In today’s digital landscape, data isn’t just a resource, it’s a competitive advantage. But how do you ensure your analytics setup is not only delivering accurate insights today, but also ready to scale with tomorrow’s technology?

Here, we explore what it means to build future-ready analytics, from getting the basics right to exploring the power of AI-driven insights.

Why Trust in Data Foundations Matters

In our previous article on analytics foundations, we highlighted how marketers can save time and effort in the long term by creating a robust digital analytics framework, and how these efforts can springboard more sophisticated data projects.

The heightened focus on data and intelligence in the past few years has made it a very exciting time to be working in web and app analytics. We’re starting to move away from using solely retroactive data as our main (and often only) source of data for insights and reporting on websites, as forecasting and predictive tools become more accessible to not only our digital analysts, but also clients and wider media stakeholders. This forecasted data is fuelled by machine learning, which primarily trains on data from existing datasets, which is why we need to trust data and its underlaying setup.

Moving Towards Analytics Maturity

At Merkle, we support clients with not only the analytics basics but also equipping clients with scalable, future-focused tools and approaches to their data.

This support can take many forms. Firstly, we would recommend reviewing setups with an analytics maturity lens, evaluating not only feature adoption, but also whether these features are being used by the client to their full potential. This allows us to review the overall landscape of a client’s analytics setup, providing project ideas and proposals to maximise benefits.

We would then look towards robust futureproofing, likely via server-side solutions. Moving your digital analytics setup into your own server container gives you more security and ownership of data requests through use of first party cookies, instead of being heavily reliant on third-party scripts. From an implementation perspective, it may also reduce the number of scripts running on your website, therefore improving page load times.

Planning for AI? Start Here

AI is also a hot topic when planning and strategizing with clients; we receive many questions about using AI to help businesses with analysis and actioning upon insights. We are keen to explore embedded (out of the box) and applied (bespoke, client-focused) AI solutions with clients, whilst remaining mindful of data integrity and security. AI has opened up project creativity, functionality and accessibility for stakeholders, and we are excited to explore this new chapter.

Not sure where to start? Here are three ways AI can advance your analytics maturity.

1. Merkle’s AI Value Calculator helps businesses assess their readiness for AI. It breaks down where you are on the journey and points you toward projects that are realistic and impactful—right now.
2. Embedded AI Tools are available within Google Analytics and other GMP products. These include value-based bidding and predictive metrics. Helping clients unlock these ‘ready-made’ solutions can then provide a springboard for more tailored, custom projects in future.
3. Applied AI Solutions includes bespoke solutions including real-time anomaly detection, performance alerting, and even content personalization based on custom KPIs. We're working toward next-generation systems that not only identify insights, but act on them too.

Let’s Build the Future, Together

If you’re ready to go beyond basic tracking and dive into strategic, AI-powered analytics, we’d love to help. The Merkle digital analytics team specializes in both the technical setup and the creative strategy to make your data work smarter, not harder.

📩 Reach out to us to explore what’s possible for your business.