How AI Search Is Recommending Outdoor Apparel and Technical Outfits: Monthly Trends

Executive Summary

Patagonia extended its lead in AI search recommendations for October 2026, and it did so with the largest single-month gain in the tracked field. The benchmark shows Patagonia's valid recommendation coverage at 86.2% in October 2026, up 5.4 points from 80.8% in August 2026, a move large enough to register as significant against the baseline. The gap to the next closest brand, Arc'teryx at 78.3%, stands at 7.9 points.

The strongest upward mover with a full series is REI. REI's valid recommendation coverage reached 67.7% in October 2026, up 5.3 points from 62.4% in September 2026 and up 67.7 points from its August 2026 baseline reading of 0.0%. That baseline reflects the month in which the brand was tracked as REI Co-op, not a market collapse. REI placed on 450 valid recommendation shortlists in October 2026, earned a top-three position in 25.0% of observations, and was recommended first in 2.1%.

The sharpest movement in the series belongs to the same entity under its prior identifier. REI Co-op recorded 67.1% valid recommendation coverage in August 2026 and 0.0% in September 2026 and October 2026, a down 67.1 point swing against baseline. This is a tracking identification transition, not a coverage collapse: the brand is measured as REI from September 2026 forward.

Against the prior month, Patagonia rose 10.8 points, Outdoor Research rose 9.3 points, Arc'teryx rose 8.6 points, and REI rose 5.3 points, each a significant month-over-month move. Marmot rose 5.2 points. The category was not stable this month: the leadership position extended, the second tier climbed with it, and the benchmark recorded mixed but broadly upward repositioning across the qualified set.

Each monthly run begins with 800 prompt-surface observations (623 unique questions in October 2026; 634 in August 2026) across the benchmark's defined AI/search surface universe. All 800 observations in both months mentioned a tracked brand or competitor; 775 were relevant and 25 irrelevant in October 2026, versus 789 relevant and 11 irrelevant in August 2026. The public metrics use the 665 qualified observations in October 2026 and 702 qualified observations in August 2026 that survive both qualification stages.

Key Findings

AI Response Inconsistency Alerts

Questions This Section Answers

• What pricing conflict did AI platforms surface for the Arc'teryx Beta SL jacket?
• Which AI surfaces disagreed, and how large was the price gap between them?

The benchmark detected one critical or high-severity factual inconsistency this month, spanning two AI platforms.

Arc'teryx

High severity, pricing topic. AI platforms provided conflicting information about the price of the Arc'teryx Beta SL jacket. When asked "What are some of the best waterproof jackets?", Google AI Mode stated that the Arc'teryx Beta SL / Beta Jacket costs $400 to $500, while Copilot stated that the Arc'teryx Beta SL Men Jacket costs $790.00. The same jacket cannot plausibly occupy both price ranges. Google AI Mode's response cited a YouTube rain-jacket review, an Edinburgh Bicycle Cooperative cycling-jacket blog, and a Better Trail best-rain-jackets roundup. Copilot's response cited a Backcountry listing for the Patagonia Torrentshell 3L jacket, an REI Co-op Rainier rain jacket product page, and an Editorialist product page for the Arc'teryx Beta SL jacket. Two sources were flagged with high confidence on the Google AI Mode side: a Better Trail rain-jacket roundup citing "Best Weather Protection Arc'teryx Beta SL ($500)" and an OutdoorGearLab best-rain-jacket page citing "Men's Premium Pick Arc'teryx Beta SL $500 List." The divergence in stated price between platforms, on a single high-intent waterproof-jacket question, is the kind of factual split that can distort how a product's value positioning is read by a shopper comparing options.

Benchmark Context

Questions This Section Answers

• How many observations qualified for the public benchmark in October 2026 compared with August 2026?
• Which research stages separate the raw collection universe from the qualified analysis set?
• How much did recommendation-shaped answer share and valid recommendation shortlist share change against the August baseline?

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

The qualified set represents a consistent share of the raw collection across both months, so the brand-level movements below reflect the same measurement funnel in each period. September 2026 sat between these two months with 696 qualified observations.

Benchmark-Level Metrics

The intermediate September 2026 reading is worth noting: recommendation-shaped answer share was 46.8% and valid recommendation shortlist share was 77.3% that month, meaning October 2026 reversed a September softening in both measures and moved above the August baseline.

AI Recommendation Trend

Questions This Section Answers

• How far does Patagonia lead the second-place brand in valid recommendation coverage?
• Which brands exceeded normal month-to-month variation against the baseline or prior month?
• Why does REI's 67.7 point gain against baseline not represent a market movement?

Patagonia Extended Its Lead While the Second Tier Closed Ranks Behind It

The October 2026 benchmark shows a clear separation between the recommendation leaders and the middle of the field, with Patagonia widening its coverage advantage and Arc'teryx, Outdoor Research, REI, and The North Face consolidating beneath it. The bottom of the table stayed compressed, with KÜHL, Marmot, Black Diamond, and Mountain Hardwear all below 35% coverage.

Patagonia and REI both exceeded normal month-to-month variation against the baseline, and Patagonia, Outdoor Research, and REI each exceeded it against the prior month. The REI series reflects a change in how the brand is identified from September 2026 onward, so its baseline movement is a tracking transition rather than a market gain. Outside those entries, the category-level change came from a combination of several smaller movements rather than one dominant shift.

What Changed This Month

Patagonia

Patagonia's valid recommendation coverage rose 5.4 points from 80.8% in August 2026 to 86.2% in October 2026, a significant move against the baseline. The prior-to-current step was sharper still: up 10.8 points from 75.4% in September 2026 to 86.2% in October 2026, the largest single-month move in the brand's series.

Placement matched the coverage gain. The top-three recommendation rate reached 75.5% in October 2026, up 9.5 points from 66.0% in August 2026, and the rank-one rate reached 53.8%, up 5.9 points from 47.9%. Patagonia placed on 573 valid recommendation shortlists with 502 top-three placements and 358 rank-one placements.

The distinction to notice is that Patagonia's lead is now compounding across coverage and placement at once. Raw mention presence was 97.9% in October 2026, up 1.0 point from 96.9% in August 2026, so the brand was already near-universally visible before the recommendation gains. The movement is in recommendation credit, not presence.

Highest-priority diagnostic: Which prompt categories are converting Patagonia's near-universal presence into additional top-three and rank-one placements?

REI and the REI Co-op Tracking Transition

REI's valid recommendation coverage was 67.7% in October 2026, up 67.7 points from a 0.0% August 2026 baseline and up 5.3 points from 62.4% in September 2026. The baseline figure belongs to the August 2026 reading under the identifier REI Co-op, which recorded 67.1% that month. The benchmark treats these as separate series entries; the swing is a function of the identification transition, not a market movement.

Under the REI identifier, the brand placed on 450 valid recommendation shortlists in October 2026, with a 25.0% top-three rate (166 placements) and a 2.1% rank-one rate (14 placements). Raw mention presence was 82.9%.

The reader should treat REI and REI Co-op as the same commercial entity across the series, sitting in third position at 67.7% coverage in October 2026. The distinction between the two rows is measurement continuity, not competitive standing.

Highest-priority diagnostic: Whether the gap between the August 2026 and October 2026 readings under consistent identification reflects genuine coverage change requires company-level inspection.

Outdoor Research

Outdoor Research rose 3.3 points from 60.3% valid recommendation coverage in August 2026 to 63.6% in October 2026, within normal baseline variation. The prior-to-current move was significant: up 9.3 points from 54.3% in September 2026 to 63.6% in October 2026.

Placement improved on the same line. The top-three rate reached 23.9% in October 2026, up 6.1 points from 17.8% in August 2026, a significant baseline move, and the rank-one rate reached 5.9%, up 1.6 points. Outdoor Research placed on 423 valid recommendation shortlists with 159 top-three placements and 39 rank-one placements.

The distinction here is a rebound rather than a steady climb. The series reads 60.3%, 54.3%, 63.6% across August, September, and October 2026, so October recovered the September decline and added to it. Raw mention presence was 72.0% in October 2026, down 0.8 points from 72.8% in August 2026, meaning the coverage gain came without a presence gain.

Highest-priority diagnostic: Which prompts drove the September-to-October recovery in top-three placements while presence held flat?

Arc'teryx

Arc'teryx rose 2.8 points from 75.5% valid recommendation coverage in August 2026 to 78.3% in October 2026, within normal baseline variation. Against the prior month the move was significant: up 8.6 points from 69.7% in September 2026 to 78.3% in October 2026.

Placement held broadly steady against baseline. The top-three rate was 55.5% in October 2026, up 1.1 points from 54.4% in August 2026, and the rank-one rate was 12.8%, unchanged. Arc'teryx placed on 521 valid recommendation shortlists with 369 top-three placements and 85 rank-one placements.

The distinction is that Arc'teryx recovered shortlist coverage without a matching gain in rank-one placement. Raw mention presence was 90.5% in October 2026, down 1.0 point from 91.5% in August 2026, so the brand held second position on stronger shortlist conversion rather than broader visibility.

Highest-priority diagnostic: Which surfaces produced the September-to-October coverage recovery without a corresponding rank-one shift?

Marmot

Marmot's valid recommendation coverage was 27.2% in October 2026, down 1.0 point from 28.2% in August 2026, within normal baseline variation. The prior-to-current move was significant: up 5.2 points from 22.0% in September 2026 to 27.2% in October 2026, recovering most of the September decline.

Placement improved against baseline. The top-three rate reached 5.4% in October 2026, up 2.7 points from 2.7% in August 2026, a significant move, and the rank-one rate reached 0.8%, up 0.5 points. Marmot placed on 181 valid recommendation shortlists with 36 top-three placements and 5 rank-one placements.

The distinction is between a recovering coverage line and a genuinely improved placement signal. The series reads 28.2%, 22.0%, 27.2% across the three months, while the top-three rate moved 2.7%, 3.0%, 5.4%. Raw mention presence was 38.5% in October 2026, down 4.1 points from 42.6% in August 2026, so Marmot is converting a smaller visible base into more prominent placements.

Highest-priority diagnostic: Which prompts are converting Marmot's smaller presence base into additional top-three placements?

The North Face

The North Face held 56.7% valid recommendation coverage in October 2026, up 0.4 points from 56.3% in August 2026, a stable baseline reading. The prior-to-current move was 4.5 points, below the significance threshold.

Placement rose meaningfully even as coverage held flat. The top-three rate reached 24.4% in October 2026, up 9.2 points from 15.2% in August 2026, a significant move, and the rank-one rate reached 3.5%, up 1.6 points. The North Face placed on 377 valid recommendation shortlists with 162 top-three placements and 23 rank-one placements.

The distinction is that coverage and placement diverged. Raw mention presence was 74.3% in October 2026, down 1.1 points from 75.4% in August 2026. The brand is appearing on roughly the same share of shortlists while being placed much higher within them.

Highest-priority diagnostic: Which prompt types are producing higher top-three placement without a change in shortlist coverage?

Mountain Hardwear

Mountain Hardwear's valid recommendation coverage was 34.7% in October 2026, down 1.8 points from 36.5% in August 2026, within normal baseline variation. The prior-to-current move was 3.5 points, below the significance threshold.

Placement was steady. The top-three rate was 9.5% in October 2026, up 1.1 points from 8.4% in August 2026, and the rank-one rate was 1.1%, unchanged. Mountain Hardwear placed on 231 valid recommendation shortlists with 63 top-three placements and 7 rank-one placements.

The distinction is a flat-to-slightly-lower coverage line against a modestly improving placement line. Raw mention presence was 44.5% in October 2026, down 4.1 points from 48.6% in August 2026. A smaller visible base produced a similar number of top-three placements, which points to conversion rather than reach.

Highest-priority diagnostic: Which prompts are producing steady top-three placements from a narrower presence base?

Columbia Sportswear

Columbia Sportswear held 46.9% valid recommendation coverage in October 2026, up 0.5 points from 46.4% in August 2026, a stable baseline reading. The prior-to-current move was 4.2 points, below the significance threshold.

Placement moved slightly. The top-three rate was 12.5% in October 2026, up 0.5 points from 12.0% in August 2026, and the rank-one rate reached 1.4%, up 0.8 points. Columbia Sportswear placed on 312 valid recommendation shortlists with 83 top-three placements and 9 rank-one placements.

The distinction is that presence declined while coverage held. Raw mention presence was 62.1% in October 2026, down 3.3 points from 65.4% in August 2026, so the same shortlist coverage was earned from fewer mentions.

Highest-priority diagnostic: Which prompts are sustaining shortlist coverage as raw mention presence narrows?

Black Diamond

Black Diamond's valid recommendation coverage was 27.7% in October 2026, up 1.2 points from 26.5% in August 2026, a stable baseline reading. The prior-to-current move was 3.3 points, below the significance threshold.

Placement against baseline moved in the opposite direction from coverage. The top-three rate was 7.4% in October 2026, down 4.6 points from 12.0% in August 2026, a significant decline, while the rank-one rate was 0.9%, down 0.1 point. Black Diamond placed on 184 valid recommendation shortlists with 49 top-three placements and 6 rank-one placements.

The distinction is a coverage gain paired with a significant placement loss. Raw mention presence was 33.4% in October 2026, up 0.9 point from 32.5% in August 2026. The brand is appearing on more shortlists but being placed lower within them.

Highest-priority diagnostic: Which high-intent prompts moved Black Diamond from top-three into lower shortlist positions despite stable presence?

KÜHL

KÜHL's valid recommendation coverage was 18.1% in October 2026, up 2.3 points from 15.8% in August 2026, a stable baseline reading. The prior-to-current move was 3.6 points, below the significance threshold. In absolute terms, KÜHL placed on 120 valid recommendation shortlists in October 2026.

Placement edged up. The top-three rate was 3.2% in October 2026, up 1.5 points from 1.7% in August 2026 (21 top-three placements), and the rank-one rate was 0.1%, unchanged (1 rank-one placement). Raw mention presence was 29.0% in October 2026, up 2.5 points from 26.5% in August 2026.

The distinction is that KÜHL's movement rests on a small absolute base. A 2.3 point coverage gain over 120 shortlist placements is a real signal but a narrow one, and the top-three and rank-one counts are small enough that single placements shift the rates measurably.

Highest-priority diagnostic: Which prompts are adding KÜHL to shortlists, and whether those additions hold across surfaces on a base of 120 valid recommendations?

Buyer-Intent Interpretation

Questions This Section Answers

• Which buyer-intent clusters had qualified observations in October 2026, and which had none?
• What can the benchmark not yet say about AI representation of price positioning and head-to-head brand trade-offs?

In October 2026, the qualified observations fell into the Brand Recommendation cluster. The Pricing & Value and Multi-Brand Comparison clusters registered no qualified observations, meaning the public benchmark cannot yet answer how AI systems represent price positioning, value comparisons, or head-to-head brand trade-offs in this vertical. That gap is commercially material: the inconsistency detected between Google AI Mode and Copilot on the Arc'teryx Beta SL price question sits precisely in the pricing class the qualified set does not yet cover, so the benchmark can flag that a conflict exists without being able to characterize how widespread pricing divergence is across the vertical.

Brand Opportunity Summary

Questions This Section Answers

• What is each brand's highest-priority diagnostic based on its October 2026 coverage signal?
• Where does the benchmark identify attention is warranted across the category, and what does it leave to company-level analysis?

The benchmark identifies where attention is warranted across the category; a company-level analysis is needed to explain why individual brands are gaining or losing recommendation credit.

Evidence Behind the Benchmark

Questions This Section Answers

• What types of prompt-level data build the aggregate metrics?
• Which interpretation notes should readers keep in mind about the REI identifier transition, small-count movements, and conflicting AI claims?

The aggregate metrics are built from prompt-level observations capturing the query, the AI surface used, the recommendation outcome, the rank of each brand mentioned, sentiment, and citations where exposed. Company-level analysis can go deeper into prompt, competitor, surface, and evidence patterns to identify why specific brands appear, are absent, or receive conflicting treatment across AI systems. Source presence in AI answers is not automatically treated as proof of causation or endorsement.

Report-Specific Interpretation Notes

• The REI Co-op to REI transition is a tracking identification change, not a measured market movement; the two series should be read as one brand across the period.
• Small-count movements are meaningful in this vertical: KÜHL's 18.1% coverage rests on 120 valid recommendations in October 2026, and its top-three and rank-one counts are small enough that single placements move the rates.
• The qualified denominator (665 observations in October 2026) differs from the raw collection universe (800 prompts); all percentages are relative to the qualified set.
• Month-over-month movement identifies changes worth investigating; it does not by itself establish cause.
• Conflicting claims across AI platforms on the same product question are a measurement observation about response consistency, not evidence about the product itself.

About This Benchmark

This report is part of the LLM Authority Index AI Visibility Market Discovery research program administered by CiteWorks Studio.

• AI Visibility Industry Market
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Next Step

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

The aggregate percentages in this benchmark identify which brands AI systems recommend, but they do not explain the mechanics behind those recommendations. Beneath Patagonia's 86.2% coverage or KÜHL's 18.1% sit specific questions: which high-intent prompts is each brand winning, which competitor takes the recommendation when a brand loses the slot, what attributes does the AI associate with each option, and which external sources shape those answers. Where AI platforms disagree, as they did on the Arc'teryx Beta SL price question, the underlying evidence trail matters as much as the conflicting claim.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It examines why Patagonia extends its lead across coverage and placement at once, why Black Diamond gained shortlist coverage while losing top-three positions, and what it would take for a mid-pack brand to close the gap.

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