The AI Discovery Shift: How Revelyst is Decoding Consumer Intent in the Age of Generative Search

As the landscape of digital commerce continues to evolve, the traditional "search and click" model is being fundamentally reshaped by generative artificial intelligence. For Revelyst, a powerhouse in the outdoor recreation and gear sector, 2026 has marked a pivotal year in understanding how consumers interact with AI platforms like ChatGPT, Claude, and Perplexity to navigate the complexities of high-investment product discovery.

The Evolution of the Consumer Journey

For decades, the standard path to purchase was linear: a consumer identified a need, performed a keyword search, clicked on a retailer’s website, and navigated the catalog. However, the emergence of AI-driven search has introduced a sophisticated intermediary layer. Consumers are now turning to AI models to perform the heavy lifting of product research, shifting the primary point of contact away from brand-owned sites and into the conversational interfaces of large language models.

Tari Huddleston, global vice president of digital and ecommerce at Revelyst, notes that this transition represents a significant change in the nature of consumer-brand interaction. "We’re seeing what the questions are that are being asked around our brand," Huddleston stated. "It’s not all transactional-based anymore. Consumers are engaging with these tools to understand features, specifications, and the technology inside our gear."

Chronology: The Rise of AI Referrals in 2026

The shift toward AI-assisted shopping has accelerated notably throughout 2026, mirroring broader trends across the retail sector.

Early 2026 (Q1 & Q2): Retailers began noticing a nascent trend of traffic originating from AI-driven platforms. During this period, AI-attributed referral traffic to major retail websites hovered between 1% and 3%. For Revelyst, this period served as an observational phase, allowing the company to categorize the types of queries being funneled through these new channels.
Mid-2026 (Q3): As AI tools became more deeply integrated into consumer workflows—aided by improved multimodal capabilities and better search indexing—the referral traffic surged. By the second half of the year, data indicated that AI-driven referrals for many retailers had climbed to between 4% and 7%.
Late 2026 (Q4): While still comprising less than 10% of total traffic, the quality of these leads has become the focal point. Data shows that users arriving via AI referrals are demonstrating higher conversion intent than those arriving through traditional organic search, largely because the AI has already facilitated the "homework" phase of the buyer’s journey.

Supporting Data: Intent Over Volume

While the volume of traffic from AI platforms remains a smaller piece of the total traffic pie—largely because most retail traffic is still driven by established social, email, and direct search channels—the metrics surrounding this specific subset are compelling.

Huddleston highlights a critical distinction: AI users are not merely browsing; they are arriving at the site with a high level of preparedness. AI responses to complex queries are directing users straight to specific product detail pages (PDPs) rather than generic homepages. This "deep-linking" effect minimizes the friction between intent and transaction.

When a customer arrives at a Revelyst brand site via an AI referral, they are statistically more likely to add a product to their cart compared to counterparts arriving via traditional search. This suggests that the AI is effectively acting as a digital sales associate, answering the "top-of-funnel" questions that would otherwise require multiple clicks and pages of research.

The "Investment" Threshold: Why Research Matters

One of the most important takeaways from Revelyst’s experience is the relationship between product price points and the necessity of AI-assisted research. Unlike consumer packaged goods or commodity items, which allow for quick, impulsive purchases, the gear manufactured by Revelyst brands often represents a "sizable investment."

Take, for instance, a power sports helmet. With a price point ranging from $400 to $900, the consumer is not merely buying a product; they are making a decision based on safety, longevity, and performance. In these categories, the discovery phase is not a short window. It involves extensive inquiry, comparative analysis, and technical validation.

Huddleston emphasizes that the "long-term investment" nature of their products is exactly why AI tools have become so valuable to their customers. "I think the reason why [AI traffic] is still small is because the discovery phase for our products is not a short window," Huddleston explained. "It’s not like someone’s deciding: ‘Hey, I need a replacement of something’—which is a quick purchase."

Official Responses and Strategic Implications

For Revelyst, the most immediate value of this trend is the unprecedented access to consumer feedback. By monitoring the queries being fed into AI models, the company is gaining a "listening post" that reveals exactly what consumers care about—and where the company’s current digital marketing might be falling short.

Bridging the Knowledge Gap

The company is now using the data gathered from AI queries to refine its website content. For example, if an AI query reveals that consumers are frequently asking about the integration of internal padding and speakers in a helmet, Revelyst can immediately update its PDPs to ensure this information is prominent and easily searchable.

"We would not have known that that was a feature that we need to call out and be able to make sure was searchable across the product unless we had been watching and seeing what type of conversations were happening inside the space," Huddleston noted. This responsive approach to content management effectively turns the AI ecosystem into a crowdsourced market research tool.

Implications for Future Ecommerce Strategy

The rise of AI-driven discovery forces a fundamental rethink of Search Engine Optimization (SEO). Traditional SEO was about ranking for keywords; "AI-Optimization" (AIO) is about becoming the primary source of truth for the large language models that generate these answers.

Direct-to-Context Marketing: Retailers must ensure that their product information is structured in a way that is easily parsed by AI models. This means focusing on detailed, high-quality descriptive text that answers complex questions rather than just stuffing keywords.
Optimizing for the "Conversational" Query: Since users are asking natural-language questions, brands need to anticipate the "how," "why," and "what if" queries. Creating comprehensive FAQ sections and technical documentation is no longer just about user experience; it is about ensuring that an AI, when asked about a specific brand feature, chooses your product as the answer.
Maintaining the Human Connection: While AI handles the discovery, the final conversion and brand loyalty still rely on the human element. Revelyst’s success in this space suggests that the goal isn’t to replace the brand site, but to ensure that the site is the destination where the AI’s research is validated and the purchase is finalized.

Conclusion: A New Era of Informed Commerce

The trajectory of 2026 suggests that the integration of AI into the shopping experience is far more than a passing fad. For companies like Revelyst, it represents a fundamental shift toward an "informed" marketplace where the barrier to entry for high-ticket items is lowered by technology that empowers the consumer.

As the industry moves into the next phase of AI development, the brands that thrive will be those that view AI not as a threat to their direct traffic, but as a partner in the discovery process. By listening to the questions being asked in the digital ether, retailers can better align their product offerings, technical specifications, and marketing messaging with the actual needs of the modern, research-heavy consumer.

The future of commerce, as demonstrated by the shifts seen within Revelyst’s portfolio, is one where the most successful retailers are those that provide the most accurate, accessible, and comprehensive answers—before the customer even sets foot on their website.