In June 2024, we took a bootstrapped SaaS founder in Bangalore from zero outbound to 31 qualified discovery calls in 30 days. No paid ads. No referrals. Just a well-built outbound system using Apollo, Clay, and n8n.
This is the exact process. Every step. Every tool setting. Every sequence structure. If you are a B2B founder in India with a defined ICP, you can replicate this.
Why most Indian B2B outbound fails
The majority of B2B cold outreach in India fails for one of three reasons. Either the list is wrong, the message is generic, or the sequence gives up too early. We cover the exact reasons cold email fails in India in a separate post.
What we are building here is a system that eliminates all three failure modes simultaneously. Apollo handles list quality. Clay handles personalization at scale. n8n handles sequence automation and timing.
Outbound is not a tactic. It is a system. If you are doing outbound without this stack, you are working ten times harder for one tenth of the results.
The stack
- Apollo.io — Prospect sourcing, list building, email finding, basic sequencing
- Clay — Data enrichment, AI personalization, firmographic layering
- n8n — Workflow automation, sequence orchestration, CRM sync
- Google Workspace — Sending domain and inbox warm-up
- Notion or Airtable — Campaign tracking and reporting
Step 1: Define your ICP with precision
Before you open Apollo, you need a precise ICP definition. Not "SaaS companies in India." Something like: "Series A or bootstrapped B2B SaaS companies in India with 10 to 80 employees, no dedicated SDR team, and a product that requires a demo to sell."
The more specific your ICP, the higher your reply rate. We have seen ICP specificity alone increase reply rates from 0.8% to 3.1% without changing a single word of copy.
ICP definition template
Company size: 10 to 80 employees. Industry: B2B SaaS. Geography: Bangalore, Pune, Delhi NCR. Seniority: Founder, VP Sales, Head of Growth. Buying signal: Recently hired SDR or posted job for sales role.
Step 2: Build the list in Apollo
Apollo is the best prospecting tool for Indian B2B markets. The data coverage for Indian companies has improved significantly in 2024. Here is the exact filter set we use:
- Job title: Founder, Co-founder, CEO, VP Sales, Head of Business Development
- Company headcount: 10 to 100
- Industry: SaaS, B2B Services, Fintech, Logistics Tech
- Location: India (filter further to city if ICP is city-specific)
- Email status: Verified only — never send to unverified emails
- Last funding round: Seed to Series B if relevant to your offer
Export 300 to 500 contacts per campaign. Larger lists dilute personalization. Smaller lists reduce the statistical likelihood of meaningful reply volumes.
Step 3: Enrich and personalize with Clay
This is where most Indian outbound teams skip a critical step. Clay takes your Apollo list and enriches every contact with live data: LinkedIn activity, company news, funding events, job postings, website copy changes.
Clay then uses that enriched data to write personalized first lines for each email using AI. Not generic AI copy. Specifically trained prompts that reference something real about each prospect.
Clay personalization prompt example
Use the prospect's most recent LinkedIn post or company news to write a 1-sentence opening that references something specific. Never mention their job title. Never say 'I came across your profile.' Reference the actual content.
The personalized first line is what moves reply rates from 1% to 3.5%+. This step cannot be skipped if you want results above industry average.
Step 4: Build the sequence in n8n
We use n8n to orchestrate the full sequence because it gives us more control than Apollo's built-in sequencer. The structure that produced qualified booked conversations:
Email 1: The problem email
Subject: [specific problem] at [company name]. Body: 3 sentences. Name the problem. State what we see in companies like theirs. One soft CTA: 'Worth a 20-minute call?'
Email 2: The proof email
Subject: How [similar company] solved [same problem]. Body: 2 sentences of proof, one result with a number, one CTA.
LinkedIn connection request
No message. Just the connection request. Adds a second touchpoint without inbox noise.
Email 3: The direct ask
One line. 'Would it make sense to spend 20 minutes on this?' Nothing else.
LinkedIn message
Reference email thread. One sentence. Keep it human.
Email 4: The break-up email
'I will stop reaching out after this. If the timing is wrong, no problem at all.' This email historically produces the second-highest reply rate in the sequence.
Step 5: Track and optimize in real time
Use n8n to push all sequence activity into a tracking sheet. Track open rates, reply rates, positive reply rates, and booked call rates. Segment by ICP, by industry, by company size.
The first 100 contacts are your calibration run. After that, double down on the ICP and messaging that is producing positive replies. Cut everything else.
The booked conversations came from 340 contacts. That is a 9.1% call booking rate. Industry average is 1.5 to 2%. The difference is ICP precision plus Clay personalization plus a break-up email that most sequences never include.
What to do after the 30 days
Once the system is running, you have two choices. Hand it to an internal SDR with full documentation and training. Or keep a growth partner running optimization and new ICP expansion. We built this entire stack inside the client's accounts. They own every piece of it.
If you want to see how the full engagement process works and what we build in the first 30 days, the process page breaks it down step by step. The full breakdown of our Outbound Pipeline OS service covers every tool, deliverable, and metric we track. To start with a paid diagnostic, go to contact.
Luma Growth Lab
B2B Growth Systems Agency
AI-powered B2B growth systems agency based in Noida, Delhi NCR. We build outbound pipelines, SEO and AEO systems, and AI automation workflows for founders across India and internationally.