AngryturtleResearch & studies
Original-data studies on how AI search and local SEO actually work for Indian businesses.
India AI Search Readiness Report: Methodology and Research Design
The India AI Search Readiness Report measures AI Overview citation readiness across 500+ Indian local businesses across 8 industries and 18 metros, using Angryturtle's proprietary 6-pillar AIO Readiness Score (Entity, Schema, Reviews, Content, Citations, Crawlability). This document describes the research methodology, scoring approach, and data collection protocols.
ReadThe Share of AI Voice Study: Methodology for Measuring AI Citation Rates for Indian Local Businesses
The Share of AI Voice (SAV) Study measures AI citation rates for Indian local businesses across a defined prompt set and four AI engines (Google AI Overviews, ChatGPT, Perplexity, Gemini). This document describes the study design, prompt set construction, measurement protocol, and analysis methodology.
ReadReview Velocity and AI Citation Threshold: Research Methodology for Indian Local Businesses
This study investigates the relationship between Google review count, review velocity (new reviews per month), and AI Overview citation frequency for Indian local businesses. The methodology tracks 200+ Indian businesses monthly across 6 categories and 4 cities, measuring when AI Overview citations begin and how review velocity affects citation consistency above threshold.
ReadThe Indian Directory AI Citation Study: How Platform Search Ranking Drives LLM Citations
This study examines how ranking position on Indian directories (Practo, JustDial, Zomato, 99acres, IndiaMART) drives LLM citation frequency for Indian local businesses. The methodology correlates directory ranking with ChatGPT and Perplexity citation rates, establishing the pathway: directory rank → AI system crawls directory → business is cited in LLM response.
ReadSchema Adoption Among Indian Local Businesses: A Measurement Study
This study measures structured data (schema markup) adoption rates among Indian local businesses across 8 industries and 10 cities, examining which schema types are most commonly implemented, which are most commonly absent, and how adoption rates correlate with AIO Readiness Scores. Preliminary data indicates schema adoption below 30% among Indian SMBs, with FAQPage schema among the least implemented despite being the highest-impact for AI Overview citations.
ReadGBP Completeness and AI Overview Citations: A Correlation Study for Indian Local Businesses
This study measures the correlation between GBP completeness scores (0–100, across category, description, services, attributes, photos, Q&A, and post frequency) and AI Overview citation rates for 300+ Indian local businesses. The hypothesis is that higher GBP completeness directly predicts higher AI Overview citation frequency, controlling for review count.
ReadNAP Inconsistency and AI Entity Confidence: A Diagnostic Study for Indian Local Businesses
This study diagnoses NAP (Name, Address, Phone) inconsistency prevalence across Indian local businesses and measures its relationship with AI entity confidence — operationalised as Share of AI Voice and AI Overview citation consistency. The hypothesis is that NAP inconsistency is significantly more prevalent among Indian businesses than US benchmarks suggest and creates measurable AI citation rate suppression.
ReadVernacular Search and AI Citations: Hindi and Regional Language AEO Research Methodology for India
This study examines AI citation rates for Indian local businesses on Hindi and regional language queries — measuring whether businesses with vernacular GBP content, Hindi FAQ sections, and regional language reviews earn higher AI citation rates on Hindi queries than those with English-only presence. The study covers 5 languages (Hindi, Tamil, Telugu, Marathi, Kannada) across 6 cities.
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