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Guide · AI search

How does an outdoor brand get onto the shortlist when people ask AI what gear to buy?

By publishing the specifications that matter for a given activity and set of conditions, keeping them consistent at every retailer, and earning a place in the expert reviews and buying guides that AI answers draw on. Outdoor gear is bought for a trip, a season or a climate, often by people who are still new to it. Those are the shoppers most likely to ask an assistant to explain the choice, and the shortlist it gives them can shape a whole kit.

By Underneath Team Guide Updated

The short version

  1. The market is big and full of newcomers: the Outdoor Industry Association (opens in a new tab) counted a record 183.2 million US participants in 2025, and more than half of today’s participants have less than 10 years of outdoor experience (Shop Eat Surf Outdoor (opens in a new tab)).
  2. The money behind it is national-scale: the outdoor recreation economy added $639.5 billion, 2.3% of US GDP, in 2023, with retail trade contributing $156.3 billion (Bureau of Economic Analysis (opens in a new tab)).
  3. Growth is concentrated in technical brands: Amer Sports grew its Arc’teryx-led Technical Apparel segment 32% to $674 million in the second quarter of 2026.
  4. AI is already moving orders for outdoor names: Shopify (opens in a new tab) reports that Stanley 1913, which it describes as growing from an iconic outdoor brand, had five times as many AI-referred US orders as in the same window a year earlier.
  5. Google opens its own AI Mode shopping announcement (opens in a new tab) with an outdoor question, “How do I choose a pair of hiking boots?”, and describes running several searches at once to work out what makes gear right for a trip’s conditions.

Who buys outdoor gear today, and what is a customer worth?

A growing, less experienced crowd of hikers, campers, anglers and families, who often expand into several activities.

The OIA’s 2026 report shows participation reaching 59% of Americans aged six and over, even as growth slowed to 1.1%. The base is changing. Americans aged 65 and older are a fast-growing group, at 23.9 million participants with a participation rate of 41.6%. Kids aged 6 to 12 grew 5% to 22.6 million. Meanwhile the average participant gets out less often: 65.2 outings a year, against 87 in 2012, according to the OIA’s research director.

What a customer is worth comes from breadth more than frequency. The same report found that more than 9 in 10 campers also hike, fish, paddle or bike, which is why coverage of the report calls camping the on-ramp. A family that buys a tent this year may buy packs, rain shells, fishing gear and a paddleboard over the next few. Our inference is that the first trip’s shopping list is the start of a multi-year relationship, and the brand on that list has the first chance at the rest.

Where the sale lands varies. REI, the largest consumer co-op in the US, reported $3.54 billion in net sales (opens in a new tab) in 2025 and more than 26 million members. Specialty retailers like it remain central for many brands. At the same time, Amer Sports’ direct-to-consumer revenue rose 39.9% to $896.8 million in the quarter, out of total revenue of $1,633 million. A brand can win the recommendation and see the sale go through its own site or a retail partner.

How do outdoor shoppers research gear, and where does AI fit?

Through expert reviews, retailer guides, forums and video, and now AI that summarizes all of them for a specific trip.

Outdoor shopping has always been research-heavy. Buyers want to know whether a tent survives wind, whether a jacket breathes on a climb, how much a pack weighs, and whether a sleeping bag is warm enough in October. Much of that guidance comes from independent testers, specialty retailers’ advice pages and community discussion.

AI search now pulls those threads together. Google says (opens in a new tab) AI Mode draws on a Shopping Graph of more than 50 billion product listings, and gives an example of the method: asked for a travel bag for a rainy trip to Portland, Oregon, it runs several simultaneous searches “to figure out what makes a bag good for rainy weather and long journeys,” then suggests waterproof options. That is exactly how outdoor gear is chosen: conditions first, then products that meet them.

Newcomers are the shoppers most likely to need that kind of help. With more than half of participants under 10 years of experience, many shoppers do not know what “hydrostatic head,” “fill power” or “R-value” mean, but they can describe the trip. Shopify’s holiday report makes the same point about AI in general: shoppers can describe a problem in their own words and an assistant can match it to a product that solves it. Shopify also reports that 65% of shoppers plan to use AI for at least one shopping task this season.

Which outdoor gear questions do people ask AI assistants?

Questions about a trip, its conditions and a budget, plus head-to-head comparisons and first-time kit lists.

We wrote the examples below to illustrate outdoor shopping questions; they are not observed prompts:

  • Conditions: “Rain jacket for Pacific Northwest hiking that still breathes on steep climbs.”
  • Weight and budget: “Two-person backpacking tent under 4 pounds for windy Colorado trips, under $400.”
  • First trip: “What do I need for our first car camping trip with two young kids?”
  • Comparison: “Arc’teryx Beta vs Patagonia Torrentshell for everyday hiking and city rain.”
  • Season: “Warmest sleeping bag under $300 for late-fall camping in the Smokies.”
  • New activity: “Good beginner binoculars for birding, light enough for long walks.”
  • Durability: “Which hiking boots can be resoled, and how long do they last?”

The first-trip question matters most commercially, in our view, because one answer can list ten or more items. A brand named for the tent may also be considered for the sleeping bags and the stove. Safety-critical gear, such as avalanche equipment or climbing protection, deserves extra care: describe certifications and intended use precisely, and do not imply that a product makes a dangerous activity safe.

How does an AI shortlist become an outdoor sale?

Through a named product, a check against trusted reviews, and a purchase at a retailer or the brand’s site.

Shortlist. The assistant names a few products for the trip and conditions described. For many newcomers, this may be the first time they hear the brand’s name.

Verification. Outdoor buyers check before spending a few hundred dollars. They read expert reviews, compare weights and ratings, and look for people who have used the gear in similar conditions. If the assistant’s description of your product disagrees with what reviewers and retailers say, the shopper notices.

Purchase. OpenAI documents (opens in a new tab) that when a shopper opens a product in ChatGPT, it may list several merchants ranked “based on factors like availability, price, quality, and whether they are the maker or primary seller of that item.” A specialty retailer with full stock data might be listed alongside, or above, the brand.

Expansion. The shopper returns for the next activity. Stanley 1913’s senior director of commerce technology told Shopify that its AI work now spans social media, PR and data analytics, “to increase our share of the agentic conversation in awareness, consideration and decision making.” That breadth fits a category where the next purchase follows the next adventure.

What decides whether an assistant names your gear?

Platforms document product data and outside content; studies show reviews, lists and fresh pages matter; the rest is inference.

Documented by the platforms. OpenAI says ChatGPT considers “structured metadata from first-party and third-party providers (e.g., price, product description) and other third-party content,” and builds review summaries from public websites. Google describes using its Shopping Graph’s reviews, prices, color options and availability, and refreshing more than 2 billion listings every hour.

Observed in our studies. Outdoor buying guides are often numbered “best” lists, and some are published by sellers. In our study of “best of” lists cited by AI, 24.2% of the cited numbered lists with an identifiable publisher ranked that publisher first. Freshness counts too. In our freshness study, the four assistants cited pages first published about half as long ago as Google’s top results for the same questions (a ratio of 0.50), and pages from the last 90 days made up 17.4% to 22.6% of their dated citations against 6.9% of Google’s top 10. Annual gear guides fit that pattern. Community discussion is a smaller factor than people assume for retail: in our Reddit study, 10.3% of retail and ecommerce AI Overviews cited a Reddit thread, and ChatGPT and Claude cited none across 80 buyer questions. Where Google’s AI did cite Reddit, the cited threads had more discussion, a median of 40 comments against 20.

Our inference for outdoor gear. The trust factors are measurable: weight and packed size, waterproof and breathability figures, temperature ratings and the standard used, materials, warranty and repair options, and real-world testing in named conditions. Independent testers and specialty retailers publish those facts in comparable form. A reasonable expectation is that a brand whose specifications match across its own site, retailer listings and test reviews gives an assistant consistent evidence. Our article on “best of” lists and our guide to how brands build authority for AI search cover the mechanics.

What does an outdoor brand risk by staying invisible to AI?

The newcomer’s first kit, and the adjacent activities that follow it.

We found no published figure for outdoor sales lost to AI answers, and we will not estimate one. The risk is structural. The fastest-growing groups, newcomers, older adults and families, need the most guidance. Camping leads into hiking, fishing and paddling. A brand missing from the answer for “what do I need for our first camping trip” loses not one item but a place in that family’s gear closet. Stanley 1913’s fivefold growth in AI-referred orders, a self-reported result, shows what the other side of that risk looks like for one outdoor brand.

How does generative engine optimization work for outdoor brands?

By making each product’s performance in real conditions clear, current and confirmed by the testers and retailers AI reads.

  • Conditions-first product pages. Say what each product is for: terrain, weather, season, trip length. Give weight, packed size, ratings and the test standards behind them in plain text, not only in images. Training apparel faces similar activity questions, covered in how sportswear brands get named by AI.
  • Retailer and feed consistency. Make specialty retailer listings, marketplace pages and product feeds match your specifications, prices and stock, so assistants can name you as the maker with accurate availability.
  • Independent testing. Get gear into expert review programs and keep reviewers informed of updates, so current-year guides include current models.
  • Beginner and kit content. Publish first-trip checklists and “how to choose” guides that answer newcomers’ questions honestly, including when they do not need the premium option.
  • Durability and repair facts. Warranty terms, repair services and resoling are real buying criteria in this category; state them clearly. Boot makers can also use how footwear brands get shoes found in AI answers.
  • Visibility tracking. Check which products are named for which trips and conditions across ChatGPT, Google AI Mode, AI Overviews, Gemini and Perplexity, repeated over time.

No one can guarantee that an assistant will recommend a product. What a brand controls is whether accurate, current, verifiable facts exist where assistants look.

What is still unknown about AI and outdoor gear sales?

How many outdoor purchases start with AI, and how assistants weigh expert tests against retailer data.

The participation and economic data here are strong; the AI-specific data are thin. We found no outdoor-only study of AI-referred sales, no published share of outdoor shoppers using AI for gear, and no platform documentation on how outdoor gear in particular is ranked. Stanley 1913’s result is a merchant story reported by Shopify. Our studies cover many industries, not outdoor gear alone. The BEA’s most recent detailed release covers 2023. Use it to choose where to start, not as proof of payback.

Where should an outdoor brand start?

With an audit of the trip and conditions questions that lead to your hero products and first-trip kit lists.

Choose the products that anchor your range, a shell, a tent, a boot, a pack, and write down the trip and conditions questions their buyers would ask. Then check what ChatGPT, Google’s AI features, Gemini and Perplexity say, run several times: which products are named, whether specifications are right, which reviewers and retailers are cited, and where the shopper is sent to buy. If you would like us to run that check, contact our team: we will map where your gear appears and where it is missing, and the work most likely to earn more places on the shortlists that turn into first kits and repeat customers. From conditions-first product pages to consistent specifications at every retailer that sells your gear, our generative engine optimization service page covers how that work is carried out.

Frequently asked questions

Do expert gear reviews still matter if shoppers use AI?

Yes. OpenAI says ChatGPT uses third-party content and public reviews, and outdoor buyers still verify before buying. Expert tests give assistants comparable facts to work from.

Should we publish our own “best of” gear lists?

You can, but be honest. In our study, about a quarter of AI-cited numbered lists with an identifiable publisher ranked that publisher first; shoppers and platforms may discount lists that look self-serving.

Will AI send gear shoppers to REI instead of our own store?

Sometimes. ChatGPT ranks merchants on availability, price, quality and whether the seller is the maker. Accurate stock and price data on your own store helps, and retailer sales still count.

How should we handle safety-critical gear in AI answers?

State certifications, ratings and intended use precisely, and never imply that a product makes a hazardous activity safe. Accurate, limited claims are less likely to be repeated wrongly.

How quickly do new models show up in AI answers?

It varies. Assistants tended to cite recently published pages in our freshness study, but new products still need reviews and listings to exist before an answer can name them.

Sources

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