Our cold email CAC is $70.22. Here's how.

Growing Jungler has been a wild ride. It was born out of a previous startup that didn't work, with the same founding team, including me, carrying through. We pivoted a bunch. Reached profitability.

One evening, after we'd realized that two years of pivots had finally produced something growing organically and that the real job now was to scale it, I happened to start reading Taylor Haren's approach to cold outreach – the man who scaled RB2B to $8M ARR with cold email.

Taylor describes a system where he emails his entire TAM (total addressable market) every 60 days. I borrowed the core idea, adapted it to our own setup, and turned it into our most efficient growth channel, by far. We acquire a new customer for only $70.22.

Now you might be wondering: "Hendrik, isn't Jungler all about finding leads who've shown actual buying intent, rather than messaging your entire TAM? Doesn't this contradict everything you're building?" It doesn't, and I want to walk through exactly why.

We run two motions in parallel. We send highly contextual emails to people who've engaged with specific LinkedIn content, and we email our entire TAM once every 60 days, until they reply. Both matter, and they work for different reasons. Here's how we run them at Jungler.

1. Building contact lists from LinkedIn engagement

Most outbound advice tells you to look for "intent signals". What it doesn't tell you is which of the dozens of available signals actually matter for your product, and why. Only you can figure that out by testing (I'll get to that soon).

The signal with the greatest value we've found for our product is who's engaging with specific LinkedIn posts.

When we layer messaging on top of that signal, our reply rates go up 5x on average. The trick is being specific about which signal you're acting on, because the right message depends on what they engaged with. We split it into four buckets.

Customer engagement

If someone engages with a post from one of our customers, we name-drop the customer in the email and otherwise keep the copy unchanged. That alone moves the needle.

If we have a case study with that customer, we lean harder into it. We describe what we did for them in two lines and ask if they want to see the material. This is almost as good as a warm intro, because they've already built a bit of trust with the customer themselves.

Competitor engagement

The temptation here is to mention the competitor by name, but try to resist the urge. It reads as defensive and slightly desperate. Trust me.

Instead, we shape the email around the specific advantage we have over that competitor. If they're engaging with a competitor that requires users to connect their LinkedIn account, we lead with the fact that Jungler doesn't. The competitor never appears in the email directly.

Our own engagement

I shitpost about GTM on LinkedIn actively. If someone engages with my content, I don't send them a cold email. I send a LinkedIn connection request instead.

If they accept the connection request (about 80% do), they'll stay in my content loop, which will keep nurturing them. Dropping them into a cold inbox instead feels… Excessive, and more importantly, unnecessary.

Thought leader engagement

If someone engages with a thought leader who posts about the problem we solve, we don't change the messaging at all.

The default copy works, because the signal is already doing the work for us – that person is solution-aware or problem-aware before the email even lands, and reply rates climb on their own.

Does it mean that everyone who likes the post is in-market? Of course not. But statistically, the odds are higher than baseline.

It's the same logic of how social media platforms decide which ads to show you. They show ads based on the content you engaged with against more of that same content. You can bring that logic to B2B cold email.

2. Why we still email everyone else

I just described why targeted, signal-based outbound is great. But it has one shortcoming. It leaves most of your TAM on the table.

Our TAM is more than a million people. At any given moment, roughly 3% of them are actively in-market. That's 30,000+ buyers right now. The vast majority of them are not going to leave a public signal at the exact moment they're ready to buy.

If we only emailed the people who engaged with specific posts, visited our website, or raised funding, we'd be leaving most of those buyers to find a different vendor. So we email our entire TAM, once every 60 days, until they reply.

Every touch we send them is a new email, on a new thread. It is not a followup. This part is important.

Followups within a week are annoying and pointless. If the offer wasn't relevant on Monday, sending the same offer on Thursday doesn't change anything.

60 days does two things. First, the prospect's situation might have actually changed – they're in a new role, a budget opened up, a tool they were using broke. Second, they've forgotten that you emailed them last time. So you stay top of mind without burning brand equity by being a pest.

The reason this may seem counterintuitive is that growth teams are always pressured to close prospects asap. That's what the quarterly quota is all about, and that's why most of the cold outbound sequences follow up at least 4 times in 2 weeks.

But if you acknowledge that 97% of your prospects aren't currently ready to buy, regardless of your offer, you'll be able to shift from "How can I close this one prospect as fast as possible?" to "How can I close as much of the total addressable market as possible in 12 months?"

Filter contacts rigorously

Emailing the entire TAM only works if your TAM is… Well, actually your TAM. We filter contacts mercilessly but fairly, before anyone enters the system.

First, we use the standard ICP filters – company size, location, job title, industry. Nothing exotic there.

Second, we have a clear picture of (a) which types of companies actually benefit from LinkedIn engagement signals and (b) who's likely to be interested in LinkedIn prospecting in the first place. We use AI to read each company's description and filter out the ones that don't fit either criterion.

But we also apply filters we've discovered through cold email itself, which is where the system pays back its own learnings. The clearest example: we only email Gmail users. The data from our cold email campaigns was unambiguous – Outlook users were not interested in us at anywhere close to the rate Gmail users were.

The offer matters more than anything

Cold email is a distribution channel, not a magic spell that can trick people to buy something they have no interest in. If your ICP doesn't care about what you sell, no amount of clever sequencing or LinkedIn signal-mining will save you.

Before you write a single email, look at your offer through the eyes of the person receiving it. Would they care? If not, fix that first. Everything else is downstream.

We learned that our offer – giving away the first 2,000 engagers within our free trial – was something our ICP cared about.

Go light on AI personalization

AI-generated personalization can be a gamechanger, but most people use way too much of it. They create paragraph-long intros that immediately tip the recipient off that a machine wrote them. If the personalization signals AI slop, it doesn't give your leads much confidence in whatever you're selling either.

We keep AI-personalization SHORT. One or two keywords about the company, directly related to our offer, woven into the email naturally. In 99% of cases, you genuinely couldn't tell it was AI-generated. If we'd cold email ourselves, those relevant keywords could be "LinkedIn prospecting".

That's the bar. If a human reading the email would notice the AI bit, you're actually hurting your performance. Less is more, by a long way.

The fastest, cheapest way to run GTM tests

If you have a growth thesis, cold email enables you to test it in the most granular, controllable way possible. You not only control the messaging, but also who exactly gets shown that messaging.

This means you can get answers to questions like: how do HubSpot users convert compared to Salesforce users? How do VPs of Sales at 200-employee companies react to Jungler's engagement monitoring vs post monitoring offer?

You can find answers to these questions within a week, for a fraction of the cost and time you'd spend with user interviews or paid media.

What this gets us

The only metric that matters to us is whether the email or domain ends up signing up for a free trial. Out of every email we send, 0.446% convert to a trial signup. Each email costs us $0.024 to send – that includes enrichment, filtering, all of it.

With our trial-to-paid conversion rate, that works out to $70.22 for every new customer who subscribes from a cold email. Ridiculously cheap, as we get the money back on the very first invoice.

The CAC for paid ads in our space would be $500–600 per customer. To see meaningful results, you'd need to invest at least $10,000 just for the pilot. But with cold outreach, you can start with just a few hundred bucks to see how it performs.

We're in the middle of scaling this across the entire TAM. Honestly, I'm not even sure how big our TAM is at this point. What I do know is that the ROI math doesn't leave us a choice – as long as there are more contacts to reach with the same conversion rate, we have to keep scaling. There is no other distribution channel that comes close on efficiency.

A big part of why this works exceptionally well for us is that most of our users prefer to self-serve. They don't need a demo call, they don't need a sales rep walking them through pricing, they just sign up free and start using Jungler. That's what lets us scale outbound this aggressively without piling on sales overhead to match. The volume goes up, the cost per customer stays flat.

Building Jungler so others could do the same

We use Jungler itself (surprise-surprise) to run this. It captures LinkedIn engagement signals automatically and enriches every contact with company and profile data, so we know who actually fits our ICP. Without it, we'd never have the bandwidth to do any of this at the scale we do.

We've built it so anyone can set the signal up in minutes, self-serve. From there, you can push ICP-filtered contacts straight into whatever GTM tool you already run.

What we're shipping in the coming months will make it even simpler, so that anyone can build a hyper-relevant contact list without juggling between dozens of tools. Or skip the UI entirely and plug straight into our API or MCP.

Can't wait to see more teams bend their growth curve with this data, the way we did.