1440's $15M decision

This KPI changed how 1440 thought about its business and led them to scale aggressively.

👋 Hi friends -

Welcome to The Newsletter Growth Memo. Twice a month, I share short reflections with my newsletter clients + other operators.

Zero formality, ads, or affiliate links - just a guy sharing learnings from working with media operators doing $25k-$1M+ / month with newsletters.

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Quick note: I’ll be at the Newsletter Conference in NYC on Friday - come find me if you’re there!

I was reviewing questions I’ve gotten this quarter to write today’s letter.

The #1 topic I’m asked about is paid growth - a lot of those questions look unique, but are actually the same thing.

Example of questions since January:

  • Multiple ad-monetized readers doing anywhere between $100k-$5M: How much should I be spending on paid growth + what’s my ROI? 

  • A large personal brand doing $10M+: I’m selling XYZ info product and organic is slowing down, will running paid to the newsletter work?

  • A subscription newsletter client @$300k/year we’re doing email nurture for: I’ve got X people paying for my newsletter subscription, is that good… can I run paid to that?

What do these have in common?

These are all secretly LTV questions. You don’t really need me for these Q’s - they’re just math that boils down to:

  1. How much is a subscriber worth?

  2. What can you acquire a subscriber for from paid ads?

  3. Is the return on that sufficiently high in a short enough time?

So I want to spend the next 5 minutes:

  1. Talking about how company-defining tracking LTV can be (with 1440 as the example)

  2. Showing you how to calculate it

LTV is the single most important metric in your business

Let me give you an example from a catch-up I had with Tim Huelskamp (1440's CEO) on Friday:

1440 was at a $20-22M revenue run-rate last year when I got to know them and is on track to do well above that this year.

Tim came from the private equity world.

Those people make a lot of money - at the vice president / principal level, the opportunity cost of pursuing a startup for even 2-3 years is over a million dollars.

It’s obvious now that 1440 is a breakout success.

What I wanted to know: How did Tim know it back in 2017/2018 and leave finance to go all-in?

It came down to unit economics:

  • 1440 has a $20+ LTV (over years)

  • The majority of subscriber churn happens in the first 90 days - Tim knows quite quickly what a subscriber will be worth

  • They acquire subscribers at $2-3 each ($1/each back in the day)

Tim was staring down a 10-20X ROAS in the early days. He knew he could aggressively scale.

And so he raised money to go from 50k → 500k subscribers (debt, not venture).

Had they not made a data-based call to raise money, Tim believes 1440 would be a third of the size it is today.

That makes their good decision worth $15M+ every year.

LTV-based decision-making sounding pretty valuable right now?

Damn straight it is

The problem is that almost no one I meet tracks it often or accurately.

Let’s crack open calculating LTV

Generally, LTV is calculated as:

LTV = ARPU × Subscriber Lifetime (usually months)

But ARPU (Average Revenue Per User) means completely different things based on your business model:

  • Subscriptions: ARPU = conversion rate × subscription price

  • Digital Products: ARPU = conversion rate × average order value × number of orders

  • Ad monetization: ???

Ad monetization is way trickier!

Nobody's published a formula because the consumer doesn’t buy anything from you - your sales team sells attention.

Here's what you need to track in a nutshell:

  1. Cohort behavior - follow just the group that signed up in, say January 2024, over months and months

  2. Email opens per user in month 1, 2, 3 and beyond (will decline quickly and then plateau)

  3. Revenue per email open based on your CPM (more on that in a second)

A Step-by-Step LTV Calculation

Tim's got a great business model at 1440.

The average person opens 15 emails out of the 25 they send per month (60% open rate).

To calculate your own LTV, you need to think about open rates over time.

For 1440, most of the drop-off happens in the first 90 days, then it's pretty flat.

I don’t have all of Tim’s numbers, but here's a real example from a 7-figure newsletter my agency works with:

(Note: We’re not looking at a single cohort over time here, which is why the data is so lumpy - each bar is a distinct cohort of readers, but let’s just roll with it for simplicity)

You can see their open rate starts around 45% and never drops below 35%.

For our calculation example, let's say:

  • Open rate starts at 45% in month 1 (M1)

  • Declines to 40% M2, 37% M3, and 35% in M4 onward

  • You send 25 emails per month

  • Your CPM is $40 ($0.04 per open)

Here's the math:

Month 1:

  • 25 emails × 45% open rate = 11.25 opens

  • 11.25 opens × $0.04 = $0.45 revenue

Month 2:

  • 25 emails × 40% open rate = 10 opens

  • 10 opens × $0.04 = $0.40 revenue

Month 3:

  • 25 emails × 37% open rate = 9.25 opens

  • 9.25 opens × $0.04 = $0.37 revenue

Month 4+:

  • 25 emails × 35% open rate = 8.75 opens/month

  • 8.75 opens × $0.04 = $0.35/month

LTV After 12 Months:

  • Months 1-3 = $1.22

  • Months 4-12 = 9 months × $0.35 = $3.15

  • Total: $1.22 + $3.15 = $4.37

LTV After 24 Months:

  • Add another 12 months at $0.35/month: $4.20

  • Total: $4.37 + $4.20 = $8.57

So in this example, your 2-year LTV is ~$8.50 per subscriber.

Practical Applications

Now you can make smarter decisions:

Maximum subscriber acquisition cost:

  • If your LTV is $8.57, you probably shouldn't spend more than $2.00-3.00 acquiring subscribers

Fast validation of business model:

  • Low LTV? Time to add new revenue streams or, if you’re early in the newsletter game, potentially pick another niche entirely

  • High LTV? Time to scale acquisition - back up the truck!!

Common Pitfalls That Hurt LTV

Gross vs. Net revenue: Bulk discounts of 10-15% for anchor sponsors are standard. If your published CPM is $40 but you give 15% discounts all the time, your actual CPM is only $34 and your revenue per open 0.034, not 0.04.

Static vs. Dynamic pricing: Most newsletters have a flat rate card they update quarterly.

This is a problem for two reasons:

  1. You're delaying LTV capture - each new subscriber you acquire is technically worth $0 until you update your rate card.

  2. Most subscriber churn occurs in the first 3 months. So you've got a portion of subscribers you'll never make a single penny on.

A better way is dynamic pricing - my understanding is 1440 does / did a version of this.

Clients agree to a CPM and get charged based on the number of opens when the send goes out. Every subscriber is monetized as soon as they join the newsletter.

Weekly vs. Daily newsletters: Weekly newsletters struggle with sponsor-only models - it’s not enough sends to create a $1M+ sponsor sale business even with $100+ CPMs.

You need backend LTV from products and services.

How To Boost Your Newsletter LTV

Two ways (broadly):

  1. Improve your sponsor performance: Advertisers will then pay you more. I’ve written a guide on this here

  2. Build a back-end media mullet: events, custom content, subscriptions, etc. - I write about what the top newsletters are doing here

How do you choose between projects that raise LTV?

The #1 way is to listen to your customers and give them what they want.

Make your content undeniably good so you get 1440-level open rates and customers who provide you 24/7 feedback.

1440 has some of the best sponsor performance in the industry and famously doesn't use images in its newsletter.

That came from emailing with readers who said photos got in the way of them reading/scanning the content.

Run through walls to talk to your readers - email them, survey them, get on calls with them.

I get to cheat a bit here - I run an agency and so, part of my business model requires I am constantly on calls with clients + readers.

When people like a newsletter topic, they tell me!

For most newsletter operators, it's easy to forget this when you hit 100K or 1M subscribers.

Better data = better decisions.

Alright, I’ve kept you too long.

That’s the letter.

- Nathan May

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