Using AI to Personalise at Scale

AI-driven personalisation has become one of the clearest demonstrations of how data transforms business performance. Streaming and retail leaders have proven its value: Netflix attributes roughly 75–80% of content watched to its recommendation system, while Amazon’s product suggestions account for about 35% of total revenue. These results illustrate how effectively trained algorithms can surface the right product or show at exactly the right time.

Consumers now expect customisation as standard. McKinsey finds that 71% of customers anticipate tailored experiences, and 76% become frustrated when personalisation is missing. Around two-thirds say targeted offers influence their buying decisions. In practice, this means brands that fail to personalise risk losing both relevance and revenue.

AI enables real-time understanding of individual preferences—everything from browsing patterns to purchase behaviour. Retailers and platforms use this intelligence to adjust prices dynamically, craft segment-specific messaging, and power virtual assistants that act like personal shoppers. Generative AI is expanding these capabilities further, producing bespoke emails and product recommendations that scale to millions of users while maintaining a sense of one-to-one connection.

Data-driven marketing brings responsibility. With privacy laws such as GDPR, firms are implementing on-device inference and synthetic data to respect user consent while preserving personalisation accuracy. Many now prompt explicit opt-ins for AI-driven recommendations, building trust through transparency.

Modern personalisation relies on unified customer data platforms that consolidate behaviour, demographic, and transactional data. AI models then cluster and predict what each user wants next. Continuous A/B testing—automated by AI—lets marketers trial thousands of creative variations in real time, learning what resonates with each audience segment.

Netflix segments its audience into thousands of “taste communities,” refining its homepage for each viewer. The company estimates that these algorithms deliver more than $1 billion in annual retention value. Coca-Cola’s global “Create Real Magic” campaign invited fans to co-create AI-generated artwork, producing over 120,000 submissions and valuable engagement data. Meanwhile, B2B marketers using AI personalisation report 10–15% revenue uplifts, with over half of consumers saying they’re happy to share data in exchange for tailored offers.

Analysts describe generative AI as a marketing equaliser—allowing smaller brands to produce customised content with the sophistication once reserved for global players. However, experts warn that automation must complement creativity. As one CMO noted, “AI personalisation frees our team from manual analysis so we can focus on quality and storytelling.” Measurement is also critical: leading firms now track personalisation’s effect on conversion rates, lifetime value, and churn reduction.

Businesses should view AI personalisation as an engine for growth, not a niche tool. Start with clean, consented data and transparent practices to earn trust. Blend automation with human oversight to maintain authenticity and brand integrity. Used responsibly, AI personalisation does more than increase clicks—it builds loyalty, enhances customer experience, and strengthens long-term competitiveness.