As artificial intelligence fundamentally rewrites how consumers discover products, a startling reality is dawning on marketing executives worldwide: traditional search engine optimization (SEO) supremacy offers no immunity against being ignored by AI. Brands that dominate Google’s front page for decades can find themselves entirely invisible when a consumer asks an AI assistant for a product recommendation.
This exact challenge confronted pet food giant Freshpet as generative search engines, AI Overviews, and large language models (LLMs) began capturing a significant share of product discovery. To understand how legacy authority fails in the age of generative engine optimization (GEO), a recent industry webinar brought together Steven Elwell, Director of Digital Marketing at Freshpet, alongside Intero Digital experts Brittni Ratliff and Cosima Compton.
The resulting discussion mapped out a blueprint for how brands can audit their digital footprint, adapt to machine readability, and secure their rightful place in AI-generated answers.
Main Facts: The AI Visibility Crisis for Established Brands
The core thesis of the Freshpet case study is deceptively simple: strong SEO metrics do not automatically translate into AI visibility. When consumers turn to conversational AI platforms for purchasing advice, LLMs operate under a different set of rules than traditional search algorithms.
Instead of merely indexing keywords and counting backlinks, LLMs parse semantic relationships, analyze entity contexts, and synthesize multi-source information to construct a single, definitive answer. If a brand’s digital ecosystem does not clearly establish its conceptual relationship to a user’s query, the AI will bypass it entirely—regardless of how recognizable the brand name is in the physical world.
Freshpet entered the AI optimization landscape with a robust content library, widespread third-party media coverage, and commanding market share in the fresh pet food category. Yet, when testing how LLMs responded to common consumer queries about pet nutrition and fresh feeding options, Freshpet’s presence was inconsistent or missing.
The insights shared during the webinar reveal that mastering AI visibility requires a four-pillar framework:
- Relevance: Aligning content with the specific, multi-intent questions consumers ask AI.
- Authority: Earning contextual, niche-specific validation rather than relying solely on broad, top-tier media mentions.
- Structure: Organizing technical infrastructure and editorial layouts so that machine crawlers can easily extract facts and quotes.
- Engagement: Monitoring community discussions on platforms like Reddit not for direct PR, but to harvest real-world consumer questions for content creation.
Chronology: From SEO Assumptions to a Deliberate GEO Strategy
The evolution of Freshpet’s digital strategy from traditional search to generative engine optimization highlights a critical timeline every modern brand must navigate.
Phase 1: The Assumption of Inherent Relevance
Initially, Freshpet’s digital marketing team operated under the conventional assumption that their strong brand equity and high traditional search rankings would naturally carry over into AI-generated search results. Years of producing magazine-style articles, investing in search visibility, and securing media coverage were viewed as a sufficient foundation for the AI era.
Phase 2: Observation and the Reality Check
The turning point arrived when the team abandoned assumptions and began actively testing what LLMs returned for customer-centric prompts. By posing real-world consumer questions to major AI platforms, they discovered a stark visibility gap. Freshpet was either missing from crucial recommendations, misrepresented, or plagued by outdated information that failed to reflect its current market offerings.
Phase 3: Technical and Editorial Restructuring
Recognizing that legacy content was written to guide human readers sequentially through long narratives—making key facts difficult for machines to extract—Freshpet initiated a comprehensive overhaul. The team revamped page templates, cleaned up messy HTML, ensured proper schema markup was applied, and fixed critical technical oversights, such as product reviews and Q&A content hidden behind unreadable JavaScript.
Phase 4: Scaling the Prompt Framework and Measurement
Armed with a granular understanding of how LLMs interpret their brand, Freshpet scaled up its tracking infrastructure. The team began monitoring 475 distinct prompts across major LLMs, categorizing them into topic clusters. This allowed them to pinpoint weak spots, deploy subject-matter experts to answer complex nutritional questions, and establish new measurement models to track referral traffic and direct business impact.
Supporting Data and Frameworks: The Anatomy of GEO
To operationalize AI visibility, marketers must move beyond vague concepts like "writing for AI" and adopt rigorous structural frameworks. Intero Digital outlined several foundational methodologies during the session.
Restructuring Content for Machine Comprehension
Traditional digital content often relies on narrative flow, emotive language, and creative headlines. While this style engages human readers, it presents hurdles for LLMs attempting to extract precise answers. Elwell and his team realized they needed to write content that could be quoted, not merely read.
Practically, this involved:
- Breaking down long-form essays into focused, modular sections that stand independently.
- Implementing descriptive headings that directly mirror potential user queries.
- Utilizing meaningful lists and short paragraphs to highlight core data points.
- Ensuring parseable HTML rather than relying on dynamic JavaScript elements that conceal vital text from crawlers.
Contextual Authority Over Generic Backlinks
A common trap for marketers is assuming that any high-authority backlink aids AI visibility. However, Compton and Ratliff emphasized the vital difference between broad-scale links and contextual authority.
While a mention in a national publication carries weight, an endorsement from a specialized, credible pet industry publication does far more to establish a brand’s niche expertise within an LLM’s neural network. Furthermore, the surrounding anchor text matters: if earned media continually points to a homepage using only the brand name, the AI misses the semantic context linking the brand to specific subject matter.
Mining Community Sentiments for Content Gaps
Platforms like Reddit have become training grounds for conversational AI, meaning public sentiment on these forums directly influences LLM outputs. Freshpet adopted a listening-first approach to community engagement. Recognizing that pet nutrition is an emotionally charged topic, the brand avoided combative forum threads. Instead, they used community monitoring as a research tool to identify recurring consumer questions, anxieties, and misconceptions, subsequently building authoritative, evidence-backed onsite resources to address them.
Official Responses and Strategic Perspectives
Throughout the webinar, industry leaders shared candid perspectives on the realities of retrofitting a digital marketing strategy for the age of artificial intelligence.
Steven Elwell on the Limits of Legacy Content:
"We came in with years of content and established visibility, assuming that foundation would automatically make us relevant to AI-generated results. It did not. You have to ask the questions your customers are likely to ask, record what the systems return, and identify where your brand is missing or misrepresented."
Cosima Compton on Holistic Brand Integration:
"LLMs try to understand industries, concepts, and relationships between entities, not simply reproduce a conventional search results page. Onsite content, SEO, earned media, and social strategy should reinforce the same priority topics instead of operating as disconnected channels."
Brittni Ratliff on Technical Transparency:
"Valuable content can exist on a page but remain difficult for crawlers to access. You must audit the rendered experience, not just the editorial inventory, checking crawler controls, JavaScript dependencies, and whether the most important answers are available in parseable HTML."
Implications: The Future of Digital Marketing and Measurement
The transition from traditional SEO to GEO carries profound implications for how marketing teams operate, allocate budgets, and measure success.
The Attribution Challenge
One of the most complex hurdles highlighted in the session is the difficulty of measuring ROI from AI visibility. Unlike traditional ecommerce funnels where clicks map directly to linear conversions, AI search often operates as a zero-click environment or sends traffic indirectly.
Freshpet noted that while subscription-based models allow for clearer transaction tracking, primary retail sites often send consumers off-platform to third-party brick-and-mortar or digital retailers. Marketers must learn to balance directional indicators—such as visibility trends, citation frequency, and modeled relationships—while being transparent about what the data can and cannot prove.
GEO Enhances, Rather Than Replaces, SEO
A reassuring takeaway for digital marketing professionals is that generative engine optimization is not an antagonistic replacement for traditional search optimization. The fundamental pillars of strong digital health remain intact:
- Keyword alignment and site architecture still matter.
- Crawlability and page speed remain critical technical baselines.
- Credible sourcing and clear editorial standards support both human readers and machine crawlers.
Better-structured, highly quotable pages naturally support both AI visibility and conventional search performance, even as zero-click behavior shifts traditional traffic patterns.
Actionable Takeaways for Marketing Teams
For organizations looking to build their own prompt sets and audit their AI visibility, the Intero Digital and Freshpet framework suggests a clear roadmap:
- Build a representative prompt list that captures the full spectrum of the customer journey—from informational queries to transactional comparisons.
- Audit the gaps across major LLMs to see where competitors dominate the narrative.
- Optimize editorial assets for extractability by using clean HTML, structured data, and modular formatting.
- Strengthen contextual authority through niche-relevant earned media rather than generic high-authority links.
- Treat community listening as a research engine to feed content planning with real consumer questions.
As artificial intelligence continues to mediate the relationship between brands and buyers, organizations that cling exclusively to traditional SEO metrics risk fading into digital obscurity. Freshpet’s proactive pivot demonstrates that with disciplined observation, technical rigor, and a commitment to genuine usefulness, brands can ensure they are not just seen by AI, but trusted by it.
