RAKUTEN THE BIG PICTURE - GA Strategy
For the Rakuten The Big Picture 2021 project, we implemented a data-driven Google Analytics 4 strategy focused on measuring global reach, campaign engagement, and user interaction across a large-scale branded digital experience.
The objective of this analytics framework was to transform high-volume campaign traffic into actionable insights, allowing the team to understand how users discovered the platform, interacted with the experience, and engaged with its core participation features.
This implementation was aligned with the tagging architecture defined in the Google Tag Manager strategy for Rakuten The Big Picture, ensuring a structured, reliable, and scalable measurement system.
By combining acquisition analysis, interaction tracking, and user behavior interpretation, the project provides a clear view of how global campaign visibility translated into measurable engagement.
Google Analytics – Performance:
2021
The acquisition model is clearly campaign-driven, with Organic Social, Email, and Direct traffic standing out as the main traffic sources.
The data shows that social platforms generated the largest share of users, while email distribution and direct access reinforced campaign visibility and repeat exposure. This combination reflects a strategy built around audience activation, cross-channel promotion, and large-scale reach.
From a global perspective, the platform reached more than 70,000 active users and more than 70,000 new users, with an average engagement time of around 48 seconds. The strongest traffic peaks were concentrated around the campaign launch and activation periods.
The project also shows a strong international footprint, led by Spain, India, France, the United States, Mexico, and Colombia, confirming the scalability of the campaign beyond a single market.
At the technology level, the experience was overwhelmingly mobile-first, with mobile devices accounting for the vast majority of users, which made mobile usability a critical factor in overall campaign performance.
This performance confirms a strategy designed to maximize global reach, multi-channel visibility, and large-scale interaction during a highly concentrated campaign window.
2021
Google Analytics – Events:
2021
The measurement model was based on a structured interaction tracking system designed to capture navigation behavior, engagement signals, and participation-related actions across the platform.
Core interactions such as page navigation, session activity, active engagement, and scrolling behavior provided a strong baseline for understanding how users consumed the experience.
Beyond these core signals, the implementation also measured higher-intent actions related to interface interaction, discovery tools, visual controls, participation features, login-related actions, downloads, and media engagement. Rather than relying on literal naming, the analysis focuses on the meaning of user actions and their strategic value.
The data shows more than 600,000 recorded interactions, confirming a very high level of activity across the platform and indicating that users were not only visiting the campaign, but also actively interacting with its main features.
This interaction-based approach makes it possible to understand campaign depth, not just campaign reach, by identifying where users moved from passive exposure to active participation.
By analyzing these engagement patterns, we can:
- Measure meaningful user activity beyond page views
- Identify the most relevant interaction points in the experience
- Understand how users engaged with participation-oriented features
2021
Google Analytics –
Funnels & Explorations:
2021
No predefined funnels or explorations were configured for this project, so the analysis was developed through observed interaction patterns rather than formal funnel reports.
Even without a configured funnel structure, the available data makes it possible to interpret the user journey at a strategic level. Users first arrived through high-volume campaign channels, then generated strong navigation and engagement signals, and finally interacted with deeper participation features.
The main behavioral transition occurred between initial visibility and active interaction, which is typical in large-scale brand and participation campaigns. A large share of users consumed the experience at a surface level, while a smaller segment moved into more engaged actions.
This means that the project was highly effective at generating attention and interaction at scale, while its deepest value lies in understanding how visibility converted into meaningful engagement.
This type of analysis allows us to:
- Interpret the user journey without relying on predefined funnels
- Identify gaps between campaign exposure and deeper interaction
- Optimize future campaign flows based on observed behavior
By combining acquisition data and interaction analysis, the strategy provides a realistic and compliant view of user progression, establishing a strong analytical basis for future campaign optimization.
(The data shown in this page might be out of date or inactive)
(The project might be finished or deleted)
