Measurement and Personalization in Consumer Products: From Data to Direct-to-Consumer (D2C) Growth

In today’s rapidly evolving consumer products (CP) landscape—spanning food, beverage, home, and personal care—brands face a dual imperative: harness the power of data to drive direct-to-consumer (D2C) growth and deliver truly personalized experiences. As digital disruptors and shifting consumer expectations reshape the market, CP firms must move beyond traditional retail models, leveraging measurement, analytics, and AI to unlock new value, operationalize insights, and build lasting customer relationships.

The New D2C Opportunity: Why Measurement and Personalization Matter

The acceleration of digital commerce and the rise of D2C models have opened new avenues for CP brands to engage consumers directly, collect valuable first-party data, and differentiate through tailored experiences. Yet, while more than half of CP firms describe themselves as “partially” or “mostly” digital, only a small fraction have fully mastered the data and analytics platforms required to realize the full potential of D2C.

Personalization is no longer a luxury—it’s a growth imperative. Research shows that over 80% of consumers are more likely to purchase when brands offer personalized experiences, and companies that execute personalization at scale see revenue growth rates two to three times faster than their peers. In a crowded marketplace, the ability to cut through the noise with relevant, timely, and context-aware engagement is a key driver of both conversion and loyalty.

The Measurement Challenge: Unifying Data and Extracting Actionable Insights

Despite widespread investment in digital channels, AI, and analytics, CP brands face persistent challenges in:

• Unifying data across channels and touchpoints: Data is often siloed by brand, market, or department, making it difficult to create a holistic view of the customer journey.
• Extracting actionable insights: While most CPs collect data from social media, search, e-commerce, and D2C partners, turning this data into meaningful, operational insights remains a top challenge. Only about a third of firms use data to its greatest extent for service improvement, personalization, and product recommendations.
• Building the right teams and technology: A shortage of AI-specific skills, lack of employee adoption, and limited data fluency among leadership are common roadblocks. Many organizations are still experimenting with key technologies or lack a unified platform for analytics and orchestration.

The result is a “data disconnect”—a gap between what’s collected and what’s used to drive business outcomes. Less than half of CPs enrich their first-party data with second- and third-party sources, and many struggle to operationalize insights for innovation, decision-making, and customer experience improvement.

AI and Analytics: From Experimentation to Operationalization

AI adoption is on the rise, with 65% of CPs having initiated multiple AI projects and 63% using AI to analyze product or consumer data. The most valuable applications include:

• Automating insight generation for faster, more accurate decision-making
• Personalizing customer experiences across digital and physical channels
• Optimizing product recommendations and search
• Improving service and convenience

However, to move from experimentation to operationalization, CP brands must:

• Invest in unified data platforms that connect insights across the enterprise
• Automate processes to enable real-time personalization and demand planning
• Build cross-functional teams with the right mix of data, technology, and business expertise
• Foster a culture of experimentation and change, encouraging rapid test-and-learn cycles and transparent measurement of AI effectiveness

Practical Steps for Advancing Data Transformation and D2C Growth

1. Prioritize First-Party Data Collection and Integration
   • Actively collect data from owned D2C channels and enrich it with external sources for a 360-degree customer view.
   • Invest in customer data platforms (CDPs) and analytics tools that enable real-time data ingestion and activation.
2. Unify Data and Break Down Silos
   • Centralize data management to connect insights across brands, markets, and functions.
   • Map the customer journey across all touchpoints—digital, in-store, and service—to identify friction points and opportunities for personalization.
3. Operationalize Insights for Personalization at Scale
   • Use AI and analytics to automate segmentation, targeting, and content delivery.
   • Enable real-time optimization of offers, recommendations, and communications based on customer behavior and context.
   • Measure the impact of personalization on conversion, retention, and lifetime value.
4. Build the Right Teams and Capabilities
   • Upskill internal talent in data science, analytics, and digital marketing.
   • Leverage external partners or offshore resources to fill immediate capability gaps while developing long-term internal expertise.
   • Encourage cross-functional collaboration and a general management mindset to align teams around shared business outcomes.
5. Foster a Culture of Experimentation and Change
   • Establish a test-and-learn environment, using analytics to monitor and iterate on AI and personalization initiatives.
   • Involve leadership in setting KPIs, tracking progress, and communicating the value of data-driven transformation.
   • Celebrate quick wins and learn from failures to build organizational buy-in and momentum.

Overcoming Barriers: Data Privacy, Trust, and Value Exchange

As CP brands deepen their use of data and AI, building and maintaining consumer trust is paramount. Transparency around data collection, privacy, and the value exchange is essential. Consumers are willing to share data in exchange for meaningful benefits—exclusive offers, convenience, and personalized experiences—but expect brands to safeguard their information and use it responsibly.

The Road Ahead: From Data to Differentiation

The future of consumer products is data-driven, direct, and deeply personal. Brands that succeed will be those that:

• Unify and operationalize data to deliver seamless, omnichannel experiences
• Leverage AI and analytics to personalize at scale and drive innovation
• Build agile, cross-functional teams and a culture of continuous improvement
• Earn consumer trust through transparency and value creation

Publicis Sapient partners with leading CP firms to accelerate this transformation—helping brands modernize their data infrastructure, activate insights, and unlock new growth through D2C channels. The opportunity is clear: by mastering measurement and personalization, CP brands can move from data to differentiation, building stronger customer relationships and driving sustainable, profitable growth in a dynamic marketplace.

Ready to advance your data transformation journey? Let’s connect and explore how Publicis Sapient can help your brand achieve D2C excellence through measurement, analytics, and personalization.

Relevant Links

• The State of Measurement 2022: Insights and Challenges in Fashion, Luxury, and Beauty Marketing
• Regional Deep Dive: The State of Measurement in Australian Retail and Consumer Brands
• Retail à la Croisée des Chemins : L’Impératif de la Transformation Digitale en Europe (Europe)
• The State of Measurement 2022: Insights and Challenges in Fashion, Luxury, and Beauty Marketing
• Retail en una Encrucijada: La Imperativa Transformación Digital en América Latina (LATAM)
• Retail à la Croisée des Chemins : L’Impératif de la Transformation Digitale en France (Europe)
• Retail en una Encrucijada: El Imperativo de la Transformación Digital en América Latina (LATAM)
• The Omnichannel Measurement Imperative: Bridging Digital and Physical Retail in Australia
• Beyond Fashion: Measurement and Attribution in Consumer Products E-commerce and D2C
• Retail en una Encrucijada: El Imperativo de la Transformación Digital en América Latina (LATAM)