Artificial intelligence visibility is becoming crucial for brands as generative AI and large language models reshape digital product discovery. Freshpet encountered this firsthand when its traditional SEO strengths did not translate into prominence within AI-generated content recommendations. This article explores how Freshpet developed an advanced generative engine optimization (GEO) strategy to close the AI visibility gap by focusing on relevance, authority, structure, and engagement.

The Challenge with Traditional SEO in AI Visibility

Freshpet, a well-established pet food brand, initially assumed that its existing strong SEO foundation and brand recognition would secure its position in AI-driven answers regarding fresh pet food. Contrary to expectations, the brand found itself largely absent in responses from large language models (LLMs). This highlights a key distinction: AI systems aim to understand the relationships among concepts and entities rather than merely reproducing ranked search results.

Brittni Ratliff, a digital strategy expert, notes,

“Brands must realize that AI visibility demands more than just ranking well. It necessitates explicit, contextual connections between the brand and the queries users ask.”

Assessing AI visibility involves actively interrogating the AI systems with relevant user questions and analyzing the nature and accuracy of the brand’s representation in answers.

Critical Areas to Address for Generative Engine Optimization

Intero Digital outlined a practical framework emphasizing four areas critical to improving AI visibility:

Relevance

Content must directly address the specific questions users pose to AI. This requires continuously monitoring and updating content to reflect current audience intent and timely information such as recent statistics or industry developments.

Authority

Establishing trustworthiness involves linking claims to credible sources, demonstrating expert authorship, and leveraging industry-recognized citations. This also includes cultivating contextual backlinks from specialized publications to strengthen authority within relevant niches.

Structure

The technical format of content plays a significant role. Clean HTML coding, quick page loading speeds, descriptive headings, and schema markup facilitate AI systems in parsing and extracting key information efficiently. Complex topics benefit from concise paragraphs and segmented sections enabling easier quoting by LLMs.

Engagement

Brand perception on social platforms, forums, and review sites forms an important data source for AI models. Monitoring community discourse enables brands to address common concerns or misconceptions by producing authoritative, well-sourced content that AI systems reference.

Organizing Content for AI Quotation

Freshpet discovered that much of its legacy content was crafted more like narrative magazine articles that, while engaging for human readers, obscured critical facts essential for AI comprehension. The strategic shift involved restructuring content into standalone, quote-ready segments with direct answers and clear hierarchy.

Steven Elwell, Freshpet’s marketing lead, explains,

“We moved from storytelling that flows to distinct sections that can be independently cited by AI, improving both machine readability and user clarity.”

This included refining blog templates, cleaning up cumbersome HTML elements, and applying accurate schema markup for better AI integration.

Another technical insight was that valuable content delivered via JavaScript—such as reviews and Q&A—was not fully accessible to AI crawlers. This underlines the importance of auditing the rendered page experience from a crawler’s perspective, ensuring critical content is embedded in parseable HTML rather than reliant on scripts.

The Value of Contextual Third-Party Authority

While high-profile backlinks provide some SEO value, Freshpet’s team emphasized the amplified impact of industry-specific endorsements. Recognition from authoritative pet nutrition publications delivered stronger contextual signals that AI models leverage to associate the brand with specialized expertise.

Brittni Ratliff adds,

“It’s not enough to have numerous mentions; each must explain the brand’s role and knowledge in context, with appropriate onsite resources linked for AI confirmation.”

This means anchor text diversity and relevant content surroundings are critical in helping LLMs resolve brand-topic associations accurately.

Leveraging Community Discussions as Insight

Online communities such as Reddit provide raw, candid consumer opinions that AI models incorporate. Rather than engaging in every conversation, Freshpet takes a listening approach, looking for prevalent themes or misunderstandings that its experts can clarify with targeted content.

Elwell describes this as a powerful research tool,

“Monitoring forums informs our content priorities and helps us address repeated queries with evidence-backed responses that serve both users and AI algorithms.”

This proactive content development based on community signals enhances the brand’s authoritative footprint across multiple digital touchpoints.

Building a Comprehensive AI Prompt Set

For organizations without specialized AI visibility platforms, a recommended starting point is creating a broad set of 20 to 30 sample prompts reflecting typical customer questions. Testing responses across popular LLMs reveals how the brand is cited and identifies gaps or inaccuracies.

Freshpet’s scale is larger, tracking 475 prompt variations categorized by topic, which allows them to identify clusters of poor coverage and deploy subject-matter experts to strengthen content precisely where needed. This methodology prioritizes work based on potential conversion impact and customer objections.

Measuring AI Visibility and Attribution

AI visibility metrics differ from traditional SEO measurements. Freshpet experiences indirect attribution challenges, especially when customers are referred to third-party retailers for purchases. Its subscription-based services provide clearer transactional data.

Tracking includes monitoring referral traffic from AI citations, user behaviors downstream, and modeled relationships between AI exposure and website visits. Elwell cautions,

“Avoid overstating attribution from AI sources. Use a combination of directional data and business outcomes to evaluate the true effect.”

Generative Engine Optimization Enhances, Not Replaces, SEO

GEO strategies complement traditional SEO rather than supplant it. Elements like keyword relevance, crawlable architecture, credible sourcing, and site structure remain fundamental to digital presence.

Brittni Ratliff advises,

“Update existing pages to reflect current AI insights instead of diluting authority with competing similar content. Use pillar pages and clusters for complex subjects to organize information logically.”

Freshpet’s experience shows that content freshness, prompt specificity, and balanced use of AI assistance contribute to sustained improvements in both AI visibility and organic search.

In conclusion, generative engine optimization is a comprehensive process involving audit, content refinement, authority building, technical enhancements, and strategic measurement. Freshpet’s approach offers a practical model for other brands aiming to establish trust and presence within AI-driven discovery landscapes.

For organizations looking to automate and enhance their AI visibility efforts, exploring advanced AI marketing platforms can further streamline this complex work. Consider the benefits of AI-powered advertising agents like Google Ads AI agents and Meta Ads AI agents to optimize campaigns intelligently.

Integration With Broader AI Search Visibility Strategies

Freshpet’s approach is aligned with emerging trends in AI search where local and specialized business visibility matters increasingly. A practical understanding of local optimization factors, review volume, and social signals can further enhance brand presence across AI models. For more comprehensive insights, see our article on key factors for local business visibility in AI search.

The importance of measuring AI visibility beyond simple rankings is growing. Brands must differentiate between mentions and authoritative citations when optimizing for generative AI environments. Our analysis on AI visibility metrics and their impact on SEO strategy provides useful frameworks for marketers.

Final Thoughts

Generative engine optimization demands a multidisciplinary effort, combining editorial rigor, technical precision, industry expertise, and data-driven measurement. Freshpet’s experience underscores the necessity for brands to evolve alongside AI technologies by adopting deliberate, data-informed strategies that address AI’s unique understanding of relevance and authority.

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