How we measured awareness

Peptide advertising is heavily restricted across ad platforms, so ad-spend data alone only tells a fraction of the story. To answer "which peptides do people actually know the name of?" we combined three independent, cross-validating data signals rather than relying on any single source — then merged them into one transparent, auditable Composite Popularity Score.

43 candidate peptides SpyFu Keyword API SerpApi Google Trends SerpApi Google Search Equal-weighted composite score
The Three Signals
Each signal captures a different slice of "public awareness," and each has known blind spots on its own — which is exactly why we don't rely on just one.
1

SpyFu Keyword Data (Exact-Match Search Volume)

Using the SpyFu Keyword API (POST /v2/related/getKeywordInformation), we pulled Search Volume, Live Search Volume, Ranking Difficulty, and Paid Competitor counts for each peptide name in the US market. Live Search Volume was used as our primary signal since it captures current momentum — e.g. Retatrutide and Semax both showed far higher Live Search Volume than their stale legacy Search Volume figure. This is a direct measurement of how many people type that exact word into Google every month, the clearest "do people know this name" signal available. Paid Competitor counts also gave us a direct read on how ad-restricted each term actually is.

2

Google Trends Relative Interest (via SerpApi)

Google Trends only reports relative interest (0–100, scaled to the highest-volume term in a request) and only allows 5 terms per comparison. To make all 43 candidates comparable on one scale, we split them into batches and included BPC-157 as a fixed anchor term in every batch, then mathematically rescaled every other term relative to a single global anchor value. This let us stitch together one directly comparable interest score across all 43 terms from ~12 separate Trends API calls, using 12 months of weekly data per peptide. Data quality note: Google Trends internally mangles some special characters (e.g. "NAD+" is returned as "NAD "), so we built normalized alphanumeric-only string matching into the parser and verified the correct series was read for every term before trusting the output.

3

Google SERP Breadth (via SerpApi)

For each peptide we ran a live Google Search query and captured Total Indexed Results (log-scaled, since it spans orders of magnitude) as a proxy for how much content exists about the compound across news, forums, retailers, and educational sites, plus Related Searches, People Also Ask questions, and Google Autocomplete suggestions as qualitative signals of what people associate with and ask about each peptide.

Composite Scoring Formula
Each of the three quantitative signals — Live Search Volume, Trends Normalized Interest, and log(SERP Total Results) — was independently rescaled to a 0–100 range using min-max normalization across all 43 candidates. The Composite Popularity Score is the simple average of those three 0–100 scores.

Why equal weighting?

No single source (paid, organic-trend, or content-breadth) was assumed to be more "correct" than another, precisely because each has known blind spots in this category: ad restrictions suppress paid signal, Trends has batch-relative scaling quirks, and raw indexed-result counts can be noisy from content-farm SEO. Averaging three independently-normalized signals means no single quirky data source can dominate the final ranking.

Candidate list

We started from 40 peptides and peptide-adjacent research compounds commonly sold by research peptide vendors, compiled from a review of top peptide company catalogs and industry roundup articles. This list was deliberately broad so the ranking isn't biased toward compounds we assumed were popular going in. Ozempic, Mounjaro, and Zepbound were later added as additional candidates at the user's request. None of them are peptides themselves — they're FDA-approved brand names for the underlying peptide compounds (Ozempic = semaglutide; Mounjaro and Zepbound = tirzepatide, marketed for diabetes and weight loss respectively). They're included and flagged because they're an extremely useful reference point for how mainstream/celebrity "brand power" compares against true research-peptide awareness — and as the results show, brand names now occupy 3 of the top 6 spots overall.

Non-peptide flags

NAD+ and Glutathione are flagged in the results because NAD+ is technically a dinucleotide coenzyme, not a peptide (though it's commonly sold alongside peptides by the same vendors and shows up in the same customer searches). Glutathione is a genuine tripeptide (glutamate + cysteine + glycine) so it qualifies as a true peptide despite the flag drawing attention to its dual identity as a mainstream supplement.

Key Findings
A few notable patterns emerged from cross-referencing all three signals.

Ozempic dwarfs everything else (#1 overall)

Ozempic has the highest Live Search Volume in the entire dataset (672,000/mo, nearly 3x Tirzepatide) and the second-highest Trends interest, driven by massive mainstream/celebrity media coverage as a weight-loss brand. It's flagged because it's a brand name for semaglutide, not a peptide itself — but it's a useful benchmark showing just how much bigger true mainstream awareness is compared to even the best-known research peptides.

Brand names now occupy half the Top 6

Adding Mounjaro and Zepbound (both tirzepatide brand names) confirmed the pattern: Zepbound entered at #3 overall (49.7, driven by 222,000/mo search volume and 5,770 indexed results — the richest content footprint of any branded term) and Mounjaro landed at #6 (39.4, with an enormous 674.79 Trends score, actually higher than Ozempic's). Together with Ozempic, branded consumer drug names now occupy 3 of the top 6 spots — a striking illustration of how much FDA-approved brand marketing outweighs organic research-community awareness, even for the same underlying molecule (tirzepatide/semaglutide).

GLP-1 drugs dominate raw awareness

Tirzepatide, Semaglutide, and Retatrutide occupy 3 of the top 6 spots, reflecting massive mainstream media coverage of weight-loss drugs (Ozempic/Zepbound/Mounjaro) bleeding into search behavior for the underlying compound names.

BPC-157 is the most recognized "true" research peptide

It ranks #5 overall and has by far the richest organic content ecosystem, plus the strongest brand pairing — "BPC-157 and TB-500" and "TB-500 vs BPC-157" are each other's top related search, confirming the industry belief that this is the most recognized recovery-peptide stack.

Oxytocin ranks unexpectedly high (#2 overall)

Likely driven by its dual identity as a well-known mainstream "hormone" in health/psychology content, not just a research peptide — a useful caveat for peptide-company-specific marketing decisions.

Semax & Tesamorelin: high volume, thin content

Both show very high Live Search Volume but comparatively thin content footprints and modest Trends scores — suggesting a smaller, highly repetitive searcher base (existing users re-searching dosing info) rather than broad new public awareness.

Ad-restriction hypothesis confirmed

Classic gray-market peptides show real advertiser activity via SpyFu's paid-competitor counts, but nowhere near what raw organic search volume would imply. Ad data alone would have completely mis-ranked this category — undercounting Semax/Tesamorelin and overweighting anything with aggressive advertisers.

Full Report & Raw Data
Every number in this site traces back to a raw API response saved to disk before any processing. Download the full report and underlying data files for a complete audit trail.
FileDescription
PEPTIDE_POPULARITY_REPORT.mdFull written report with methodology, results table, and findings
final_report_table.csvComplete scored dataset for all 43 candidates (spreadsheet-ready)
final_scores.jsonFull merged dataset with all sub-scores, sorted
spyfu_raw.jsonRaw SpyFu API response (search volume, CPC, competitors, difficulty)
trends_raw.jsonRaw SerpApi Google Trends responses (all batches)
trends_normalized.jsonCross-batch normalized Google Trends interest scores
serp_details_summary.jsonRelated searches, People Also Ask, autocomplete per peptide
candidate_peptides.jsonMaster list of 43 candidate peptides/compounds researched