Can AI-Powered Personalisation Unlock $2 Trillion in Growth for Consumer Goods? Insights from AgileIntel

In the consumer goods sector, companies that fail to meet evolving consumer expectations risk losing significant market share. According to a personalisation report by the Boston Consulting Group, over the next five years, US$2 trillion in revenue is expected to shift to companies that can deliver personalised experiences and communications. Leading brands that implement AI-driven personalisation grow their revenue approximately 10% points faster than their peers, highlighting the material advantage of this capability. 

For consumer-packaged goods (CPG) companies, AI-enabled personalisation is not simply a marketing tactic; it is a strategic lever to deepen engagement, improve loyalty, and capture incremental revenue. 

Why Personalisation is a Strategic Priority 

Consumers increasingly expect relevant offers, product recommendations, and experiences tailored to their preferences. Traditional segmentation approaches based on broad demographics are no longer sufficient. AI enables brands to move from generic campaigns to dynamic, data-driven insights that reflect individual behaviours and consumption patterns. 

The business opportunity is significant. Companies that excel in personalisation can achieve 10–30% revenue uplift and improve marketing efficiency by 10–20%. These results stem from better targeting, more relevant experiences, and automated decision-making at scale. For CPG brands, this translates into higher conversion rates, increased average order value, stronger retention, and sustainable competitive advantage. 

How AI Transforms Consumer Engagement 

AI enhances personalisation in three key areas: deeper consumer insight, real-time decision-making, and scalable execution. 

Deeper consumer insight: AI integrates multiple data streams, including transaction history, loyalty programs, online browsing behaviour, in-store interactions, and social signals. This holistic view allows brands to identify micro-segments and predict consumer preferences. For instance, a global beauty brand leverages AI to analyse product trial patterns and deliver personalised skincare recommendations. 

Real-time decision-making: AI enables brands to act on consumer behaviour instantly. Offers, product recommendations, and engagement strategies can adjust dynamically based on context, channel, and past interactions. Real-time personalisation increases the likelihood of conversion and strengthens consumer satisfaction. 

Scalable execution: AI automates segmentation, targeting, and offer deployment, making one-to-one personalisation feasible at scale. Campaigns no longer require manual effort and can be applied consistently across millions of consumers. This ensures marketing is both relevant and efficient without adding operational complexity. 

Measurable Impact for Consumer Goods Brands 

The benefits of AI-driven personalisation are tangible. Leading CPG brands report measurable improvements in both top-line growth and operational efficiency. A major global beverage company, for example, implemented AI-driven personalised promotions across digital and retail channels, resulting in double-digit sales growth in targeted segments and improved marketing ROI. 

Key outcomes include: 

• Conversion uplift: Consumers engage more when offers and recommendations are relevant to their interests. 
  

• Revenue and margin growth: Personalised bundles and offers increase average order value while optimising marketing spend. 
  

• Stronger retention: Tailored experiences foster loyalty, resulting in increased repeat purchases and higher customer lifetime value. 
  

• Operational efficiency: Automation reduces campaign complexity and enables continuous optimisation. 
  

By applying AI-driven personalisation across both marketing and product decisions, CPG brands can drive measurable growth and create differentiated experiences for consumers. 

Challenges in Scaling Personalisation 

Executing AI-driven personalisation at scale involves multiple challenges: 

Data quality and integration: Fragmented systems across e-commerce, retail partners, loyalty programmes, and mobile platforms can limit the effectiveness of AI. A unified data foundation is essential for accurate insights. 

Consumer trust and privacy: Consumers may perceive highly targeted experiences as intrusive. Transparent policies and clear communication about data usage are critical to maintaining trust. 

Organisational alignment: Personalisation spans marketing, analytics, IT, and commerce teams. Transparent governance, accountability, and agile experimentation are required to ensure consistent execution. 

Measurement and attribution: Quantifying the incremental impact of personalisation on revenue, retention, and customer lifetime value is essential to optimise campaigns and justify investment. 

Channel consistency: Delivering a seamless experience across digital, retail, and partner channels is complex but crucial to maintain relevance throughout the consumer journey. 

Strategic Roadmap for Marketers 

CPG brands can implement AI-driven personalisation through a structured, phased approach: 

1. Establish a unified data foundation: Consolidate consumer data across channels, resolve duplicate identities, maintain data accuracy, and ensure compliance with relevant privacy regulations. 
   

2. Define business-driven personalisation objectives: Prioritise high-impact use cases linked to revenue, retention, or efficiency. Start with pilot programmes to build proof points. 
   

3. Implement agile experimentation: Deploy AI-driven campaigns iteratively, testing recommendations, offers, and engagement strategies to optimise results. 
   

4. Scale across channels and the value chain: Extend personalisation from digital platforms to retail, loyalty programmes, and product development. Use AI insights to optimise bundles, promotions, and channel strategies. 
   

5. Embed transparency and trust: Communicate clearly how consumer data is used, give consumers control, and ensure experiences deliver real value. 
   

6. Measure and optimise continuously: Use control groups, A/B testing, and analytics to assess performance and iterate for improved relevance and business impact. 
   

Conclusion:  

AI-powered personalisation has become a strategic imperative for consumer goods brands. With US$2 trillion in revenue projected to shift to companies that master personalised experiences and the potential to grow revenue 10% faster than their peers, the opportunity is significant. Leading companies that implement AI-driven personalisation effectively capture growth, improve operational efficiency, and build deeper consumer relationships. 

Success requires more than technology; it demands high-quality data, cross-functional alignment, agile experimentation, and a focus on consumer trust. For CPG brands, mastering personalisation will not only increase revenue but also establish sustainable competitive advantage and long-term loyalty.