Apollo.io Reviews

1. michelleturner

   · Managing Director at Nuvoro Digital · 11 months ago
   Apollo for automated outreach

   We use Apollo with our Sales and BDR team to manage our cold outreach. The strength of the platform is the sequences and cadences that you can set up. Compared to other tools we have used in the past like Salesloft the UI is much easier to navigate. The main limitation is that the quality of data isn't as vast and often I can find prospects on Linkedin but not in Apollo.

   🏁 Competitors: SalesLoft

   👍 Pros:    Creating email sequences|Ab testing of emails|Good user experience

   👎 Cons:    Data quality is lacking sometimes|Onboardin process was cumbersome

Linear Reviews

Apollo.io mentions (69)

• Enriching Free Trial Signups: The PLG Data Stack for Turning Inbound Users Into Qualified Pipeline

  Personal email domains destroy this. Clearbit's Enrichment API returns a null company when it hits gmail.com. Apollo routes personal domains straight to a consumer bucket and skips B2B fields entirely. Even PDL's /person/enrich endpoint — the most permissive of the major providers — gives you around 32% hit rate on Gmail addresses versus 74% on corporate domains. I measured this across 6,200 signups for a... - Source: dev.to / 3 months ago

• Clearbit Is Now HubSpot-Only: A 1-to-1 API Migration Map for Teams Getting Locked Out

  A few things worth flagging: PDL beats Clearbit's historical rates for US and Western European companies, but drops to ~52% match rate for Japan and South Korea specifically. Apollo underperforms on raw company matching but returns significantly more contacts per domain in Prospector-style queries than Clearbit's Prospector ever did — the tradeoff is more stale titles in the result set. Hunter.io is fast and cheap... - Source: dev.to / 3 months ago

• Auto-Enriching Your CRM on New Contact Creation: A No-Code Webhook Playbook

  One thing comparison guides consistently get wrong: Clay is not an enrichment API. It's a waterfall orchestration tool that calls People Data Labs, Apollo, Clearbit, and others in sequence for you. It's useful, but it adds 2–8 seconds of latency per row in my runs and costs more per match than going direct. For a CRM webhook flow where you need sub-second enrichment calls, Clay is the wrong layer to hit first. - Source: dev.to / 4 months ago

• How to Build an OSINT-Powered B2B Prospecting Workflow in 2026 (Without Getting Banned)

  Last year I ran the same LinkedIn Sales Navigator export through three enrichment APIs. Apollo matched 61% of the emails. Hunter.io matched 54%. An OSINT-first pipeline I'd built in n8n — pulling from public sources before hitting any paid API — matched 79% and cost roughly $0.003 per contact. The delta wasn't magic. It was sequence. - Source: dev.to / 4 months ago

• LinkedIn Scraping Is Dead: 5 Legal, ToS-Safe Alternatives That Actually Work in 2026

  Despite having its LinkedIn Page removed in 2025, Apollo remains a functional enrichment and outreach platform with 275M+ contacts. The free tier includes 10,000 credits and the $49/month basic plan is the cheapest entry point for a combined enrichment-plus-sequencing workflow. Apollo's data collection methods have attracted LinkedIn's attention, but the product continues to operate. The risk I'd assign it:... - Source: dev.to / 4 months ago

Linear mentions (162)

• The Tradeoff That Slows Production Teams Down: Flexibility vs Actually Shipping

  Speed matters. Not speed in sprint or linear dashboards. Not speed in story points. - Source: dev.to / 3 months ago

• Freshworks Just Shipped an MCP Gateway Inside Its ITSM Platform. Here's What That Actually Changes.

  Model Context Protocol, for context, is the emerging standard for letting AI agents pull live data from external systems without custom integration code. Freshworks has implemented it as a native layer in Freddy AI, which means agents can now reach into Notion, ClickUp, Linear, Workday, Rippling, and the rest of the enterprise stack — not through brittle webhooks or bespoke connectors, but through a standardized... - Source: dev.to / 3 months ago

• How to Document and Track Technical Debt

  Issue trackers: GitHub Issues, Linear, or Jira work well because technical debt records live in the same tool as feature work. This makes them easier to pull into sprint planning and keeps the debt backlog visible alongside the feature backlog. The main risk is that debt issues get buried under feature issues without careful labeling and triage discipline. - Source: dev.to / 3 months ago

• How to Write a Technical Debt Remediation Plan for Non-Technical Stakeholders

  Linear and similar tools can track velocity metrics per area of the codebase over time, making the before/after comparison straightforward to document. - Source: dev.to / 3 months ago

• Master the in demand of salary negotiation and system design: What Fails

  Most engineers fail salary negotiations because they use vague statements like "I work hard" or "I’m a good teammate" instead of quantified, verifiable impact. After 15 years of negotiating offers, I’ve found that engineers who tie their ask to concrete business outcomes land 30% higher offers than those who don’t. For example, instead of saying "I improved the API", say "I reduced API p99 latency by 400ms, which... - Source: dev.to / 4 months ago