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cold email playbook

How we booked ~73 calls with senior execs, from cold email

Some people will tell you C-suite execs don't read cold email. They do. Over ~2 months, for an executive coaching client, just over email.

This is the whole system. Not just what we did, the principles underneath it, real examples, and prompts you can paste into AI to build your own version. Take it.

Max Pidvalnyi, Maxionlabs
~35k
emails sent
~450
positive replies
121
execs registered
~73
calls booked
~47
calls held
~69
sends per positive (winner)

Booked and held are conservative floors, the coaches don't log every call, so the real numbers are higher. First month of sending ran on Instantly, the rest on EmailBison.

the real lever

It was never the volume

The easy read is "they just sent a lot of emails." We didn't. ~35k over two months is small. And the winning angle got a positive every ~69 sends, while a worse angle on the same list needed ~202. Same people, same inboxes. The only thing that changed was the thinking below.

So here are the six things that actually moved it. Each one has the principle, what we did, how you run it yourself, and a prompt you can hand to AI to figure out your own version.

principle 1

Target by intent, not by demographics

"Cold" usually means a list of total strangers who match a job title. Execs ignore that, and honestly so would you. The list that booked 73 exec calls wasn't strangers. It was people who had raised their hand with the brand once and gone quiet over time. Cold in time, warm in intent. That is a completely different email.

what we did
Two pools, two playbooks, never blended. A big pool of lapsed and ex-members who had touched the brand before got the core offer. A small warmer pool of active paying members got a softer, "here's something else we do" framing. A lapsed member and a never-heard-of-you stranger need a different first line, so they never got the same email.
how you apply it
Before you scrape a fresh demographic list, ask: who already raised a hand once and went cold? Lapsed customers, churned free users, past webinar or event registrants, old inbound that never closed, trial-no-converts. At high deal sizes that pool out-converts a cold demographic scrape every time. If you only have a cold pool, segment it by any prior-intent signal you can find, and write to that signal.
prompt for AIMy product is [X], ACV [$Y], sold to [buyer type]. List 12 audiences who already showed intent once and likely went cold since: lapsed customers, churned free users, past webinar/event registrants, old unconverted inbound, free-tool users, competitor switchers, etc. For each, name the exact signal that proves the prior intent and where I would actually find that list.
principle 2

At high prices, sell the free step, not the product

Nobody buys a 5-figure program off a cold email. So we didn't ask them to. The email's only job was to get the in-market 1 to 3 percent to take a free, low-friction step. A human closed the real thing later, on the call.

what we did
The offer in the email was a free advisor consultation, not the coaching program. The email sold the call. The coach sold the program, on the call, where a long deliberation and a real conversation can happen. Trying to sell the program in the email is why most high-ACV cold goes silent.
how you apply it
Match the friction of your ask to your price. Low ACV, you can pitch the thing directly. High ACV with a long sales cycle, the cold offer is a free value-step the buyer actually wants (a consult, an audit, a teardown, a useful asset), and the sale happens after. If your cold email asks a stranger to buy something expensive, fix the offer before you touch the copy.
prompt for AIMy offer is [$X] with a [Y]-week sales cycle, sold to [buyer]. Design 4 FREE front-end offers (a consult, an audit, a teardown, a genuinely useful asset or list) that an in-market buyer would actually want, and that a human could convert into the paid sale on a call. Rank them by how low-friction the "yes" is, and for each, the one line I would use to offer it.
principle 3

Lead with real urgency, never fake scarcity

"Act now, only 3 spots left" reads as a scam, especially to a senior exec. But a real reason to move now beats "here's our mechanism" by a mile, because it gives the in-market person a reason to act instead of bookmarking you forever.

what we did
The winning angle was built on a real timing fact in their world: the thing they actually want fills up months ahead, so starting now matters. That angle got a positive every ~69 sends. The "here is how our thing works" angle on the same list needed ~202. The urgency was the difference, and it was true, so it held up when they replied.
how you apply it
Find the real clock in your buyer's world. A deadline, a season, a cohort that starts, a capacity that fills, a cost that's about to go up, a window that closes. Lead with that. If you genuinely can't find a real one, do not invent one, go back and fix the offer instead.
prompt for AIMy buyer is [persona] buying [thing]. Give me 6 REAL, defensible reasons they'd act now instead of in 6 months: deadlines, seasons, cohort starts, capacity limits, rising costs, closing windows. No fake scarcity, nothing I couldn't defend if they pushed back. For each, the one line I'd say it in.
principle 4

Write to their worldview, not yours

The buyers here are senior, often in their 60s and 70s, not AI-native. Copy that pattern-matches to a modern SaaS blast, or an AI-coded opener like "Quick thought,", reads wrong to them. It has to feel like a considered note from a peer, not the 4th email in a sequence.

what we did
Every email did exactly two jobs. One, build curiosity about the dream outcome THEY care about. Two, make it believable for someone who hasn't bought yet, with a named example or a real outcome. Nothing else in the email. And the register matched them, an advisory note, not a pitch.
how you apply it
Write to the actual reader. A 25-year-old founder and a 65-year-old exec read completely different things as trustworthy. The two-job rule holds for both though: curiosity (the dream they want) plus believability (proof it's real for someone like them). If a line does neither, cut it.
prompt for AIMy buyer is [persona, seniority, rough age, how sophisticated they are]. Here's my draft: [paste]. Rewrite it in their worldview so it reads like a note they'd actually trust, doing two jobs only: (1) build curiosity about [the dream outcome they want], (2) make it believable for someone who hasn't bought yet. Kill any SaaS-bro phrasing, AI-coded openers, and hype.
principle 5

Test the offer first, and measure the right number

Reply rate lies. It counts "not interested" replies and tire-kickers. The number that ties to money is sends-per-positive, how many emails it takes to get one genuinely interested reply, because that walks straight to cost-per-booked-call and CAC. And the biggest lever on that number is the OFFER, not the prose. A different offer can move it 3 to 5x. Polishing copy moves it maybe 20 percent.

what we did
We tested different OFFERS on stable copy, not 4 versions of the same offer. The urgency offer hit ~69 sends per positive, the mechanism offer ~202, same list, same everything else. We read the result on sends-per-positive once there were enough sends to actually mean something, not on a week-1 reply rate.
how you apply it
Pick the metric that ties to cash: sends-per-positive, then cost per booked call. Test different OFFERS, hold the copy stable, and give each one enough sends to read (don't call a winner off 200 emails). Then scale the winning offer, and only then start fiddling with copy.
prompt for AIHere are my campaign results by variant: [paste sends and positive replies per variant]. Compute sends-per-positive for each. Tell me which is actually winning, whether each has enough volume to be significant yet, and whether the variants differ on the OFFER or just the copy, because only an offer difference is worth scaling.
principle 6

Clean the list ruthlessly, it's part of the result

A real chunk of why this worked is what we did NOT send. Unsubscribed people, dead addresses, gateway-protected inboxes, bots, typos. They tank deliverability and convert zero, and a single spam flag can block a whole company.

what we did
Never emailed an unsubscribe (they were ~30 percent of the pool and converted 0). Dropped secure-email-gateway-protected cold addresses instead of pushing into them. Re-verified every address before load with Reoon and BounceBan. Filtered obvious bot and typo signups out quietly.
how you apply it
Before any send: strip unsubscribes, re-verify the whole list, drop gateway-protected cold addresses, kill obvious bot and typo addresses. A smaller clean list beats a bigger dirty one every time, on deliverability and on results.
prompt for AIHere's a sample of my cold list: [paste / describe]. Give me a pre-send hygiene checklist: exactly what to strip (unsubscribes, role accounts, secure-gateway domains, bots, typo domains), which verification tools to run, and the order to do it in, so I protect deliverability and don't burn the domains.
the email

The actual winning email, as a fill-in template

This is the real winner from the campaign, the one that got a positive every ~69 sends. I stripped out the client-specific bits and left brackets for you to fill. Keep the structure, that's the part that worked: a real timing reason up top, a prior-intent hook, a free first step, and the ask is a link to a call, never the program.

Map it back to the principles. Line 1 is the real urgency (principle 3). "Since you're already [...]" is the intent hook (principle 1). The free consult is the front-end step, the email sells the call not the program (principle 2). And the whole thing is one curiosity beat plus a soft ask, in their language (principle 4). If you run a follow-up, it just adds one proof point (a named example for someone like them), it never flips to a new pitch.

honest part

When this works, and when it doesn't

This works when the deal size is high, the sales cycle is long, there's a pool with some prior intent, and there's a human who can close on a call. It does not work for a cheap transactional product, a pure-cold demographic list with zero prior intent, or a team with nobody to take the calls. If that's you, the fix is the offer and the targeting, not more emails.

If you'd rather we just run it for you

This is what we do done-for-you at Maxionlabs, the targeting, the offer, the copy, the infrastructure, the whole engine. We take it off your plate and you only deal with the qualified calls that land.

Reach me at maxionlabs.com or on X @marioleads. Either way, the playbook above is yours, run it.