Found AI Market Strategy Report - Weight Loss and Metabolic Health

Answer Capsule

Found holds 24.5% valid recommendation coverage in the September 2026 LLM Authority Index benchmark for Weight Loss and Metabolic Health, ranking fourth of nine tracked brands. The brand is visible but under-recommended: it appears in 35.7% of qualified observations yet converts that presence into a valid recommendation less than a quarter of the time. Found's clearest strength is framing quality, with a net sentiment score of 0.8235 and zero negative mentions across 286 qualified observations. Its clearest weakness is first-position power, with a rank-one rate of 2.1% against Noom's 15.7% and Ro's 12.6%. The clearest opportunity sits in the gap between reference and recommendation, where Found is named as context far more often than it is shortlisted.

Who This Report Is For

This report is written for Found's growth, brand, and commercial leadership, and for category strategists tracking how AI-generated recommendations shape buyer shortlists in weight loss and metabolic health.

Report Card

Executive Summary

Found holds 24.5% valid recommendation coverage in September 2026, placing it fourth among nine tracked brands in the Weight Loss and Metabolic Health benchmark. The brand was mentioned in 35.7% of qualified observations, a presence rate that sits well above its recommendation coverage, which means Found is frequently named without being shortlisted. That gap between raw mention presence and valid recommendation coverage is the central finding of this report.

The benchmark recorded 102 mentions of Found across 286 qualified observations, split into 84 positive, 18 neutral, and zero negative. The absence of negative framing is a genuine asset. Found's net sentiment score of 0.8235 is the second highest in the category behind Noom's 0.8267, and it is achieved on a smaller and therefore more fragile mention base.

Found's strongest cluster is the Brand Recommendation cluster, which is also the only cluster with qualified observations this month. Within it, Found produced 70 valid recommendations, 38 top-three placements, and 6 rank-one placements. The brand's average recommended rank of 2.9 is the weakest among the four leading brands, behind Noom at 2.02, Ro at 2.06, and WeightWatchers at 2.22.

The clearest platform signal is Google AI Overviews, where Found reached 32.6% valid recommendation coverage and a 23.3% top-three rate. The clearest platform gap is Perplexity, where Found recorded a single mention, one valid recommendation, and a 3.3% coverage rate. Copilot is a second gap: Found appeared in 43.8% of Copilot observations but converted only 34.4% of them into valid recommendations, with no rank-one placements at all.

Found's rank-one rate of 2.1% is the sharpest weakness in its profile. The brand is being recommended, but it is rarely being recommended first. Noom holds 45 rank-one placements, Ro holds 36, and WeightWatchers holds 31, against Found's 6. In a category where the first recommendation often becomes the buyer shortlist, that is the difference between being considered and being chosen.

What Found Is Winning

Questions This Section Answers

• What evidence supports Found's framing quality as a genuine asset?
• Where is Found converting AI recommendations most effectively across platforms?

Found's framing quality is its strongest evidence-backed asset. Across 286 qualified observations, the benchmark recorded zero negative mentions and 84 positive mentions, producing a net sentiment score of 0.8235. Only Noom scores higher, and only marginally.

Found's second win is its Google AI Overviews performance. The brand reached 32.6% valid recommendation coverage on that surface, its highest across all six platforms, with 28 valid recommendations and 20 top-three placements. Google AI Overviews is the largest opportunity pool in the benchmark, and Found is converting there at a rate above its category average.

Found's third win is stability. The brand's coverage moved from 22.9% in July 2026 to 24.5% in September 2026, a 1.6-point gain that the benchmark classifies as within normal variation. In a month where one brand rose 32.9 points and another fell 4.7 points, Found held its position without erosion.

These are real but narrow wins. Found does not lead any platform, any placement tier, or any coverage measure in this benchmark.

Where Found Has the Clearest AI Visibility Gaps

Questions This Section Answers

• Why is Found's rank-one rate so low compared to competitors?
• What explains Found's weak conversion on Copilot and Perplexity?

Found's most consequential gap is first-position conversion. The brand holds a 13.3% top-three rate and a 2.1% rank-one rate. Noom holds a 27.6% top-three rate and a 15.7% rank-one rate on lower overall presence than WeightWatchers. Found is present in the recommendation conversation but is not winning the slot that matters most.

The second gap is Copilot. Found appeared in 43.8% of Copilot observations, a presence rate comparable to Ro's 78.1% and Noom's 59.4% when adjusted for platform volume, but converted only 34.4% of those appearances into valid recommendations. The brand recorded zero rank-one placements on Copilot. Competitors are being named first on that surface while Found is being named alongside them.

The third gap is Perplexity. Found recorded one mention, one valid recommendation, and a 3.3% coverage rate on that platform. Noom reached 60.0% coverage and a 36.7% rank-one rate on the same surface. Perplexity is a small opportunity pool in this benchmark, but the disparity is stark enough to indicate a source and citation gap rather than a demand gap.

The fourth gap is average recommended rank. Found's average recommended rank of 2.9 places it behind all three brands above it in the standings. When Found does enter a shortlist, it enters lower. That position disadvantage compounds across prompts and reduces the probability that a buyer sees Found before forming a preference.

Biggest Opportunity

Questions This Section Answers

• How many qualified observations did Found lose between mention and recommendation?
• Where should Found focus to convert existing mentions into top-three placements?

Found's single largest opportunity is converting its existing mention presence into top-three and rank-one placements in the Brand Recommendation cluster. The brand already appears in 35.7% of qualified observations, which means the retrieval layer is working. What is not working is the recommendation layer: the same prompts that name Found are placing Noom, Ro, and WeightWatchers ahead of it.

The specific path is to strengthen the evidence that AI systems use when ranking options within a shortlist. Found's 24.5% coverage against a 35.7% presence rate represents roughly 32 qualified observations where the brand was named but not recommended. Closing even half of that gap would move Found from fourth to a credible challenge for third, and would do so without requiring new presence in prompts where the brand is currently absent.

Competitive Landscape

Questions This Section Answers

• Which brands lead the Weight Loss and Metabolic Health category in AI recommendations?
• How does Found's sentiment rank compare to its placement rank?

WeightWatchers holds the strongest recommendation position in the category at 46.9% coverage, with Noom and Ro forming a clear upper tier behind it. Found sits in a second tier with meaningful presence but materially weaker first-position power than the three brands above it.

Average recommended rank covers rank-eligible recommendations only.

Found ranks fourth on top-three rate and fourth on rank-one rate, with a sentiment score that ranks second. The table shows a brand with strong framing and weak placement: Found is liked more than it is chosen, and the distance between its sentiment rank and its placement rank is the widest of any brand in the tracked set.

Prompt Evidence

Questions This Section Answers

• On which platforms did Found achieve top-three placements?
• Where did Found fail to convert mentions into recommendations?

Google AI Overviews / Brand Recommendation Prompt: "What is the best online weight loss prescription program?" Result: Found appeared in the recommendation set with a top-three placement, consistent with its strongest platform performance.

Perplexity / Brand Recommendation Prompt: "Which is the most successful weight loss program?" Result: Found recorded no recommendation credit on this surface, where Noom reached a 36.7% rank-one rate.

Copilot / Brand Recommendation Prompt: "What are the best programs to lose weight?" Result: Found was named in the response but did not convert to a valid recommendation, reflecting its 34.4% Copilot conversion rate.

Google AI Mode / Brand Recommendation Prompt: "Which is the best product for losing weight?" Result: Found appeared with a top-three placement in one of the 68 AI Mode observations, where its coverage rate was 14.7%.

What CiteWorks Studio Would Do Next

Phase 1: AI Market Discovery Audit Map every prompt where Found is named but not recommended, and identify which competitors take the placement instead.

Phase 2: Recommendation Readiness Plan Prioritize the Copilot and Perplexity gaps, where Found's presence-to-recommendation conversion is weakest relative to the category.

Phase 3: Owned Answer Layer Buildout Strengthen the pages and structured content that answer the specific comparison and selection prompts where Found currently ranks fourth or lower.

Phase 4: Citation / Authority Layer Development Build the public evidence layer that AI systems retrieve when ranking options, focusing on the sources that support first-position placement rather than general mention.

Phase 5: Monthly AI Visibility and Recommendation Tracking Track top-three and rank-one rates separately from presence, so placement gains are visible before they show up in coverage.

Why This Matters

Questions This Section Answers

• What is the difference between AI visibility and recommendation placement for Found?
• Why is Found's high sentiment not translating into first-position recommendations?

Found is already in the room. The brand appears in more than a third of qualified AI responses in its category, and it does so without a single negative mention. That is a stronger starting position than most brands in this benchmark hold. But appearing in the room is not the same as being handed the shortlist, and the benchmark shows Found converting presence into recommendation at a rate well below the three brands ahead of it.

The next move is not more visibility. It is targeted correction of the prompt, page, and citation layers that determine placement within a recommendation set. Found's sentiment profile suggests the brand is well regarded. Its rank-one rate suggests that regard is not yet translating into selection. Closing that specific gap is the difference between being one of several options and being the option.

Core Metrics

Sentiment Score

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

For Found, that is (84 × 1 + 18 × 0 + 0 × -1) / 102, which produces a score of 0.8235.

This matters because unclassified mention counts are misleading. A brand named 102 times could be described positively, referenced neutrally as a comparison anchor, or flagged with a caution, and a raw count would treat all three as identical. Share of voice is a diagnostic metric, not a business KPI. It tells you how often a brand appears, not how it is being framed when it does.

A positive recommendation, a neutral reference, a cautionary mention, and a competitor-displaced mention are not equal events. Counting all mentions as wins is bad measurement, because it hides the difference between a brand that is being recommended and a brand that is being used as context for someone else's recommendation. Classified sentiment is required before interpreting AI visibility, and Found's profile is unusually clean: zero negative mentions across 286 qualified observations, with 82.4% of its mentions carrying positive framing.

Sentiment by Platform

Methodology

1. This report is a benchmark-based analysis of Found's position in the LLM Authority Index AI Market Discovery Index for Weight Loss and Metabolic Health. It is not a client implementation result.
2. The reporting month is September 2026, with comparison points from July 2026 and August 2026 where the benchmark provides them.
3. Six AI surface families were tracked: ChatGPT, Copilot, Gemini, Perplexity, Google AI Overviews, and Google AI Mode. All six produced qualified observations in September 2026.
4. The September 2026 run began with 800 prompt-surface observations and 725 unique questions, of which 525 were relevant to the category and 286 qualified for the public benchmark.
5. Nine brands were tracked: Found, GNC, Herbalife, Hims, LifeMD, Noom, Ro, Vitamin Shoppe, and WeightWatchers.
6. The qualified observation set fell entirely within the Brand Recommendation buyer-intent cluster. No qualified observations were recorded in the Pricing & Value or Multi-Brand Comparison clusters this month.
7. Stage 0 extraction produced the prompt-level records that retain query, surface, answer, brand outcome, recommendation placement, sentiment, and citations where exposed.
8. A mention is counted when a tracked brand is named in a qualified observation, regardless of whether it is recommended.
9. A valid recommendation is counted only when the brand appears in a recommendation shortlist, as marked by the dataset. Neutral, cautionary, and comparison-anchor mentions are not counted as valid recommendations.
10. Top-three rate and rank-one rate are calculated against the 286 qualified observations, not against the brand's own mention count.
11. Average recommended rank covers rank-eligible recommendations only. Brands with no rank-eligible recommendations are shown as N/A.
12. The benchmark tracks the entity recorded as "Ro (Roman)" in July and August 2026 separately from the entity recorded as "Ro" in September 2026. Readers should treat the naming change as a discontinuity in that brand series rather than continuous movement for a single entity.
13. Small counts for brands such as Herbalife, LifeMD, GNC, and Vitamin Shoppe move in large relative swings on minor absolute changes and should be read with caution.
14. Source presence in the evidence layer is treated as information about the retrieval environment. It is not treated as proof that a source caused a recommendation.

See Where AI Is Recommending Your Brand

The public benchmark shows where Found stands in AI-generated recommendations across the Weight Loss and Metabolic Health category. A company-level AI visibility audit maps the specific prompts where Found is named but not shortlisted, which competitors take the placement instead, and which sources shape those answers.