You read → You decide AI-Powered Search AI searches → AI reads → AI decides → AI cites The question: How do you get cited? Metehan Yesilyurt - FePSeM Paris 2026
FAR BEHIND OF THE GOOGLE SEARCH, HYPE Google AI Overviews 30 to 50%+ of searches Rapidly expanding Perplexity Growing AI-native search Metehan Yesilyurt - FePSeM Paris 2026
web search "What is photosynthesis?" Search-Triggered Retrieves fresh web data "Best smartphones 2026" Hybrid Combines both sources "Compare React vs Vue in 2026" Search Triggers: Time-sensitive, specific facts, current events Metehan Yesilyurt - FePSeM Paris 2026
SCRAPERS TO FETCH & RERANK Google search results Confirmed by The Information investigation (Aug 2025) SerpAPI listed OpenAI as customer (removed May 2024) Also serves Meta, Apple, Perplexity Google attempted to block SerpAPI crawler The Irony: ChatGPT competes with Google while depending on Google's index Metehan Yesilyurt - FePSeM Paris 2026
ChatGPT shopping results scraped from Google Shopping • Uses SCRAPER service (similar to SerpAPI) • Product IDs match Google Merchant Center exactly • Named Entity Recognition uses Google Shopping Graph Implication: Optimize Google Merchant Center = Better ChatGPT Shopping visibility Source: RESONEO / think.resoneo.com Metehan Yesilyurt - FePSeM Paris 2026
SEGONZAC 1 Search Fan-Out Text queries • 1-4 per conversation IN AVG • Up to 20 in thinking mode • Traditional web search 2 Shopping Fan-Out Product queries • 1-3 per conversation IN AVG • Shorter, product-focused • Google Shopping (SearchApi.io) 3 *VISUAL Fan-Out (GOOGLE) Visual content • 5-10 per conversation • Bing or proprietary index • High volume queries Not all searches use fanouts! Simple factual queries = single search Metehan Yesilyurt - FePSeM Paris 2026
(varies by query complexity) Rank 1-20 High probability Rank 21-40 HIGH & MODERATE probability (RERANKING) Rank 41-65 Low probability (DEEP RESEARCH CAN CHANGE THIS) Rank 66+ PROBABLY Not retrieved = Zero chance The Math: If you're not in the retrieval window, RRF score = 0 Metehan Yesilyurt - FePSeM Paris 2026
training data only ✗ No sources cited ✗ Can hallucinate ✗ "Based on my knowledge..." With Grounding ✓ Must reference retrieved URLs ✓ Citations mandatory ✓ Facts tied to sources ✓ "According to [Source]..." Why It Matters: Grounded responses = Traffic opportunity Metehan Yesilyurt - FePSeM Paris 2026
CLASSIFICATION Single or fanouts? 3 Data Source SerpAPI / SearchApi / Bing 4 Retrieval 38-200 sources per query* 5 Scoring/INTENT CLASSIFICATION RRF or HYBRID 6 Filtering Top X RESULTS 7 LLM Synthesis Grounded answer 8 Citations clickable sources * If DEEP RESEARCH IS IN PROGRESS, IT MAY FETCH UP TO 200 SOURCES Metehan Yesilyurt - FePSeM Paris 2026
LLMS HAVE RECENCY BIAS, UPDATE YOUR POSTS/PAGES OLDER THAN 6 months chatgpt ıs usıng longer fanouts, run base prompts multıple tımes CHECK FOR LLM CONSISTENCY SIMILAR/SAME PROMPTS ON GOOGLE AI MODE, PERPLEXITY, MISTRAL SAVE FANOUTS, RUN ANALYSIS, IDENTIFY TOPIC GAPS Metehan Yesilyurt - FePSeM Paris 2026 CHECK REDDIT CITATIONS, LOOK FOR USERS QUESTIONS, IDENTIFY GAPS NICHE DOWN AS POSSIBLE, CREATE PROMPTS FOR DIFFERENT BUYER PERSONAS, THEY LIKELY PROMPTING; “I’m thinking of, fınd me, search for me x,y,z”
consensus on optimal chunk size. No published case studies. What We Know: • Google: 500 tokens (Discovery Engine) • Chunks preserve heading hierarchy • Different for each LLM • No proven "best" size What Actually Matters: • Good for UX regardless of SEO • Clear section breaks help humans • Logical content organization • Scannable structure PrACTICAL Approach: Structure in ~400-word sections with clear H2/H3 headings Metehan Yesilyurt - FePSeM Paris 2026
Ad Format • Bottom of answers • Clearly labeled 'Sponsored' • Click to chat with brand • Conversational (revolutionary!) Pricing Model • ~$60 CPM (vs Meta $20-25) • Impression-based • $1M minimum commitment • Early access required Will NOT • Influence ChatGPT answers • Show to users under 18 • Appear in health/politics • Sell user conversation data New Revenue Channel: Projected $25B by 2029 Metehan Yesilyurt - FePSeM Paris 2026
ONE query Position #1 → RRF: 0.0164 Not ranking for related queries Total Score: 0.0164 Strategy B Rank #5-8 for FOUR queries Query 1, Position #5 → 0.0154 Query 2, Position #6 → 0.0152 Query 3, Position #7 → 0.0149 Query 4, Position #8 → 0.0147 Total Score: 0.0602 Strategy B wins by 367% Lesson: Coverage beats perfection Metehan Yesilyurt - FePSeM Paris 2026
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