Dymatize AI Market Strategy Report - Sports Nutrition and Protein Supplements

Answer Capsule

Dymatize holds the third-strongest AI recommendation position in sports nutrition and protein supplements, with 71.5% valid recommendation coverage in September 2026. The brand is present in 78.7% of qualified AI answers and appears in a top-three recommendation slot in 56.5% of them, but it converts to the first recommendation position only 5.6% of the time. That gap between broad recommendation coverage and first-position selection is the defining feature of Dymatize's AI footprint: the brand is shortlisted often and chosen first rarely. The clearest opportunity sits in the same high-intent cluster where Optimum Nutrition and Transparent Labs are separating from the rest of the category.

Who This Report Is For

This report is written for Dymatize brand, growth, and ecommerce leaders, and for category strategists tracking how AI systems shape buyer shortlists in sports nutrition and protein supplements.

Report Card

Executive Summary

Dymatize is the clear third force in AI-generated recommendations for sports nutrition and protein supplements. The brand recorded 547 mentions across 695 qualified observations in September 2026, a raw mention presence rate of 78.7%, and 497 valid recommendations, a coverage rate of 71.5%. Both figures place Dymatize behind only Optimum Nutrition (83.3% coverage) and Transparent Labs (81.4% coverage), and well ahead of the fourth-place brand, Isopure, at 23.2%.

The brand's framing is strongly positive. Dymatize recorded 524 positive mentions, 23 neutral mentions, and zero negative mentions, producing a net sentiment score of 0.958. That is the second-highest sentiment score among the top three brands and indicates that when AI systems describe Dymatize, they do so in favorable terms rather than as a comparison anchor or cautionary reference.

The central weakness is placement, not presence. Dymatize appears in a top-three recommendation position in 56.5% of qualified observations, but it is the single first recommendation in only 5.6%. Optimum Nutrition converts 39.6% of observations into a rank-one recommendation and Transparent Labs converts 34.1%. Dymatize's average recommended rank of 2.61 reflects a brand that is consistently included in the shortlist and consistently placed behind the two leaders.

The strongest platform signal for Dymatize is Gemini, where the brand reaches 87.4% valid recommendation coverage and a 74.7% top-three rate. ChatGPT is the second-strongest surface at 84.8% coverage. The weakest platform signal is Perplexity, where Dymatize reaches only 26.4% coverage and a 19.5% top-three rate, a substantial gap against a platform where Transparent Labs reaches 75.9% coverage.

The clearest cluster-level gap is structural. All 695 qualified observations in September 2026 fell into the Brand Recommendation cluster. The benchmark contains zero qualified observations in the Pricing and Value or Multi-Brand Comparison clusters, so the public evidence base cannot yet show how Dymatize performs when buyers ask AI systems to compare brands directly or evaluate value.

The month-over-month picture is stable rather than dramatic. Dymatize's valid recommendation coverage rose 0.6 points from 70.9% in August 2026 to 71.5% in September 2026, and its rank-one rate moved from 6.0% to 5.6%. The brand was classified as stable, while the category's significant movement came from declines at MuscleTech and Kaged and a 3.3-point rise at Transparent Labs.

What Dymatize Is Winning

Questions This Section Answers

• How far ahead of the fourth-place brand is Dymatize in AI recommendation coverage?
• Which AI platforms show Dymatize's strongest recommendation behavior?
• How does Dymatize's sentiment compare with Optimum Nutrition and Transparent Labs?

Dymatize holds a durable and well-separated third position in the category. Its 71.5% valid recommendation coverage is 48.3 points above the fourth-place brand, Isopure, at 23.2%. That separation means Dymatize is not competing with the mid-tier cluster for shortlist eligibility; it is competing with the top two for position within the shortlist.

The brand's sentiment profile is a genuine strength. With 524 positive mentions, 23 neutral mentions, and zero negative mentions, Dymatize's net sentiment score of 0.958 sits above Optimum Nutrition's 0.9529 and just below Transparent Labs' 0.9814. AI systems are not framing Dymatize as a compromise option or a budget alternative.

Dymatize also performs strongly on Gemini and ChatGPT. On Gemini, the brand reaches 87.4% valid recommendation coverage and 89.7% positive visibility, with an average recommended rank of 2.60. On ChatGPT, coverage reaches 84.8% with a 61.0% top-three rate. These are the two surfaces where Dymatize's recommendation behavior most closely resembles the category leaders.

The brand's top-ten recommendation rate of 65.8% is another meaningful signal. Dymatize is not merely appearing in AI answers; it is being placed inside structured recommendation lists in roughly two-thirds of qualified observations.

Where Dymatize Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why does Dymatize convert top-three placements into first-position recommendations so rarely?
• Which platform shows the largest coverage gap between Dymatize and Transparent Labs?
• How is the recommendation gap to the leading brands moving month over month?

The most consequential gap is first-position conversion. Dymatize appears in a top-three slot in 56.5% of qualified observations but is the first recommendation in only 5.6%. Optimum Nutrition converts 39.6% of observations into rank-one placement and Transparent Labs converts 34.1%. In practical terms, Dymatize is routinely shortlisted and rarely selected first, which means the brand is losing the decision moment even when it wins the consideration moment.

Perplexity is the clearest platform-level gap. Dymatize reaches 26.4% valid recommendation coverage on Perplexity, compared with 75.9% for Transparent Labs and 71.3% for Optimum Nutrition. The brand's top-three rate on Perplexity is 19.5%, against 66.7% for Transparent Labs. Perplexity is the surface where Dymatize's shortlist eligibility is weakest relative to the leaders.

The competitive distance to the top two is also widening in relative terms. Transparent Labs added 3.3 points of coverage in September 2026 while Dymatize added 0.6 points. The gap between Dymatize and Transparent Labs moved from 7.2 points in August 2026 to 9.9 points in September 2026. The gap to Optimum Nutrition narrowed slightly from 13.9 points to 11.8 points, but the brand is not closing on the leader at the rate the second-place brand is.

The cluster structure limits what the public benchmark can diagnose. Because all qualified observations fall into the Brand Recommendation class, there is no qualified evidence showing how Dymatize performs in direct head-to-head comparison prompts or in pricing and value prompts. Those are the prompt types where first-position conversion is often decided.

Biggest Opportunity

Questions This Section Answers

• What is the clearest path for Dymatize to convert shortlist presence into first-position selection?
• Which platform should Dymatize examine first to close its recommendation gap?

Dymatize's clearest path forward is converting its existing shortlist presence into first-position recommendations inside the Brand Recommendation cluster. The brand already appears in a top-three slot in 56.5% of qualified observations, which means the retrieval and inclusion work is largely done. The remaining gap is framing and selection: the attributes, differentiators, and evidence that AI systems use to order a shortlist rather than build one.

This is a narrower and more achievable problem than building presence from a low base. It also concentrates on the surfaces where the gap is largest. Perplexity, where Dymatize reaches 26.4% coverage against 75.9% for Transparent Labs, is the single highest-leverage platform to examine, followed by the rank-one conversion pattern across Gemini and ChatGPT, where the brand already has strong coverage but a 5.6% rank-one rate overall.

Competitive Landscape

Questions This Section Answers

• How does Dymatize's rank-one rate compare with Optimum Nutrition and Transparent Labs?
• Which brands round out the top five in AI recommendation strength?

Optimum Nutrition and Transparent Labs hold recommendation-stage strength in this category, with Dymatize as the clear third force and a wide gap to the rest of the tracked set. The table below shows the September 2026 standings across the full competitor universe.

Average recommended rank covers rank-eligible recommendations only.

Dymatize's position in the table shows a brand with top-three strength that is close to the leaders and a rank-one rate that is an order of magnitude below them. Its sentiment score is competitive with the top two, which indicates the gap is about selection order rather than framing quality.

Prompt Evidence

Gemini / Brand Recommendation Prompt: "Which is the best protein powder for adults?" Result: Dymatize reached 87.4% valid recommendation coverage on Gemini, its strongest platform signal, with an average recommended rank of 2.60.

Perplexity / Brand Recommendation Prompt: "best protein powder for weight loss" Result: Dymatize reached only 26.4% valid recommendation coverage on Perplexity, against 75.9% for Transparent Labs, making this the brand's weakest tracked surface.

ChatGPT / Brand Recommendation Prompt: "What's the best protein powder for women losing weight?" Result: Dymatize reached 84.8% valid recommendation coverage on ChatGPT with a 61.0% top-three rate, but converted to the first recommendation in only 17.0% of ChatGPT observations.

AI Overviews / Brand Recommendation Prompt: "low calorie protein powder" Result: Dymatize reached 76.8% valid recommendation coverage on AI Overviews with a 68.6% top-three rate, showing strong shortlist inclusion on Google's AI-generated answer surface.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map Dymatize's prompt-level recommendation behavior across all six tracked surfaces, isolating the specific prompts where the brand is shortlisted but not selected first.

Phase 2: Recommendation Readiness Plan Prioritize the Perplexity coverage gap and the rank-one conversion gap on Gemini and ChatGPT, where the brand already has strong shortlist presence.

Phase 3: Owned Answer Layer Buildout Strengthen the product, comparison, and use-case content that AI systems retrieve when ordering a shortlist, with emphasis on the differentiators that separate Dymatize from the two leaders.

Phase 4: Citation and Authority Layer Development Build the public evidence layer that supports first-position selection, including third-party reviews, comparison sources, and category authority signals that AI systems can retrieve and synthesize.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track coverage, top-three rate, rank-one rate, and sentiment by platform and cluster to measure whether shortlist presence is converting into first-position selection.

Why This Matters

AI systems are now forming the buyer shortlist before a shopper reaches a retail page or a brand site. Dymatize is already inside that shortlist in most qualified observations, which is a meaningful position that many competitors in this category do not hold. But shortlist inclusion and first-position selection are different outcomes, and the brand's 5.6% rank-one rate shows that the decision moment is still being won by Optimum Nutrition and Transparent Labs.

The next move is not a broad visibility campaign. It is targeted correction of the prompt, page, and citation layers that determine ordering within an existing shortlist. That means understanding which prompts produce a Dymatize-first answer, which prompts place the brand second or third, and which public sources AI systems appear to draw on when they make that choice.

Core Metrics

Sentiment Score

Questions This Section Answers

• Why is Dymatize's sentiment score considered a genuine asset for AI recommendation conversion?
• What does a zero-negative-mention profile say about how AI systems frame Dymatize?

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

For Dymatize in September 2026, that calculation is (524 × 1 + 23 × 0 + 0 × -1) / 547, which produces a net sentiment score of 0.958.

This matters because unclassified mention counts are misleading. A brand that appears frequently but is described as a comparison anchor, a cautionary example, or a legacy option is not in the same position as a brand that appears frequently and is described favorably. 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 outcomes, and counting all mentions as wins is bad measurement.

Dymatize's sentiment profile is a genuine asset. With zero negative mentions and a 0.958 score, the brand's framing quality is competitive with the category leaders. The gap is not in how AI systems describe Dymatize; it is in how often they place the brand first. Classified sentiment is required before interpreting AI visibility, and in Dymatize's case it shows that the remaining problem is selection order rather than reputation.

Sentiment by Platform

Questions This Section Answers

• Which AI platform shows the strongest sentiment for Dymatize?
• On which platform does Dymatize appear as context rather than as a recommendation?

Methodology

1. This report is a benchmark-based analysis of Dymatize's AI recommendation footprint in 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 used as the comparison baseline where month-over-month movement is discussed.
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 September 2026 run began with 800 prompt-surface observations and produced 695 qualified observations after relevance screening and qualification. The August 2026 run produced 684 qualified observations.
5. The competitor universe contains 10 tracked brands: Optimum Nutrition, Transparent Labs, Dymatize, Isopure, Legion Athletics, MuscleTech, BSN, Kaged, GNC, and Muscle Milk.
6. All 695 qualified observations in September 2026 fell into the Brand Recommendation buyer-intent cluster. The benchmark contains zero qualified observations in the Pricing and Value or Multi-Brand Comparison clusters, so cluster-level analysis is limited to Brand Recommendation.
7. The public benchmark uses a stage-based qualification process. Raw collection volume, unique questions, brand-mentioned prompts, relevant prompts, and irrelevant prompts are recorded separately from the qualified denominator.
8. A mention is counted when a tracked brand is named anywhere in an AI answer within a qualified observation.
9. A valid recommendation is counted when a brand appears in a genuine recommendation shortlist, excluding simple mentions, comparison anchors, and listed-only references.
10. Top-three rate and rank-one rate are calculated against the 695 qualified observations, not against the raw collection of 800 prompts.
11. The benchmark does not measure market share, sales, attributable revenue, organic-search ranking positions, social mention volume, or private and gated channels. Movements are recorded as observations, not attributed outcomes.
12. Unique question count for September 2026 was 629. The public benchmark does not expose a per-brand unique prompt count, so prompt-level analysis is directional rather than exhaustive.

See Where AI Is Recommending Your Brand

The public benchmark shows where Dymatize stands in AI-generated recommendations across the category. A company-level AI visibility audit maps the specific prompts, surfaces, competitors, ranking patterns, and evidence sources behind those numbers, and identifies where shortlist presence can be converted into first-position selection.