Kaged AI Market Strategy Report - Sports Nutrition and Protein Supplements

Answer Capsule

Kaged holds a small but real position in AI-generated recommendations for sports nutrition and protein supplements, with a valid recommendation coverage of 5.32% in September 2026. The brand is present in 6.33% of qualified AI observations but converts that presence into a genuine recommendation shortlist only 5.32% of the time, a narrow gap that suggests its mentions are mostly recommendation-shaped rather than incidental. Its clearest win is a positive framing profile, with a net sentiment score of 0.8409 and zero negative mentions across 44 appearances. Its clearest weakness is placement: a top-three rate of 1.87% and a rank-one rate of 0.14% mean Kaged is almost never the first or second option AI systems surface. The clearest opportunity is closing the distance between being named and being shortlisted in the consideration-stage prompts where the category is decided.

Who This Report Is For

This report is written for Kaged's brand, growth, and ecommerce leadership, and for the retail and distribution partners who need to understand where the brand stands when buyers ask AI systems what to buy.

Report Card

Executive Summary

Kaged is visible in AI answers but rarely recommended at the top of them. Across 695 qualified observations in September 2026, the brand appeared in 44, a raw mention presence rate of 6.33%, and earned a valid recommendation in 37 of those, a coverage rate of 5.32%. That is a healthy conversion ratio from mention to recommendation, and it tells a different story than a brand that is widely named but never shortlisted. The problem for Kaged is not credibility. It is scale and placement.

The framing around Kaged is strongly positive. Of its 44 mentions, 37 were positive and 7 were neutral, with zero negative mentions recorded in the month. That produces a net sentiment score of 0.8409, which sits below the category's top two brands but comfortably above the mid-tier. AI systems are not cautioning buyers about Kaged. They are simply not reaching for it often enough, and when they do, they place it deep in the list.

Placement is where the gap becomes commercially meaningful. Kaged's top-three recommendation rate was 1.87% in September 2026, meaning the brand landed in positions one through three in only 13 of 695 qualified observations. Its rank-one rate was 0.14%, a single observation in the entire month. Its average recommended rank was 4.09, the weakest average position of any brand tracked with rank-eligible recommendations. Kaged is being recommended, but it is being recommended fourth.

The month-over-month picture is the most concerning element of this report. Kaged's valid recommendation coverage fell 3.0 points from 8.3% in August 2026 to 5.3% in September 2026, a decline the benchmark classified as significant and beyond normal month-to-month variation. Raw mention presence fell from 9.4% to 6.3%, and the top-three rate fell from 4.2% to 1.9%. Net sentiment also softened from 0.94 to 0.84. This was not a single weak metric. It was a broad-based contraction.

The strongest platform signal for Kaged is Google AI Mode, where the brand recorded a 6.42% valid recommendation coverage rate and a 2.14% top-three rate, the highest of any surface in the dataset. Perplexity also showed a comparatively strong positive visibility rate of 10.34%. The clearest platform gap is Gemini, where Kaged recorded two valid recommendations but no rank-eligible placement and no captured recommendation value, and Copilot, where the brand appeared in five observations without converting any into a top-three position.

The category context matters here. Optimum Nutrition leads with 83.31% valid recommendation coverage and Transparent Labs follows at 81.44%, a gap of just 1.9 points. Dymatize holds third at 71.51%. Below that, the field drops sharply, with Isopure at 23.17% and every remaining brand under 15%. Kaged sits eighth of ten. The distance to the leaders is not a matter of degree. It is a different tier of visibility entirely.

What Kaged Is Winning

Questions This Section Answers

• How does Kaged's sentiment profile compare with other sports nutrition brands?
• Why do Kaged's AI mentions convert into recommendations more efficiently than GNC's?

Kaged's clearest win is framing quality. With 37 positive mentions, 7 neutral mentions, and zero negative mentions, the brand carries a net sentiment score of 0.8409. That is a cleaner profile than MuscleTech at 0.7895, BSN at 0.7818, and Muscle Milk at 0.6562, and it indicates that when AI systems do discuss Kaged, they describe it favorably rather than as a cautionary example or a comparison anchor.

The second win is mention-to-recommendation efficiency. Kaged converted 37 of its 44 mentions into valid recommendations, a ratio of roughly 84%. By contrast, GNC appeared in 131 observations and earned only 16 valid recommendations, a ratio near 12%. Kaged's mentions are recommendation-shaped rather than incidental. The brand is not being named as a passing reference. It is being named because an AI system judged it worth including in a shortlist.

The third win is platform-specific strength on Google AI Mode. Kaged recorded a 6.42% valid recommendation coverage rate and a 2.14% top-three rate on that surface, both above its overall averages. Perplexity showed a 10.34% positive visibility rate, the highest positive visibility figure for Kaged across any platform. These are narrow pockets, but they are real and they indicate where the brand's public evidence layer is already doing useful work.

These wins are modest in absolute terms. Kaged holds 13 top-three placements and a single rank-one placement across the entire month. The brand should not read this section as evidence of strength. It should read it as evidence that the underlying recommendation quality is sound and the constraint is reach.

Where Kaged Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why is Kaged's average recommended rank a bigger problem than its recommendation coverage?
• Which competitor gained the ground Kaged lost between August and September 2026?
• Where did Kaged fail to convert AI appearances into placements on Copilot and Gemini?

The most consequential gap is placement depth. Kaged's average recommended rank of 4.09 is the weakest of any brand in the tracked set with rank-eligible recommendations. Optimum Nutrition averages 1.80, Transparent Labs averages 2.00, Dymatize averages 2.61, and even Muscle Milk, which has far lower coverage, averages 4.74 only because its sample is tiny. Kaged is consistently the fourth name in a list where buyers typically act on the first two or three.

The second gap is the collapse in top-three placement. Kaged's top-three rate fell from 4.2% in August 2026 to 1.9% in September 2026, a 2.3-point decline that the benchmark flagged as significant on its own. This is a more serious signal than the coverage decline, because top-three placement is where recommendation converts into consideration. A brand that is recommended fourth is functionally closer to being absent than to being chosen.

The third gap is the loss of presence. Kaged appeared in 64 of 684 qualified observations in August 2026 and 44 of 695 in September 2026. That is a loss of 20 appearances month over month, against a denominator that grew by 11. The brand did not simply get recommended less often within the same conversations. It disappeared from conversations it had previously been part of. The benchmark's own diagnostic framing points to the right question: which specific product or use-case queries drove the loss of top-three placement, and which brands captured those slots.

The fourth gap is platform inconsistency. Kaged recorded zero captured recommendation value on Copilot and Gemini in September 2026, despite appearing in five and two observations respectively on those surfaces. On ChatGPT, the brand recorded a 3.39% valid recommendation coverage rate and a 687.47 AI Authority Value figure, which is meaningful but small relative to the surface's total opportunity. The brand's presence is concentrated rather than distributed, which makes it fragile to shifts in how any single platform assembles its answers.

The competitive comparison sharpens the picture. Transparent Labs gained 3.3 points of coverage in the same month Kaged lost 3.0. The gap between Kaged and Transparent Labs widened from 69.8 points in August 2026 to 76.1 points in September 2026. The gap between Kaged and MuscleTech, the other significant decliner, narrowed slightly, which means Kaged is now competing for position at the bottom of the mid-tier rather than closing on the leaders.

Biggest Opportunity

Questions This Section Answers

• Which protein and pre-workout prompts should Kaged prioritize to move into top-three placement?
• What placement target would put Kaged in the same band as Dymatize?

Kaged's single clearest opportunity is to convert its existing positive framing into top-three placement in the consideration-stage prompt cluster where the category is decided. The brand already earns valid recommendations at a high rate relative to its presence. What it does not do is earn them early. Moving average recommended rank from 4.09 toward the 2.5 to 3.0 range would place Kaged in the same placement band as Dymatize, which holds 56.55% top-three coverage on a comparable positive sentiment profile.

This is a placement problem, not a credibility problem, and placement problems are addressable through the owned answer layer and the citation layer. The prompts that matter most are the ones already visible in the dataset: best protein powder, best whey protein, best pre workout, best protein powder for weight loss, and best tasting protein powder. These are the queries where Kaged is being named but not shortlisted early, and they are the queries where a focused correction of product pages, comparison content, and third-party source coverage would have the most direct effect on where the brand lands in the list.

Competitive Landscape

Questions This Section Answers

• How does Kaged's placement in AI recommendations compare with Optimum Nutrition, Transparent Labs, and other tracked brands?
• Where does Kaged rank in top-three placement and average recommended position across the category?

Optimum Nutrition and Transparent Labs hold recommendation-stage strength in this category, separated by 1.9 points of valid recommendation coverage, with Dymatize a clear but distant third. Kaged sits eighth of ten, with a positive framing profile that outperforms its placement.

Average recommended rank covers rank-eligible recommendations only.

Kaged's top-three rate of 1.87% places it eighth in the tracked set, below MuscleTech and BSN despite a stronger sentiment profile than either. Its average recommended rank of 4.09 is the weakest in the table. The numbers show a brand that is recommended positively but late, in a category where the first three positions carry most of the decision weight.

Prompt Evidence

Questions This Section Answers

• Which prompts show Kaged earning top-three placement, and which show it being named without placement?
• What do the platform prompt observations reveal about Kaged's strongest and weakest surfaces?

Google AI Mode / Best Sports Nutrition and Protein Supplements Prompt: "best pre workout" Result: Kaged appeared in the observation and earned a top-three placement, contributing to its strongest platform-level top-three rate of 2.14%.

Perplexity / Best Sports Nutrition and Protein Supplements Prompt: "best protein powder for weight loss" Result: Kaged recorded a positive visibility rate of 10.34% on Perplexity, its highest across any platform, but converted only three of nine valid recommendations into top-three placements.

Copilot / Best Sports Nutrition and Protein Supplements Prompt: "best whey protein powder" Result: Kaged appeared in five Copilot observations and earned three valid recommendations, but recorded no top-three placement and no captured recommendation value on the surface.

Gemini / Best Sports Nutrition and Protein Supplements Prompt: "Which protein powder brand is best?" Result: Kaged appeared in two Gemini observations with positive framing but no rank-eligible placement, leaving the surface with zero captured recommendation value for the brand.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map the specific prompts where Kaged lost presence and top-three placement between August and September 2026, and identify which competitors absorbed those slots.

Phase 2: Recommendation Readiness Plan Prioritize the consideration-stage prompts where Kaged is named but placed fourth, and define the placement target for each.

Phase 3: Owned Answer Layer Buildout Strengthen the product, comparison, and use-case pages that AI systems retrieve when assembling shortlists for protein powder, pre-workout, and weight-loss queries.

Phase 4: Citation / Authority Layer Development Build third-party source coverage on the review, retail, and editorial pages that appear to shape how AI systems rank Kaged against Optimum Nutrition, Transparent Labs, and Dymatize.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track top-three rate and average recommended rank as the primary placement metrics, alongside coverage and sentiment, to confirm whether the September decline reverses.

Why This Matters

AI systems are now where a meaningful share of supplement buyers form their shortlist. A brand that is named positively but placed fourth is not in the consideration set that most buyers act on. Kaged's September 2026 results show a brand with sound framing and weak placement, losing ground to a competitor that gained in the same month.

The next move is not a broad visibility campaign. It is targeted correction of the specific prompts, pages, and sources that determine where Kaged lands in the list. Presence alone will not close a 76-point gap to the category leader. Placement will.

Core Metrics

Sentiment Score

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

For Kaged in September 2026: (37 × 1 + 7 × 0 + 0 × -1) / 44 = 0.8409.

This matters because unclassified mention counts are misleading. A brand with 44 mentions could be described positively in every one, or it could be named 44 times as a cautionary example, and a raw presence number would look identical in both cases. Kaged's score of 0.8409 tells a specific story: AI systems describe the brand favorably, and they do not warn buyers away from it.

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 in commercial weight, and counting all mentions as wins is bad measurement. Kaged's 44 mentions include 7 neutral references that carry no recommendation weight at all. The 37 positive mentions are the ones that matter, and the 13 top-three placements within those are the ones that convert.

Classified sentiment is required before interpreting AI visibility. Kaged's sentiment score is strong, and that strength is exactly why the placement gap is the right thing to focus on. The brand does not have a reputation problem in AI answers. It has a ranking problem, and the two require completely different responses.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Kaged's position in AI-generated recommendations for sports nutrition and protein supplements, produced from the LLM Authority Index AI Market Discovery Index for September 2026.
2. The reporting window is September 2026, with August 2026 included as the comparison month for movement analysis.
3. Six AI surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, AI Overviews, and AI Mode. Keyword variants were rolled up into their parent surface families.
4. The benchmark began with 800 prompt-surface observations in September 2026 and produced 695 qualified observations after relevance screening and qualification. August 2026 began with 800 observations and produced 684 qualified observations.
5. The competitor universe contains ten tracked brands: Optimum Nutrition, Transparent Labs, Dymatize, Isopure, Legion Athletics, MuscleTech, BSN, Kaged, Muscle Milk, and GNC.
6. One public high-intent cluster qualified for analysis in September 2026: Best Sports Nutrition and Protein Supplements, classified at the consideration buyer stage. The Pricing and Value and Multi-Brand Comparison clusters contained zero qualified observations in the public series.
7. Stage 0 extraction retained the query, AI surface, answer, brand outcome, recommendation placement, sentiment, and, where exposed, citations or attributable evidence sources for each observation.
8. A mention is counted when a brand is named anywhere in an AI answer within a qualified observation. Kaged recorded 44 mentions in September 2026.
9. A valid recommendation is counted when a brand appears in a genuine recommendation shortlist, excluding simple mentions, comparison anchors, and cautionary references. Kaged recorded 37 valid recommendations in September 2026.
10. Top-three rate measures the share of qualified observations where a brand is recommended in positions one through three. Rank-one rate measures the share where a brand is the single first recommendation. Average recommended rank covers rank-eligible recommendations only.
11. The unique question count for September 2026 was 629. The public benchmark does not expose a per-brand unique prompt count, so prompt-level attribution in this report is drawn from the cluster prompt examples and platform-level aggregates.
12. Movement between months is directional analysis that identifies changes worth investigating. It does not by itself establish the cause of those changes. Small absolute counts for brands with low coverage mean percentage movements can appear larger than their commercial weight.

See Where Kaged Stands in AI Recommendations

The public benchmark shows where Kaged is winning and losing across AI surfaces. A company-level AI visibility audit maps the specific prompts, competitors, surfaces, and evidence sources behind those numbers into a prioritized placement strategy.