Read the output schema before you read the price.
Field names, nested paths, published schemas and empty values: a practical guide to judging whether a scraper returns the data your workflow needs.
The short answer
The output schema is the most honest description of what a scraper can return. It lists field names and types, but it does not guarantee that every row is populated. Match the schema to the fields your workflow actually uses, then test a small run and measure completeness.
Catalogue and method checked 2026-11-12. See how tools are scored.Two tools can cover the same website and still return different datasets. One exposes a flat table with phone and website; another nests social links and location coordinates. The difference decides whether the export can feed a spreadsheet, a CRM or an agent without a transformation layer.
Flat fields, nested fields and arrays
A flat field is easy to send to a spreadsheet or database. A nested field such as location.lat requires a path when you map it. An array such as emails or socialLinks may contain zero, one or many values, so the downstream system needs a rule for each case.
The field count on a target page is the published schema length. It is useful for comparison, but it is not a quality score. Ten populated fields can be more useful than fifty fields that are mostly empty.
Schema source matters
A schema read from a public build is stronger evidence than a schema inferred from a description. If the publisher does not expose a schema, the catalogue applies a low prior rather than assuming the field exists. That is why some tools rank lower even when their marketing copy sounds complete.
A schema can also change. Treat the check date as part of the evidence and recheck the Store page before you build a production workflow.
Test completeness, not only presence
Run a small sample that matches the real input. Count how many rows contain the fields you need. A phone field present on 20 percent of rows may be enough for one task and useless for another. Record the sample size and date so the judgment is repeatable.
Questions people ask
What does a published output schema mean?
It lists the field names and types the Actor exposes in its dataset. It does not guarantee that every record has a value for every field, or that the field is accurate.
Why do field counts differ between tools for the same site?
Publishers model the dataset differently. One may flatten fields, another may nest objects, and another may include enrichment fields from a second step. Compare the actual paths and types, not only the count.
How do I find a tool with one specific field?
Use the field finder, choose the target and type the field name. It searches the published schemas in the catalogue. If no schema includes the field, do not assume a tool returns it.
Should I choose the tool with the most fields?
No. Choose the tool that returns the fields the workflow uses with acceptable completeness. Extra fields can add noise, cost and schema maintenance without improving the job.
Sources
These sources support the general method on this page. A specific tool's price, schema or access route is on its target page with the check date.
- Apify dataset schema documentation
- Apify Actors documentation
- Data sources and check policy
- Ranking method
Pick the website you need data from
Each website has a route map: every catalogue Actor for it, the fields each one returns, the price per 1,000 results and the official API beside them. Or search all 394 Actors by the field you need.