IndiaMART InterMESH, one of India’s largest B2B online marketplaces, is restricting access to parts of its website to protect its proprietary business data from Google Search, web scrapers and artificial intelligence agents. The company has moved selected information behind login requirements, introduced stricter access controls and stopped displaying certain strategic information on search engines and large language models (LLMs). The decision reflects growing concerns among online platforms that AI companies could use their data to generate answers without sending users back to the original websites.
IndiaMART co-founder and CEO Dinesh Agarwal discussed the strategy during the company’s second-quarter FY27 earnings call. He said the company was prepared to sacrifice 10–20% of its current unique business enquiries to protect its data advantage. The move comes as IndiaMART’s unique business enquiries declined 14% year-on-year to approximately 27 million during the July–September 2026 quarter. IndiaMART Q2 FY27 earnings call transcript.
Why IndiaMART Is Restricting Access to Its Data
IndiaMART connects businesses looking to purchase products with manufacturers, wholesalers, distributors and suppliers. Its platform contains extensive information about products, supplier listings, categories and business enquiries.
This information is valuable because it helps buyers discover suppliers and compare available products. It also gives IndiaMART an advantage built through years of collecting, organising and maintaining business data.
However, the growth of generative AI and AI-powered search is changing how people discover information online.
Instead of visiting multiple websites, users can increasingly ask AI tools to find suppliers, compare products and summarise information. These systems can use publicly accessible web content to generate answers directly.
IndiaMART believes unrestricted access could allow AI companies to benefit from its proprietary information without necessarily directing users back to its marketplace.
During the earnings call, Agarwal explained that the company had started taking three steps:
- Moving selected website content behind login requirements.
- Restricting unrestricted website scraping.
- Removing certain strategic and proprietary information from Google Search and AI platforms.
The objective is to retain control over information that IndiaMART considers an important competitive advantage. IndiaMART earnings call transcript.
IndiaMART Is Willing to Lose 10–20% of Business Enquiries
One of the most significant statements from Agarwal was that IndiaMART was willing to sacrifice 10–20% of its current unique business enquiries to protect its data.
This suggests that the company is prioritising long-term control over its proprietary information instead of maximising every possible source of website traffic.
IndiaMART’s management also acknowledged that the shift towards AI-powered search could reduce the number of users reaching its website through traditional search engines.
Agarwal pointed to the growing presence of Google’s AI Overviews as another factor affecting website traffic. He said that, according to the company’s assessment, AI Overviews had expanded from appearing in around 10–20% of searches to approximately 50% or more.
He also acknowledged that some of the decline in enquiries was a consequence of IndiaMART’s own decision to restrict information.
The company is therefore dealing with two changes simultaneously: users are increasingly discovering information through AI-powered interfaces, and IndiaMART is deliberately limiting the information available to those systems.
IndiaMART’s Business Enquiries Decline 14%
The decision comes amid a decline in IndiaMART’s unique business enquiries.
During the July–September 2026 quarter, the company recorded approximately 27 million unique business enquiries, down 14% compared with the same period a year earlier.
| Business metric | Q2 FY27 performance |
|---|---|
| Unique business enquiries | 27 million |
| Year-on-year change | Down 14% |
| Enquiries compared with previous peak | Down approximately 10–15% |
| Management’s acceptable potential enquiry loss | 10–20% |
| Quarterly performance advertising expenditure | ₹8–10 crore |
Management attributed the decline partly to changes in buyer behaviour and partly to restrictions on data access.
The company also indicated that enquiries had fallen approximately 10–15% from their previous peak levels.
This makes the strategy important for IndiaMART’s future growth. The company needs to protect its information while ensuring that genuine buyers continue discovering suppliers through its marketplace. IndiaMART Q2 FY27 earnings call transcript.
IndiaMART Is Increasing Advertising to Replace Lost Traffic
To reduce its dependence on organic search traffic, IndiaMART is increasing its investment in performance advertising.
Agarwal said the company was spending approximately ₹8–10 crore every quarter on performance marketing, concentrating on the categories that generate the largest volume of business.
IndiaMART operates across approximately 100,000 product categories. Rather than distributing advertising expenditure equally, the company is focusing on the top 25% of categories, where it sees the greatest business opportunity.
The strategy is intended to generate more qualified enquiries from buyers who are actively looking for products and suppliers.
Management shared several details about the advertising approach:
| Advertising metric | Reported figure |
|---|---|
| Quarterly advertising expenditure | ₹8–10 crore |
| Categories covered by the marketplace | Approximately 100,000 |
| Priority categories | Top 25% |
| Share of traffic from paid channels | Approximately 10% |
| Targeted enquiries generated monthly | Approximately 1 million |
| Paid traffic that cannibalises organic traffic | 20–40% |
The cannibalisation figure is important. It means that some users arriving through paid advertisements might otherwise have discovered IndiaMART through organic search results.
Therefore, advertising does not automatically translate into an equivalent increase in total enquiries. IndiaMART data restrictions and advertising strategy.
IndiaMART May Monetise Its Data for AI Training
Although IndiaMART is restricting unrestricted access to its information, the company has not ruled out commercial partnerships with AI developers.
Agarwal explained that the company could consider licensing certain types of data for AI training if there is a clear revenue opportunity.
However, he distinguished between different ways AI companies can use information:
- AI training: IndiaMART is open to considering redacted, non-personal data for training if it can earn revenue.
- Retrieval-augmented generation (RAG): The company wants to evaluate which information should be made available and under what conditions.
- AI agents: IndiaMART has not decided exactly which agents should be allowed to access its platform or how frequently they should be permitted to interact with it.
The distinction matters because training an AI model, retrieving information to answer a user query and allowing an autonomous agent to interact with a website are different activities.
IndiaMART appears interested in generating revenue from controlled data licensing rather than allowing unrestricted access to its proprietary information.
This could create a new business opportunity if AI developers become willing to pay for reliable, specialised B2B information. IndiaMART Q2 FY27 earnings call transcript.
IndiaMART Is Also Using AI Across Its Own Platform
While restricting external AI access, IndiaMART is expanding its own use of artificial intelligence.
The company has been developing AI-powered capabilities for buyer interactions, supplier discovery and customer support.
One notable development is its voice-based AI system, which management said handles approximately 80,000–100,000 buyer calls daily.
This demonstrates how IndiaMART is attempting to use AI to improve its own operations while maintaining control over the underlying business information.
The company has also been working on standardised product cataloguing, intelligent matchmaking, content moderation and multilingual search.
These capabilities could improve the quality of information available on the platform and help buyers find relevant suppliers more efficiently. IndiaMART Q1 FY27 earnings call transcript.
The Bigger Picture
IndiaMART’s decision highlights a growing conflict between traditional internet businesses and AI companies over access to information.
For years, online platforms benefited from making their content discoverable through search engines. Google directed visitors to websites, while businesses earned revenue through advertising, subscriptions, leads and transactions.
AI-powered search is changing this relationship. AI systems can summarise information and answer questions directly, potentially reducing the need for users to visit the original websites.
For data-intensive businesses such as IndiaMART, this creates a difficult choice: make information freely accessible and risk losing control over its commercial value, or restrict access and potentially lose traffic from search engines and AI platforms.
IndiaMART is choosing to protect selected information while exploring paid licensing opportunities. Its decision could become an example for other online marketplaces that rely on proprietary business listings and structured data.
Looking Ahead
IndiaMART’s strategy will be tested over the coming quarters as AI-powered search becomes more widely adopted. The company will need to determine whether protecting its data creates enough long-term value to compensate for the enquiries and traffic it may lose in the process. Its investment in performance advertising and internal AI tools will also be important in maintaining buyer engagement.
The broader question is whether AI companies will eventually pay publishers, marketplaces and other data owners for reliable information. If commercial data licensing becomes more common, IndiaMART could find a new way to monetise its information. Until then, the company is taking a cautious approach to sharing its most valuable data with external AI systems.
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