Escaping CPG’s small package: Privacy, personalization and data reckoning

The regulatory ground has shifted fast for Consumer Packaged Goods.

In 2025, 65% of the world's population is covered by privacy regulations, according to Gartner, and the pace is accelerating. The updated CCPA regulations effective January 2026 added cybersecurity audit mandates, risk assessments for automated decision-making, and even expanded the definition of sensitive personal information to include neural data. Seventeen U.S. states have now enacted AI-specific marketing regulations, and no two are identical, meaning a campaign compliant in California could violate Connecticut's bias prevention rules.

Globally, the EU AI Act raises the stakes. Penalties reach €35 million or 7% of total worldwide revenue for non-compliance, and the AI-generated content disclosure deadline has been accelerated to December 2, 2026. The operational impact is already visible: one global CPG marketing director reported that legal review timelines for AI-assisted creative went from three days to eleven once EU enforcement began. Compliance is no longer a legal footnote — it's a campaign timeline and budget line item.

The third-party data foundation has collapsed

For decades, CPG brands relied on second- and third-party data to compensate for their limited direct consumer relationships, most of which purchase through retailers rather than brand-owned channels. That model is broken. With browser cookie deprecation and sweeping legislative restrictions, 75% of brands plan to phase out dependence on third-party data by 2026, with spending on data privacy and compliance tools climbing 28% year over year.

The replacement strategy centers on first- and zero-party data: information collected directly from consumers, with explicit consent, often in exchange for a clear value proposition. Zero-party data is forecast to grow at a 36.8% CAGR in customer data platforms as organizations adopt privacy-first approaches. For CPG brands selling through large box and massive online retailers, zero-party data is one of the few ways to build a direct consumer understanding on platforms where the retailer owns the relationship.

Clean rooms: The collaboration infrastructure

Data clean rooms have become the critical bridge between CPG brands and the retailer data they need. With retail media networks projected to reach $70 billion in 2026, these privacy-safe collaboration environments allow brands and retailers to analyze combined datasets generating attribution and audience insights without exposing raw consumer data. CPG brands are already activating this through partnerships with Kroger Precision Marketing, Walmart Connect, and Nectar 360 to enrich first-party profiles and improve ad targeting. Yet fewer than 48% of U.S. retail media networks currently offer clean room capabilities — making this an area of significant competitive differentiation for those who move first.

The technology foundation underlying all of this is the Customer Data Platform. Businesses deploying CDPs achieve 2.4x higher revenue growth than those operating with siloed data systems, according to Forrester — yet 78% of B2C marketing executives still concede their marketing and loyalty technologies are siloed, according to Forrester.

Context is king

In CPG industry, data context rules. Great context data separates raw numbers from improved decisions. Sales figures, sensor readings, or shopper transactions mean little in isolation. Value emerges when data is tied to the people, machines, materials, methods, and conditions that produced it, creating what's often called an "in-context data model." Building such a model out of field data from control systems and other IT/OT systems lets a plant describe its operations in relation to operators, machines, materials, methods, Standard Operating Procedures (SOPs), and energy use in near real time, which brings substantial business value to a complex CPG factory environments and supply chains.

Context matters just as much on the demand side: companies today need a 360-degree view of their customers and the context around them, since aggregate patterns often don't hold up in local markets, and details like spending patterns, demographics, and purchase occasion are what actually drive useful insight. Much of the trove of data on their consumers are in unstructured forms and spread across business units and the enterprise, so an important first step is identifying and activating unstructured data. Ultimately, contextualized data lets CPG companies move from reactive guesswork to proactive, precise decisions across quality control, product innovation, pricing, and personalized marketing.

AI personalization is widening the competitive gap

The CPG companies and brands investing in AI-driven personalization are pulling ahead. McKinsey finds that brands excelling in personalization outgrow peers significantly, with AI-powered marketing delivering revenue uplifts of 3–15% and sales ROI uplifts of 10–20%.

AI and best practices in data governance are solving one of CPG's oldest structural problems: fragmented consumer identity. By probabilistically matching loyalty program data, Direct-to-Consumer (DTC) purchases, retail transactions, and behavioral signals, AI can unify incomplete consumer records across touchpoints into a single, privacy compliant view, without exposing personally identifiable information.

The strategic reframe

The CPG brands best positioned for the next three years are those treating privacy compliance not as a cost center, but as the design principle around which their personalization strategy is built. Transparent data practices and clear communication about data usage can genuinely differentiate brands in a market where consumer trust is eroding and brand loyalty is weakening.

The winning playbook combines consent-driven data collection, a unified Consumer Data Platform (CDP) infrastructure, clean room retailer partnerships, and AI governance frameworks that can operate across an increasingly fragmented global regulatory environment. For CPG leaders, the question is no longer whether to invest in this architecture — it's how quickly they can build it before the window for competitive advantage closes.

Sources: Gartner, McKinsey, Forrester, Deloitte, IAB, eMarketer, Lathrop GPM, Flaster Greenberg, PR News, LiveRamp, Skai, CookieYes, MetricsCart, EverWorker AI, SAP Engagement Cloud (Emarsys), Klaviyo, Sci-Tech Today, Kiteworks, Collibra, BRG ThinkSet

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  Ben Wyman

  Ben Wyman

  Area Vice President of Sales, Healthcare & Life Science

  Collibra