Metro Shoes: 7x Growth from AI Platforms with Infidigit’s LLM SEO Strategy
The Client
Metro Shoes is one of India’s most established fashion and lifestyle retail brands with a legacy of premium craftsmanship and nationwide presence. Recognised for its curated selection of footwear and accessories for men, women, and kids, the brand caters to diverse fashion preferences through a combination of timeless elegance and modern trends. With its wide distribution network and strong customer loyalty, Metro Shoes holds a dominant position in India’s organised footwear retail market.
The Objective
Metro Shoes wanted to strengthen its visibility on AI-driven search platforms such as ChatGPT, Gemini, Perplexity, and Copilot. The goal was to ensure that when users asked AI tools for footwear suggestions, styling advice, or buying recommendations, Metro Shoes would be mentioned more often.
The Challenge
Infidigit’s audit uncovered several areas that limited Metro Shoes’ ability to surface within AI responses:
1. Insufficient AI-Optimized Content Structure
Existing content lacked the semantic depth and clarity LLMs need to confidently reference brand information.
2. Gaps in Schema Consistency
Product, WebPage, and FAQ schema were partially implemented, preventing AI systems from understanding product taxonomy and contextual relationships.
3. Missing Coverage for AI-First Questions
AI platforms increasingly prioritize natural-language queries such as
“Which shoes work best for office wear?” or
“Top sandals for long walking hours.”
Metro Shoes’ pages did not fully address these conversational intents.
4. Limited Direct Answers for AI Summaries
AI tools often extract crisp, factual responses. Metro’s pages lacked concise insights that LLMs could lift as authoritative statements.
5. Lack of AI-Optimised FAQ’s
High-intent FAQs were not organized in a way that AI systems could directly use.
6. Weak Interconnections Between Key Content Pieces
Internal linking between style guides, category pages, and buying advice was sparse, limiting semantic clarity for AI crawlers.
The Solution
Infidigit implemented a tailored LLM SEO strategy built specifically for Metro Shoes’ content ecosystem and user search behavior trends.
1. AI-Readable Content Restructuring
Category and blog pages were improved with richer product features, usage scenarios, styling clarity, and material explanations—making the content more interpretable for generative models.
2. Comprehensive Schema Reinforcement
Structured data was expanded across Product, Breadcrumb, FAQ, and WebPage layers to help AI systems clearly understand hierarchy, product attributes, and contextual cues.
3. Deep Optimization for Conversational Queries
Content was aligned with how real users phrase queries in AI tools—from occasion-based footwear to comfort-focused and trend-driven recommendations.
4. Creation of Extractable Insights
Short, authoritative “answer-ready” statements were added to high-impact pages to support AI platforms in generating summaries where Metro Shoes could appear.
5. Development of High-Intent FAQs
Question-based sections were built across key categories and top-performing blogs to match LLM response formats.
6. Semantic Internal Linking Framework
A structured linking model connected buying guides, style tips, category pages, and relevant product clusters, strengthening AI comprehension and topic relationships.
The Result
After the implementation of Infidigit’s LLM-oriented SEO system, Metro Shoes experienced outstanding traction from AI-based discovery channels.
7x
Improvement in LLM-Referred Traffic (Jan–Oct 2025)
Key Performance Highlights
- Strongest Acceleration in Q3: AI sessions grew more than 3× from early Q2 to late Q3.
- Peak Month Performance: The highest monthly spike exceeded 70% growth over the previous month.
- Consistent Upward Curve: Even months with seasonal dips maintained long-term positive trajectory.
- Compounding AI Visibility: Once optimized, pages increasingly appeared in generative AI shopping, styling, and comparison responses.
Strategic Impact
1. Stronger AI Discoverability
Metro Shoes began appearing more frequently within AI-generated recommendations, style suggestions, and product explanations.
2. Competitive Positioning in AI Search
Enhanced entity clarity and structured content helped the brand outperform competitors in high-intent AI queries.
3. High-Intent Traffic Acquisition
LLM-driven visitors showed deeper engagement—aligning with informed, mid-to-late funnel shopping behaviour.
4. Foundation for Future AI Search Dominance
Metro Shoes now has a scalable, AI-ready content structure that supports long-term visibility as voice and conversational search continue to grow.
60+
Client Testimonial
200+
Global Brands
70+
Awards & Recognition
130+
Success Stories
Beauty & Fitness
Health
Our Solutions
200+ brands scaled revenue using our data-backed playbook.
Let’s Begin with Your Details
- Your data is properly secured encrypted by SSL.
- We hate spam too, your inbox is safe with us.
