BFSI
Many BFSI brands invest heavily in SEO but fail to see the expected results.
Traditional techniques that once worked reliably are delivering diminishing returns. The reason is clear: search has changed. Large Language Models (LLMs) are now central to how search engines interpret and rank content.
Instead of rewarding keyword-heavy or backlink-driven strategies, LLM-powered algorithms prioritise content that is conversational, semantic, and designed around user intent. For BFSI brands, this means old techniques are becoming less effective.
As Sarvesh Bagla, CEO of India's leading digital marketing agency, Techmagnate, explains: "SEO in the BFSI industry is no longer about stuffing keywords or building links at scale. Search engines powered by LLMs demand content that addresses user intent directly, with context and depth. BFSI brands that adapt quickly to this shift will reduce acquisition costs and build long-term visibility."
Let's explore why many BFSI firms struggle with SEO today and outline a practical roadmap for success through LLM Optimization for the BFSI industry.
For years, BFSI brands have relied on keyword-heavy content, generic blogs, and aggressive backlinking campaigns. While these strategies once worked, they are no longer sufficient in the era of AI search trends in BFSI.
Outdated approaches
Tactics such as keyword stuffing, over-reliance on directory backlinks, or thin blog posts offer little value to modern algorithms. LLMs evaluate content contextually, rewarding depth, quality, and semantic relevance.
The Impact of LLMs
LLMs such as ChatGPT, Perplexity, Claude, and Gemini interpret user intent in ways traditional algorithms never could. They process language in a conversational manner and surface content that directly answers questions with accuracy and clarity.
For BFSI brands, this means generic landing pages are quickly outperformed by content that provides detailed, context-driven answers.
Besides, very rapidly, customer search behaviour and patterns have shifted to LLMs. Here are a few numbers to consider.
These figures indicate very clearly that AI and LLMs are here to stay and their impact on search behaviour and the resulting traffic has already begun at massive scales.
Keywords without context: Generic terms like "best savings account" fail compared to specific, intent-driven queries such as "Which savings account offers benefits for students?"
Overlooking conversational queries: Websites of BFSI brands still rely on jargon-heavy content, while LLMs prioritise natural, question-based searches such as "How do I apply for a personal loan without collateral?"
Poor structured data: Without schema markup or chunk optimization, BFSI content often misses opportunities to appear in featured snippets, voice search, position zero results, or LLM search results.
Together, these issues explain why many BFSI firms see stagnant rankings despite ongoing SEO investment.
These challenges highlight why many BFSI brands struggle with SEO despite consistent effort. The good news is that they can be resolved with clear, practical actions.
By aligning strategies with how Large Language Models interpret and rank content, BFSI firms can move beyond outdated methods and start building sustainable visibility. The first step is rethinking the approach to keywords.
The first step toward more effective SEO is recognising that LLMs evaluate content differently. Keywords still matter, but how they are used is critical in AI led environments.
Focus on conversational and long-tail queries
Instead of relying on broad terms like "personal loans," BFSI marketers should target natural queries that reflect user conversations. For example:
"How can I get the best personal loan with low income?"
"What documents do I need to apply for a car loan?"
LLMs prefer this style of query because it aligns with real user behaviour.
Embrace semantic optimization
Search today is not about one phrase but about the ecosystem of related terms. A page targeting "home loan" should also cover "EMI calculator," "eligibility criteria," and "how to apply for a housing loan." This builds semantic depth and improves relevance.
Benchmark competitors with AI tools
Platforms like MarketMuse, SEMrush, or Surfer SEO reveal how top-performing BFSI brands are adapting to semantic and conversational search. By closing these gaps, marketers can align their strategy with LLM SEO best practices.
Once the right keyword approach is in place, BFSI brands need to develop content designed for AI-powered engines.
Contextually-rich and authoritative content
Instead of thin blogs, create detailed guides that directly answer user questions. For example, replace generic articles on "business loans" with in-depth content like "How to get a business loan without collateral in India?" This mirrors real user queries and satisfies semantic search for BFSI.
Natural language and intent
Tone matters. Content should be written in a natural, conversational style that mirrors how users search. LLMs reward readability and relevance over jargon-heavy copy.
Structured data for rich snippets
Schema markup (FAQ, How-To, Review) plays a vital role in visibility. Optimizing content with schema increases the chances of appearing in featured snippets and voice search results, which LLMs often power.
Search is dynamic, and BFSI brands need to adjust strategies continuously. Data-driven decisions ensure alignment with changing AI algorithms.
AI-powered analytics
Tools like Google Analytics, SEMrush, and Surfer SEO help identify which pages perform well in AI search and where gaps exist. These insights allow BFSI brands to refine content and strategy.
Continuous content refinement
SEO in the age of LLMs is iterative. Regularly updating pages to reflect new queries, adding FAQs, or expanding answers improves long-term performance.
Monitoring LLM-driven performance
Google Search Console and analytics platforms reveal how content performs in SERPs, including CTRs, featured snippet appearances, and position zero rankings. Tracking these metrics shows whether AI SEO services are delivering measurable improvements.
The transition to LLM-driven search represents one of the most significant changes in digital marketing. BFSI firms cannot afford to ignore it.
Sarvesh Bagla, CEO of Techmagnate, notes: "Leaders in BFSI need to see LLM optimization not as a short-term SEO tactic, but as a strategic investment. It is about reshaping how brands communicate online, prioritising trust, authority, and clarity in every interaction. Those who make this shift now will define the benchmarks for digital growth in the industry."
A key BFSI client of Techmagnate illustrates the impact of LLMs. By adapting content for conversational queries, optimising for schema, and aligning with semantic relevance, the brand achieved a 57x increase in LLM referral traffic.
"There was no way we could have achieved these results if the client leadership had not made strategic pivots early enough in the game" adds Bagla.
The message is clear: leadership that embraces this shift ensures that SEO investments create scalable, long-term results.
One of the bigger dilemmas for BFSI to contend with is this: SEO has changed and since 2023, search has evolved more rapidly than industries can keep up with.
But have search optimization practices evolved accordingly? And if not, what will it take to get there?
Brands that continue relying on outdated SEO practices risk falling further behind, but LLM optimization can carve a path forward.
Understanding the need to evolve here is critical because that's how strategic and tactical approaches will change effectively. "Before LLMs became such a massive presence, SEOs were optimizing for the Top 10 search rankings. Winning SEO meant winning on Google SERPs. But the landscape has changed now," muses Bagla.
The landscape now includes spaces that demand a drastically different approach. SEO marketers must create content for multiple user personas and use cases; and they must also take into account chunk-level optimization, where a specific part of the content is optimized for a specific query."
By refining keyword approaches, building context-rich content, strengthening technical SEO, and leveraging AI-powered analytics, financial service providers can align with how modern search engines evaluate relevance.
At Techmagnate, a leading digital marketing agency in New Delhi, LLM SEO strategies are already helping BFSI brands adapt quickly and future-proof their visibility in a new reality. Explore their AI SEO services to understand how conversational, semantic optimisation can transform search performance and lower acquisition costs.
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