Results at a glance

• 30 meetings booked from 131 leads, so 22.9% of every lead generated reached a meeting

• A settled channel verdict: LinkedIn produced 63% of all leads and most of the accounts at meeting stage

• 41 accounts carried forward live at close, 19 of them at meeting stage

A buyer you can find by title.

This client is an AI-powered recruitment company, hiring for employers across IT and technology, customer experience, BFSI, healthcare, retail and manufacturing, and selling a set of AI hiring tools alongside the core service. Its buyer is whoever owns hiring inside a company. That person has a title, a public professional profile and a phone number, which makes the account reachable on two channels at once.

That turns the interesting question from whether we can reach them into which channel actually books the meeting. So we ran both against the same accounts and let the volume answer it. LinkedIn opened the programme, cold calling scaled from the third month, and four and a half months of matched data settled the argument.

Where they were

• One channel live, with LinkedIn running alone through the opening two months

• No benchmark for what a dial is worth against a connection request

• A third channel opened and never sent against

• No segment-level read on which part of the ICP converts

• No account-level follow-up instruction coming back from the client

Three compounding systems.

• Segmented list engine. Every lead tagged to one of three ICP definitions at the point it entered the tracker, so segment concentration was readable while the campaign ran rather than after it. One segment alone produced 73 of the 131 leads.

• Two channels, same accounts. LinkedIn as the volume engine at 1,712 connection requests and 594 accepts. Cold calling as the direct-contact engine at 3,328 dials into 493 live conversations. Running both against one target list is what made the comparison real rather than theoretical.

• Outcome logging and a client feedback loop. Every call logged by what actually happened, whether positive, negative, wrong person, wrong number or no answer, and every account carrying a status and a follow-up instruction collected back from the client. 23 accounts were explicitly cleared for another touch.

What changed

• Two channels live and measured against the same accounts

• Per-channel lead rates established at 4.8% of LinkedIn requests and 1.5% of dials

• 131 leads and 30 meetings from 5,040 outreach touches

• One ICP segment identified as carrying 56% of the pipeline

• 50 accounts carrying an explicit follow-up instruction, 23 of them cleared and warm

Two channels, and the split is not close.

LinkedIn produced 63% of all leads, converting 4.8% of requests sent and 13.8% of accepted connections, and it held a steady three to eleven leads a week from the first month onward. Cold calling reached 493 people and turned 48 of those conversations into leads, but only 14.8% of dials reached anyone at all.

Read as a conversion problem the phone looks weak. Read as a reach problem, with almost one in ten connected conversations becoming a lead, it says the dial list needs better numbers rather than a better script. Across the programme that works out at roughly one meeting for every 170 contacts approached, which is the planning number the next cycle gets built on.

The numbers

• 131 Leads generated

• 30 Meetings booked

• 5,040 Outreach touches

• 1,087 People engaged

• 63% Of pipeline from one channel

• 41 Accounts live at close

Engagement

• Client: AI-powered recruitment company

• Industry: Recruitment services

• Market: India

• Engagement: Roughly four and a half months, 2026

• Channels: LinkedIn · Cold calling

• Personas: Talent leadership · Hiring managers · Founders

• Services: SDR as a Service · List Building & ICP Segmentation · Appointment Setting

• Focus: Business Services · Recruitment · Two Channel