Summary
- Client: a property and casualty insurance brand (financial services)
- Challenge: strict personal data standards in financial services meant member data could not be uploaded to combine with digital behaviour, so the insurance purchase journey was hard to analyse
- Approach: CloudAD built a de-identified “point, line and plane” data model in GA4 and helped build a data culture through training and consulting
- Result: behaviour paths and cross-product behaviour can be analysed within financial regulations and personal data rules, supporting cross-selling strategy
Since the pandemic, winding and unpredictable purchase journeys have become the norm, and financial products are no exception. According to Google research, consumers are more open than ever when choosing a financial brand and more willing to research. An average purchase decision takes more than one and a half months and involves about nine information channels. Understanding user behaviour signals is therefore the most important step in planning marketing and improving the user experience.
Financial services, however, protect personal data more strictly than other industries, and privacy policies are blurring user identification and labels, turning behaviour into a black box. Without a clear view of potential customers and their needs, acquisition costs stay high and existing members may drift into one-time customers.
To meet these challenges, since it was founded in 2019 CloudAD has focused on helping brands grow with data. As the only Taiwan-headquartered company among the GA360 sales partners in Taiwan, CloudAD brings deep experience in GA4 and GA4 360 planning and implementation, data integration, visualisation and analysis, helping clients find opportunities, support business decisions and develop cross-media marketing strategies.
With a deep understanding of financial services and data expertise, CloudAD uses Google Analytics 4 to build a first-party online data foundation for financial brands. Why GA4? There is a myth that GA4 is only for ecommerce. In fact, its data security and flexibility in tracking and analysis let financial brands get the most from their data while protecting personal information.
Point, line and plane: GA4 analysis for new and existing customers
To protect personal data, financial brands usually avoid uploading member data to cloud systems, which means they cannot combine website activity at the member level to analyse journeys and policy status. The insurance brand faced the same challenge when implementing GA4. To protect personal data and still get the most from analysis, CloudAD started from de-identified group behaviour, broke the user journey into a series of connected actions, and built a point, line and plane data model that overcomes the limits on analysis for financial brands.
A point is a single action. After reviewing the marketing team’s analysis needs and the customer communication journey, CloudAD mapped each interaction to a GA4 event, strengthening tracking of individual actions. A line is a behaviour path: the paths taken by users who complete or abandon a purchase are closely tied to how the brand improves its messaging and experience. Studying the order of actions, time taken, retention and drop-off helps the brand keep the right users with the right experience. A plane is the cross-product behaviour network: cross-selling is the best way to raise customer lifetime value.
“When cross-selling to existing members, we always faced three problems: who to target, which product, and how to communicate.”
— Marketing lead, the insurance brand
With CloudAD’s point, line and plane GA4 setup, the brand can easily see how users move between products and use association and propensity analysis to build data-driven strategies for growing customer value.
Building a data culture together
Letting data thinking lead decisions and making data part of everyday work builds an objective, shared data culture. That culture helps a brand make sound business decisions and work more efficiently from departments down to individuals.
Building a data culture is a long journey, and CloudAD’s role in this project was to build it step by step with the brand. Training and consulting help colleagues across departments understand how GA4 works from the ground up. We do not just hand over a fishing rod; we teach the team to make their own, so data informs decisions large and small.
Data work often needs collaboration across departments. As the brand’s IT lead put it: “Understanding how data tracking works is key to responding quickly and correctly to changes in the brand and its environment, and it is what makes cross-department work run smoothly.” When services expand or financial and privacy regulations change, standard data flows and collection rules help the brand respond faster. This is both a measure of strategy and a corporate responsibility to protect user data.
Quotes translated from Chinese.
Broadening the brand’s view of data
Financial services do not lack data. To build a data solution, CloudAD recommends two priorities. First, strengthen security: the point, line and plane model in GA4 creates a security-first data platform where all data collection complies with financial regulations.
Second, build data thinking across the team. This releases the value of the platform, widens the team’s view and is key to digital transformation. CloudAD’s data team and domain know-how support people at every level and in every department to build a data culture that lasts.
In the digital age, GA4 is not only a tool for businesses, so if you want to ride this wave of data, get in touch.
