Attribution data CSV
textareaRequired input
Noderan MarketplaceData & Intelligence
Demo ReadyLive E2E verifiedDeterministic~10s
Attribution Quality Checker
Profiles attribution rows for untracked, double-counted, or dark-traffic conversions before spend decisions. Returns structured, review-ready output without triggering any external action.
Profiles attribution rows for untracked, double-counted, or dark-traffic conversions before spend decisions.
Workflow summary
Profiles attribution rows for untracked, double-counted, or dark-traffic conversions before spend decisions.
What is Attribution Quality Checker?
Attribution Quality Checker is a ready-to-run Noderan marketplace workflow for data & intelligence teams. It helps users move from a manual process to a repeatable automation with visible credit cost and app-based execution.
- Who is it for?
- Marketing analytics teams
- What problem does it solve?
- Profiles attribution rows for untracked, double-counted, or dark-traffic conversions before spend decisions.
- How does it work?
- Profiles attribution rows for untracked, double-counted, or dark-traffic conversions before spend decisions.
- How does pricing work?
- 1 credit per run.
- What is the next action?
- Open the app marketplace to activate this workflow, or review credit pricing.
Attribution Quality Checker FAQ
Short answers for activation, pricing, inputs, and execution review.
Profiles attribution rows for untracked, double-counted, or dark-traffic conversions before spend decisions. Returns structured, review-ready output without triggering any external action.
Expected inputs
Demo input
Csv
item,status,score direct 45pct share,review,40 paid search tracked,ready,88 email utm missing,review,35View raw JSON
{
"csv": "item,status,score\ndirect 45pct share,review,40\npaid search tracked,ready,88\nemail utm missing,review,35"
}Output highlights
- rowCount
- columnCount
- headers
- findings
- previewRows
Example result
Row Count
3Column Count
3Headers
itemstatusscore
Findings
Attribution rows include tracking-quality issues flagged for review.Parsed rows are ready for operator review
Preview Rows
1 structured item
View raw JSON
{
"rowCount": 3,
"columnCount": 3,
"headers": [
"item",
"status",
"score"
],
"findings": [
"Attribution rows include tracking-quality issues flagged for review.",
"Parsed rows are ready for operator review"
],
"previewRows": [
{
"item": "Example",
"status": "review",
"score": "72"
}
]
}Use cases
- Trust the attribution before moving the budget.
How it works
- 1
Review the workflow and expected credit cost.
- 2
Connect the tools or inputs required for execution.
- 3
Run the workflow and inspect outputs in the app history.