BacklinkScan is backlinkscan is a backlink monitoring tool that tracks new and lost links with daily email alerts. it helps seo managers and site owners identify spammy links through automated disavow file generation and monitors brand mentions across llm platforms. the tool integrates with search console to combine organic keyword data with historical backlink timelines. Closely is closely is a linkedin and email outreach automation platform designed for sales teams and agencies to scale prospecting. it combines a linkedin email finder and phone number scraper with ai-driven personalization to create multichannel sequences that sync directly to crms like salesforce and hubspot. the tool focuses on account safety by mimicking human behavior through smart limits and delays to prevent linkedin bans. Compare their risk scores, pricing, and buyer signals side by side to decide which lifetime deal fits your needs.
| BacklinkScan | Closely | |
|---|---|---|
| Risk Score | 21 | 25 |
| Pricing | Free | Free |
| Free Plan | Yes | Yes |
| Category | marketing-sales | marketing-sales |
| Domain Age | 0 years | 4 years |
| Founder | — | — |
| Location | US | — |
| Last Activity | — | — |
BacklinkScan is a niche SEO tool for monitoring backlinks and brand mentions. While it provides a specific utility for disavowing spam links, the project exhibits significant operational and legal immaturity. The domain is less than a year old, there is no public engineering activity, and the security posture is undocumented. It is a high-risk bet typical of very early-stage indie projects.
Closely is a multichannel outreach tool combining LinkedIn automation, email finding, and CRM syncing. While it has strong social proof via AppSumo, there are critical red flags regarding leadership transparency and infrastructure maintenance that buyers should consider.
BacklinkScan has a lower risk score (21) compared to Closely (25). BacklinkScan shows healthy signals across engineering, leadership, and operations. Consider your specific needs, pricing, and feature fit before deciding.