API reference · Developer guide
Explore an SEO report, finding by finding
See the evidence, the exact JSON fields, and the decision they support. Start with a real report before connecting the API to your application.
From a report field to a useful decision
This saved example analyzes our SEO API comparison page for best seo api in the US. Choose a finding to see how its data supports an application feature.
A missing term becomes a question to investigate
What the report says
The report marks testing as missing. Its target count is zero, and seven of ten comparison pages contain it.
How to use it
Inspect the reliability section. A practical provider-testing method would help readers evaluate the APIs being compared.
The recommendation is an editorial decision. The API does not provide the paragraph to change or an instruction to repeat the keyword.
entity_coverage.natural_language_entities + competitor_term_coverage
{
"entity_coverage": {
"natural_language_entities": [
{
"entity": "testing",
"importance": 4,
"coverage_status": "missing"
}
]
},
"competitor_term_coverage": {
"domains": [
"dataforseo.com",
"seoprofy.com",
"analytify.io",
"nimbleway.com",
"apyhub.com",
"serpapi.com",
"coherentmarketinsights.com",
"botsify.com",
"position.digital",
"seranking.com"
],
"terms": [
{
"keyword": "testing",
"importance": 4,
"your_url_count": 0,
"competitor_counts": [
0,
2,
2,
2,
1,
0,
1,
0,
1,
1
]
}
]
}
}Use the same data in your own application
Download the selected response fields to follow the example locally. The file retains the entity matrix and selected score, structured-data, and originality findings used here. It is an excerpt, not the complete report.
The API supplies observations. Your application adds thresholds, priorities, editing suggestions, and approval states. Keep those decisions separate so users can understand why a recommendation was made.
- Interpret entity coverage and missing topics, including the difference between a missing term and wording already present.
- Build an information-gain research brief using original-data and similarity findings.
- Build a content optimizer with runnable JavaScript and Python clients.
- Read the report schema for section availability and response formats.