We offer a specialized Search Data as a Service platform that provides businesses with access to historical search volume and emerging trend analysis across millions of keywords and diverse industries.

A free, representative 100-term sample of the 2,361-term US health search trends dataset, with the identical 15-column schema and the full 72-month interest series on every row. Covers all 22 topical categories, all seven patient-journey stages and all three trend-strength tiers. Deliberately not a top-100 cut - the strength mix tracks the full product, so what you evaluate is what you buy.


<h3>What this is</h3>
<p>100 rows drawn from the paid product, with the same 15 columns and the
same meanings. It exists so you can judge the classification quality and
the shape of the trend data before spending anything.</p>

<h3>How the 100 were chosen</h3>
<p>A systematic spread across the full trend-strength ranking, topped up so
every value of every classification appears at least once. Facet
representatives are picked pseudo-randomly within each facet rather than by
highest strength, so the sample does not look stronger than the product.
The selection is deterministic: this sample does not change between
requests.</p>

<h3>What it is honest about</h3>
<ul>
  <li><b>Strength mix</b> - 27% Strong, 47% Solid, 26% Moderate here,
  against 20% / 50% / 30% in the full product. Within sampling noise at
  n=100, not a flattered cut.</li>
  <li><b>Contamination is flagged, not hidden.</b> 3 rows carry
  <code>is_veterinary</code> and 11 carry a <code>qa_note</code>, at
  roughly product rates. The full dataset has a small Pet &amp; Animal
  Health category (17 terms) and an Other / Miscellaneous residual (16),
  both excludable.</li>
  <li><b>Every term in this dataset is growing</b> - direction is constant
  by construction, because the set is filtered for durable growth. The
  differentiating field is strength, not direction.</li>
</ul>

<h3>The full product</h3>
<p>2,361 terms, same schema, one request, CSV export enabled.</p>


US Health Search Trends - Free 100-Row Sample

keyword

trend_strength_score

trend_strength_tier

topical_category

journey_stage

intent_type

brand_signal

has_brand_name

has_generic_name

is_comparison_query

has_cost_or_access_signal

buyer_relevance

monthly_search_interest

qa_note

is_veterinary

data

AP Analytics

ENDPOINT

A free, representative 100-term sample of the 26,250-term US psoriasis search universe, with the identical 24-column schema. Spans the whole product from the highest-demand term to rank 23,841, and carries at least one example of every trend label, journey stage, search intent, brand signal and clinical focus in the paid dataset. Deliberately not a top-100 cut - 80% of these rows sit in the lowest volume band, matching the 84% in the full product, so what you evaluate is what you buy.


<h3>What this is</h3>
<p>100 rows drawn from the paid product, with the same 24 columns and the
same meanings. It exists so you can judge the classification quality and
the shape of the long tail before spending anything.</p>

<h3>How the 100 were chosen</h3>
<p>A systematic spread across the full demand ranking, topped up so every
value of every classification appears at least once. Facet
representatives are picked pseudo-randomly within each facet rather than
by highest volume - picking the top member of each rare category would
have pulled the sample to 61% lowest-band against the product's true 84%,
making the dataset look denser than it is. The selection is
deterministic: this sample does not change between requests.</p>

<h3>What it is honest about</h3>
<ul>
  <li><b>80% of these rows are in the 10-30 monthly-searches band</b>,
  against 84% in the full product. Google's reporting floor is 10, so the
  long tail is not further resolvable. The value of the full dataset is
  coverage and classification, not volume precision.</li>
  <li><b>Around 30% of terms are insufficient_data for trend</b> - too few
  active months to make a claim. That is visible here too.</li>
  <li><b>clinical_focus is general for about two thirds of terms.</b>
  Most search terms name no specific aspect of the disease.</li>
</ul>

<h3>Column meanings</h3>
<p>Identical to the full product - see the paid listing for the column
table, the volume-banding method and the trend method.</p>

<h3>The full product</h3>
<p>26,250 terms, same schema, one request, CSV export enabled.</p>


US Psoriasis Search Terms - Free 100-Row Sample

volume_lower

volume_upper

volume_rank

demand_index_series

data_through_month

trend_label

trend_confidence

growth_rank

clinical_focus

drug_mentioned

drug_class

rank_in_journey_stage

rank_in_clinical_focus

rank_in_brand_signal

rank_for_drug

variant_count

word_count

is_long_tail

is_question

Returns 26,250 US English psoriasis and psoriatic arthritis search terms, one row each, with a banded monthly search volume, a 48-month demand index, a trend direction, and five classification facets covering patient journey stage, search intent, brand signal, clinical focus and buyer segment. Built from a Google Ads Keyword Planner measurement of a 108,953-term discovery pool, deduplicated against Google's own close-variant grouping and annotated term by term. Sizes where psoriasis demand actually sits, which stage of the patient journey it comes from, and which way it is moving - without running your own keyword research.


<h3>What this is</h3>
<p>One row per canonical search term. 26,250 US English terms about
psoriasis, psoriatic arthritis and psoriasiform disease, each carrying a
demand band, a 48-month shape, a trend direction and five facets.</p>

<h3>What this is not</h3>
<ul>
  <li><b>Volumes are bands, not figures.</b> Google Ads reports the midpoint
  of a bucket on a fixed geometric ladder, so its own numbers are estimates.
  We publish the band those estimates fall in, deliberately coarser than the
  source ladder.</li>
  <li><b>The demand index is within-term only.</b> Each series is scaled
  0-100 against that term's own peak. Comparable across months for one term,
  never between terms - use the volume bands to compare terms.</li>
  <li><b>Rows are canonical terms, not raw phrasings.</b> Google groups close
  variants onto one bucket; <code>variant_count</code> tells you how many
  phrasings collapsed into each row. Do not sum volume across rows without
  accounting for it.</li>
  <li><b>stable and insufficient_data are different claims.</b> One means we
  measured and it did not move; the other means we could not measure.</li>
  <li><b>This is education-and-discovery demand.</b> 74% of terms sit in
  treatment-discovery or condition-understanding and only 4% name a brand.
  It is not a brand-share dataset.</li>
</ul>

<h3>Columns</h3>
<table>
  <tr><th>Column</th><th>Type</th><th>Meaning</th></tr>
  <tr><td>keyword</td><td>STRING</td><td>The canonical search term</td></tr>
  <tr><td>volume_lower / volume_upper</td><td>INT64</td><td>Monthly-searches band, lower inclusive, upper exclusive</td></tr>
  <tr><td>volume_rank</td><td>INT64</td><td>Rank by volume, 1 = highest. Filter on this for top-N</td></tr>
  <tr><td>demand_index_series</td><td>STRING</td><td>48 comma-separated integers 0-100, 2022-08 to 2026-07</td></tr>
  <tr><td>data_through_month</td><td>STRING</td><td>Vintage of the series (2026-07)</td></tr>
  <tr><td>trend_label</td><td>STRING</td><td>rising_fast 3.0% · rising 2.2% · stable 53.1% · declining 8.6% · declining_fast 2.0% · volatile 1.6% · insufficient_data 29.6%</td></tr>
  <tr><td>trend_confidence</td><td>STRING</td><td>high · medium · low · none</td></tr>
  <tr><td>growth_rank</td><td>INT64</td><td>Rank by change among directional terms</td></tr>
  <tr><td>journey_stage</td><td>STRING</td><td>treatment_discovery 38.7% · condition_understanding 35.2% · ongoing_management 8.9% · treatment_evaluation 6.3% · differential_seeking 4.8% · symptom_noticing 3.5% · treatment_access 2.7%</td></tr>
  <tr><td>intent_type</td><td>STRING</td><td>informational 49.1% · product_discovery 28.1% · procedural_clinical 9.0% · comparison 5.6% · brand_navigational 4.4% · community_social 3.7%</td></tr>
  <tr><td>brand_signal</td><td>STRING</td><td>unbranded_disease 82.1% · unbranded_product_category 13.3% · branded_consumer 2.5% · branded_rx 1.5% · unbranded_drug_class 0.7%</td></tr>
  <tr><td>clinical_focus</td><td>STRING</td><td>general 66.4% · psoriatic_arthritis 13.6% · scalp 10.5% · plaque · nails · face · hands_feet · guttate · trunk_limbs · genital · inverse · pustular · erythrodermic</td></tr>
  <tr><td>buyer_relevance</td><td>STRING</td><td>Pipe-separated, one or more of: health_education, content_seo, provider_hco, consumer_health, retail_pharmacy, general_market, pharma_competitive, payer_access, pharma_brand, investor_signal</td></tr>
  <tr><td>drug_mentioned / drug_class</td><td>STRING</td><td>Named therapy (27 in the vocabulary, generics resolved to brand) and its class</td></tr>
  <tr><td>rank_in_journey_stage / _clinical_focus / _brand_signal / rank_for_drug</td><td>INT64</td><td>Volume rank within each facet - filter for per-segment top-N</td></tr>
  <tr><td>variant_count</td><td>INT64</td><td>Phrasings that collapsed onto this canonical term</td></tr>
  <tr><td>word_count / is_long_tail / is_question</td><td>INT64 / BOOL</td><td>Query shape</td></tr>
</table>

<h3>Method</h3>
<p><b>Volume bands.</b> Every second point of Google's published ladder is a
band edge, so each band spans two ladder points and no single reported value
is recoverable. Edges: 10, 30, 50, 90, 140, 210, 320, 480, 720, 1000, 1600,
2400, 3600, 5400, 8100, 12100, 18100, 27100, 40500, 60500, 90500, 135000,
201000, 301000, 450000, 673000, 1000000, 1500000, 2240000, 3350000.</p>
<p><b>Trend.</b> Median of the last 12 months against the median of the
previous 12. Medians so a single spike cannot move them, a full year each
side so seasonality cancels. The threshold varies by volume because one
ladder step is +100% at the bottom and ~22% at the top; a term must move
further than the source could express by rounding before it is called a
direction. That bar is applied per term during the build; the label is what
ships.</p>
<p><b>Classification.</b> journey_stage and intent_type are LLM annotations
(structured output, temperature 0); median confidence 0.80, 2.7% below 0.65.
brand_signal, clinical_focus and drug_mentioned are deterministic matches
against controlled vocabularies. buyer_relevance is derived by rules.</p>

<h3>Example queries</h3>
<pre>?volume_rank=&lt;=200                              top 200 terms by demand
?clinical_focus=scalp&amp;rank_in_clinical_focus=&lt;=50   top 50 scalp terms
?trend_label=rising_fast&amp;trend_confidence=high      confident risers
?journey_stage=treatment_access                  cost and coverage demand
?drug_mentioned=skyrizi                          one therapy's full term set
?brand_signal=unbranded_disease&amp;is_question=true  unmet education demand</pre>

<h3>Coverage</h3>
<p>United States, English. Series 2022-08 to 2026-07 (48 months). 26,250
terms measured from a 108,953-term discovery pool; 8,599 returned no data,
2,727 were close-variant duplicates and 874 sat at zero volume.</p>

<h3>Known limitations</h3>
<ul>
  <li>84% of terms fall in the 10-30 band. Google's reporting floor is 10,
  so the long tail is not further resolvable. The value is coverage and
  faceting, not volume precision.</li>
  <li>30% of terms are insufficient_data for trend - too few active months
  in the compared windows to make a claim.</li>
  <li>clinical_focus is general for 66%; most terms name no specific aspect.</li>
  <li>Brand tagging is list-based. A therapy outside the 27-drug vocabulary
  is not tagged.</li>
  <li>Reported search volume is not automatically ground truth - bot and AI
  traffic can inflate it. 2,034 terms carry a non-seasonal spike of 5x or
  more above their median; these are retained, not removed.</li>
  <li>US English only, and a periodic re-cut rather than a live feed.</li>
</ul>

<h3>Refresh</h3>
<p>Periodic re-cut, not a live feed. data_through_month carries the vintage
so your pipeline can detect staleness without reading this page.</p>


US Psoriasis Search Universe - 26K Classified Terms

4,142 fast-rising U.S. Google search terms (2020–2025) across 24 industries — each with a monthly interest time series, growth strength rating, search intent, and a plain-English explanation of what it is.

<p><strong>Fast Growing Search Trends 2026</strong> is a curated dataset of 4,142 U.S. Google search terms whose popularity rose steadily from January 2020 through December 2025. These are durable, growing demand signals — not one-off viral spikes — selected for consistent upward trajectory over six years.</p>
<p>Every keyword is human-readable and enriched so you can act on it without extra cleanup:</p>
<ul>
  <li><strong>Trending Theme</strong> — the search term itself.</li>
  <li><strong>What It Is About</strong> — a one-sentence plain-English explanation of the query, so non-experts understand each term instantly.</li>
  <li><strong>Industry &amp; Sub-category</strong> — mapped to 24 industries (Shopping, Computers &amp; Electronics, Food &amp; Drink, Travel, Finance, Autos, Beauty &amp; Fitness, and more) plus a granular secondary category.</li>
  <li><strong>Search Intent</strong> — commercial, informational, or navigational.</li>
  <li><strong>Entity Type</strong> — brand, person, place, or other.</li>
  <li><strong>Strength</strong> — a High / Medium / Low rating of how strong and consistent the growth trend is.</li>
  <li><strong>Monthly Search Interest Index</strong> — 72 monthly values (Jan 2020 → Dec 2025) on Google's 0–100 relative scale, ready to chart as a time series.</li>
  <li><strong>Live URL</strong> — a direct Google Trends link to inspect each term.</li>
</ul>
<p><strong>Coverage:</strong> United States · monthly · January 2020 – December 2025 · 24 industry verticals.</p>
<p><strong>Ideal for</strong> market researchers, brand and category managers, investors, and content/SEO teams looking to spot emerging consumer demand early, size a category's momentum, or benchmark a brand against a rising theme.</p>
<p><strong>Methodology note:</strong> Google Trends reports a 0–100 index normalized to each keyword's own peak month. Values describe a term's shape over time; they are not comparable as absolute search volume across terms.</p>

Fast Growing Search Trends by Industry

Trending_Theme

Industry

Strength

What_It_is_About

Live_Url

Secondary_Category

Subcategory

Search_Intent

Entity_Type

Search_Interest_Index_Jan2020_Dec2025

2,361 fast-rising U.S. health search terms (2020–2026), each with a monthly interest time series, growth-strength score, patient-journey stage, search intent, brand signal, and the industry buyers it matters to.

<p><strong>Health Search Trends 2026</strong> is a curated dataset of 2,361 U.S. health-related Google search terms whose popularity rose steadily and consistently from January 2020 through December 2025. Every term passed a statistical filter for durable growth (positive linear slope and R-squared of at least 0.50) — these are structural shifts in health demand, not one-off spikes.</p>
<p>Each keyword is enriched well beyond a raw trend line, so buyers can segment by commercial and patient-journey meaning without extra modeling:</p>
<ul>
  <li><strong>Growth strength</strong> — a 0–100 <em>trend-strength score</em> combining how fast a term rose with how consistently it rose, plus a Strong / Solid / Moderate tier. The underlying slope and R-squared are the selection filter described above; the score is what ships, because it is the form you can rank and segment on directly.</li>
  <li><strong>Topical category</strong> — one of 22 clusters, including a small <em>Pet &amp; Animal Health</em> group (17 terms, also flagged by <code>is_veterinary</code>) and an <em>Other / Miscellaneous</em> residual (16 terms), so you can exclude both (GLP-1 &amp; weight, gut health, cholesterol, thyroid, autoimmune skin, mental health, and more).</li>
  <li><strong>Journey stage</strong> — where the search sits in the patient journey (symptom noticing, condition understanding, diagnosis seeking, treatment discovery, ongoing management, and others).</li>
  <li><strong>Intent type</strong> — what the searcher wants (informational, product discovery, comparison, diagnostic-interpretive, access/affordability, and more).</li>
  <li><strong>Brand signal</strong> — whether a named brand is present and its commercial relationship (branded drug, unbranded disease, unbranded drug class, and others).</li>
  <li><strong>Buyer relevance</strong> — which industry segments the signal matters to (pharma brand, provider/HCO, consumer health, retail pharmacy, payer/insurance, investor).</li>
  <li><strong>Commercial flags</strong> — generic drug name present, comparison query, or a cost/access/insurance signal.</li>
  <li><strong>Monthly Search Interest Index</strong> — 72 monthly values (Jan 2020 → Dec 2025) on Google's 0–100 relative scale, ready to chart.</li>
</ul>
<p><strong>Coverage:</strong> United States · monthly · January 2020 – December 2025 · 21 health categories · 2,361 keywords.</p>
<p><strong>Ideal for</strong> pharma brand and market-access teams, consumer-health and OTC marketers, health-tech and digital-health startups, payers, providers, and healthcare investors who need to spot rising conditions, treatments, and branded demand early.</p>
<p><strong>Methodology note:</strong> Google Trends reports a 0–100 index normalized to each keyword's own peak month. Values describe a term's shape over time; they are not comparable as absolute search volume across terms. The five annotation fields were produced by an LLM against a fixed schema and reflect a single best-fit label per field.</p>

Health Search Trends 2026  USA

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US Health Search Trends - Free 100-Row Sample

US Psoriasis Search Terms - Free 100-Row Sample

US Psoriasis Search Universe - 26K Classified Terms

Fast Growing Search Trends by Industry

Health Search Trends 2026 USA