SerpApi's Google Trends Autocomplete engine resolves ambiguous keywords into Knowledge Graph entity IDs before interest-over-time queries run. Each successful autocomplete call costs one credit from the shared monthly pool, and most production workflows need a second credit on engine=google_trends for the resolved topic. This page covers only autocomplete pricing: per-lookup cost, two-step credit math, and when entity resolution belongs in the budget.
Ambiguous keywords are the hidden multiplier in Google Trends budgets. SerpApi exposes entity resolution through engine=google_trends_autocomplete, and every fresh lookup costs one credit from the account's shared monthly pool. Teams that resolve entity IDs before pulling interest-over-time data routinely spend two credits per keyword. That second step is easy to omit from spreadsheets until the pool empties mid-sprint.
For SerpApi's full Google Trends pricing across interest-over-time, autocomplete, and Trending Now engines, see SerpApi Google Trends API pricing. This page stays on autocomplete only.
SerpApi scrapes Google's Trends autocomplete API and returns JSON. A typical response includes a suggestions array. Each item carries:
q: the search term or Knowledge Graph entity IDtitle: the human-readable labeltype: category such as Search term, Company, or Web browserlink: a Google Trends explore URLserpapi_link: a pre-built pointer to engine=google_trends with data_type=TIMESERIESThe endpoint URL shape is:
GET https://serpapi.com/search?engine=google_trends_autocomplete&q=meta&api_key=YOUR_KEY
Optional hl sets language. no_cache=true forces a live scrape and always costs one credit. The default allows SerpApi to serve a cached copy when the query and parameters match a request from the past hour. Cached responses are free.
Autocomplete draws from the same credit pool as Google Search, Google Shopping, Trending Now, and every other SerpApi engine. There is no separate autocomplete SKU.
| Plan | Monthly price | Included searches | Cost per fresh lookup (if fully used) | Throughput cap |
|---|---|---|---|---|
| Free | $0 | 250 | $0.00 | 50/hour |
| Starter | $25 | 1,000 | $0.025 | 200/hour |
| Developer | $75 | 5,000 | $0.015 | 1,000/hour |
| Production | $150 | 15,000 | $0.010 | 3,000/hour |
| Big Data | $275 | 30,000 | $0.009 | 6,000/hour |
Suggestion count does not change the charge. A response with twelve entity matches and an empty response both cost one credit when the request succeeds.
Autocomplete is rarely the final step. SerpApi's own documentation describes a two-call pattern: autocomplete to find the entity q, then engine=google_trends with that q for a clean timeseries.
Assume every brand needs entity resolution before interest-over-time data.
| Step | Calls | Credits |
|---|---|---|
| Autocomplete per brand | 50 | 50 |
| Interest-over-time per resolved entity | 50 | 50 |
| Total | 100 | 100 |
On Starter ($25, 1,000 credits), effective cost is $2.50 for the batch if no other engines share the pool. On Free (250 credits), the same batch exhausts the monthly allocation in one job.
An analyst types partial queries (running sh, running sho, running shoe) to harvest related entity suggestions before choosing a target keyword. Three autocomplete calls per seed phrase, 20 seed phrases, 60 credits before any timeseries pull. Add 20 timeseries calls and the sprint consumes 80 credits on autocomplete and resolution alone.
A dashboard resolves the same 10 brand entities daily. With default cache behavior, identical autocomplete parameters within one hour return free cached JSON. Once per day with no cache hits: 10 credits per day, roughly 300 per month. Developer plan ($75, 5,000 credits) covers it with room for timeseries calls.
SerpApi also exposes engine=google_autocomplete, which scrapes google.com completion suggestions for web search. That engine returns query strings like coffee near me with relevance scores. It does not return Knowledge Graph entity IDs for Trends.
| Engine | Purpose | Typical output | Trends timeseries link |
|---|---|---|---|
google_trends_autocomplete |
Resolve Trends entities | Entity IDs (/g/..., /m/...) and topic types |
Yes, via serpapi_link |
google_autocomplete |
Web search completion | Query string suggestions | No |
Teams paying for web-search autocomplete and Trends autocomplete on the same keyword are buying two different products. Both cost one credit per successful call.
For Trending Now polling costs in the same SerpApi cluster, see SerpApi Trending Now API pricing.
Trends MCP accepts plain keywords on source: "google search" and returns normalized 0-100 weekly series without a separate autocomplete step. Entity disambiguation is the caller's problem: pass a precise keyword or accept blended intent in the curve.
| Plan | Monthly price | Included requests |
|---|---|---|
| Free | $0 | 100 |
| Starter | $19 | 1,000 |
| Pro | $49 | 5,000 |
| Business | $199 | 25,000 |
One get_trends call with source: "google search" and keyword: "Stripe" equals one request. The response includes roughly five years of weekly value and volume fields where available. Cross-platform checks add sources in separate calls or comma-separated get_growth source lists, still counted per source plus keyword.
For the 50-brand batch (Google Search only, no entity resolution step), Trends MCP Starter ($19, 1,000 requests) covers 50 lookups with headroom. SerpApi Starter ($25, 1,000 credits) needs 100 credits if every brand requires autocomplete plus timeseries.
Neither approach is universally cheaper. SerpApi wins when the workflow demands Google's exact entity-level Trends curves and the team already pays for SerpApi on other engines. Trends MCP wins when the question spans TikTok, Reddit, YouTube, or Amazon in the same JSON contract and literal keyword series are enough.
SerpApi autocomplete fits pipelines that must map ambiguous terms to Knowledge Graph topics before charting. Brand monitoring for names like Delta, Target, or Meta benefits from entity IDs that filter out unrelated homonyms. SEO teams comparing topic-level curves across Google's category taxonomy also need the resolution step.
SerpApi autocomplete is a poor fit when every keyword is already unique, when the budget counts credits per lookup and the batch is large, or when the research question requires signals outside Google. Paying two credits per keyword for Google-only resolution, then wiring separate vendors for TikTok and Reddit, stacks cost faster than a multi-source API with one request shape.
For the broader vendor comparison, see the trend data API pricing comparison. For Google-only pricing across pytrends and official alpha access, see Google Trends API pricing comparison.
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