10, 2025, during a period of significant retail media infrastructure development worldwide as the sector grows toward projected $300 billion global spending by 2030.

Where: Published by IAB Australia for the Australian retail media market, though the frameworks apply to global retail media operations. The blueprint addresses challenges affecting retail media networks across international markets as over 200 platforms compete for advertiser investment.

Why: Addresses persistent fragmentation limiting retail media adoption by establishing systematic approaches that transform first-party data into measurable advertising performance. The blueprint responds to industry needs for standardization, transparency, and measurement rigor as retail media transitions from experimental tactic to strategic advertising infrastructure delivering 1.8 times better results than traditional digital advertising.