How AI Search Is Recommending Outdoor Retail and Gear Marketplaces: Monthly Trends

Executive Summary

REI remains the clear leader in AI-driven recommendations in the Outdoor Retail and Gear Marketplaces category, holding its position with 32.8% valid recommendation coverage in September 2026, a slight rise from 32.4% in August 2026. REI has led the category in both tracked months, and September's result extends that pattern rather than changing it. The gap to second-place Bass Pro Shops stands at 11.8 points (32.8% vs. 21.0%), wider than the 10.4-point gap in August.

September 2026 was a quiet month for the category. Every tracked brand is classified as stable, and no brand's movement in valid recommendation coverage was large enough to register as a notable riser or decliner. The largest point movement was Scheels, which fell 3.4 points to 11.6% from 15.0% in August. Cabela's also declined, down 2.6 points to 16.1% from 18.7%, while Public Lands recorded the largest upward move, rising 1.6 points to 5.8% from 4.2%.

The overall structure of the category is unchanged from August to September, with the same top three brands — REI, Bass Pro Shops, and Cabela's — holding their relative order. The point gap between Scheels and Public Lands narrowed from 10.8 points in August to 5.8 points in September, driven mainly by Scheels' decline rather than a large gain from Public Lands.

Each monthly run begins with 800 prompt-surface observations (682 unique questions in August, 647 in September) across the benchmark's defined AI/search surface universe. Of those, all 800 in each month mentioned a tracked brand or competitor; 730 were relevant and 70 were irrelevant in August, while 740 were relevant and 60 were irrelevant in September. The public metrics use the 519 eligible observations in August and 534 in September that survive both qualification stages.

Key Findings

Benchmark Context

The report separates the raw collection universe from the qualified analysis set. Brand-level recommendation percentages are calculated within the qualified benchmark set.

The following core metrics summarize category-wide behavior across the two tracked months, independent of any single brand's performance.

Benchmark-Level Metrics

The movement between the two funnel stages tells a nuanced story. Even though the recommendation-shaped answer share rose, the valid recommendation shortlist share fell, meaning fewer of the qualified observations yielded a recommendation the benchmark could credit to a specific brand. This is worth watching in October 2026.

AI Recommendation Trend

REI Leads a Stable Category With a Widening Gap Behind It

The category structure is unchanged from August to September 2026. REI leads with 32.8% valid recommendation coverage, and the ranking of the top three is intact, though the gap between REI and second-place Bass Pro Shops has widened to 11.8 points.

Note: Sierra and Academy Sports + Outdoors are both at 10.7% in September 2026. Sierra is ranked 7th on the strength of its upward movement; Academy Sports + Outdoors is 6th based on the August starting position. No brand in September 2026 moved enough in valid recommendation coverage to be classified outside normal month-to-month variation.

What Changed This Month

REI: Leadership Stable, Presence Growing Faster Than Recommendations

REI's valid recommendation coverage was essentially flat, rising from 32.4% in August to 32.8% in September, with 175 valid recommendations out of 534 observations. The largest movement recorded for the brand this month was in raw mention presence, which rose 6.4 points, from 81.1% in August to 87.5% in September — though this did not change REI's recommendation-coverage rank or the category's overall stable classification.

REI's top-three rate was essentially unchanged at 21.9% (down 0.1 points), and its rank-one rate rose slightly to 16.9% from 16.6%, representing 90 rank-one placements in September. Its net sentiment framing rose to 50.3% from 47.5%.

REI is gaining ground in raw presence across AI surfaces, but its share of valid recommendations is holding steady — the brand is becoming more ubiquitous in AI answers without yet converting that presence into a higher proportion of actual recommendations.

Highest-priority diagnostic: Which prompt categories are driving REI's increase in mentions without a corresponding rise in recommendation coverage?

Scheels: The Sharpest Decline, From Fourth Toward the Lower Tier

Scheels fell 3.4 points in valid recommendation coverage, from 15.0% in August to 11.6% in September, the largest movement in the category. This moved it from fourth place in August to fifth place in September, now behind Backcountry.

The decline was broad-based. Raw mention presence fell 4.7 points to 44.4% from 49.1%, and its valid recommendation count dropped to 62 from 78. Notably, its top-three rate actually improved to 7.3% from 6.2%, and its rank-one rate rose to 3.2% from 2.5%, meaning when Scheels was recommended, it was placed higher.

Scheels lost ground in overall recommendation coverage while improving its placement quality — its challenge is breadth of recommendation, not ranking strength.

Highest-priority diagnostic: Which specific prompts or product categories drove the decline in Scheels' recommendation count, and which competitor captured those slots?

Cabela's: Slipping in Coverage While Holding Top-Three Position

Cabela's declined 2.6 points in valid recommendation coverage, from 18.7% in August to 16.1% in September. Its valid recommendation count fell to 86 from 97. Despite this, its top-three rate was essentially unchanged at 9.0% (up 0.1 points), and its rank-one rate rose slightly to 0.9% from 0.8%.

Unlike Scheels, Cabela's decline was concentrated in its raw presence, which fell 3.8 points to 66.5% from 70.3%. When Cabela's did appear and was recommended, its position quality held steady.

Cabela's relative position in the category is stable at third, but its point gap to REI has widened to 16.7 points (32.8% vs. 16.1%), from 13.7 points in August — the brand is failing to keep pace with the leader rather than losing share to a direct rival.

Highest-priority diagnostic: Which surfaces or prompt types account for the decline in Cabela's raw presence, and what is driving the divergence from Bass Pro Shops' stability?

Public Lands: Small-Count Gain Worth Watching

Public Lands was the largest upward mover on a percentage-point basis, rising 1.6 points from 4.2% to 5.8%. This gain came from 31 valid recommendations out of 534 observations in September, up from 22 out of 519 in August.

Its raw mention presence rose 2.2 points to 15.5%, and its top-three rate improved by 0.5 points to 3.0%. Rank-one placements were unchanged at 0.2%, representing just 1 observation in each month.

Public Lands' gains are real but based on only 22-to-31 valid recommendations — meaningful for a brand at this level but not yet a signal of broader change.

Highest-priority diagnostic: Which specific prompts drove the additional valid recommendations, and are they concentrated in a particular product category or surface?

Buyer-Intent Interpretation

The benchmark classifies each qualified observation into one of three buyer-intent clusters to help distinguish what kind of question AI systems are actually answering.

In September 2026, all 534 qualified observations fell into the Brand Recommendation cluster. The benchmark universe did not contain qualified observations that mapped to Pricing & Value or Multi-Brand Comparison intent. As a result, the public benchmark can currently speak to which retailers AI systems recommend for outdoor gear, but it cannot answer commercial questions about price positioning, value perception, or direct head-to-head comparison between brands. Those questions require a deeper, prompt-level read of the underlying data.

Brand Opportunity Summary

The benchmark identifies where attention is warranted; a company-level analysis is needed to explain why.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations (query, surface, recommendation outcome, rank, sentiment, and citations where exposed). Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns. Source presence is not automatically treated as proof of causation.

About This Benchmark

This report is part of the LLM Authority Index AI Market Discovery research program.

• AI Industry Market Discovery Benchmark
• AI Industry Market Discovery Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Movement between months is directional analysis. It identifies changes worth investigating, but does not by itself establish the cause of those changes.
• Several brands in this category (Public Lands, evo, CampSaver) have low valid recommendation counts. Their coverage rates are more sensitive to small absolute changes and should be read with that caveat in mind.
• The qualified denominator (534 observations in September) differs from the raw collection universe (800 prompts). All brand-level percentages are calculated within the qualified set only.

Next Step

The Public Benchmark Shows Where a Brand Is Winning or Losing. A Company-Level Audit Shows Why.

The aggregate percentages in this report raise questions that the benchmark alone cannot answer. Which high-intent prompts is a brand winning, and which is it losing? When a competitor takes the recommendation, which one is it and what attributes does the AI cite? What external sources are shaping those answers, and are they consistent across ChatGPT, Gemini, Copilot, Perplexity, AI Overviews, and AI Mode?

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It turns the benchmark's directional signals into specific, actionable intelligence for a single brand.

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