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Oona Insurance Case Study: SEO Growth 7.7K Monthly Organic Visits
Achieved first-page rankings in Google and Scaled to 7.7K monthly organic visits in six months, expanding multilingual content using Addlly AI.
For digital-first brands, scaling organic visibility now requires structured, AI-ready content systems that work across both search engines and generative discovery platforms. Addlly AI provides this foundation through knowledge bases and AI agents for marketing that systemize execution. When Oona Insurance set out to expand across Southeast Asia, the team used Addlly AI to transform its limited content footprint into a scalable growth channel.
Data as of February 4 2026.
Key Results at a Glance
- Built a consistent organic presence from a limited content base
- Reached 7.7K monthly organic visits within six months
- Secured first-page rankings for high-intent insurance queries
- Scaled multilingual content across Indonesia and the Philippines
- Increased publishing cadence to weekly, structured output
- Reduced agency dependency with a repeatable in-house workflow
- Strengthened internal linking to drive policy discovery and conversions
Tool Used
| Tool | Purpose |
|---|---|
| Multiple LLMs | Research and drafting |
| Blog Post Idea Generator | Topic discovery |
| AI Blog Writer | Rapid first drafts |
| SEO AI Agent | SEO structure and optimization |
About Oona Insurance
Oona Insurance is a Southeast Asia-focused insurer built for digital-native customers, offering fully online policy discovery, comparison, and purchase experiences. Rather than relying on traditional offline distribution, the brand enables customers to research coverage, understand benefits, and complete transactions entirely through its digital platforms.
Operating across Indonesia and the Philippines, Oona serves diverse markets with localized, multilingual experiences tailored to regional needs. As the company expanded its footprint and product offerings, building a stronger content presence became increasingly important to educate buyers, answer questions, and support consistent organic discovery.
What Challenges Did Oona Insurance Face Before Addlly AI?
As a fully digital insurer, Oona depended on search visibility to acquire and educate customers. Yet its content operations were not built to scale, creating gaps in traffic, production, and discoverability across markets.
1. No Meaningful Organic Visibility
Despite offering competitive insurance products, Oona struggled to appear where customers were actively searching for answers and comparisons.
- Little to no organic traffic across core pages
- Most high-intent insurance queries showed competitor sites instead
- Policy and product pages lacked search presence
- Educational content was too limited to build authority
2. Manual Content Creation Bottlenecks
Every new article required significant manual effort, which slowed momentum and made consistent publishing difficult.
- Drafting, editing, and approvals consumed internal bandwidth
- Publishing cadence dropped to sporadic updates
- Backlogs formed around simple content requests
- Scaling required agencies or additional hires
3. Multilingual and Localization Complexity
Expanding into Indonesia and the Philippines introduced operational friction that compounded with each new market.
- Separate language versions for each article
- Local regulations required extra checks
- Messaging needed cultural adaptation, not translation
- Content efforts duplicated across regions
4. Weak Internal Linking and SEO Structure
Even published content worked in isolation, reducing its ability to guide users or signal relevance to search engines.
- Blogs rarely connected to policy pages
- No clear topic clusters or supporting content hubs
- Limited pathways from education to conversion
- Poor structure for AI systems to interpret relationships
How Did Addlly AI Build Oona’s Knowledge Base and Content System?
Rather than treating content as isolated blog posts, Oona first built a structured knowledge foundation. Addlly AI organized product information, policies, and brand context into a centralized knowledge base, allowing every article to draw from accurate, reusable data through a RAG-powered workflow.
Step 1 – Centralize Insurance Knowledge
The first step was consolidating scattered information into a single, reliable source of truth.
- Integrated policy details, FAQs, and coverage terms
- Captured brand voice and compliance guidelines
- Standardized product naming and positioning
- Created reusable knowledge for all future content
Step 2 – Map Search Intent Across Markets
With the knowledge base in place, the team identified what customers were actually searching for in Indonesia and the Philippines.
- Clustered queries around real insurance questions
- Prioritized informational and comparison intent
- Connected each topic to specific policy pages
- Built a structured content roadmap
Step 3 – Generate Localized Content Using RAG
Addlly AI generated drafts grounded in Oona’s knowledge base, ensuring accuracy and consistency across languages.
- Pulled verified information directly from the knowledge system
- Produced English and Bahasa content simultaneously
- Reduced factual errors and rewrites
- Maintained brand and regulatory alignment
Step 4 – Structure and Interlink for Discoverability
Content was then formatted to help both users and AI systems understand relationships between topics and products.
- Embedded SEO structure and schema-ready formatting
- Added contextual links to policies and guides
- Organized pages into clear topic clusters
- Strengthened signals for search and AI citations
Step 5 – Editor-Ready Outputs for Fast Review & Approval
All content produced by Addlly AI was delivered in an editor-ready format, enabling ATT Systems’ in-house editors to review and approve efficiently before publishing. This reduced turnaround time and external agency costs, while maintaining full editorial control.
- Content drafts were pre-structured, on-brand, and aligned to ATT Systems’ positioning
- Product details, terminology, and technical claims were already validated in the workflow
- Editors focused on light-touch refinement and final sign-off, rather than rewriting from scratch
Impact: Faster go-to-market, lower content production costs, and consistent quality at scale.
Step 6 – Establish a Repeatable Publishing Rhythm
Finally, the team turned the process into a predictable workflow that could scale month after month.
- Set a consistent weekly publishing cadence
- Monitored rankings and visibility
- Refreshed high-performing content
- Compounded authority over time
What Results Did Oona Achieve in Six Months?
Within six months of implementing Addlly AI’s knowledge base and RAG-powered workflow, Oona established a consistent organic presence and measurable growth across both markets.
| Metric | Before Addlly AI | After 6 Months |
|---|---|---|
| Monthly organic traffic | Minimal / near zero | 7,700+ visits |
| Search rankings | Limited visibility | First page for key insurance queries |
| Publishing cadence | Sporadic | Weekly, consistent output |
| Content coverage | Fragmented | Structured multilingual content |
| Internal linking | Ad hoc | Systematic, intent-driven linking |
| Team effort | Heavy manual work | Streamlined, AI-assisted workflow |
How Did This Impact Oona’s Marketing and Operations?
Beyond traffic growth, the shift to a structured knowledge base and AI-assisted workflow changed how Oona’s team planned, created, and scaled content. What was once a manual, reactive process became predictable and repeatable.
- Reduced manual writing and editing workload
- Lower dependence on agencies and external resources
- Faster turnaround from brief to publish
- Consistent multilingual output without doubling effort
- Clear alignment between educational content and policy pages
- A scalable system that supported expansion into new markets
How Can Insurance Teams Replicate This Growth With Addlly AI?
Oona’s success came from systemizing content rather than producing it ad hoc. Insurance teams can follow the same knowledge-first approach to create consistent visibility across both search engines and AI-driven discovery.
1. Build a Knowledge Foundation
Centralize product details, policies, FAQs, and brand guidelines so every piece of content draws from accurate, reusable information.
2. Align Content With Real Search Intent
Use GEO and SEO research to prioritize the questions customers actually ask, then connect each topic directly to a relevant policy or solution.
3. Scale With AI Agents
Deploy specialized AI Agents to handle research, drafting, optimization, and updates automatically. This allows teams to publish localized, on-brand content consistently while reducing manual effort and maintaining quality at scale.
Teams that adopt this agent-led model turn content into a dependable growth channel rather than a one-off marketing task.
Addlly AI’s AI Agents have significantly reduced our content creation turnaround time, enabling us to consistently produce content that reflects our brand voice and achieve top rankings on Google Search.
Saiful Haris
Head of SEO, Oona Insurance
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Answers to
Frequently
Asked Questions
Oona began seeing early improvements in rankings and visibility within the first few months. Consistent publishing and structured optimization helped compound results over a six-month period.
Content production was limited, publishing was inconsistent, and pages lacked strong SEO structure and internal linking, making it difficult for search engines and AI systems to surface the site.
Addlly AI provided AI Agents that automated research, drafting, optimization, and internal linking while grounding content in a centralized knowledge base for accuracy.
Product details, policy terms, and FAQs were stored in one verified source, allowing every article to pull accurate information and maintain consistency across markets.
No. The AI Agents handled repetitive production tasks, allowing the existing team to scale output without increasing headcount or agency dependence.
Content was generated and localized for Indonesia and the Philippines simultaneously, adapting messaging to each market rather than relying on direct translation.
Educational guides, comparison posts, and intent-driven FAQs aligned closely with customer questions and drove the strongest rankings and policy discovery.
Systematic linking connected blogs to relevant policy pages, improving discoverability, strengthening topical authority, and guiding users toward conversion paths.
Yes. Structured, intent-led content improves traditional rankings while also increasing the likelihood of being cited in AI-generated answers and summaries.
Lean marketing teams, digital-first brands, and regulated industries benefit most, especially when they need consistent, scalable content without adding operational complexity.