How AI-First SEO Fueled 282% LLM Traffic Growth for ABHI
The Client
Aditya Birla Health Insurance Co. Limited, established in 2016, specialises in offering health insurance products.
The company provides a range of health insurance plans, with a strong focus on chronic care and wellness programs. It serves millions of customers across the country through a vast network of branches, partner offices, and digital platforms.
The Objective
As search technology evolves rapidly, the focus is shifting beyond traditional SEO rankings to enhancing a brand’s visibility on LLM-powered platforms such as ChatGPT, Gemini, and Perplexity. These LLM platforms are becoming central to how users interact with content and find information.
To remain competitive, SEO strategies need to evolve not just to improve rankings in traditional search results, but also to ensure the brand is discoverable and authoritative in these emerging AI-assisted search environments.
This requires revisiting and refining SEO approaches to effectively target both LLM platforms and AI-driven features within the SERP, ensuring continued visibility and success in this new digital landscape.
Planned Goals:
- Increase referral traffic and brand mentions from LLM-based platforms like ChatGPT, Gemini, and Perplexity.
The Challenge
As AI-driven search experiences began influencing how users discover insurance information, the website faced several structural and content-level gaps that limited visibility across LLM platforms and AI-enhanced search results.
- Content Not Optimized for LLM Discovery
- Limited Coverage of Conversational & Intent-Driven Queries
- Weak Entity Signals Across Insurance Topics
- Incomplete Structured Data Implementation
- Fragmented Internal Linking Structure
- Lack of Extractable Answer Blocks
The Solution
To improve LLM discovery and AI search visibility, the strategy focused on aligning content, technical SEO, and semantic structure with how AI systems retrieve, interpret, and surface information.
- LLM-Optimized Content Framework: Key insurance & blog pages were restructured using entity-driven content architecture, ensuring topics like protection, tax savings, health coverage, and retirement planning were clearly defined and interconnected. This helped AI systems better understand topical authority.
- Conversational Query Optimization: Content updates focused on real user questions commonly surfaced on AI platforms. Pages were enhanced with natural-language explanations and simplified definitions to help LLMs confidently reference the brand in generated responses.
- Direct-Answer Content Formatting: Important insurance concepts & generic articles were rewritten into concise, extractable statements to increase eligibility for AI summaries and LLM responses.
- AI-Focused FAQ Implementation: High-intent FAQ sections were introduced across priority pages to match the Q&A format preferred by LLM platforms. These FAQs targeted informational and decision-stage insurance queries.
- Structured Data & Schema Enhancement: Schema implementation (FAQ, Breadcrumbs, Articles & more) were added across priority pages to improve machine interpretability and content hierarchy understanding.
- Semantic Internal Linking Network: A stronger internal linking structure was built between insurance categories, health insurance guides, and active living articles (educational resources) to reinforce topical relationships and improve AI comprehension.
- LLM Visibility Monitoring via Infigrowth: Using Infidigit’s proprietary platform, Infigrowth, the team tracked LLM discovery patterns and the LLM platform share.
The Result
The implementation of an AI-aligned SEO strategy significantly improved the brand’s discoverability across LLM platforms and AI-powered search environments.
282%
Improvement in AI Sessions via LLM Platforms
60+
Client Testimonial
200+
Global Brands
70+
Awards & Recognition
130+
Success Stories
Beauty & Fitness
Health
Our Solutions
