Mailwarm increases your email deliverability by raising your sender reputation. It warms up, increases the positive actions & keep your email activity flat. Emails are sent from your account to Mailwarm: they're put out of spam, opened, starred & replied.
This is the 2nd launch from Mailwarm. View more
Mailwarm 2.0
Launched this week
Most founders rely on email to grow, but emails don’t land in the inbox by magic. Mailwarm 2.0 is the premium email warmup and deliverability system built to give your emails the best chance of reaching the inbox. It combines automated warmup, real engagement, monitoring, infrastructure checks, and experts call available for every subscriber.
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Hey Thami,
Cool launch! Quick question: do you see Mailwarm as something companies should use long term or only when launching on new domain?
Mailwarm
@bhouy To be honest, this has been one of our biggest challenges.
When we launched Mailwarm 6 years ago, “email warmup” was barely a known category. But the word warmup makes people think it’s only for the beginning, like a short-term setup step.
After seeing thousands of senders over the years, our view is different: warmup is useful long term to keep positive engagement and protect sender reputation. Or at least, it should be reactivated when reputation drops or before scaling a new campaign.
So I’d say: new domain = warmup is critical. Existing domain = warmup + monitoring is how you avoid silent reputation drops.
Are you asking because you see warmup as a one-time setup, or because you’re thinking about long-term deliverability?
@thamibenjelloun I totally get the challenge because for me warmup implies once and done. I do care about long term deliverability of course, but I have to admit I'm not sure why I would need a warmup tool for that.
Mailwarm
@bhouy Benjamin, that’s the perception we need to change.
Warmup is not only “get the domain ready once”. It’s more like reputation maintenance.
If you already send, Mailwarm keeps creating positive inbox interactions around your inboxes so your sender reputation stays healthier over time. It does not replace good sending practices, clean lists, or relevant emails, but it adds a consistent trust signal to the providers, in the background.
The way I see it:
New domain: warmup helps you start safely.
Existing domain: warmup helps you recover and improve reputation.
Scaling campaign: warmup helps reduce the risk of a sudden reputation drop.
So the real question is not “do I need warmup forever?”
It’s more: “how much reputation protection do I need based on my sending volume and risk?”
Are you currently sending cold emails regularly, or more occasional campaigns/newsletters?
Just curious about how long it typically takes to see a noticeable improvement in deliverability? Asking because most cold outreach tools promise inbox placement, but the warm-up window is where campaigns usually stall.
Mailwarm
@arjayyy Usually 3-4 weeks for noticeable improvement, depending on your starting reputation. You're right that the warmup window is where campaigns stall, most tools rush it. Gradual ramp clears placement faster than aggressive volume.
Mailwarm
@arjayyy We get this kind of question every day, and honestly, it’s smart to ask before starting.
It depends a lot on the domain: fresh or aged, past sending history, current reputation, provider, list quality, and how aggressively you start sending while warmup is running.
Some users see strong movement quickly (check this comment with a screenshot : https://www.producthunt.com/products/mailwarm?comment=5426071).
For example, this account went from:
First test: 75.64% spam
Previous week: 19.72%
Current week: 13.61%
Another went from 54.55% spam to 7.29%, then slightly up to 12.14% once campaigns started, which is normal because real sending behavior also affects reputation.
So warmup is not magic. It improves the reputation layer, but your actual sending setup and behavior still matter.
What’s your situation: fresh domain, aged domain, or already sending cold outreach today?
Mailwarm
Bonjour Product Hunt 👋
I spent the last 15 years in digital marketing, and a big chunk of that running email at scale at one point, sending over 1.5 million emails a day as an affiliate across more than 30 brands. When you want to operate at that volume, you learn one lesson fast: sender reputation isn't something you set up once. It's something you build, every day, with behavior. And if you don't, perfect DNS, perfect copy, perfect lists won't save you.
That's the gap most teams hit. They configure SPF/DKIM/DMARC, write great emails, build clean lists, and still land in spam. Because reputation isn't a configuration. It's a pattern of activity that inbox providers learn to trust over time. New domains have none of it. Quiet domains lose it. Aggressive senders blow through it.
Mailwarm is what we built to solve that, alongside @bengeekly and @thamibenjelloun. Today is a big one for us; we're launching Mailwarm v2, with real-time reputation monitoring, a smarter warm-up per ESP engine, content warm-up, and more. It's the biggest update we've shipped since launch.
If you have poor email performance, drop your situation in the comments, and I'll dig in.
Excited to launch today 🚀
ProdShort
@othman_katim Bonjour 👋, how long does it typically take before someone sees improvement in their inbox placement rates? Congrats, amazing team !!
Curious how you decide when warmup should taper off vs stay steady—especially for teams whose real sending volume spikes. Any heuristics you recommend for keeping signals “natural” at scale?
Mailwarm
@leventbuilds Great technical question, the transition phase is where a lot of teams accidentally tank their reputation.
In our experience, you shouldn't completely taper off if you are running active campaigns. Instead, you switch from ramp up mode to maintenance.
A good rule of thumb is keeping a steady background signal running, because when your real sending spikes, your domain needs an algorithmic safety net. Those background signals ensure that if a couple of grumpy recipients mark your real email as spam, a steady stream of positive thread interactions is happening simultaneously to balance the scales.
To keep it looking natural to ESPs the key is variance, so staggering the times, randomizing the thread replies, and making sure the engagement mimics actual human workflows rather than a mechanical pattern :)
If Gmail can fingerprint your seed network, doesn't sustained warm-up traffic itself become a negative signal? How do you keep the network from getting flagged wholesale?
Mailwarm
@zanc_zhao That’s a fair concern, Zanc. If a warmup network is small, repetitive, and predictable, it can become a bad signal. That’s why scale, diversity, email provider mix, B2B and B2C emails, rotation, and human-like engagement matter a lot. Mailwarm is built around 50,000+ real inboxes and positive interaction patterns, not the same tiny pool repeating forever.
Warmup only works if it looks like healthy reputation activity, not automation spam.
Mailwarm
@sa206 It can help in both cases, but the approach is different.
For a new domain, the goal is to start clean: warm up gradually, create positive inbox interactions, and avoid damaging reputation too early.
For a damaged domain, warmup can help with recovery, but we first need to understand what caused the drop: reputation, infrastructure, blacklist, content, or sending behavior.
That’s why Mailwarm 2.0 combines warmup, monitoring, checks, and expert review.
Are you asking for a fresh domain or one that is already landing in spam?
How can users separate real-world deliverability lift from your own network's engagement in the dashboard?"
Mailwarm
@sergebulaev great question! It was one of our main worries while building the spam score feature. Does measuring spam score inside our network give an accurate picture of what senders experience in the real world? Are all spam scores fake? These are difficult questions to answer, because of the nature of deliverability.
It's always dynamic, and, inside providers systems, it's dependent on a lot of different unknown parameters that are given to machine learning models to decide.
So, going for a full reverse engineering of the system is quite impossible, which is good, don't get me wrong, spam filters are very useful!
Our approach in dealing with this was statistical.
We asked: what would simulate the real world but inside our system? The most obvious answer was a sender interacting with new mailboxes, since we now have a lot of mailboxes, any sender is sure to be interacting with both new and old ones.
So, internally, we created different spam scores depending on whether the sender already interacted with a mailbox or it's their first time. And we noticed around 3 to 5% differences.
This gave us more confidence in how representative the feature is of the real world. We even created an internal tool for testing the score only without email warm up to further test and find more insights, maybe we'll make it public soon.
But, again, really interesting question, thank you for the walk down memory lane.