How AI Search Is Recommending Folding and Compact Electric Bikes: Monthly Trends

Executive Summary

Lectric eBikes remains the clear leader in AI search recommendations for the folding and compact electric bikes category. In September 2026, its valid recommendation coverage stood at 77.9%, down slightly from 78.6% in July 2026 but up 1.2 points from August 2026. The gap to the next brand widened, with Aventon at 67.5% in September, down from 71.6% in July.

GOTRAX was the standout riser this month, extending a two-month upward streak. Its coverage reached 13.2% in September 2026, up from 6.9% in July, driven by gains across presence and recommendation placement. The benchmark classified this as a significant rise.

The sharpest decliners were Rad Power Bikes and Blix. Rad Power Bikes fell to 18.5% coverage in September from 35.8% in July, a significant decline now spanning two consecutive months. Blix, at 0.7%, also recorded a significant decline from its 2.2% baseline, with only 5 valid recommendations in the current month.

The category is in a mixed state. While two brands recorded significant declines, GOTRAX's rise and several stable high performers mean the overall picture is one of uneven movement across brands rather than a single uniform trend.

This monthly benchmark begins with 800 prompt-surface observations per period across the tracked AI/search surface universe. Unique questions within that pool were 486 in July 2026, 550 in August 2026, and 556 in September 2026. All 800 observations in each period mentioned a tracked brand or competitor. Of those, 792 were relevant and 8 were irrelevant in July, while 790 were relevant and 10 were irrelevant in both August and September. The public metrics use the qualified observations that survive both qualification stages: 726 in July, 704 in August, and 719 in September.

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.

These figures set the denominator for every brand-level percentage that follows. All coverage, presence, top-three, and rank-one rates below apply the qualified count for each period — 726 in July 2026 and 719 in September 2026 — rather than the larger raw collection total.

Benchmark-Level Metrics

The August 2026 run saw the smallest observation count of the series at 704, and also registered a notable dip in recommendation-shaped answer share, at 44.2%. The September reading of 46.3% represents a partial recovery from that intermediate month.

AI Recommendation Trend

The leadership position is stable, but the middle of the category is shifting as GOTRAX narrows the gap to Rad Power Bikes.

The category-level movement came from a combination of several smaller shifts alongside two outsized ones. The declines for Rad Power Bikes and Blix exceeded normal month-to-month variation, while GOTRAX's rise did as well. The leaders, Lectric eBikes and Aventon, moved within expected ranges.

What Changed This Month

GOTRAX: Significant Riser

GOTRAX's valid recommendation coverage rose to 13.2% in September 2026, up 6.3 points from the 6.9% recorded in July 2026. This extends a two-month upward streak, with the largest single-month gain of 5.2 points happening between July and August. The rise is accompanied by a gain in presence: raw mention presence reached 21.6% in September, climbing from 12.5% in July.

Placement quality also improved. GOTRAX's top-three rate reached 5.6% in September, up from 3.0% in July. Its rank-one rate reached 1.8%, up from 0.1%, representing 13 rank-one mentions in the current month's 719 qualified observations.

The distinction to notice is between visibility and recommendation credit. GOTRAX's raw mention presence (21.6%) remains well above its valid recommendation coverage (13.2%), meaning it is appearing in answers without always being put forward as the choice. Net sentiment held roughly steady, at 0.6 in both July and September.

Highest-priority diagnostic: Which specific prompts and product categories are driving GOTRAX's recommendation gains, and which high-intent queries still surface the brand without a recommendation?

Rad Power Bikes: Significant Decliner

Rad Power Bikes saw valid recommendation coverage fall to 18.5% in September 2026, down 17.3 points from 35.8% in July 2026. The decline was also significant in the immediate prior period, down 5.9 points from August, marking two consecutive months of significant decline. The largest single-month drop was 11.4 points.

The decline is broad-based. Raw mention presence fell to 35.7% in September, down from 47.5% in July. The top-three rate dropped to 7.5% from 13.5%. Notably, the rank-one rate stayed flat at 1.4%, suggesting the brand retains a foothold for first-place recommendations even as its broader presence shrinks.

The gap between GOTRAX and Rad Power Bikes narrowed from -28.9 points in July to -5.3 points in September, narrowing in every month covered by this series. The gap between Heybike and Rad Power Bikes also narrowed, from -28.9 to -9.0 points over the same period. At the same time, the gap between Rad Power Bikes and Velotric widened, from -26.6 to -46.7 points.

Highest-priority diagnostic: Which prompt surfaces and question types are no longer surfacing Rad Power Bikes, and where is the brand losing recommendation placement to GOTRAX and Heybike?

Blix: Significant Decliner

Blix's valid recommendation coverage fell to 0.7% in September 2026, down 1.5 points from 2.2% in July 2026. This is a significant decline on a small base, with only 5 valid recommendations from 719 qualified observations in September, compared with 16 valid recommendations from 726 observations in July.

Presence declined in parallel. Raw mention presence was 1.5% in September, down from 2.5% in July, though this change was not flagged as significant on its own. Rank-one recommendations fell to zero in September, from 1 in July. Net sentiment also softened, from 1.0 in July to 0.7 in September.

With only 5 valid recommendations in the current month, single-observation changes translate into noticeable percentage swings, and this reading should be interpreted as a narrowing footprint rather than a categorical verdict.

Highest-priority diagnostic: Which remaining prompts still surface Blix, and which competitor is taking the recommendation in the folding and compact electric bike queries where Blix used to appear?

Velotric: Notable Prior-Month Riser

While not flagged as a significant riser across the full baseline-to-current series, Velotric posted the sharpest single prior-month gain in September 2026. Coverage rose to 65.2%, up 5.1 points from 60.1% in August, a move that exceeded the significance threshold for that period.

Raw mention presence reached 80.7% in September, up from 72.6% in July. The top-three rate rose to 28.0% from 24.4% over the same span, though this change was not flagged as significant. Rank-one rate eased to 3.1% in September from 4.0% in July.

Velotric's presence and coverage are converging on the top tier, but its rank-one rate remains below peers at its coverage level. It is frequently recommended, yet less often as the single first-choice answer.

Highest-priority diagnostic: Which prompt categories drove the September jump, and where is Velotric appearing in top-three positions without converting to rank-one recommendations?

Buyer-Intent Interpretation

In September 2026, all 719 qualified observations fell into the Brand Recommendation cluster. The benchmark run did not capture qualifying observations for the Pricing & Value or Multi-Brand Comparison clusters, which means the public metrics cannot yet answer questions about which brands win on price-related prompts or direct comparison prompts. The commercial question of who leads on value or head-to-head matchups remains open and would require a company-level analysis to resolve.

Brand Opportunity Summary

The benchmark identifies where attention is warranted across these ten brands; a company-level analysis is needed to explain why these patterns are occurring.

Evidence Behind the Benchmark

The aggregate metrics are built from prompt-level observations capturing the query, the AI surface used, the recommendation outcome, the rank of the brand mentioned, 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 Methodology
• AI Industry Market Discovery Metrics
• AI Industry Market Discovery Standards

Report-Specific Interpretation Notes

• Coverage rates in this report are calculated against the qualified observation set (719 in September 2026), not the larger raw collection universe of 800 prompt-surface observations.
• Movement between months identifies changes worth investigating; it does not by itself establish the cause of those changes.
• The baseline-to-current comparisons reference July 2026 as the starting point for this three-month series.
• Small counts for brands like Blix, with 5 valid recommendations in September, mean that percentage movement can be amplified by a single observation.
• This is directional AI market-discovery analysis intended to guide further investigation, not a definitive category ranking or estimate of overall market share.

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 only a deeper analysis can answer: which high-intent prompts is each brand winning, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources are shaping those answers.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. Where the public benchmark identifies movement, the audit identifies the underlying drivers and the actions that could shift them.

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