Normalized claim
Time: 54 x
Real-time campaigns delivered 54x ROAS on average.
beBit TECH uses Gemini and Vertex AI for real-time personalized marketing on Google Cloud
Use case typeCustomer targetingUpdated Jun 13, 2026
beBit TECH built a no-code customer data platform on Google Cloud to unify fragmented customer and marketing data from ecommerce, loyalty, and chat systems. The platform uses BigQuery, Google Kubernetes Engine, and Vertex AI, with Gemini driving audience segmentation and product recommendations through an Agent-to-Agent integration model. It automatically launches and adapts LINE, email, and SMS campaigns in real time so marketers can act on customer behavior without manual IT support.
- Organization
- beBit TECH
- Industry
- Retail
- Location
- Japan
- Published
- June 2026
Reported outcomes
3x
quantified impactRevenue & growth
54xtime1.2xrevenue+55%revenue
Strategic outcomes
Customer experience & trustDelivered real-time personalized campaignsNew product / capabilityBuilt a no-code customer data platformNew product / capabilityEnabled AI-driven segmentation and recommendations
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 3 x increase
Conversion increased 3x.
Normalized claim
Revenue: 1.2 x increase
For Versuni, new customer sign-ups grew 1.23x, online revenue rose 55%, and repeat purchase rates doubled.
Normalized claim
Revenue: 55% increase
For Versuni, new customer sign-ups grew 1.23x, online revenue rose 55%, and repeat purchase rates doubled.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- beBit TECH, Cha Tzu Tang, Versuni
- Provider
- GCP
- Maturity
- Scaled Production
- Linked source
- Google Cloud Customer Stories
Used BigQuery to store and analyze customer data at scale and Google Kubernetes Engine to handle traffic spikes
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 4
- 1Personalized marketing automation
- 2Customer data platform
- 3Campaign orchestration
- Customer and marketing data were fragmented across multiple systems.
- Marketers could not respond instantly to customer behavior during high-traffic periods.
- The organization wanted a continuous plan-do-check-act marketing loop that could adapt in real time.
- Built a no-code customer data platform on Google Cloud.
- Used BigQuery to store and analyze customer data at scale and Google Kubernetes Engine to handle traffic spikes.
- Used Vertex AI to manage machine learning workflows and Gemini for audience segmentation and product recommendations.
- Integrated third-party tools through an Agent-to-Agent model and automated LINE, email, and SMS campaign triggers.
Technologies
- Real-time campaigns delivered 54x ROAS on average.
- In some abandoned-cart scenarios, ROAS reached 507.
- Conversion increased 3x.
- For Versuni, new customer sign-ups grew 1.23x, online revenue rose 55%, and repeat purchase rates doubled.
Architecture
beBit TECH built a no-code customer data platform on Google Cloud that unifies customer data from multiple channels, analyzes it with BigQuery, orchestrates workloads on Google Kubernetes Engine, and uses Vertex AI plus Gemini for segmentation, recommendations, and real-time campaign adaptation. The system connects external tools through an Agent-to-Agent model and automatically executes LINE, email, and SMS marketing actions.
Sources & evidence1
Evidence: Medium65/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Primary source available
- Quantified outcome available
- Technical implementation details available
Type: Customer StoryPublished: Jun 3, 2026Publisher: Google CloudEvidence: VendorConfidence: High
AI-generated summary. Verify important details with the linked sources before relying on this case.
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