How Ecommerce Startups Can Master AI Visibility and Structured Data in the Modern Digital Landscape

In the rapidly evolving landscape of digital commerce, the intersection of artificial intelligence and consumer search behavior has fundamentally altered how brands attract customers. For ecommerce startups, the traditional playbook of relying solely on paid search and social media advertising is no longer sufficient to maintain a competitive edge. Kenny Trusnik, founder of the Cleveland-based marketing agency Forest City Digital, suggests that the modern merchant must prioritize the technical foundation of their product data to remain visible in an era dominated by Large Language Models (LLMs) such as ChatGPT, Claude, and Gemini.

The Shift Toward Agentic Search and AI Visibility

The rise of generative AI has ushered in a new epoch of search—often referred to as "Agentic Search"—where platforms act as intermediaries between the user and the merchant. Unlike traditional search engines, which present a list of blue links, LLMs synthesize information to provide direct answers. This shift necessitates a structural change in how ecommerce brands manage their catalogs.

Trusnik emphasizes that for a brand to be recommended by an AI, it must be "crawlable" and "understandable." This is achieved through meticulous backend metadata management. Shopify’s recent integration of Agentic Storefronts serves as a primary example of this shift. By exposing a merchant’s full catalog—including granular details like product materials, specific features, sizing, and color variants—to AI crawlers, brands can ensure their products appear in relevant AI-generated responses.

Data suggests that proactive optimization for these new search channels is yielding tangible results. According to Trusnik, clients who prioritize this technical visibility are already seeing upwards of 10% of their total online revenue attributed to traffic originating from LLM interactions. For many businesses, this represents a significant, previously untapped revenue stream that effectively bridges the gap between traditional SEO and emerging conversational search.

A Chronological Perspective: From Corporate Foundations to Agency Strategy

The evolution of Forest City Digital mirrors the broader maturation of the ecommerce industry over the last decade. Trusnik, who began his career in the structured, goal-oriented environments of corporate giants like Toyota and Sherwin-Williams, founded his agency in 2020. His transition from corporate marketing to the startup ecosystem was driven by an observation: many small-to-medium enterprises struggled to connect marketing activities to core business outcomes.

By applying the rigorous, goal-oriented frameworks common in large-scale corporate environments to the agility of a startup, Trusnik has focused on three pillars: search, social, and retention. The timeline of this approach reflects the industry’s shift away from "vanity metrics"—such as mere social media impressions or email open rates—toward bottom-line impact. By utilizing platforms like Klaviyo or Brevo to optimize sales funnels and address churn, his agency aims to ensure that every marketing dollar spent correlates with a measurable increase in lifetime customer value.

The Technical Requirements for Modern Visibility

For startups looking to scale in 2026 and beyond, the strategy for customer acquisition must be rooted in technical hygiene. Trusnik identifies two critical, low-cost actions for merchants:

1. Robots.txt Optimization: A fundamental oversight for many retailers is the accidental blocking of AI crawlers via the site’s robots.txt file. Ensuring that generative AI platforms have permission to index the site is the foundational step toward AI visibility.
2. Structured Data Implementation: The use of Schema.org markup remains non-negotiable. This structured data provides a "map" for algorithms, allowing them to interpret the purpose of a webpage, the specific attributes of a product, and the context of the brand.

Beyond technical configuration, the acquisition of backlinks remains a vital signal for LLMs. Unlike traditional SEO, where the goal is to rank for a specific keyword, the goal in the age of AI is to be cited as an authoritative source in "best-of" listicles and comparative articles. These mentions serve as validation for the LLM, signaling that the brand is a reputable entity in its respective niche.

Analysis of the "Novelty" Factor in Product Development

While technical infrastructure provides the visibility, the underlying product strategy must remain rooted in solving genuine pain points. Trusnik notes that successful startups often avoid radical "blue ocean" inventions in favor of "iterative novelty."

This strategy is evident in the current success of the hemp beverage market. While the underlying product (hemp-derived drinks) is not a new invention, the positioning of these products as sophisticated alternatives to alcohol in social settings provides the necessary novelty to capture market share. Similarly, the vitamin industry has seen brands like Grüns successfully reposition gummy vitamins as "superfood" supplements. By adding value to existing product categories rather than reinventing the wheel, these brands minimize the risk associated with consumer adoption while maximizing the appeal of their value proposition.

Broader Implications and Future Outlook

The implications of this shift are profound for the ecommerce sector. As LLMs become more integrated into daily search habits, the "gatekeeper" role held by Google’s traditional index is being challenged. Merchants who fail to adopt a structured approach to their data risk becoming invisible in an environment where the consumer no longer visits the merchant’s website until the final stage of the buying journey.

Furthermore, the rise of AI-generated content presents a challenge to traditional content marketing. Trusnik argues that generic, AI-repurposed content is losing its value. In contrast, original, research-backed information—articles, videos, and social media content that provide unique data or insights—is becoming increasingly important. As AI platforms prioritize high-quality, verifiable information, brands that invest in original content will likely see their authority grow, both in the eyes of search algorithms and human consumers.

Strategic Recommendations for Emerging Brands

For a startup operating in the current climate, the priority list is clear:

• Phase 1: Foundation. Ensure that product data is clean, deep, and structured. This includes complete metadata, high-resolution imagery, and accurate product descriptions that allow AI to understand the product’s function.
• Phase 2: Visibility. Actively manage the site’s technical infrastructure to allow for crawler access. Opt into modern integrations like Shopify’s Agentic Storefronts to keep catalogs synced with the major LLMs.
• Phase 3: Authority. Pursue earned media and placements in reputable listicles. These citations serve as the "trust signals" that help LLMs decide which products to recommend.
• Phase 4: Scaling. Once the foundation is set, utilize paid channels, such as Meta ads, to build top-of-funnel awareness. This creates a feedback loop where paid traffic increases brand recognition, which in turn leads to more organic citations and better AI rankings.

Ultimately, the goal is to create a digital presence that is as accessible to the machine as it is to the human. As Trusnik concludes, the future of ecommerce is not necessarily about outspending the competition on ads, but about out-structuring them. By focusing on data integrity and technical accessibility, startups can position themselves to thrive in an AI-dominated landscape, ensuring they are the ones being recommended when a consumer asks, "What is the best product for my needs?"

The shift from manual search to agentic discovery is not merely a trend; it is a structural evolution of the internet. Brands that treat their data as their most valuable asset will be the ones that define the next generation of online commerce. By aligning their marketing strategy with these technical realities, merchants can move from being passive participants in the digital economy to active players in the new era of conversational commerce.