How to benchmark your newsletter against competitors

Most newsletter benchmark reports hand you one number and call it insight. A 37% open rate. A 2% click rate. That figure is fine for a board slide and close to worthless for a decision. The skill that changes your sends is knowing how to benchmark your newsletter against competitors, the three to five publications fighting for the same inbox attention you are, instead of against a mean pulled across every industry on earth.

Here is the uncomfortable part. The industry average is the most quoted and least useful benchmark in email. This article walks through why, which competitor metrics you can read from the outside, which ones you can only estimate honestly, and a six-line scorecard you can fill in this afternoon.

Why the industry average is the wrong benchmark

Picture the 37% trap. A report tells you the average newsletter open rate is around 37%. You sit at 41%, so you relax. The problem is that the average folds nonprofits, retail, B2B SaaS, and local news into one figure, and those audiences behave nothing alike. A 41% open rate is strong in ecommerce and middling in tight-knit B2B. The number told you nothing about your own race.

We see this every week in our own data. Across the B2B SaaS newsletters Newsletrix tracks, estimated open rates run from the high 20s to the low 50s, a spread north of 20 points inside one niche. The gap between the top and bottom of a single category is wider than the gap most operators fixate on between themselves and the industry mean. Chasing the average is chasing a figure that matches no publication you are competing with.

So stop benchmarking against an industry and start benchmarking against a roster. Pick three to five publications that compete for your reader: same topic, same rough audience, ideally the ones your subscribers also open. That roster is your benchmark. Everything below assumes you have named those rivals first, because a benchmark without names is just trivia with a percent sign.

What you can observe and what you can only estimate

Here is where competitor benchmarking quietly cheats. People claim to know a rival's open rate. You cannot. Open rate is private data sitting in someone else's platform, and Apple Mail Privacy Protection has made it murky even for the senders themselves. Being honest about what is observable versus what is estimated is the line between intelligence and guesswork.

What you can observe directly, send after send, is real. You can read their cadence, how often they mail and on which days. You can read the send time their server stamps on each message. You can read the sending platform from link-wrapper hosts and headers, so a Mailchimp list-manage.com link, a Brevo domain, a Substack publication, or a self-hosted SendGrid pipeline each gives itself away. You can read subject-line patterns across a run of sends, the authentication posture including whether they publish BIMI and a strict DMARC policy, and the footer and compliance structure. None of that requires guessing. It requires being on the list and reading the headers. Our guide on how to find what ESP a company uses lists the wrapper fingerprints for the platform column.

What you can only estimate is the engagement layer: open rate, click rate, subscriber count. You triangulate these. A newsletter that mails daily with heavy ad inventory is signalling list size. A sudden shift to re-engagement subject lines hints their opens are sliding. You can bracket a competitor inside an industry benchmark range, but you should never write down a rival's open rate as if you measured it. Estimate it, label it as an estimate, and move on.

The clean rule we use: deliverability you can test, engagement you can only infer. Run a competitor's domain through a DMARC checker and you have a fact. Claim their click rate to two decimals and you have fiction. Keep those two columns separate on the scorecard and the whole exercise stays defensible.

A six-metric competitor benchmark scorecard

You do not need a data warehouse for this. Six metrics, one row per competitor, one row for yourself. Score each on a simple scale or just record the raw value, then read down the column.

• Send cadence and the specific days each rival mails.
• Send-time cluster, the hour band their messages tend to land in.
• Subject-line shape: average length, emoji rate, question versus command.
• Sending platform, read from link wrappers and headers.
• Deliverability authentication: SPF, DKIM, DMARC policy, and BIMI presence.
• Content format: curated links, single essay, or a hybrid.

Fill the six rows for each rival, then add your own. The value is not the individual cells, it is the column read. If four of your five competitors mail Thursday and you mail Monday, that is either a deliberate edge or a blind spot, and the scorecard forces you to decide which. If every rival publishes DMARC at p=reject and you sit at p=none, you have found the cheapest deliverability win on the board. To pressure-test your own subject lines against the patterns you log in the third row, run a few through our newsletter subject line tester before you commit to a send.

Two of these rows have full guides behind them. For the timing column, our competitor send-time analysis covers how to turn a month of timestamps into a heatmap. And when you need a defensible range for the engagement estimate, our newsletter open rate benchmarks give you the per-niche bands to triangulate against rather than the all-industry mush.

Reading the gap: a worked example

Say you run a weekly B2B SaaS newsletter that goes out Tuesday at 9am. You build the scorecard for three rivals. Two of them mailed Tuesday mornings in January. By March, both had moved to Thursday at 6am. Your column did not move.

That single gap is worth more than any open-rate estimate you could have scraped. Two competitors independently shifting to early Thursday is a sign they ran the test and liked the result. It does not mean you copy them, audiences differ, but it does mean you owe yourself a send-time test before you assume Tuesday 9am is still your best slot. The scorecard turned a vague hunch into a specific experiment.

Now layer the platform column on top. Suppose one of those rivals also moved off a free Mailchimp tier onto a dedicated SendGrid setup in the same quarter. A platform migration paired with a cadence change rarely happens by accident. It usually means a new hire, a budget, and a push to scale the list. That competitor just told you they are investing, and the scorecard caught it without a single leaked metric. For the structured version of this read, our competitor email marketing analysis walks through turning these signals into a plan.

I will say it plainly: benchmarking your newsletter against an industry average is close to malpractice for anyone who has named competitors. It feels rigorous because there is a number attached, but it points you at a fiction. The gap that matters is always against a roster you can name, on metrics you can see for yourself.

How often to re-benchmark

Benchmarking once is a snapshot. The value compounds when you re-run it on a schedule. Two cadences work for most teams. Re-score cadence, send time, platform, and content format quarterly, because those shift slowly and a quarter is enough to catch a real move without chasing noise. Track subject-line patterns monthly, because that is where competitors test fastest and where a new formula shows up first.

There is a real cost here, and I will name it. Manual benchmarking decays. The first month you fill the scorecard diligently. By month three you have skipped two competitors and half the subject lines, and the dataset has holes exactly where the trend lines should be. The honest tradeoff is between a free manual process you will abandon and an automated tracker that keeps the dataset complete whether or not you remember to check. We built Newsletrix because we kept abandoning our own spreadsheets. If you want to see how an always-on tracker compares with a pure benchmarking tool, our Newsletrix vs Panoramata breakdown lays out the difference.

Start narrow. Name three competitors before lunch, fill the six rows for their last four sends each, and find the one column where you are the outlier. That gap is your next test. The roster grows from there.

Frequently asked questions

How do I benchmark my newsletter against competitors?

Name three to five direct competitors first, then score each on observable metrics: send cadence, send time, sending platform, subject-line patterns, deliverability authentication, and content format. Add a row for your own newsletter and compare the columns. The goal is to find the metric where you are the outlier, not to match an industry average. Treat engagement figures like open rate as estimates, never as facts.

Can you see a competitor's open rate?

No. Open rate is private data inside the competitor's email platform, and Apple Mail Privacy Protection has made it imprecise even for the senders themselves. You can estimate a range by triangulating from send frequency, ad load, and re-engagement signals, then bracketing against per-niche benchmarks. Record it as an estimate and never present a rival's open rate as a measured number.

How many competitors should I benchmark against?

Three to five. Fewer than three and you have no pattern to read; more than five and the manual tracking overhead grows faster than the insight. Pick the publications that compete for the same reader and that your own subscribers are likely to also open. You can widen the roster later once the process is automated.

What newsletter metrics are observable from the outside?

Send cadence, send day and time, the sending platform (from link-wrapper hosts and headers), subject-line length and structure, deliverability authentication such as SPF, DKIM, DMARC and BIMI, and footer or compliance structure. All of these you can read directly by subscribing and inspecting the email. Engagement metrics like open rate, click rate, and subscriber count are not observable and must be estimated.

Is the industry-average open rate useful?

Barely. An industry average folds dozens of audience types into one figure that describes no real newsletter, and within a single niche open rates can span more than 20 points. It is useful only as a rough sanity range when you estimate a competitor's engagement. For decisions, benchmark against three to five named rivals instead.

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