The LLM & Affiliate Playbook: Winning in AI-powered Search

Emerging AI technologies are rapidly changing the affiliate and influencer marketing landscape, transforming the way content is created, optimized and discovered across platforms.

Affiliate marketing is no longer just a sales channel; it is a strategic driver of AI search visibility. Of 58% of consumers Because we’re already turning to generative AI instead of traditional search results for product recommendations, a holistic digital strategy is no longer optional.

As generative AI changes the way people discover and interact with brands, affiliate marketing has a more influential seat at the digital table than ever before.

In this article, Account Director Ben Norton explores how large language models (LLMs) are changing the landscape, how affiliate partnerships can increase discoverability of AI responses, and practical steps to future-proof your affiliate program through Large Language Model Optimization (LLMO).

Who are the top LLMs and how do they support e-commerce?

Gemini, OpenAI and Perplexity are the three main LLM operators, each offering different solutions that transform e-commerce discovery and interaction.

• Twin – Google’s Search Generative Experience (SGE), powered by Gemini, is redefining the way users interact with content. Gemini is embedded in Google’s ecosystem and influences every stage of the customer journey, from product research and consideration to purchasing decisions.

• OpenAI – While Google dominates traditional search, OpenAI leads the LLM market, with more than 800 million active users, a number that has doubled since February 2025. OpenAI continues to roll out new features that make it easier for consumers to shop directly based on AI-generated results, including the launch of the in-app ecommerce solution, allowing consumers to make a purchase without leaving the app.

• Bewilderment – Often described as an “answer machine,” Perplexity combines LLM technology with real-time sourcing and citation-driven responses. By combining AI-generated insights with verifiable web links, it provides both trust and visibility, making it an increasingly powerful channel for brands and affiliates to surface in product discovery.

What is the difference between an SEO and LLM strategy?

Although there are synergies between SEO and LLM activities, strategies must remain fundamentally different because they use different logics. With new technology comes new acronyms that every marketer should be aware of:

• SEO. Optimizes content so search engine algorithms can rank in traditional search results.

• LLMO. Focuses on shaping the way language models interpret, summarize, and present your brand in AI-driven responses across chat, voice, and search interfaces.

• LLM SEO. A subset of LLMO that focuses specifically on visibility within AI-powered search results (such as Google’s SGE), combining traditional SEO tactics with AI-driven content signals.

The possibility for affiliate marketing

The rise of AI-powered search is rewriting the rules of affiliate marketing. Many affiliates are seeing significant drops in organic traffic because these AI search summaries aren’t generating clicks, impacting their ability to generate revenue and continue investing in brands. At the same time, publishers with high authority are favored in terms of AI-driven visibility, with their structured content, reviews and deal data providing the foundation for AI discovery.

By aligning affiliate strategies with LLM logic, brands can increase their chances of showing up in AI-generated responses. Key tactics include:

1. Activate content on high domain authority sites with search power. Partner with affiliates who have a high domain authority. These sites are favored by LLM models and usually provide brands with high-quality content.

1. Optimize content for discoverability. Encourage affiliates to use natural, question-based language, such as “What are the most comfortable running shoes?” or “How do I open a crypto wallet?” That’s how users talk to AI.

1. Structure content for AI visibility. LLMs prefer well-structured content. Work with affiliate partners to optimize content formats (Q&A, lists, comparisons) to increase AI (AEO/GEO) visibility, rather than relying solely on keywords. Brands that actively coach affiliates on formatting, internal links and natural language can increase the discoverability of AI tools and gain an edge over the competition.

1. Refine product details. Prepare your product feed for AI environments, including rich metadata such as price, availability, category, images, descriptions, reviews and shipping information. Structured data increases the chances of your products being included in AI-generated shopping responses.

1. Improve brand sentiment, at scale. LLMs summarize a brand using third-party content. When partners explain a brand clearly and positively, it helps shape AI’s language and sentiment toward the brand. Make sure partners go further than just posting links. Detailed product and brand context increases the likelihood of appearing in AI summaries.

1. Follow implementation. Add unique tracking codes to product links shared with affiliates or to early AI integrations (for example, links embedded in a ChatGPT-generated list). These codes can help monitor traffic sources and basic affiliate attribution, even as affiliate tracking technology is still evolving.

1. Greater role for trusted content partners. While LLMs focus on quality, there is an opportunity to increase the number of editorial-style affiliates who publish structured, useful content.

How do you find partners who are suitable to support LLMO?

A combination of traditional affiliate and SEO specialist tools can be used together when searching for relevant partners.

• Use SEO tools to identify high-ranking affiliates. SEO tools like SEMrush, Ahrefs or Surfer SEO identify ranking domains for high-intent searches related to a brand or category.

• Combine SEO and affiliate data. Once you’ve identified SEO-strong affiliates, compare them to your current affiliate platform data. Program approaches will vary, but in general it is essential to find the right balance between high-level domains and overall performance.

• Manually source LLM outputs directly. Run relevant brand and product queries directly within LLM platforms. It’s free, fast and gives a clear picture of which sites LLMs are popping up most often. These affiliates are strong candidates for a partnership. Don’t stop at your own brand; also conduct competitor searches, which can reveal opportunities for capture and content gaps that can be addressed.

In a world where AI writes the rules, affiliates hold the pen. Brands that adapt now won’t just keep up; they will be the ones LLMs like to cite.