如何在不設定 Google Ads API 的情況下，使用 Apify 的 Google Keyword Search Volume & CPC Checker 取得關鍵字搜尋量與 CPC

If you need Google keyword data for SEO workflows, internal tools, content planning, or automation, the hard part usually isn't the metrics themselves.

It's the setup.

You often need to:

manage a third-party API account
handle authentication
normalize responses
add caching
structure output for downstream tools
make it usable for non-technical teammates

That friction is exactly why we built Google Keyword Search Volume & CPC Checker on Apify.

What it does

The Actor lets you fetch structured keyword metrics such as:

search volume
CPC
competition
competition index
bid estimates
monthly search trends

You provide a list of keywords, choose the location and language, and get structured results back.

No separate DataForSEO account or API credentials are required.

A typical use case

Imagine you already have a list of keywords:

web hosting
seo tools
keyword research
email marketing software
crm software

You don't need another keyword-generation tool.

You just want to know:

Which of these keywords actually have search demand?

And:

How competitive and commercially valuable are they?

That's where a simple keyword-metrics workflow makes sense.

Example input

{
  "keywords": [
    "web hosting",
    "seo tools",
    "keyword research"
  ],
  "locationCode": 2840,
  "languageCode": "en",
  "includeMonthlySearches": true,
  "freshnessDays": 7
}

The Actor can process up to 1,000 keywords per run.

Example output

For each keyword, you can get fields such as:

search_volume
cpc
competition
competition_index
low_top_of_page_bid
high_top_of_page_bid
monthly_searches
cache_hit
fetched_at

The results are structured, so they can be exported or consumed by another application.

Why structured output matters

This becomes especially useful when keyword research is only one step in a larger workflow.

For example:

AI generates keyword ideas → keyword metrics are fetched → low-value keywords are removed → the remaining keywords are used for content planning.

Or:

A customer uploads a keyword list → metrics are enriched automatically → the final dataset is exported to a dashboard.

This is much easier when the output is predictable and machine-readable.

Fresh data vs cached data

The Actor also supports cached results.

If recent data for the same keyword, location, and language already exists, it can be reused instead of making another upstream request.

The output tells you whether a result was served from cache through:

cache_hit: true

You can also control the acceptable cache age using freshnessDays.

If you explicitly need fresh data, set:

freshnessDays: 0

Missing data stays missing

One detail that matters when building automated data pipelines: a missing value should not automatically become zero.

If a provider doesn't return a metric, the Actor returns null.

That makes it possible to distinguish between:

an actual value of zero
unavailable data

This prevents misleading downstream analysis.

When this approach makes sense

This workflow is useful when you:

already have a keyword list
need metrics for dozens or hundreds of keywords
want structured JSON or dataset output
are building an SEO automation
want keyword data inside an AI workflow
don't want to maintain another API integration

It is not intended to replace full SEO platforms like Ahrefs or Semrush.

Those products solve much broader problems.

The goal here is intentionally narrower:

keywords in → useful keyword metrics out.

Try it on Apify

We built Google Keyword Search Volume & CPC Checker as part of DokeLab.

You can try it here:

https://apify.com/dokelab/keyword-metrics-pro

If you're building SEO, PPC, content, or AI automation workflows, I'm also interested in hearing what other keyword-data operations would be useful to expose in this format.

Built by DokeLab.