Rakuten wesentlich besser als Rocket
Data privacy is everything in business and customer consent is not optional.
With more than 70 businesses, Rakuten’s access to first-party data across a range of consumer services is a unique differentiator. Our ability to combine this data with insights from mobile data usage is unprecedented.
Japan’s consumer data privacy laws are among the most robust in Asia and are similar to other global standards like the EU’s GDPR, so Rakuten’s boundaries and possibilities for using data are no different from others.
My focus within Rakuten is uncovering new ways to interpret data in an unending quest to increase ARPU, reduce churn and better monetize what we know about how our services are used.
Cell tower analysis to discover domestic travel patterns
If Rakuten can understand popular travel destinations of its users, it can extend offers that deliver value and are more likely to be acted upon.
One of our earliest and most compelling proofs of concept used anonymized mobile network data to analyze domestic travel behavior across Japan. We hypothesized that if we aggregate overnight device to tower connection patterns with respect to geography, we could infer patterns of travel clusters if vectors appeared greater than 75 km (our arbitrary threshold).
We were able to create characterizations of mobile user travel without ever identifying individuals. Over time, we identified clear seasonal patterns. For example, users who reside in southern Japan during the winter months tend to avoid northern destinations like Sapporo or the Tohoku region due to the cold. This insight allowed Rakuten Travel to personalize offers based on likely behavior, showing customers in warmer regions more relevant travel deals that align with known preferences.
Perhaps we identify that a cohort enjoys visiting shrines in the mountains or maybe consistently chooses beach vacations. We can tailor communications to highlight relevant destinations domestically or internationally with these touchpoints to increase engagement while still respecting boundaries.
Real usage intelligence to boost merchant network for mobile payments
Our data programs also inform surgical business decisions.
Rakuten wanted to strategically boost the network of merchants that accepted Rakuten Pay as a method of payment in specific regions where competitive mobile payment usage was heavy.
We studied Rakuten Mobile subscriber usage of Rakuten Pay, creating a visual geographic overlay to easily identify where mobile payment usage thrived but Rakuten Pay usage was relatively low. This map immediately became a field-enablement tool, identifying streets and districts that were ripe for targeting by the Rakuten Pay sales staff. Teams were able to prioritize outreach in neighborhoods where merchant acquisition would have the greatest impact.
This approach reflects how even small shifts in customer behavior can yield valuable business insights and how mobile network operators can create value far beyond connectivity.
Optimizing Rakuten Mobile retail locations with demographic and usage data
As Rakuten Mobile steadily grew its physical retail presence, it had to prioritize investments where stores would have the greatest impact.
We developed a location intelligence model that combines census data, internal group data and behavioral insights to evaluate over 60 attributes per site. This included considering whether a site is located in a residential or commercial district, the average foot traffic during lunch hours, proximity to competitor stores, local parking availability and how deeply Rakuten’s services are already used in the surrounding zip code.
In some cases, we have even tailored shop features based on hyperlocal trends. For instance, placing more seating in stores that serve older customers who enjoy chatting or emphasizing faster service in areas with heavy weekday foot traffic.
Feedback loops from the retail team also influence the model’s refinement. In Tokyo, where parking is scarce, we found that offering modest proximity to available parking had a significant impact on store traffic.
Analyzing the right data allows us to be iterative and responsive to real-world inputs and make better decisions over time.
Prepping for AI-powered data analysis enhancements
All good data science begins with human analysis, experience and business intuition.
AI also requires us to consider structure, consistency and purpose, taking deliberate steps to ensure data is built for scalable intelligence.
A core component of this effort is a tagging system we’ve implemented that assigns behavioral and contextual labels to user populations based on patterns found in mobile usage, service activity, location data and other Rakuten group interactions.
To be clear, we’re not talking about demographics here. Rather, these are functional indicators. Maybe we’ll tag someone who frequently checks in at golf courses or streams sports content as a “golfer.” Someone who consistently books international travel and uses roaming services might be labeled an “international traveler.”
Importantly, we can abstract personal identities and build intelligence around user behavior types, which is critical from both a privacy and AI-readiness perspective. Each tag becomes a data point that feeds future models, enabling smarter segmentation, targeting and personalization. The tagging is dynamic and context-aware, so we can implement a more flexible input layer for reinforcement learning and predictive algorithms.
Everything we do today is laying the groundwork for intelligent automation tomorrow. By centralizing these behavioral indicators in a shared database, we are creating a powerful input stream that will eventually help AI systems power prescriptive actions.
By this time, we’ll be able to amplify what we are proving already works.
Proven in Japan, ready for the world
What we are doing in Japan is unique and visionary. It is also completely replicable by other tier-one telcos, especially those willing to break out of the mindset of cost-cutting and embrace a culture of experimentation. We are seeing mobile data drive 3-4x better outcomes than when compared to other data sources, due to the high quality and real-time nature.
Yes, Rakuten benefits from an ecosystem of 70+ consumer businesses that can both leverage our insights and feed our findings.
But in actuality, any operator can establish similar value by striking strategic partnerships and asking smarter questions of the data they already have.
With the right differential privacy practices, strict internal controls and a privacy-first mindset in place, competitive intelligence, personalized experience and insight monetization are all possible.
Truthfully, the differentiator isn’t the data itself but the willingness to think differently and act on new ideas. It’s about fostering a company culture where data privacy is respected without compromise and data is viewed as a resource that can responsibly drive innovation.
https://www.linkedin.com/pulse/...uten-mobile-rakuten-symphony-aruke/
Im Juni 2025 finden bei Rakuten Mobile mehrere interessante Ereignisse und Kampagnen statt. Dazu gehören das "SAIKYO Summer Thanksgiving Festival" vom 3. bis 27. Juni, das Nutzer mit verschiedenen Vorteilen belohnt, sowie die "U-NEXT Early Access" Kampagne für Rakuten Saikyo Plan Abonnenten, die am 23. Juni startet. Zudem war Rakuten Mobile Gastgeber des O-RAN ALLIANCE June 2025 F2F Meetings in Fukuoka und stellte Fortschritte bei der großflächigen Bereitstellung von O-RAN-konformen Netzwerken vor.
Hier ist eine detailliertere Übersicht:
Veranstaltungen und Kampagnen:
SAIKYO Summer Thanksgiving Festival:
Dieses Festival, das vom 3. bis 27. Juni stattfindet, soll die Nutzer für ihre Treue belohnen und bietet verschiedene Vorteile und Kampagnen.
U-NEXT Early Access Kampagne:
Diese zeitlich begrenzte Aktion startet am 23. Juni und ermöglicht Rakuten Saikyo Plan Abonnenten, den U-NEXT Dienst mit unbegrenztem Datenvolumen für einen Monat zum Preis von 2.200 Yen (inkl. Steuern) zu testen.
O-RAN ALLIANCE June 2025 F2F Meeting:
Rakuten Mobile war Gastgeber dieses Treffens in Fukuoka und präsentierte Fortschritte bei der O-RAN-Implementierung, einschließlich des landesweiten RIC-Platforms und der Beiträge zur O-RAN-Standardisierung.
Weitere wichtige Punkte:
Rakuten AI for Business:
Rakuten Mobile plant, bis Januar 2026 eine generative KI-Lösung für Geschäftskunden zu entwickeln, die verschiedene Unternehmensfunktionen unterstützen soll.
Edge AI in Stadien:
Es gibt ein Projekt, das sich auf den Einsatz von Edge-KI zur Verbesserung der Sicherheit in Stadien konzentriert und voraussichtlich von Juni 2025 bis Januar 2026 läuft.
Zusammenfassend lässt sich sagen, dass der Juni 2025 für Rakuten Mobile eine Zeit intensiver Aktivitäten und Innovationen ist, mit Kampagnen, Veranstaltungen und Projekten, die sowohl bestehende als auch potenzielle Kunden ansprechen.
https://www.google.de/...B7ASwgcIMS4yLjcuMTbIB9sB&sclient=gws-wiz
June 26, 2025
O-RAN (Open Radio Access Networks) Market Size reached US$ 2.92 billion in 2024 and is expected to reach US$ 45.70 billion by 2032, growing with a CAGR of 41.03% during the forecast period 2025-2032.
The Open Radio Access Network (O-RAN) sector is experiencing rapid development, driven by the growing adoption of cloud-based technologies in telecommunications and the increasing need for flexible, scalable network solutions. As digital transformation accelerates, both public and private network operators are turning to Open RAN frameworks to support automation and cloud-native infrastructure.
Key trends fueling this shift include the rollout of 5G, advancements in network virtualization, the push for vendor diversity, and efforts to improve connectivity in underserved rural areas. By decoupling hardware from software, Open RAN presents a cost-effective and adaptable alternative to traditional, proprietary systems helping address the compatibility issues that have emerged over successive generations of mobile networks, from AMPS to 5G.
Similarly, Rakuten Mobile began offering commercial 4G and 5G services using Open RAN infrastructure in Japan in September 2022. By incorporating equipment from multiple vendors, Rakuten demonstrates the flexibility and interoperability of Open RAN in real-world deployments highlighting its potential to support scalable and cost-effective 5G networks.
These developments reflect the growing momentum behind Open RAN as a strategic solution for meeting the complex demands of modern wireless communication.
https://kalkinemedia.com/news/world-news/...-based-network-innovation