Why data foundations matter for AI-powered marketing

As artificial intelligence reshapes marketing, brands are eager to adopt AI tools, but Nur Raihana and Jason Pua, GMP (Google marketing platform) consultants at Ayudante APAC, stress that AI is not a silver bullet. Without a strong data foundation, it can produce unreliable insights.

Founded in Japan in 2001 as the country’s first SEO agency, Ayudante has grown into a regional digital consulting firm focused on SEO, analytics, digital advertising, and measurement. It works with global brands like Singapore Airlines, Uniqlo, and Fujifilm, helping them tackle fragmented data systems and align measurement strategies with business outcomes.

“From the beginning, it’s always been about helping brands to navigate digital complexity,” Raihana said. “Our core focus areas are SEO, data measurement, analytics platform development, and digital advertising. But what we really solve for is the fragmentation that a lot of organizations face in their data.”

Addressing common misconceptions

Many brands assume AI can fix messy or incomplete data. “There’s this mindset that bringing in an AI tool will somehow magically solve all of their existing data issues,” Raihana explained. “The reality is that AI is only as smart as the measurement ecosystem it’s built on. If the data is incomplete or disconnected, the outputs will be unreliable and misleading.”

She added:

Just because something is measurable doesn’t mean it’s useful. Are we tracking data that actually matters, or just what’s easy to collect?

Raihana highlighted three pillars of a strong data infrastructure:

• Consistency: Standardizing data capture across websites, apps, CRM systems, and ad platforms.
• Connectivity: Linking data points to provide a full view of the customer journey.
• Scalability: Ensuring infrastructure grows with the business, supporting new markets, platforms, and AI initiatives.

“Measurement isn’t a one-off project. It has to grow as your company evolves and scales,” she said.

AI as a tool, not a replacement

AI can reveal insights traditional methods might miss. Pua shared, “Using machine learning to analyse user behaviour, we were able to spot very interesting patterns, like specific user actions or demographics that are more likely to lead to a sale or conversion.”

However, he emphasised, “AI is actually more to help us validate or refine marketers’ thinking or hypothesis. It’s not about leaving it to AI to discover insights independently.”

Pua added that AI is about efficiency, not replacement.

We cannot expect a silver bullet mindset, where we apply AI to everything and come up with things that don’t exist in the first place.

Strong data foundations remain critical: “The resilience of the foundation we built from the beginning, how those data fit into AI models, is super critical and key.”

Looking ahead, both consultants see AI transforming creative content and real-time analytics. “Generative AI is going to revolutionize that space. Using real-time analytics, we can power things like hyper-personalisation, where content constantly updates according to interactions, preferences, and behaviour,” Pua said.

Join Ayudante APAC’s chairman and CEO, Naohiro Yamaura, at Digital Marketing Asia 2025 in Singapore on 24–25 September, where he will share a case study titled: "The future of AI-powered marketing measurement: building a resilient data foundation for growth".

Accelerate your brand’s growth with AI-first strategies, emerging tech and data-driven experiences. Join 500+ marketing leaders at Digital Marketing Asia 2025 Singapore on 24–25 September to uncover transformative trends, real-world wins and powerful ideas for 2025 and beyond. 

This article was written in collaboration with Ayudante APAC.