How to estimate a competitor's newsletter revenue

You can estimate a competitor's newsletter revenue from the outside without ever seeing their dashboard. Every input you need leaves a trace. The list size turns up in their own brag posts and on their signup page, the send cadence turns up in your inbox, the sponsors turn up in the links, and the going rate for those sponsors is more or less public by niche. Put those four things together and the revenue number falls out of plain arithmetic. The mistake most people make is starting and stopping at subscriber count, which is the least reliable number in the whole calculation.

The formula that estimates newsletter revenue

Here is the whole thing in one line. Estimated subscribers times open rate gives you opened impressions. Opened impressions times the niche CPM, divided by 1,000, times ad slots per issue, times sends per month, gives you monthly sponsorship revenue. Nothing in there needs access to their account.

Work an example. A newsletter with 25,000 subscribers opening at 42% puts roughly 10,500 issues in front of readers each send. Two sponsor slots per issue, four sends a month, and a $100 CPM gives you 10,500 times two times four, or 84,000 paid impressions a month, billed at $100 per thousand. That is about $8,400 a month from sponsorship, or just over $100,000 a year from ad slots alone.

One caveat before you take that number anywhere. This estimates sponsorship revenue only. Paid subscriptions, affiliate cuts, and any course or community a publisher sells sit on separate lines you usually cannot see from the outside, so treat the sponsorship figure as one slice of the pie, not the whole pie. For most ad-supported newsletters it is the biggest slice, which is why it is the one worth estimating first.

Where each input comes from without their dashboard

Start with the subscriber count, because it anchors everything and because it is the input people get most wrong. Publishers love a round brag number, and "100,000 readers" on a homepage usually counts every address ever collected, not the active list. We walk through the discount you have to apply, plus the signup-velocity and social-proof signals worth trusting, in our guide on how to estimate a newsletter's subscriber count. Whatever number you land on, carry it forward as a range, not a single point.

Open rate is the input you almost never get to measure, so you borrow it. If you cannot see the real number, substitute the niche benchmark. B2B and fintech lists run higher, big consumer and crypto lists run lower, and the spread between them is wide enough to swing your estimate by half. Our piece on what counts as a good newsletter engagement rate has the bands we use. Since Apple's Mail Privacy Protection inflates reported opens, lean on the conservative end of the range when you are unsure.

Cadence and slot count are the easy ones, because you can just watch. Subscribe with a clean research inbox, let four weeks of issues pile up, and count two things: how many times they send, and how many distinct paid blocks appear per issue. A daily that ships 20 times a month with two slots each is selling 40 placements. A weekly with one slot is selling four. That gap matters more than people expect, and our send-frequency benchmark shows where each niche usually lands.

CPM is the last input, and it is the one that has quietly stopped being a single number. The rate a newsletter charges per thousand impressions now depends almost entirely on niche. In our 2026 sample, B2B SaaS lists ran $90 to $180 with a median around $112, finance landed between $70 and $130, and creator and lifestyle lists sat at $25 to $55. Our sponsorship rates by niche breakdown has the full table, and the sponsorship pricing guide covers how slot position moves the rate inside one issue.

Same list, three niches, three revenue numbers

To see why niche dominates this calculation, hold every other input fixed and change only the niche. Same 25,000-subscriber list, same 42% open rate, same two slots across four monthly sends. That is 84,000 paid impressions a month in every row. Only the CPM moves.

The identical audience earns nearly three times as much in B2B SaaS as it does in a creator niche. If you estimate a competitor's revenue without pinning their niche first, you can be off by a multiple before you make a single other mistake. This is also why "how big is their list" is the wrong opening question and "what do they charge per thousand" is the right one.

Why subscriber count is the wrong headline number

Subscriber count is the number every newsletter prints on its media kit and the number you should trust least. Revenue does not track list size. It tracks opened impressions, which is list size multiplied by the fraction of people who actually open. A big list with a dead open rate is a small list wearing a bigger jacket.

Put two newsletters side by side. The first has 12,000 subscribers in B2B SaaS and opens at 48%, high but normal for a tight professional list. The second has 90,000 subscribers in a broad creator niche and opens at 19%. On subscribers, the second looks seven times bigger and seven times more valuable. On opened impressions per send, the gap shrinks to about 5,760 against 17,100. Then apply the niche CPMs from our sample. The B2B SaaS list at $112 books roughly $645 per slot, while the creator list at a $34 CPM books about $581. The list seven times smaller earns more per slot.

That is the whole argument against headline subscriber counts in one example. We watch operators talk themselves out of pitching a sharp 12,000-subscriber list because a 90,000-subscriber competitor looks more impressive, when the smaller list is the better audience and, slot for slot, the better business. Convert to opened impressions first, then to revenue, and the bragging number stops fooling you.

CPM versus CPA, the adjustment that breaks naive estimates

The formula assumes sponsors pay per impression. A growing share do not. Performance deals price on outcomes instead: a cost per click, often $0.85 to $1.40 in our data, or a flat bounty per signup that runs $25 to $45. When a newsletter sells this way, a pure CPM estimate can miss in either direction, and you need to know which.

A high-intent list that converts well can clear more than its CPM-implied number, sometimes well more, because the sponsor is happy to pay per result and the results are good. A list with soft engagement earns less than the CPM math suggests, because the clicks never show up. You can usually spot performance deals from the link structure, where a tracked redirect carrying a signup or affiliate tag replaces a flat brand URL. Our guide on tracking a competitor's sponsors over time covers how to read those links issue over issue. When you see performance pricing, do not throw out the CPM estimate. Widen the band around it, because you are now guessing at conversion you cannot see.

How wrong your revenue estimate will be, and how to tighten it

Every step in this chain carries error, and honesty about the size of it is what separates a useful estimate from a confident guess. Plan for plus or minus 30% on a good day, and more when you are working from thin signal.

The subscriber estimate is the first wobble. Even with good signals you land in a range, not on a number, and that range flows straight into everything downstream. The open-rate proxy is the bigger problem. Borrowing a niche benchmark instead of measuring the real list is the single largest source of drift, because open rates inside one niche still vary widely between a sharp list and a tired one, and Apple's Mail Privacy Protection has made reported opens noisier since 2021. Get the niche wrong and you are not 30% off, you are off by a multiple.

So tighten the inputs you can observe. Count more issues before you trust the cadence and slot numbers, because a publisher who ran two slots last week might run one next week. Pin the niche precisely, since it sets the CPM and the CPM sets the answer. Tools that store a sender's full history, rather than the snapshot you get from one forwarded issue, turn most of this from guesswork into reading, which is the gap we built Newsletrix to fill. It is also why a flat brand list from a tool like MailCharts leaves money on the table: it shows you who advertised without the cadence that prices the deal. Once you have a defensible band, the Newsletrix AI prompt generator can turn the inputs into a competitive brief you can hand your team. Treat the final figure as a band you rank competitors by, not a number you would put in a pitch deck as fact. Ranked right, even a rough estimate tells you which competitor is the real business and which one just has a big list.

Frequently asked questions

How do you estimate a newsletter's revenue without access to its analytics?

You rebuild it from observable signals. Estimate the subscriber count, apply a niche open rate to get opened impressions, count the ad slots and sends over a four-week window, then multiply by the niche CPM. The output is a sponsorship-revenue estimate, not their full accounts, because subscriptions and affiliate income sit on separate lines you usually cannot see from the outside.

How much does a 20,000-subscriber newsletter make?

It depends far more on niche and open rate than on the 20,000. A 20,000-subscriber B2B SaaS list opening at 40% with two slots across four monthly sends books around $7,000 a month in sponsorship at a $112 CPM. The same list in a creator niche at a $40 CPM books closer to $2,600. List size alone cannot answer the question.

How many subscribers does a newsletter need to be profitable?

There is no fixed subscriber threshold, because profit is revenue minus cost and a free list on a cheap ESP carries almost no cost. On sponsorship alone, a premium niche like B2B SaaS or fintech can clear four figures a month at 10,000 to 15,000 engaged subscribers, while a low-CPM consumer list might need 50,000 or more to reach the same number. Engagement and niche set the floor, not raw list size.

Is CPM or CPA a better basis for estimating revenue?

CPM is the better default for an outside estimate because it only needs reach and a niche rate, both of which you can observe. CPA is more accurate when you know a list sells on performance, but it needs click-through and conversion numbers you rarely have from the outside. When a newsletter clearly runs performance deals, widen your error bar: high-intent lists can clear above their CPM-implied figure, and weak ones fall below it.

What's a realistic margin of error on an outside revenue estimate?

Expect plus or minus 30% at best, and treat that as a floor on the uncertainty rather than a ceiling. The subscriber estimate carries its own error, and the open-rate proxy is the single largest source of drift because you are borrowing a niche benchmark instead of measuring the real list. The estimate is reliable for ranking and comparison, not for stating a competitor's revenue to the dollar.

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