Backlinks are still one of the strongest ranking signals, and managing them at scale can be a challenge. I recently automated a bulk backlink export using the SerpSpur Bulk Backlink Exporter API. Here's a script that processes multiple domains at once:
python
import requests
import csv
API_KEY = "your_api_key_here"
def export_backlinks_bulk(domains):
all_backlinks = {}
for domain in domains:
response = requests.get(
f"https://api.serpspur.com/v1/bulk-backlink-exporter?domains={domain}",
headers={"Authorization": f"Bearer {API_KEY}"}
)
data = response.json()
all_backlinks[domain] = data.get("backlinks", [])
return all_backlinks
Example usage
domains = ["site1.com", "site2.com", "site3.com"]
backlinks_data = export_backlinks_bulk(domains)
Save to CSV
with open("backlinks_export.csv", "w", newline="") as csvfile:
writer = csv.writer(csvfile)
writer.writerow(["Domain", "Source URL", "Anchor Text", "Domain Authority"])
for domain, backlinks in backlinks_data.items():
for bl in backlinks[:10]: # Limit to first 10 per domain
writer.writerow([domain, bl["source_url"], bl["anchor_text"], bl["domain_authority"]])
print("Backlinks exported to backlinks_export.csv")
This saved me hours of manual work. I usually combine this with a disavow file generator for cleanup. How do you handle large-scale backlink analysis?
Top comments (1)
Great approach! I've been using a similar automation but with Ahrefs' API—curious how SerpSpur's data quality compares for detecting toxic links. Do you also factor in link velocity trends when deciding what to disavow?