Why quality data is the missing ingredient in AI-powered personalisation

Without quality data, all the machine learning in the world won’t stop your next campaign from falling flat. Trent Lloyd, head of APAC at Eyeota, makes the case for why personalisation fails without complete, compliant and contextual data.

Today’s consumers expect more than just functional brand interactions. They expect intelligent, personalised experiences delivered in real time.

According to McKinsey, 71% of consumers expect companies to deliver personalised experiences and 76% become frustrated when that doesn’t happen. In other words, personalisation is a baseline expectation.

Thankfully, consumer expectations for personalisation have risen right alongside the enhanced capabilities of large language models and artificial intelligence. As the backbone of personalisation at scale, AI can power dynamic ad creative, automate product recommendations and optimise customer journeys across channels.

But even the most sophisticated AI models are only as good as the data that powers them. Without complete, relevant and high-quality data, AI can misfire - delivering mistimed messages, irrelevant offers, or broken user journeys that erode trust rather than build it.

The urgency of AI-driven personalisation

Marketers are already using data and AI to make their campaigns smarter and more efficient. For example, an online grocer might analyse past behaviour to recommend weekly meal plans before customers even search. A hotel brand could adjust email content based on the weather forecast in a traveller’s destination.

A fintech app might offer personalised onboarding experiences depending on a user’s financial goals and behaviour patterns.

What all of these strategies have in common is the need for data - lots of it. AI systems need fuel to learn and optimise. And while first-party data is essential, particularly for retention efforts, it often doesn’t tell the whole story. It’s limited to a brand’s owned environments and can leave gaps in understanding who a consumer really is across channels and devices.

Why third-party data matters more than ever

Despite increasing investment in first-party strategies, third-party data continues to serve a critical role in modern marketing. It helps brands build more complete audience profiles, extend reach and resolve identities in a fragmented ecosystem - especially as traditional identifiers like third-party cookies decline in relevance.

When sourced and applied responsibly, third-party data enhances the performance of AI-driven strategies by enriching audience insights, improving targeting precision and supporting real-time personalisation across platforms.

However, maintaining quality and privacy compliance in an ever-changing regulatory environment requires an experienced hand. The result? Better personalisation, stronger campaign outcomes and more relevant experiences for the consumer.

Balancing automation with human oversight

AI can help marketers scale personalisation, but the human touch still matters. In fact, it matters more than ever. Consumers want to feel understood and respected. That requires emotional intelligence, brand authenticity and ethical decision-making that AI alone can’t guarantee.

Marketers must remain involved in guiding AI-driven experiences to ensure they reflect a brand’s values and avoid unintended consequences. That means using data ethically and transparently, putting safeguards in place to prevent bias or exclusion, and maintaining oversight of how personalisation algorithms respond to shifting behaviours and societal norms.

Trust is earned, not automated. Consumers are increasingly aware of how their data is used, and they reward brands that demonstrate transparency and respect for privacy. Marketers who can combine AI efficiency with human empathy are better positioned to build lasting customer relationships.

Responsible data, smarter AI

Used responsibly, the combination of AI and high-quality data unlocks tremendous value. It allows brands to anticipate customer needs and intent in real time, deliver personalised content and offers that are timely and relevant, improve ROI by focusing on the audiences most likely to engage or convert, and continuously learn and optimise campaigns using performance feedback.

The expectations around personalisation will only continue to rise. As consumers grow more accustomed to seamless, tailored experiences across apps, websites and connected devices, brands must evolve to meet them, without compromising on privacy or trust.

That’s the opportunity - and the challenge - of modern marketing. AI may be the engine, but data is the fuel. And to win in a world of disappearing identifiers and rising expectations, brands must invest in data that’s complete, compliant and contextual.