Kaged AI Visibility Market Strategy Report - Sports Nutrition and Protein Supplements

Answer Capsule

Kaged holds a narrow but real recommendation pocket in the sports nutrition and protein supplements category, with valid recommendation coverage of 5.92% in October 2026. The brand is visible but under-recommended relative to category leaders, appearing in 6.36% of qualified observations while converting only 5.92% into valid recommendations. Kaged's clearest win is its high net sentiment score of 0.9318, indicating positive framing when the brand does appear. Its clearest weakness is a rank-one rate of just 0.29%, meaning it is almost never the first recommendation. The clearest opportunity is converting that positive sentiment into higher placement within recommendation shortlists.

Who This Report Is For

This report is for Kaged's marketing, brand, and ecommerce leadership teams, as well as category analysts tracking AI recommendation behavior in the sports nutrition and protein supplements vertical.

Report Card

Executive Summary

Kaged operates in a category where AI recommendation power is heavily concentrated at the top. The benchmark shows Optimum Nutrition and Transparent Labs each holding 75.14% top-three recommendation rates, while Kaged reaches just 2.46%. This is not a visibility problem alone. Kaged appears in 6.36% of qualified observations but converts only 5.92% into valid recommendations, a conversion rate that trails every brand except BSN and Muscle Milk.

The brand's strongest signal is sentiment. Kaged recorded 41 positive mentions against zero negative mentions in October 2026, producing a net sentiment score of 0.9318. Only Transparent Labs (0.9812) and Legion Athletics (0.9640) scored higher. When Kaged appears in AI responses, the framing is overwhelmingly positive.

The weakest signal is placement. Kaged recorded only 2 rank-one recommendations across 692 qualified observations, a rank-one rate of 0.29%. The brand's average recommended rank of 4.00 is the lowest among all tracked brands, meaning that when Kaged does earn a recommendation, it typically sits at the bottom of the shortlist.

The strongest platform signal for Kaged is Perplexity, where the brand achieved 7.87% valid recommendation coverage and a 3.37% top-three rate. Copilot also showed relative strength with 10.84% valid recommendation coverage. The weakest platform signal is Gemini, where Kaged recorded just 3 mentions and 2.35% valid recommendation coverage.

The clearest gap is between presence and recommendation conversion. Kaged is mentioned in qualified observations at nearly the same rate as its valid recommendation coverage, suggesting the brand is being referenced as context rather than actively recommended. The category's top brands convert presence into recommendations at rates exceeding 80%, while Kaged converts at 5.92%.

All 692 qualified observations in October 2026 fell into the Brand Recommendation cluster. The Pricing and Value and Multi-Brand Comparison clusters carry no qualified observations, limiting what can be concluded about how Kaged performs on cost or head-to-head tradeoff queries.

What Kaged Is Winning

Questions This Section Answers

• Why is Kaged's sentiment score considered its strongest AI visibility signal?
• Which platforms show relatively stronger recommendation coverage for Kaged?
• What limits how much these wins can change Kaged's overall position?

Kaged's clearest win is sentiment quality. The brand recorded 41 positive mentions and zero negative mentions, producing a net sentiment score of 0.9318. This places Kaged third in the vertical for sentiment, behind only Transparent Labs and Legion Athletics. The absence of negative framing is a meaningful signal that AI systems do not associate Kaged with cautionary or critical language.

The brand also shows a narrow but measurable recommendation pocket on Perplexity. Kaged achieved 7.87% valid recommendation coverage on that platform, more than double its overall rate. Perplexity's citation-heavy response style may favor brands with clear, retrievable product information.

Kaged's Copilot performance also stands out relative to its baseline. The brand recorded 10.84% valid recommendation coverage on Copilot, with 9 valid recommendations from 83 observations. This suggests that Copilot's synthesis patterns are more receptive to Kaged's public evidence layer than other platforms.

These wins are real but narrow. Kaged does not lead any cluster, does not lead any platform, and does not appear in the top three for any placement metric. The brand's positive sentiment has not yet translated into recommendation volume or placement strength.

Where Kaged Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why does Kaged's presence rate not translate into valid recommendations?
• Which competitors are capturing the recommendations Kaged misses?
• Where is Kaged's placement gap most severe across platforms?

Kaged's most significant gap is recommendation conversion. The brand appears in 6.36% of qualified observations but earns valid recommendations in only 5.92%. This near-parity between presence and recommendation suggests that when AI systems mention Kaged, they are often doing so as a reference point rather than an active recommendation.

The placement gap is more severe. Kaged's top-three recommendation rate of 2.46% means the brand appears in a top-three position in fewer than 3 of every 100 qualified observations. Its rank-one rate of 0.29% means it is the first recommendation in fewer than 1 of every 300 observations. By comparison, Optimum Nutrition achieves a 41.62% rank-one rate and Transparent Labs achieves 36.99%.

The average recommended rank tells a similar story. Kaged's average recommended rank of 4.00 is the lowest among all tracked brands, meaning that when the brand does earn a recommendation, it typically appears fourth in the shortlist. Optimum Nutrition averages 1.79 and Transparent Labs averages 1.89.

Platform-level gaps compound the issue. On Gemini, Kaged recorded only 3 mentions and 2.35% valid recommendation coverage. On ChatGPT, the brand achieved 4.92% valid recommendation coverage with 3 valid recommendations from 61 observations. These are the platforms where Kaged's absence is most pronounced.

The competitive displacement pattern is clear. When Kaged is not recommended, the slot is typically filled by Optimum Nutrition, Transparent Labs, or Dymatize. These three brands hold 75.14%, 75.14%, and 60.12% top-three rates respectively, leaving little room for mid-tier brands to gain placement without displacing an incumbent.

Biggest Opportunity

Questions This Section Answers

• How could Kaged convert its positive sentiment into higher recommendation placement?
• What evidence gaps explain why AI systems mention Kaged without recommending it?

Kaged's biggest opportunity is converting its positive sentiment into higher placement within recommendation shortlists. The brand already earns positive framing when it appears. The gap is that it appears too rarely in top-three positions and almost never in the rank-one position.

The path forward is to strengthen the public evidence layer that AI systems retrieve when forming recommendations. Kaged's high sentiment score suggests that when AI systems find information about the brand, they frame it positively. The issue is that they are not finding enough of that information, or they are finding it in sources that carry less recommendation weight than the sources supporting Optimum Nutrition and Transparent Labs.

The brand's relative strength on Perplexity and Copilot suggests that platforms with different retrieval patterns may be more receptive to Kaged's current source footprint. Understanding what those platforms are retrieving and synthesizing could reveal which source types and page structures are most effective for the brand.

Competitive Landscape

Questions This Section Answers

• Where does Kaged rank against Optimum Nutrition, Transparent Labs, and other tracked brands?
• What do Kaged's top-three and rank-one rates reveal about its shortlist position?

Optimum Nutrition and Transparent Labs hold recommendation-stage strength in the sports nutrition and protein supplements category, each achieving 75.14% top-three rates. Kaged sits in the lower tier of the tracked set, with a 2.46% top-three rate and a 0.29% rank-one rate.

Average recommended rank covers rank-eligible recommendations only.

Kaged's position in the table reflects a brand with strong sentiment but weak placement. The brand's 2.46% top-three rate places it eighth among ten tracked brands, ahead of only BSN and Muscle Milk. Its 0.29% rank-one rate is the second-lowest in the set, ahead of only MuscleTech and BSN, both of which recorded zero rank-one recommendations.

Prompt Evidence

Perplexity / Brand Recommendation Prompt: "Which is the most recommended protein powder?" Result: Kaged appeared in the response but was not placed in a top-three recommendation position, consistent with the brand's low placement rates on this platform despite relatively higher coverage.

Copilot / Brand Recommendation Prompt: "What brand is the best for protein powder?" Result: Kaged received a valid recommendation on Copilot, where the brand's coverage rate of 10.84% exceeds its overall performance, suggesting Copilot's retrieval patterns are more receptive to Kaged's source footprint.

ChatGPT / Brand Recommendation Prompt: "Which protein powder brand is best?" Result: Kaged was mentioned but not recommended in a top-three position, reflecting the brand's 4.92% valid recommendation coverage on ChatGPT and its absence from rank-one placements.

Gemini / Brand Recommendation Prompt: "Which creatine brand is best?" Result: Kaged recorded minimal presence on Gemini, with only 3 mentions across 85 observations on that platform, indicating a significant visibility gap on this surface.

What CiteWorks Studio Would Do Next

Phase 1: AI Visibility Market Discovery Audit Map the specific prompts and platforms where Kaged appears but is not recommended, and identify which competitors are capturing those recommendation slots.

Phase 2: Recommendation Readiness Plan Assess whether Kaged's owned content and product pages contain the structured information AI systems need to form confident recommendations.

Phase 3: Owned Answer Layer Buildout Develop clear, retrievable answer content that addresses the high-intent prompts where Kaged currently appears as context rather than recommendation.

Phase 4: Citation / Authority Layer Development Strengthen the public evidence layer by pursuing citations and references from the source types AI systems retrieve most frequently in this vertical.

Phase 5: Monthly AI Visibility and Recommendation Tracking Monitor Kaged's recommendation coverage, placement rates, and sentiment across all six tracked platforms to measure progress and identify emerging gaps.

Why This Matters

AI presence alone is not enough. Kaged's 6.36% presence rate and 5.92% recommendation coverage suggest the brand is being mentioned in AI responses but not actively recommended. The difference between a mention and a recommendation is the difference between being part of the conversation and being part of the buyer's shortlist.

The next move is targeted correction of the prompt, page, and citation layers. Kaged's positive sentiment indicates that AI systems frame the brand favorably when they find it. The opportunity is to ensure they find it more often, in more authoritative sources, and in formats that support recommendation rather than mere reference.

Core Metrics

Sentiment Score

Questions This Section Answers

• Why does Kaged's zero negative mentions matter more than its raw mention count?
• How is the net sentiment score calculated for Kaged?

Sentiment Score = (positive mentions × 1 + neutral mentions × 0 + negative mentions × -1) / total mentions

For Kaged in October 2026: (41 × 1 + 3 × 0 + 0 × -1) / 44 = 0.9318

This score matters because unclassified mention counts are misleading. A brand with 44 mentions could appear to be performing well, but if those mentions are neutral references rather than positive recommendations, the commercial value is limited. Share of voice is a diagnostic metric, not a business KPI.

A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal. Kaged's 41 positive mentions carry more weight than 41 neutral mentions would. The brand's zero negative mentions is also significant, indicating that AI systems do not associate Kaged with critical or cautionary framing.

Counting all mentions as wins is bad measurement. Classified sentiment is required before interpreting AI visibility. Kaged's high sentiment score suggests that when the brand appears, it appears favorably. The challenge is increasing the frequency and placement of those appearances.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Kaged's AI recommendation visibility in the sports nutrition and protein supplements category. It is not a client implementation case study.
2. The reporting month is October 2026. The benchmark series covers August 2026 through October 2026.
3. Six AI platforms were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. Keyword variants were rolled up into their parent surface families.
4. The October 2026 benchmark produced 692 qualified observations after relevance screening and qualification. The raw collection began with 800 prompt-surface observations.
5. The competitor universe includes ten tracked brands: Optimum Nutrition, Transparent Labs, Dymatize, Isopure, Legion Athletics, MuscleTech, Kaged, BSN, GNC, and Muscle Milk.
6. Three public high-intent clusters were defined: Brand Recommendation (C01), Pricing and Value (C02), and Multi-Brand Comparison (C03). Only C01 carried qualified observations in October 2026.
7. Stage 0 extraction retains the query, AI surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources.
8. A mention is defined as any appearance of the brand name in an AI response, regardless of whether the brand is recommended.
9. A valid recommendation is defined as an appearance in a genuine recommendation shortlist, excluding simple mentions, neutral references, or comparison anchors.
10. Brand-level percentages use the 692 qualified observations as the public denominator, not the raw collection of 800 prompts.
11. Unique question count for October 2026 was 591 after deduplication. The benchmark does not publish a unique prompt count for the public version.
12. Movements between months are directional observations, not attributed outcomes. Source presence is not treated as proof of causation.

See How AI Is Recommending Your Brand

The public benchmark shows where Kaged stands in AI recommendations across the sports nutrition and protein supplements category. An AI visibility audit can map the specific prompts, platforms, and sources shaping those recommendations, and identify where targeted corrections would have the greatest impact.