datawebotExtraction guide
Build an inspectable research dataset
Define the sample before interpreting the market.
01 / INPUTSource list + market + category
02 / YOUR WORKFLOWCollect → audit coverage → summarize
03 / OUTPUTResearch table with limitations
Keep the right fields.
Workflow field map| Field / step | Input | Rule |
|---|---|---|
| Sampling frame | Included sources and scope | Record exclusions and retrieval dates. |
| Comparable unit | Variant, pack and currency | Normalize only with sufficient evidence. |
| Coverage | Completeness and missing fields | Avoid treating accessible records as the whole market. |
02 / Inspect the example
| Variant | SKU | Example price | Example availability |
|---|---|---|---|
| Small / Navy | DEMO-TEE-S-NV | USD 32.00 | Example: available |
| Medium / Navy | DEMO-TEE-M-NV | USD 32.00 | Example: available |
| Medium / Sand | DEMO-TEE-M-SD | USD 34.00 | Example: unavailable |
| Large / Navy | DEMO-TEE-L-NV | USD 32.00 | Example: unknown |
All names, identifiers, prices and availability values are fictional. They do not describe a merchant’s catalog or inventory.
Before you use the output
A small extraction sample does not establish market share, sales volume or demand. Retain the collection method alongside each analysis.
Check one record first.
Start with the smallest useful scope. Compare the returned record with its source, confirm variant identity and inspect missing fields before applying the mapping to a larger dataset.
Keep extraction warnings and the retrieval timestamp with downstream output. When a required field is missing, leave it unresolved or return to the source; do not fill it from an assumption.