The LinkedIn Outreach Stack
Prospect on LinkedIn, enrich with Apollo, close in a CRM — the modern LinkedIn-first outbound loop.
A scalable LinkedIn outbound system that converts connection requests into booked calls. Built from Dripify, Apollo.io, Close for about $137/mo — the tier each tool actually needs, not the free or headline price. Best for Smb, Solo.
What's in the stack.
LinkedIn outreach automation that runs prospect sequences while you focus on replies.
from $39/mo (Basic) — check pricing
Find prospects, verify contact data, and run outbound sequences from one platform.
from $49/mo (Basic) — check pricing
A CRM built for outbound sales — built-in calling, SMS, and email sequences.
from $49/mo (Startup) — check pricing
The rationale.
Cold email is getting harder — inbox filters are tightening and reply rates are falling. LinkedIn outbound has different economics: connection request acceptance rates of 20–35% are normal, and a reply from a LinkedIn message carries more social context than an email. This stack is built for LinkedIn-first outbound. Apollo finds and filters the prospects — 300M+ contacts with job title, company size, and funding filters — and verifies contact data. Dripify runs the LinkedIn sequence automatically: connection request with a personalized note, a follow-up message on acceptance, a second message with value or a question. Close captures the replies that become conversations, tracks the pipeline, and handles follow-up calls. The key distinction from the Cold-Email Engine or Outbound-to-Demo stacks: LinkedIn outreach is slower per rep and better for higher-ACV deals where a warm connection is worth more than email scale.
The handoffs.
Filter your Apollo prospect list by ICP (job title, company size, industry, location). Export the list as a CSV including LinkedIn profile URLs. Import into Dripify as a new campaign audience — Dripify reads the LinkedIn URLs and queues each contact for the sequence. Apollo provides the prospect intelligence; Dripify handles the LinkedIn execution.
When a prospect replies to a Dripify LinkedIn message, Dripify fires a webhook on the 'replied' event. Route this via Zapier to create a new Lead in Close with the prospect's name, LinkedIn URL, and reply content as a note. The lead surfaces in Close with context — no manual data entry between platforms.
Where tools overlap.
Where AI speeds this up.
Dripify's personalization variables pull first name and company from your imported list — but AI takes this further. Use Claude to generate 5 connection note variants per ICP segment (each under 300 characters, LinkedIn's limit) and A/B test them across campaigns. Apollo's AI features can suggest similar prospect profiles and surface intent signals. In Close, AI call summaries reduce post-call admin — the rep takes the call; the summary writes itself.
What to watch for.
- LinkedIn's terms of service restrict automated outreach. Dripify operates within LinkedIn's platform in a way that mimics human behavior (rate limits, randomised delays), but automated connection requests remain against LinkedIn's ToS in the strict sense. Understand the risk before scaling — LinkedIn accounts can be restricted if activity patterns are flagged. Most users operate without issue at moderate volume, but this is not zero-risk.
- LinkedIn outreach caps your daily activity: typically 20–30 connection requests per day per account for accounts without LinkedIn Premium, 100–150 for premium accounts. This limits throughput significantly compared to email — LinkedIn outreach is quality-over-volume, not a mass-sending channel.
- Dripify's Basic plan runs one active campaign. If you need to run simultaneous sequences for different ICP segments, the Advanced plan ($59/mo) is required.
- Apollo's contact data is strong for US markets and tech/SaaS industries. Coverage is patchier for EMEA and SMB-level contacts outside major metros — verify a sample of your target list before building the full campaign.
How we scored this stack.
You get the deal, we get a referral — it funds the research. Same tool, often a better price. Full detail on how we make money.
Last reviewed: 2026-06-12
Evidence basis: Documentation Verified
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