Carl Fernandes leads Google’s data and measurement platforms in Europe, the Middle East, and Africa. Here, he explains how ad measurement journeys are changing — and how marketers can get started.
The way marketers measure ads is changing. The shift from Universal Analytics 360 (UA360) to Google Analytics 4 (GA4) signals not only the deprecation of a foundational marketing tool, but also an industry-wide move towards predictive measurement powered by AI.
To take full advantage of new opportunities requires more than adopting a new AI tool: it needs a fundamental change in mindset and strategy. Here’s how marketers can get started.
Build a first-party data foundation
So where to begin? “It’s about changing your mindset on the amount of data you need,” says Viet Anh Chu, a customer success manager at digital analytics and advertising agency Optimics, who has been helping Czechia-based travel aggregator Invia shift to a first-party data strategy.
Invia offers customers trips from well-known tour operators, flights from more than 550 airlines, and rooms in more than 200,000 hotels worldwide. Marek Lacina, its performance marketing director, explained that typical customer journeys have as many as “300 to 400 touch points”, which generates lots of data. But with consumer demand for privacy informing new regulations it is becoming “harder to measure performance impact and understand how to best meet those customers…at those touch points”.
To solve this challenge, Lacina’s team, together with Optimics, has built a first-party data strategy where consenting users are assigned an ID at the start of each journey. This has helped them consolidate data and make it more accurate and usable. The changes have also meant they are now “far less reliant on cookies to measure”.
“First-party data is probably the most valuable asset a company can have,” Lacina continued. “For people who haven’t started building a strategy, do it as soon as possible. Our mistake was not starting this process three or four years ago. Now, with the right foundation we can bring data into Google’s ecosystem. And that’s when it becomes really interesting.”
Align your first-party data with key measurement tools
With consented first-party data now central to their underlying strategy, Invia’s task was then to analyse and understand what the data was telling them.
Invia improved the accuracy of their conversion measurements, deploying Google tag to collect consented first-party data and match it with logged-in accounts. By attributing conversions to specific user IDs, Lacina’s team gained a clearer understanding of each customer’s journey, which led to a 13% increase in online purchases.
Invia and Optimics also sought to better understand the value of those conversions to the business, more so than just sheer volume, to help Lacina and his team reach higher-value customers more effectively. Additionally, the team utilised the first-party data collected as a reference point to create and reach highly specific audience segments across platforms, helping them to more accurately allocate marketing resource.
Adopt AI to fuel your predictive measurement
With a consented first-party data foundation in place and integrated into an array of measurement tools, what’s next for future-proofing ad measurement? Alexander Krull, senior process and project manager at German retailer Bonprix, suggests real-time prediction using AI.
For Bonprix and many other brands, predictive measurement used to require extensive data and significant time investment because it relied on analysing past behaviour to forecast future trends. However, with the help of their agency partner Trkkn, Bonprix has developed a more agile and efficient system that relies on much less data. Krull and his team can now generate highly accurate predictive analytics, such as purchase probability and customer lifetime value for the next 30 days.
The system leverages first-party data starting in GA4, connected to a custom-built BigQuery model where information flows back and forth in a data enrichment process. Audiences are clustered to avoid any focus on user-level data, while maintaining a constant stream of information to ensure the integrity of the output.
Alejandro Marruedo is the digital analytics consultant at Trkkn who has been working closely with Bonprix on the project. He helped Bonprix migrate from UA360 to GA4 at the beginning of the process.
“Those out of the box solutions, like predictive metrics, can be used for more advanced use cases like Bonprix’s.” Marruedo is confident that predictive measurement is the future of the whole ads ecosystem — something that his Bonprix counterpart fully agrees with.
This, however, is no longer solely about marketing. “There are two separate lenses, one for data privacy and another for marketing technology,” explains Krull. “This is about bringing both sides together so they are complementary.”
He is convinced that embracing predictive measurement is the key to unlocking deeper customer connections for Bonprix. “It’s a game-changer.”
Moving to predictive measurement: A marketer’s checklist
- Conduct a data audit to evaluate your current data collection methods.
- Educate teams in your organisation about the value of first-party data.
- Deploy tools, such as:
- Google tag to ensure comprehensive data collection across your domain.
- Enhanced conversions to improve measurement accuracy.
- Integrate your data with GA4.
- Explore AI-powered predictive models in GA4 with your analytics partner.
- Regularly review your data governance strategy.
- Share insights across teams to inform strategy and decision-making.
For more information about switching to GA4 see this support article. It’s important to make the necessary changes now, otherwise you’re at risk of losing audience and measurement functionality from your campaigns.
