How AI Search Is Recommending Crypto Exchanges: Monthly Trends

Executive Summary

Kraken reasserts its category leadership in September 2026 after a sharp one-month disruption, rising to 63.9% valid recommendation coverage from 17.6% in August, a gain of 46.3 points. Kraken leads the next closest brand, Crypto.com, by 15.7 points (63.9% versus 48.2%). This reverses the August contraction and returns the category to the pattern established in May and July, when Kraken held the top position with 41.2% and 72.4% coverage respectively.

Six of the nine tracked brands recorded significant gains from August to September, led by Kraken's 46.3-point rise. Binance climbed 32.5 points (15.6% to 48.1%), Crypto.com rose 34.2 points (14.0% to 48.2%), and Gemini added 29.8 points (12.8% to 42.6%). The recovery lifted every brand that had been tracked consistently since May back toward coverage levels closer to their July peaks than their August troughs.

The August contraction now appears as a single-month interruption rather than a trend reversal. Across the full baseline-to-current window, every actively tracked brand shows significant gains from May to September: Kraken up 22.7 points, Crypto.com up 24.2 points, Gemini up 21.0 points, Binance up 18.9 points, Uphold up 13.2 points, and Uniswap up 7.6 points. PayPal, Robinhood, and Pionex.US remain absent from the September qualified set, classified as significant decliners over the full window.

The September 2026 measurement began with 800 prompt-surface observations (557 unique questions) across the benchmark's defined AI/search surface universe. Of those, 800 mentioned a tracked brand or competitor; 751 were relevant and 49 were irrelevant. The public metrics use the 676 qualified observations that survive both qualification stages. The May 2026 baseline recorded 1,591 qualified observations without a prompt funnel; July 2026 began with 800 prompts (703 qualified) and August 2026 began with 800 prompts (681 qualified).

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.

July 2026 collection began with 800 prompts, 703 of which qualified, and August 2026 with 800 prompts, 681 of which qualified. The May 2026 measurement did not record a prompt funnel, so only the 1,591 qualified observations are available for that month.

Benchmark-Level Metrics

August 2026 formed the low point of the series for most brands, with recommendation-shaped answer share at 10.0% and valid recommendation shortlist share at 17.6%. The September figures represent a recovery above the May baseline, though qualified observations remain lower than the May collection of 1,591.

AI Recommendation Trend

Leader Solidifies After One-Month Disruption; Field Returns to Broad Coverage

The September recovery exceeded normal month-to-month variation for every brand still tracked since May. Category-level change reflects the combination of six individually significant rises rather than a single brand's movement; the data describes the distribution across brands, not the mechanism behind it.

What Changed This Month

Kraken

Kraken's valid recommendation coverage rose from 17.6% in August to 63.9% in September, up 46.3 points in a single month. Across the baseline-to-current window, coverage rose from 41.2% in May to 63.9% in September, up 22.7 points.

The recovery reached placement depth. Kraken's recommended top-three rate rose from 30.9% in May to 47.0% in September, up 16.1 points, and its rank-one rate rose from 15.0% to 20.0%, up 5.0 points. Raw mention presence climbed from 48.3% to 97.8%, up 49.5 points. In absolute terms, Kraken earned 432 valid recommendations in September out of 676 observations, compared with 120 out of 681 in August.

The distinction to notice: Kraken is not merely present again, it is recommended at the top of answers. The brand's 20.0% rank-one rate in September exceeds the May baseline of 15.0%.

Highest-priority diagnostic: Which surfaces that went quiet for Kraken in August resumed producing recommendations in September, and did the recovery come from the same prompt clusters that drove the July peak?

Crypto.com, Binance, and Gemini

These three brands recorded the strongest baseline-to-current gains among the risers. Crypto.com rose from 24.0% in May to 48.2% in September (up 24.2 points), Binance from 29.2% to 48.1% (up 18.9 points), and Gemini from 21.6% to 42.6% (up 21.0 points). Each also rose sharply from August: Crypto.com up 34.2 points, Binance up 32.5 points, Gemini up 29.8 points.

Crypto.com held 326 valid recommendations in September (676 observations) versus 95 in August (681). Binance held 325 versus 106, and Gemini held 288 versus 87. Top-three rates rose for all three: Crypto.com from 6.9% to 9.6%, Binance from 17.0% to 23.8%, Gemini from 5.5% to 14.3%.

The distinction: Binance holds the strongest top-three rate of the three at 23.8%, yet Crypto.com leads the group on headline coverage at 48.2%. The two brands now sit nearly level on overall coverage, within 0.1 points, but differ in placement depth.

Highest-priority diagnostic: Which prompt clusters return Binance to top-three placement more often than Crypto.com, and which evidence sources support Gemini's 14.3% top-three rate?

Uniswap and Uphold

Uniswap rose from 3.9% in May to 11.5% in September (up 7.6 points), and from 4.7% in August to 11.5% (up 6.8 points). Uphold rose from 5.1% to 18.3% (up 13.2 points) across the baseline window, and from 6.6% to 18.3% (up 11.7 points) from August.

Uniswap held 78 valid recommendations in September versus 32 in August. Uphold held 124 versus 45. Raw mention presence rose for both: Uniswap from 6.8% to 22.6% (up 15.8 points), Uphold from 6.3% to 26.0% (up 19.7 points). Neither reaches meaningful rank-one placement, with Uphold at 0.4% and Uniswap at 0.1%.

The distinction: these brands remain recommendation-visible without winning top placement. Their coverage gains reflect broader inclusion in AI answers rather than leadership in any prompt cluster.

Highest-priority diagnostic: Which comparison or consideration prompts include Uniswap and Uphold in the recommended set but not at rank one?

PayPal, Robinhood, and Pionex.US

PayPal and Robinhood were tracked in May but no longer appear in the September company list. PayPal's coverage fell from 1.2% to 0.0% and Robinhood's from 19.6% to 0.0% across the baseline-to-current window. Pionex.US fell from 0.7% to 0.0%, and from 1.3% in July to 0.0%.

Pionex.US had 0 valid recommendations in September, matching August, after holding 11 in May and 9 in July. Robinhood held 312 valid recommendations in May; the September data shows no presence, consistent with August.

The distinction: PayPal, Robinhood, and Pionex.US are absent rather than merely low-ranked. A brand can be present without being recommended; these were not present at all in the September qualified set. Based on the recorded monthly series, the absence extends across three consecutive months for Robinhood (July through September) and two consecutive months for Pionex.US (August through September).

Highest-priority diagnostic: For Robinhood, which prompt clusters and surfaces have now failed to surface the brand for three consecutive months, and is this a coverage gap or a genuine withdrawal from AI-visible sources?

Buyer-Intent Interpretation

In May 2026, the qualified observations split across three clusters: 1,069 in brand recommendation, 98 in pricing and value, and 424 in multi-brand comparison. In July, August, and September, all qualified observations fell into the brand recommendation cluster, with the pricing and comparison clusters empty.

The public benchmark therefore cannot currently answer questions about fee-based recommendations or head-to-head comparison outcomes for this category. The evidence base is concentrated entirely on direct brand recommendation prompts. The September recovery lifted recommendation-shaped answers to 30.3% of observations from 10.0% in August, but the pricing and comparison clusters remain unmeasured.

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 CiteWorks Studio AI Market Discovery research program.

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

Report-Specific Interpretation Notes

• Small-count movements: Pionex.US moved from 11 valid recommendations in May to 0 in September; these absolute counts should anchor any reading of the percentage movement.
• Qualified denominator vs. raw collection: September's 676 qualified observations come from 800 collected prompts across 6 AI surface families; May's 1,591 qualified observations had no prompt funnel recorded.
• Directional analysis: Month-over-month movement identifies changes worth investigating; it does not by itself establish the cause of those changes. The August contraction and September recovery describe output distribution, not the mechanism behind either shift.

Next Step

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

The aggregate percentages hide the questions that matter commercially: which high-intent prompts are being won, which competitor takes the recommendation when a brand loses, what attributes AI systems associate with each option, and which external sources shape those answers. The September recovery could reflect a handful of prompt clusters, a specific surface, or a change in which evidence sources appear most often in AI answers.

A company-specific AI visibility audit maps those prompt, surface, competitor, ranking, sentiment, and evidence-source patterns into a prioritized visibility strategy. It answers why a brand gained 46.3 points in a single month, or why others recorded no measurable presence at all.

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