.IN moves to Top 10 among cctlds , latest Verisign Domains Brief . With 3.9 million registrations .IN is now firmly in a growth phase
https://www.dnib.com/articles/the-domain-name-industry-brief-q3-2025
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In short how Domain Name valuations have been done for .com , Keyword Domains. https://domainsherpa.com/rosener-equation-value-domain-names/
For .IN and .CO.IN , something similar will be apparent as India market evolves and grows
Monthly Search Volume in India X Cost Per Click = Domain Name Price and Valuation
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Search Advertising and Keyword Domains
Search Ad Revenues and How they are related to Keywords (Exact Match Descriptive Word Domain Names)
India's Search Ad market is roughly $2.5 billion in 2025 https://lnkd.in/d8XSVaDm
Search Advertising is primarily bidding on Keywords , based on Monthly Search Volume and CPC (Cost per click) . Monthly search volume in India has been rising and CPC is going up as well. At the root of this are Keyword Domain names for India, namely .in and .co.in keywords that will be valued in line with rising Monthly Search Volumes and CPC's .
Many websites provide this data for keywords and India market - see Google Keyword Planner or others such as Wordstream, AnswerthePublic etc.
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How to value .IN Domain Names ? What factors are involved ? Different from Real Estate. Descriptive Generic Keyword Domains
https://www.youtube.com/watch?v=DZ1Jg-UtReo
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Exact Match Domains (EMDs)
How do AI engines look at EMDs (Exact Matching Domains) or Descriptive Generic Keywords ?
Gemini answer
Yes, exact-match domains (EMDs) can function as entity signals within AI training infrastructure, particularly in the context of AI-driven search and information retrieval systems. They act as clear, initial signals of topical relevance and identity for both users and AI models.
In modern AI systems, EMDs are reframed as "governance-backed anchors" that help reinforce the identity and provenance of content across various platforms and languages. While they are no longer a standalone "magic bullet" for ranking, their value lies in clarifying expertise and ensuring that an entity (the website/brand) is correctly identified and selected by AI answer engines and generative summaries.
Key aspects of how EMDs function as entity signals in AI contexts:
- Topical Alignment: An EMD directly signals the core topic or entity the domain represents, which helps AI models quickly categorize and understand the website's subject matter.
- Clarity and Unambiguity: In a complex web of information, an EMD provides an unambiguous signal about its content. AI models, such as Large Language Models (LLMs) used for entity matching, benefit from clear and well-structured data sources.
- Trust and Authority: When paired with high-quality content and a good user experience, an EMD can build immediate user trust and credibility, which in turn reinforces the website's Experience, Expertise, Authority, and Trust (EEAT) signals that AI systems use to evaluate content quality.
- Data Provenance: In sophisticated AI frameworks, EMDs are used as part of an "auditable signal lineage" that tracks the origin and integrity of information. This helps ensure that the content is traceable and reliable as it is processed and potentially translated by AI systems.
- Hybrid Search Systems: Many current AI search platforms use hybrid retrieval systems (combining lexical and semantic search). Lexical search still relies on exact matches, meaning EMDs can still be effective for precision in specific, niche queries.
In essence, EMDs help in the process of entity matching and resolution, where AI agents connect different pieces of information to a single, clearly defined real-world entity.
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