How Results Repeat Optimizes for LLMs and Traditional Search Engines

What’s Changing and Why It Matters for You

Note: This blog kicks off a series in optimization for Large Language Models (LLM), AI, and traditional search engines, and what Results Repeat is doing to help our clients show up online across multiple platforms. If you’re interested in the full, month-long series, please subscribe to our blog on the right-hand side of this page.

Search is undergoing a dramatic transformation. Instead of relying solely on Google search results, users now turn to Large Language Models (LLMs) like ChatGPT, Gemini (Google), Perplexity, and Bing Copilot. Tools that provide full, AI-generated answers by pulling from reliable online sources.

These shifts don’t just affect how people search, they change how your brand shows up.

• Over 52% of U.S. adults now use LLMs weekly (SparkToro)
• Longer tail, low-volume queries (<1,000/month) are the most likely to trigger AI Overview results in Google
• Studies show that 50% of queries in Google Search return AI Overviews
• About 60% of search queries result in zero-click (SparkToro)
  • Rich Results, Featured Snippets, Knowledge Panels, and now AI Overviews are keeping users in the search results by directly answering questions users are asking, not requiring a click to more comprehensive content
• Google holds 85%+ of search market share, but Bing and AI tools are growing fast
  • AI and Social Media are more commonly used to find information
  • Visibility across all platforms is more essential to business success now

At Results Repeat, we’re staying ahead of these changes by focusing on key strategies that boost visibility in both traditional search and LLM-powered results.

1. Optimizing for LLMs and RAG (Retrieval-Augmented Generation)

LLMs scan the web for clear, structured answers. We ensure your content is ready.

What We’re Doing:

• Writing content that answers questions directly

• Using proper heading and content hierarchy, bulleted/numbered lists, and tables

• Targeting long-tail keywords and natural language phrases

• Creating semantically organized content that’s easy for both users and machines to interpret

LLMs like ChatGPT and Gemini favor content with semantic structure and question/answer formats

How It Works: The system queries a database or the web, retrieves up-to-date information, and then generates a response using both retrieved data and its trained model.

2. Building a Future-Proof Technical SEO Foundation

While AI is changing things, Google still dominates search and SEO fundamentals remain critical. 

What We’re Doing:

• Implementing advanced schema markup code, for machine readability

• Enhancing Core Web Vitals, technical SEO, and internal linking

• Auditing your site for crawlability and accessibility (especially avoiding JavaScript-heavy pages LLMs can’t read)

Currently LLMs make up about 1% of the search market share. 30% of prompts are considered “search”

Gemini most often cites results from Google’s top 10-12 positions. Structured, high-quality pages (that rank well in traditional search results) commonly win in AI Overviews

3. Optimizing for Bing (and Everyone Else)

LLMs like Perplexity and ChatGPT often pull from Bing’s search index.

What We’re Doing:

• Ensuring your content is structured and present for Bing indexing

• Submitting sitemaps and verifying technical readiness across engines

• Helping you build visibility on non-Google platforms like Reddit, Amazon, Instagram, LinkedIn

Bing accounts for about 5% of search market share and powers results in several top GenAI tools

4. Mapping the Full Funnel

AI tools often serve informational and navigational searches. Purchase-ready queries are sought out here, but not as commonly. To stay visible, brands must cover the entire customer journey.

What We’re Doing:

• Creating Top, Middle, Bottom of Funnel Content
  • Top – Awareness
  • Middle – Consideration
  • Bottom – Conversion

• Repurposing content across social, email, and ads to build brand familiarity

• Emphasizing brand building and visibility in areas where AI relies on recognition

Intent of Prompts / Queries used in LLMs
(According to Semrush study of 80M clickstream prompts):

• Non-search functions: 70% (summarization, coding, image creation)
• Search-related prompts: 30%
  • Informational: 15.7% (Top of Funnel)
    • Goal: To learn something or get information
    • Example: “What is Generative AI?”
  • Navigational: 10.3% (Middle to Bottom of Funnel)
    • Goal: To find a specific website, brand, product, or service
    • Example: “Results Repeat Pricing”
  • Commercial: 1.8% (Middle of Funnel)
    • Goal: To research products or services before making a purchase
    • Example: “SEO vs PPC”
  • Transactional: 2.3% (Bottom of Funnel)
    • Goal: To take a specific action, like making a purchase or signing up
    • Example: “Sign up for Results Repeat’s Newsletter”

ChatGPT just released its in-app purchase functionality so transactional intent queries may increase soon. We monitor analytics (beyond that of just organic traffic) and rankings for websites in order to evaluate traffic trends from these AI channels.

5. Expanding Brand Visibility — Beyond the Website

LLMs reward recognizable, trusted brands. That means digital PR and brand building are more important than ever. Consumers are also using a variety of different platforms beyond traditional search engines to find information about products and services. Social media and their AI technologies included.

What We’re Doing:

• Ensuring brand information is aligned across listings, social profiles, and directories

• Recommending and supporting client efforts on platforms like TikTok, Reddit, Meta, and industry sites

• Helping clients build PR momentum through mentions, thought leadership, and citations

Generic product prompts (“best handbags”) in LLMs often favor major players (Amazon, Target, Gucci). Brands like Vera Bradley see better results by focusing on strong-performing niches like backpacks or luggage.

How We Use AI Internally (To Help You Win)

At Results Repeat, we use AI to support our team, not replace it. We integrate AI to streamline data collection, research, analysis, keyword research, content outlining, and competitive audits.

This allows our expert staff to spend more time delivering value through strategic consultation, content planning, and performance analysis. Here’s how it helps us deliver more value:

• Content research, gap analysis, and competitive insights

• Outlining and drafting data-informed content strategies

• Schema generation and QA testing for clean technical SEO

• Improving workflow speed so we can focus on the strategy and analysis that drive your results

All AI generated deliverables are thoroughly reviewed internally by our human team for quality and accuracy 

Your Roadmap to Staying Visible in the AI Era

We’re advancing your strategy to ensure visibility across the evolving search ecosystem by:

• Optimizing for traditional Google Search as well as its AI Overviews

• Optimizing content for Bing, Perplexity, and ChatGPT

• Capitalizing on longer-tail, lower-volume, semantic, and more conversational queries

• Building upon brand-driven search and citations

There is no such thing as a “set it and forget it” digital strategy. For more than 10 years we have helped our clients through disruptive change and digital evolution. We will continue to shape your strategy so you can stay ahead of where search is headed.

If you’re interested in learning more about how Results Repeat can help your brand optimize for AI and LLM search, please reach out to us.