What It Does
- Retrieves partner relationships for a target company domain and outputs normalized partner data.
- Preserves all input columns while adding partner-specific columns (
partner_name,partner_domain,source_url,first_seen_at,last_seen_at). - Supports template variables for dynamic domain resolution per row (e.g.,
@company_domain). - Automatically resolves column name conflicts with numeric suffixes to avoid overwriting existing data.
- Test mode fetches a single page for fast validation before running full-scale enrichment.
🏁 Getting Started
1
Select Vendor
Choose
predictleads as your vendor source (currently the only option).2
Set Company Domain
Enter a static domain (e.g.,
microsoft.com) or use @ColumnName for dynamic row-based resolution.3
Configure Limit
Optionally set the maximum number of partner records to fetch. Pagination is handled automatically.
4
Connect Input (Optional)
Attach a previous node if using template variables, so
company_domain can be resolved per row.5
Run Node
Execute in Test Mode first to preview results, then Standard Mode for full enrichment.
Inputs
🛠️ Required Fields
- Company Domain (✅)
The domain or URL of the target company (e.g.,microsoft.comorhttps://www.microsoft.com).
Why it matters: Determines which company’s partners are retrieved; supports per-row dynamic resolution with@ColumnName.
🎯 Optional Fields
- Limit (⚪️)
Maximum number of partner records to fetch.
Why it matters: Controls data volume and credit usage while ensuring you capture relevant relationships.
Output
- Adds the following partner columns to your dataset:
partner_name,partner_domain,source_url,first_seen_at,last_seen_at - Preserves all original input columns.
- Column name conflicts are resolved with numeric suffixes (e.g.,
partner_name→partner_name_1).
✨ If any partner column name conflicts with your input, a numeric suffix is added automatically to preserve all data.
How It Works
- Validate settings and placeholders (
company_domainmust be non-empty or a valid column reference). - Load input data if template variables are used.
- For each row (or static domain), fetch partner relationships from PredictLeads using pagination.
- Normalize partner data to standard columns (
partner_name,partner_domain,source_url,first_seen_at,last_seen_at). - Merge partner data with input columns, resolving any conflicts with suffixes.
🚀 Example Use Cases & Prompts
| Use Case | Setup or Prompt Example |
|---|---|
| Map partner ecosystem | Fetch partners for microsoft.com to understand alliances |
| Competitive intelligence | Use @company_domain column to enrich competitor list with partners |
| Data enrichment | Add partner relationships to your CRM dataset for richer insights |
✨ Pro Tips
⚠️ Important Considerations
🛠 Troubleshooting & Gotchas
| Symptom | Likely Cause | Quick Fix |
|---|---|---|
| Blank output | No valid company_domain provided | Verify static domain or input column references |
Unexpected _1 suffixes | Column name conflicts with input | Rename outputs for clarity |
📝 FAQ
Can I fetch partners for multiple companies at once?
Can I fetch partners for multiple companies at once?
Yes — use a column with domains (
@company_domain) as input, and the node will resolve each row dynamically.What if a column already exists in my input?
What if a column already exists in my input?
Partner columns will automatically receive a numeric suffix to avoid overwriting.
How does Test Mode differ from Standard Mode?
How does Test Mode differ from Standard Mode?
Test Mode fetches only a single page of results, making it faster and cheaper for validation.
💰 Pricing
| Action | Credit Cost |
|---|---|
| Row-level partner fetch | 1 credit per page |
Credits are consumed per page of results fetched. Using Test Mode helps limit consumption while testing.
Drop this node into your Play to enrich company datasets with partner insights—automatically. 🚀