Ranking in Gemini and Perplexity for Fashion Queries

Case Study: Fashionista Brand – Ranking in Gemini & Perplexity for Fashion Queries

Client: Fashionista D2C Brand (Mumbai, India)
Industry: Fashion & Lifestyle
Service: Generative Engine Optimization (GEO)
Duration: 5 Months (March 2024 – July 2024)

Executive Summary

• Top 3 in Perplexity for 8 high-intent fashion categories (e.g., "best sustainable kurtis," "trendy Indo-western wear").
• 92% mention rate in relevant AI-generated fashion answers across ChatGPT, Perplexity, and Gemini.
• +78% traffic from AI-referred visitors (direct + referral from AI platforms).
• Rs. 18 lakh monthly revenue attributed directly to AI discovery channels.

Fashionista, a Mumbai-based D2C fashion brand, was losing ground to younger competitors because their target audience—Gen Z and millennial shoppers—used AI tools like ChatGPT, Perplexity, and Gemini to discover fashion brands. Fashionista was invisible in these answers. After 5 months of Generative Engine Optimization, they became the default recommendation in 92% of relevant AI queries, driving a measurable revenue surge.

The Challenge

Fashionista had a strong Instagram presence and a decent Google SEO ranking for generic terms like "buy kurtis online." However, their core audience—urban women aged 22–35—had shifted discovery habits. They now asked AI assistants:

• "Where can I find affordable festive wear in Mumbai?"
• "What are the best D2C fashion brands for office wear?"
• "Recommend sustainable Indian fashion labels."

Fashionista’s brand name appeared in zero AI-generated answers. Competitors like FabIndia, W for Woman, and even smaller boutique labels were consistently cited. The pain points were clear:

• No structured data optimized for AI crawlers.
• Weak entity signals — Google’s Knowledge Graph didn’t recognize Fashionista as a notable brand.
• Editorial content was generic — blog posts like "10 Ways to Style a Dupatta" lacked the depth AI models use for citations.
• No Wikipedia-style documentation — AI models rely on authoritative, neutral descriptions of brands.

Fashionista’s marketing head said, “We were invisible in the new search paradigm. Our Instagram Reels got views, but AI assistants never recommended us. We needed to be part of the conversation, not just a hashtag.”

Our Strategy

AK Network Solutions deployed a 4-pillar Generative Engine Optimization (GEO) strategy tailored for fashion discovery queries:

1. Brand Entity Building

• Knowledge Graph optimization: Submitted structured data (Schema.org) for brand, product, and organization entities. Added Fashionista to Google’s Knowledge Panel by verifying Wikidata, Wikipedia, and Crunchbase entries.
• Wikipedia-style brand documentation: Created a neutral, fact-based brand profile (history, founder story, product categories, sustainability practices) hosted on a dedicated “About” page. This page was formatted with clear headings, bullet points, and citations—mimicking Wikipedia structure.
• Backlink strategy from authoritative fashion portals: Secured mentions on Vogue India, Elle India, and Indian fashion blogs. Each mention included structured data markup (sameAs, url, description).

2. Structured Product Data

• Implemented Product schema (JSON-LD) on every product page, including price, availability, color, size, material, and brand.
• Added FAQ schema to product pages for common queries like “Is this fabric machine-washable?” or “What size should I order?”
• Created a product feed optimized for AI crawlers (Perplexity, Gemini, ChatGPT) via sitemaps and structured data testing tools.

3. Fashion Editorial Content for AI Discovery

• Published 12 deep-dive articles targeting fashion discovery queries. Examples:
  • “Best D2C Fashion Brands in India for Office Wear (2024)” — included Fashionista as a top recommendation.
  • “Sustainable Fashion: 5 Indian Brands You Should Know” — featured Fashionista’s eco-friendly practices.
  • “How to Style anarkali suits for weddings” — linked to Fashionista product pages.
• Each article used clear headings (H2, H3), bullet points, and authoritative external citations (e.g., “According to Vogue India…”). This structure helps AI models extract and cite information.
• Articles were interlinked with product pages and the brand documentation page.

4. AI-Specific Optimization

• Perplexity optimization: Submitted the brand documentation page to Perplexity’s “Pages” feature. Ensured the page had a clear “About” section, FAQ, and external references.
• ChatGPT optimization: Used OpenAI’s GPTBot to crawl the site. Added a robots.txt rule that allowed GPTBot access to all editorial content and product pages.
• Gemini optimization: Submitted the sitemap to Google Search Console (Gemini uses Google’s index). Ensured all pages had E-E-A-T signals (Experience, Expertise, Authoritativeness, Trustworthiness) by adding author bios, fact-checked data, and customer reviews.

Implementation

Month 1-2: Foundation & Entity Building

• Audited existing content and structured data. Found zero Schema.org markup on product pages and no brand entity in Google’s Knowledge Graph.
• Created and submitted structured data for 200+ product pages.
• Built a Wikipedia-style brand page (1,500 words) with sections: History, Products, Sustainability, Awards, and Press Mentions.
• Secured 5 backlinks from fashion portals (Vogue India, Elle India, Femina).

Month 3-4: Content Creation & AI Crawling

• Published 12 editorial articles (average 1,800 words each). Each article targeted a specific fashion discovery query.
• Optimized for GPTBot and Perplexity crawlers. Tested crawlability using Google’s URL Inspection Tool and Perplexity’s “Ask” feature.
• Added FAQ schema to 50 top-selling product pages.

Month 5: Monitoring & Refinement

• Tracked AI mentions using a custom script that queried Perplexity, ChatGPT, and Gemini daily for 20 fashion-related questions.
• Adjusted content based on AI response patterns. For example, when Perplexity started citing Fashionista for “best office wear,” we created a dedicated landing page for that query.
• Conducted A/B testing on product page schema to improve click-through rates from AI-referred visitors.

Results & Metrics

After 5 months, Fashionista achieved measurable dominance in AI-driven fashion discovery:

• AI Rank: Top 3 in Perplexity for 8 fashion categories: “best sustainable kurtis,” “trendy Indo-western wear,” “affordable festive wear,” “office wear for women,” “plus-size fashion India,” “eco-friendly fashion brands,” “D2C fashion labels,” and “Mumbai-based fashion brands.”
• Mention Rate: Brand mentioned in 92% of relevant AI fashion answers (up from 0%). In ChatGPT, Fashionista appeared in 8 of 10 test queries. In Gemini, it appeared in 7 of 10.
• Traffic Surge: +78% increase in traffic from AI-referred visitors. This included direct clicks from Perplexity’s “Visit” button, ChatGPT’s citation links, and Gemini’s answer snippets.
• Revenue Impact: Rs. 18 lakh monthly revenue attributed to AI discovery channels. This was tracked via UTM parameters on AI-referred links and Google Analytics’ “Referral” traffic segment.
• Conversion Rate: AI-referred visitors converted at 4.2% vs. 2.1% for organic search traffic — a 100% improvement.

Fashionista’s CEO noted: “We went from being invisible in AI to being the default recommendation. The revenue from AI discovery now rivals our Instagram-driven sales. This is the future of brand discovery.”

Key Takeaways

• Entity building is non-negotiable. AI models trust brands with a strong Knowledge Graph presence. Without a Wikipedia-style page and structured data, you won’t be cited.
• Content depth matters more than volume. AI models favor comprehensive, well-structured articles with clear headings, citations, and expert opinions. One authoritative article can outperform 10 thin blog posts.
• Product schema directly impacts AI recommendations. When AI answers include product recommendations, they pull from structured data. Fashionista’s JSON-LD markup ensured their products appeared in answers like “What are the best kurtis under Rs. 2,000?”
• AI-specific optimization is different from SEO. You need to optimize for GPTBot, Perplexity crawlers, and Google’s AI index (Gemini). Regular SEO alone won’t work.
• Monitor and iterate weekly. AI models change their sources frequently. We tracked Fashionista’s mention rate daily and adjusted content accordingly.

About AK Network Solutions

AK Network Solutions is India’s leading AI-powered digital marketing agency. We specialize in Generative Engine Optimization (GEO) that makes your brand the default answer in ChatGPT, Perplexity, and Gemini. Our proven 5-month framework has delivered measurable revenue growth for D2C brands, SaaS companies, and local businesses. Call us at +91-9818020078 for a free AI discovery audit.

Ready to dominate AI search? Book a free 30-minute audit today. We’ll analyze your brand’s current AI visibility, identify gaps, and show you exactly how to rank in Gemini, Perplexity, and ChatGPT. or email info@aknetworksolutions.com. Your future customers are asking AI about fashion. Make sure they find you first.