Protein Powder AI Visibility Index 2026

Protein powder AI visibility was led by Optimum Nutrition, named in 64.2% of 288 answers returned across Perplexity, ChatGPT, Gemini, and Claude. Transparent Labs followed at 56.3%, while the measured results show different engine patterns for whey, plant, casein, and clear protein names rather than a single format winner. This Protein / Protein Powder report is one segment of the Supplements AI Visibility Index 2026.

The practical risk is uneven exposure. A brand can appear often overall yet be absent or weak in one engine's answers, and the citations supporting answers often come from publishers rather than the brand's own site. These findings describe the 24 measured prompts on September 30, 2026. They do not describe all protein powder searches or consumer demand.

Optimum Nutrition's lead is measured on answers returned, while GNC's owned domain had the highest owned-domain citation rate among eligible brands at 18.1% of answers with retrieval evidence. Appearance and citation rates use separate denominators, so they answer different questions.

Which brands lead the protein powder leaderboard?

Optimum Nutrition ranked first with a 64.2% appearance rate, followed by Transparent Labs at 56.3%, Naked at 47.9%, Dymatize at 45.8%, and Garden of Life at 39.6%. These rates use 288 answers returned as the denominator. The ranking measures how often a brand was named, not product quality or consumer selection.

The top results include brands associated in the tally with whey, plant, casein, isolate, and clear protein product names. The measured prompts do not support a category-wide claim that one protein format wins recommendation share.

Protein powder appearance leaderboard

Appearance rate measures the share of 288 returned AI answers that named each brand.

Several adjacent ranks are within the margin of this sample. Optimum Nutrition's 95% interval of 58.5% to 69.6% overlaps Transparent Labs' 50.5% to 61.9%. Transparent Labs overlaps Naked, Naked overlaps Dymatize, and Dymatize overlaps Garden of Life. The data does not establish that one brand is more visible than another where those intervals overlap.

The leading brands have different weak points by engine, answer position, repeat consistency, and owned-domain citation rate. The profiles below use appearance rates from answers returned and citation rates from the 288 answers with retrieval evidence.

Where do the engines disagree?

Several brands produced wide differences across the four engines, even though each returned 72 answers with retrieval evidence. Those gaps may reflect each system's model and retrieval tool. They do not provide a stable measure of brand visibility beyond these prompts.

Engine-by-brand appearance patterns

Each cell is calculated from that engine's own answer count. This allows row-by-row engine comparison.

ChatGPT named Optimum Nutrition in 84.7% of its 72 answers, compared with 44.4% for Gemini and 50% for Claude. It also named Dymatize in 72.2%, Garden of Life in 68.1%, and Orgain in 65.3%. Perplexity produced different peaks: Transparent Labs appeared in 77.8% of its 72 answers, while Momentous appeared in 50% and GNC in 25%.

Some gaps were complete absences. Claude named Myprotein in 0% of its 72 answers despite 47.2% for Perplexity and 48.6% for ChatGPT. Claude also named Vega in 0%, while ChatGPT named it in 44.4%. Thorne had 0% on Claude but 36.1% on Perplexity. Sunwarrior and NOW Sports also had 0% on Claude, while each was named by the other engines.

Gemini differed for Naked, which appeared in 22.2% of Gemini answers but 76.4% of ChatGPT answers. Garage Gym Reviews was named in 25% of Gemini answers and 0% of ChatGPT and Claude answers. The heatmap is a system comparison, not evidence that one engine is right or wrong.

Which demand clusters favor each brand?

Demand-cluster results identify the brands leading within the measured question groups. They distinguish general buyer-intent questions from sub-category and specific-need questions. These groups do not represent the same type of demand.

Brand leaders by demand cluster

The answers are also regrouped by the demand cluster assigned to each sampled prompt. Each cluster rate uses its own answer count.

For general buyer-intent questions, the chart identifies the brands the engines named most often in the broad selection context. For sub-category and specific-need questions, it identifies brands attached to more defined protein needs. The cluster view is the appropriate place to assess the brief's whey, plant-based, casein, and clear protein angle because it preserves the question context instead of pooling all mentions.

Which sites receive the citations?

Publisher sites received citations across a far larger share of retrieval-supported answers than most brand-owned domains. Citation rates in this section use 288 answers with retrieval evidence as the denominator.

Owned-domain citation rates

Share of 288 answers with retrieval evidence that cited a URL from the brand's own website.

GNC had the highest owned-domain citation rate among eligible brands at 18.1%, followed by Myprotein at 12.5% and Optimum Nutrition at 8.7%. Naked reached 5.9%. Transparent Labs and Momentous each reached 2.4%, while Dymatize, Garden of Life, and Orgain each reached 1.4%. Several eligible brands had 0% owned-domain citation rates, including Vega, Thorne, KOS, Ritual, Isopure, Premier Protein, Nutricost, Truvani, and Brooks.

Publishers cited in retrieval-supported answers

Publishers used as evidence, counted once for each answer, not once for each link.

Healthline appeared in 80.9% of answers with retrieval evidence, Forbes in 64.6%, Garage Gym Reviews in 56.6%, and Fortune in 45.5%. Men's Health appeared in 23.6%, BarBend in 21.9%, YouTube in 21.2%, and ConsumerLab in 12.2%. The pattern shows that engines regularly drew support from health publishers, editorial reviews, retailer material, and testing-oriented sources.

Who is winning and who is at risk?

Winning measured positions

Optimum Nutrition is a measured leader because it ranked first at 64.2%, averaged position 3.4, and appeared across all four engines. Transparent Labs ranked second at 56.3% and had the earliest average first mention among the top ten at position 3.1. GNC is a citation leader rather than an appearance leader: it ranked nineteenth at 8% appearance but had an 18.1% owned-domain citation rate.

At-risk measured positions

Myprotein is exposed to engine dependence because Claude named it in 0% of its 72 answers despite its 28.8% overall appearance rate. Vega has the same Claude absence and a 20.1% overall rate, with an average first mention position of 8.2. Orgain's 34% appearance rate is driven unevenly across engines, ranging from 8.3% on Claude to 65.3% on ChatGPT. Garden of Life also has a wide spread, ranging from 18.1% on Claude to 68.1% on ChatGPT.

What does the tally say about protein powder visibility?

Protein powder visibility is concentrated at the top, but the first five ranks are not cleanly separated by the sample intervals. Optimum Nutrition's interval overlaps Transparent Labs, Transparent Labs overlaps Naked, Naked overlaps Dymatize, and Dymatize overlaps Garden of Life. The data supports a leading group, not a definitive ordering across those overlaps.

The engines converge on some brands. Optimum Nutrition, Transparent Labs, Naked, Dymatize, Garden of Life, Orgain, Legion, Momentous, KOS, Ritual, MuscleTech, Ascent, Isopure, Premier Protein, Kaged, GNC, and Nutricost each appeared on all four engines. Yet their rates vary across those engines, and Myprotein, Vega, Thorne, Sunwarrior, and NOW Sports were absent from Claude's measured answers.

Citations favor third-party publishers. Healthline's 80.9% answer penetration exceeds every eligible brand-owned domain citation rate. The brief named Ghost among the brands to report, but the tally rolled Ghost mentions under Brooks, which had a 5.2% appearance rate and 0% owned-domain citation rate. The tally did not provide a separate Ghost brand row.

What changed during the measurement window?

The data does not measure changes over time within the measurement window. It measures repeat-generation variation and engine differences across the same set of prompts, including repeat consistency ranging from 0% for Brooks to 63.2% for Optimum Nutrition.

How can protein brands address measured gaps?

• Audit brand pages that explain whey, plant-based, casein, isolate, and clear protein products in distinct, factual sections. The cluster chart identifies which question groups each brand misses. Re-measure appearance by the same demand cluster.
• Build pages that put macro details and ingredient information next to the exact product name. Brands with weak average first-mention positions, such as Premier Protein at 9.1 and NOW Sports at 9.8, can be re-measured for average position in answer.
• Publish sourceable product documentation on owned domains. Vega, Thorne, KOS, Ritual, Isopure, Premier Protein, Nutricost, Truvani, and Brooks each had a 0% owned-domain citation rate. Re-measure owned-domain citation rate using answers with retrieval evidence.
• Test the material against Claude-specific gaps. Myprotein, Vega, Thorne, Sunwarrior, and NOW Sports were named in 0% of Claude's 72 answers. Re-measure each brand's Claude appearance rate after new content is available.
• Review engine-specific coverage before treating an overall rate as secure. Garden of Life ranged from 18.1% on Claude to 68.1% on ChatGPT, while Orgain ranged from 8.3% to 65.3%. Re-measure by engine, not only in pooled results.
• Seek accurate inclusion in the publisher formats that engines cite. Healthline, Forbes, Garage Gym Reviews, and Fortune appeared in large shares of retrieval-supported answers. Re-measure the brand's appearance rate and owned-domain citation rate separately after any publisher coverage.

What does this mean for brands in the category?

Interpretation: protein powder visibility is not one scoreboard. A brand's overall appearance rate shows how often it was named in these measured answers. Engine-specific rates show whether that exposure travels across systems. Owned-domain citation rates show whether the brand's own material is supporting retrieval-backed answers.

Interpretation: brands associated with clean labeling and macro transparency need pages that let an engine connect product names to concrete attributes. The tally cannot establish which content change causes a citation or recommendation. It can establish the baseline that later measurement should test.

How was this study measured?

This flagship study ran 24 stratified prompts three times on Perplexity, ChatGPT, Gemini, and Claude. It produced 288 returned answers. Appearance rates use returned answers as the denominator. Citation and source rates use answers with retrieval evidence as the denominator. All 288 returned answers included retrieval evidence. These results apply to these prompts and this date, not to every protein powder question.

How this study was measured

• The sampling frame came first: 24 prompts were assigned across demand clusters before any questions were asked.
• Every engine received the same questions: Perplexity (sonar-pro), ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic), 3 trial(s) each.
• 288 of 288 attempted answers were returned, and 288 had retrieval evidence.
• Product lines were mapped to parent brands through a registry fixed before scoring.
• Appearance rate uses a 95% Wilson interval. Citation metrics include only answers with evidence.

Charts and data tables

These are not category brands. They are measured in the same way but excluded from the brand leaderboard.

Methodology appendix

This appendix comes directly from the study's measurement record. It lets any brand named here reproduce or contest the result.

What was measured

• Category: Protein / Protein Powder
• Measurement date: 2026-09-30
• Depth: flagship: 24 prompts, 3 trial(s) per prompt per engine, 4 engines
• Answers attempted: 288
• Answers returned (appearance denominator): 288
• Answers with retrieval evidence (citation denominator): 288 (100% of attempted)
• Answers that failed outright: 0
• Analysis version: study-methodology-v2 · entity registry: entity-registry-2026-08-27

Claim limit: Flagship depth uses 24 stratified prompts measured three times per engine. This makes both between-prompt and repeat-generation variation observable.

How the prompts were sampled

Fixed sampling frame: 14 buyer-intent need(s) from the client's brief are asked verbatim, one prompt each, grouped under: Protein / Protein Powder; then , then a documented set of generic commercial demand clusters (general best, everyday mainstream choice, price/value, primary use case, beginner, retail channel, gifting/occasion, specific need, comparison, trust, ownership attribution, quality tier, durability, specialist, emerging) receives the remaining allocation round-robin. The prompt writer provides wording only within these cells and does not select the category's demand structure.

Results cannot be compared strictly across engines. Each engine has a different model, retrieval tool and answer format. A gap between two engines may therefore reflect system design as much as brand visibility.

How each metric is defined

• Appearance rate — the share of returned answers that named the brand. It covers every answer returned by the engine, whether or not the engine searched the web. Retrieval behaviour therefore does not silently alter the denominator.
• Macro appearance rate — the average of per-prompt appearance rates. Each prompt therefore counts once, regardless of how many engines answered it.
• 95% interval — Wilson score interval for the appearance rate. If two brands' intervals overlap, this study does not support saying that one is more visible than the other.
• Owned-domain citation rate — the share of answers with retrieval evidence that cited a URL on the brand's own domain. This narrowly measures use of the brand's own site as a source. It does not measure total mentions.
• Share of all citations — the share of all attributed publisher citations in the study accounted for by the brand's own domain.
• Not measured — the brand's official domain was not established, so no citation result is available. It is never shown as 0%.
• 0% — the metric was evaluable, but the event did not occur.
• Average position — the average position of the brand's first mention in the answer's ordered list of named brands.
• Cross-engine consistency — the share of engines that named the brand at least once.
• Repeat consistency — the share of repeated prompt/engine cells in which the brand appeared in every trial. Lower values indicate an unstable engine answer, not brand absence.

Evidence rules

• An answer has retrieval evidence only if the engine returned a retrieval receipt (search annotations or grounding records). A URL merely typed by the model in its prose does not show that it searched.
• Sources are assigned to the publisher behind each retrieval receipt. Intermediary and redirect hosts are not reported as publishers.
• Publisher identity was not established for 0 retrieval receipt(s). They are disclosed here, not attributed or dropped.
• Source counts are at answer level: a publisher is counted once in an answer that cited it, not once per URL.

Entity handling

For brand-level metrics, product lines and model names are assigned to their parent brand using a registry fixed before scoring. Nothing is merged solely because of this study's own counts.

• Ghost counted under Brooks (product_line)

40 further name(s) found in the answers could not be confidently resolved to a brand in this category. They are held for human classification before the next study and have no metrics here.

Limits of these findings

• This is a point-in-time measure of what the named systems returned for these exact prompts on 2026-09-30. Engine behaviour can change without notice.
• The prompt set is a stratified sample of category demand, not a census. Results describe these prompts and are not representative of all searches in the category.
• When intervals overlap, brand differences are not statistically distinguishable at this sample size.
• A brand absent from this list was not measured as absent. It was simply not named in these answers.
• Appearance measures visibility. It is not an endorsement, quality judgement or market-share estimate.
• 1 of 26 ranked brand(s) had no official domain established before scoring. They have appearance results only and are excluded from citation metrics and source tables, rather than reported as zero.