r/EmailOutreach

I’m currently building Scubamail, an email marketing platform, and we’re deciding which integrations to focus on next.

Shopify and WordPress integrations are already done, but I’d love to know what everyone else is actually using in 2026.

Webflow? Framer? Wix? Ghost? Something custom?

Would genuinely help us prioritize what to build next.

One thing I didn’t expect while building a small email workflow tool was how much time teams spend trying to manage outreach replies once conversations start piling up.

A lot of platforms focus heavily on sending volume, but the messy part for us was usually everything after that. Keeping replies organized, avoiding missed conversations, and making inboxes less chaotic for smaller teams.

Still early, but it’s been interesting seeing where the actual friction points are.

Anyone else building workflow or communication tools noticing similar problems?

ok so i been trying to do cold outreach for my thing and honestly every guide i read online is the same recycled stuff. open w a compliment, keep it short, personalize it... yeah no kidding lol

what actually worked for u guys? like real examples or hooks u used that didnt get ignored. also how do u handle follow ups without coming off desperate, i never know when to stop

any help appreciated

not selling anything not pitching a service just dumping what actually moved the needle because im tired of the same hyper personalization gospel getting upvoted every week

for the first few months i drank the koolaid custom first lines for every prospect referenced their podcast appearance mentioned the recent funding round used the smart compliment trick everyone here swears by

reply rate sat at barely 1 percent across hundreds of thousands of sends

then i ran an experiment that broke my brain

i split tested deeply personalized emails against ugly 3 line emails with zero personalization just sent to anyone who matched the icp

the ugly ones pulled 3 to 4 percent

over the next 6 months i scaled that approach past 1 million sends and the number held

here is what i actually learned

1 personalization at scale is a lie the time you spend researching one prospect could send 200 more emails the math never works out unless you are selling 50k acp deals

2 you are not writing to impress you are writing to get forwarded every positive reply comes from someone who either decides or forwards to the decider the email needs to survive a 4 second skim not win a copywriting award

3 the opener is dead weight no hey saw your post no congrats on the milestone no noticed you guys are hiring just first name then the problem in one line

4 the cta does 80 percent of the work worth a quick look or open to a 10 min chat thursday outperforms every fancy calendar embed i tested

template that has been running for months

hi sarah noticed you guys are scaling the sdr team this quarter we plug into your existing stack and book 8 to 12 meetings per rep in the first 30 days without you adding headcount worth a quick look thursday

thats the whole email

no 7 link signature no ps with a case study no loom thumbnail no calendly in the first touch

the boring email wins because every inbox is drowning in clever

happy to share the infrastructure setup domains warmup sending patterns and the spintax in the comments if anyone wants it

ok i need to vent because im about to lose it.

how are you guys actually running cold email and landing in the inbox?? like genuinely asking at this point.

this is my second attempt now. swapped setups, ran variations, threw money at it, followed every "best practice" everyone keeps parroting on twitter and reddit… and im STILL going straight to spam.

and the worst part is this time i did literally everything "right":

• .com domain
• plain text only, no fancy stuff
• warmed up for a full month
• started slow with 2 sends/day and ramped +10% daily
• capped at 27 emails per inbox per day
• 3 google workspace inboxes
• zero tracking
• no links, no images in the first email
• dkim, spf, dmarc all setup through cloudflare properly
• kept warmup running alongside campaigns at 50% reply rate (12 warmup emails per inbox + 15 campaign emails), so even if my campaigns get no replies the inbox still sees activity

and somehow.. still spam lol

here's what the tests are saying:

• Mailreach: 7.9/10
• GlockApps: 25% inbox / 75% spam (lmao)
• GMass test on 5 emails: maybe 1 or 2 hit primary
• my own test across 3 personal inboxes: 1 went to spam (and funny enough it was the one i never even use)

stack im running: saleshandy for sequences, trulyinbox for warmup.

at this point idk what the hell im doing wrong anymore. like ive done everything the gurus said to do.

for anyone actually getting replies and not rotting in spam folders.. what was the thing that finally fixed deliverability for u? im open to anything at this point

Hey everyone, looking for some thoughts on my recent campaign performance.
Setup:

• 2 email accounts per domain
• 10 emails/day per email account
• Domains are ~4 months old
• Started sending after 1 month of warmup
• Targeting max 1 lead per company per day
• Targeting large enterprise accounts, mostly 500+ employees
• Sequence has 3 emails per lead

All inboxes show 100% health in smartlead, and delivery tests show 100% inbox placement to both Google Workspace and Microsoft 365/Outlook.

But the only replies I got so far from the campaign are OOO replies. reply rate 1.5%

the latest campaign metrics. Bounce rate is around 0.6%–0.8%, but actual human replies are almost zero.

What could be going wrong here? Is this likely a targeting issue, enterprise filtering issue, copy issue, timing, or something else?

i wanna run a small test, maybe 30-40 cold emails total just to see which subject lines actually pull replies (testing copy not blasting anyone). problem is everyone and their mom is saying you need to warmup a fresh domain for 2-3 weeks minimum before sending anything or you go straight to spam. but then i see people on twitter saying they bought a 5 year old domain for like $80 and were sending the same day no issues.

is the aged domain thing legit or is it one of those things that sounds good in theory but everyone still ends up in promotions tab anyway? also do you guys actually wait the full 3 weeks or is that just what the warmup tool companies want us to think lol

anyone here actually compared the two? im not trying to scale to 1000/day i literally just wanna send like 10-15 a day for a week to see what copy lands. feels stupid to wait 3 weeks for a test that takes 5 days but i also dont wanna burn money on a domain that gets flagged immediately.

is anyone else watching their AI personalized reply rates fall off a cliff right now

we went all in on clay plus openai about 5 months back first 60 days were the best numbers our team has ever seen booked more meetings than the previous 6 months combined felt unreal

now prospects can smell it from a mile away

"hey noticed your team is hiring SDRs" crickets "saw your post about scaling outbound" crickets "loved your take on the podcast" crickets

so last week i got annoyed and ran our oldest dumbest template from 2023 as a control literally first name company name one line about what we do zero personalization zero AI

pulled 5.4 percent reply rate across 12000 sends

the "hyper personalized" AI sequences pulled 1.6 on the same ICP same week same inboxes 18000 sends

i sat with that for two days because it didnt make any sense

so my honest question is are buyers actually fatigued or am i completely cooked and missing something obvious

because everyone on twitter is still posting clay table screenshots like we havent all noticed the floor giving out underneath us

what are you guys actually seeing in your real numbers not the case study numbers

So I built a tool where I'm able to get emails for 10-20% of the price it costs to buy them from Apollo.

If you wanna know how, read everything below and let me know what you think. 

The way it works is I scrape Apollo data using the Instant Data Scraper Chrome extension. 

All you're doing is collecting all the information for leads except for the emails. 

What you really need is the names of the people and the domain or website for the company they work at. 

Then my tool uses an email verification system and guesses different combinations for what the email could be, using different combinations of the name and the website domain. 

It runs the email verification on all the different combinations and only returns an email to you if it passes all tests. 

It has accuracy of 25-50%.
On average, around 35%.

That means if you scrape a thousand names from Apollo, which is very easy, you get around 350 verified email addresses. 

Downsides
#1 If you have a small ICP/target audience, this is not a way to work because you're missing out on all the emails that would have otherwise returned as unknown if you instead spent credits in Apollo downloading them and then run the verifier.

#2 If you download emails from Apollo or another platform and then run a verifier, you will get a slightly higher rate of emails that pass all verification tests. Let's say you get 350 out of 1000 that pass all verification tests. If you instead download the emails and verify all of them, you might get 450 or 500. 

#3 More work goes into it. You have to manually scrape data using a Chrome extension or something similar, and then handle and process that data. Once you get used to it, though it's simple, and at scale it's certainly worth it, in my opinion. Apollo shows 20 leads per page, and you can go through 100 pages, so you have to do it in batches of 2000 at a time.

Upsides
#1 You pay way less. In Apollo, you can buy 1000 credits for $25. Keep in mind that this allows you to download 1000 emails from Apollo, but roughly 10% of them will fail the verification. Roughly 40% of them will be returned as unknown (Catch-all), roughly 50% will pass all verification tests. So really what you get for $25 in Apollo is like 500 verified emails and 400 unknown emails.
Doing it this way, you can get 1000 verified emails for $3-$5
That's like 80-90% cheaper

#2 This way, the only emails you get are verified and have passed all verification tests, which means they will have an extremely low bounce rate. My average bounce rate on this kind of list is less than 0.1%

#3 This is a good way of doing things if you have a really big TAM, meaning there's no lack of the kind of people you want to email. For example, I'm running campaigns to all founders in Europe and there's over a million of them. I'm not going to be able to email all of them anyway, so I might as well do it this way and get the emails for a cheaper price. Yes, I know additional segmentation gives better results but if you've already done the segmentation and there's more leads than you can email right away, this is a good way to start off. 

#4 It works with leads from any platform as long as you can figure out a way to scrape the names and the websites. It's pretty easy on Apollo if you have a basic plan there. 

Let me know if you would be interested in using this kind of tool at this price point and how many emails would you want to get access to this way 

Been running cold email automation for agencies for a while now.

The problem I kept seeing wasn't deliverability or copy.

It was reply speed.

Agencies running 300-500 active leads/week were sitting on

INTERESTED replies for 4-8 hours because nobody was watching

the inbox. By the time someone responded, the prospect had

mentally moved on.

So I built a webhook listener that connects directly to Instantly.

The moment a reply comes in, it:

- Classifies it (INTERESTED, OOO, Not Interested, Referral,

Wrong Person, etc.)

- Fires a Slack alert within 5 seconds with the reply body

+ suggested next action

- Logs everything to a database for reporting

A few things worth sharing if you're thinking about building

something similar:

**Rule-based classification before AI saves ~35% in API costs.**

Most replies fit clear patterns. "Not interested," "wrong person,"

"let's connect." You don't need GPT-4 for those. Run rules first,

send only the ambiguous ones to AI.

**OOO replies are an untapped follow-up signal.**

Most agencies ignore them. But OOO replies tell you the exact

return date. We auto-flag those for a follow-up on that date.

Easy conversion opportunity that everyone leaves on the table.

**If you're using webhooks, build deduplication in from day one.**

Instantly occasionally fires the same event twice. Without a

processed check, you'll get duplicate alerts and waste API calls.

Learned this the hard way.

Currently running this for a few agencies. Reply speed went from

4-6 hours average down to under 5 minutes.

Happy to answer questions if anyone's building something similar

or thinking about automating reply handling on Instantly or

Smartlead.

I’ve been paying for warmup tools across 3 different domains for almost 4 months now. Every dashboard says my “warmup score” is perfect, but the second I launch an actual campaign to even 40–50 prospects, my deliverability tanks and replies disappear.

At this point I’m starting to think most of these warmup networks are just giant pools of bot-generated engagement that Google and Microsoft already recognize.

What’s confusing is I still see agencies bragging about 55–65% open rates consistently without spending hundreds every month on warmup subscriptions.

So now I’m wondering if the real issue is the backend setup itself:

* SPF / DKIM / DMARC alignment

* Google Workspace reputation

* Outlook tenant health

* Domain/IP separation

* Header configuration

* Sending environment structure

Basically the entire technical foundation.

Is anyone here getting strong deliverability WITHOUT relying on warmup tools anymore?

I’m honestly tired of paying the “agency tax” for software that feels good in dashboards but does nothing in real campaigns.

so ive been getting into cold email lately for my small biz and someone in a discord mentioned puzzleinbox said its good for cold email inboxes.

anyone used them? how are they performing?

Hello fellow cold emailers,

I want to know how can I build a list of multi unit operators in quick service restaurants niche in united states.

I have tried scraping apify, but it didn't work out in terms of volume.

i.e. I scraped a 18k+ business listings and when I grouped them on a number of locations a brand has. It shrank down to around 400 only. And when I tried to find the operator who owns these restaurants, the list shrank even more, because most of the list didn't get the info I was looking for.

Therefore, I am looking for a sure way to build the list with volume and accuracy.

Does anyone have any experience in this niche?

Trying to clean up my cold email setup across multiple clients right now. It technically works, but it's far from clean. Too many moving parts, and it feels like I'm constantly patching things together just to keep everything running.

Curious how others are structuring their setup in a more organized way what's your stack looking like?

I've done cold email for my business for three years now.

Here are some tips for things I've been able to do with Claude Code in the last months that make a giant difference.

When building lists, I start off with a broad company list in Apollo.
Export it for free.
Run it in my AI segmentation tool.
This tool scrapes each website and labels each company yes or no if it matches my ICP or not.
Remove all companies that are "no".
Import the "Yes" companies back into Apollo.
Filter on them and download emails for leads at those companies.
This is a way to get very segmented, specific lists at bulk scale, without doing any segmentation yourself.

I built a similar tool for MX Lookup.
Instead of using email provider matching features in smartlead or Instantly let's say you start off with a list of 10,000 leads, you can build a tool that checks the email provider for all of them. Then if all your sender addresses are Google, you just email all the leads with Google as a provider, giving you a much higher reply rate.

3
Obviously, you need to verify lists before emailing them.
Before I used to just remove all addresses that are returned as failed.
Meaning I would include two kinds of emails in my campaigns.
- Passed all verification tests.
- Unknown. Probably Catch-All.
This meant an average bounce rate of anywhere from 1% to 10%.
In the past months, I stopped including unknown catch-all emails in my campaigns, and now the bounce rate is at like 0,05%.
Obviously, this only works if you have a big TAM and you miss out on a lot of good leads returning from the Verifier as "Unknown".
But in terms of keeping deliverability and reputation clean, this is a great strategy.

I use MailSpot to auto-categorize and write draft replies for all incoming leads showing interest (that's like an email AI service tool).
I don't only do this because I'm too lazy to write the emails myself, but on a typical day I have about 30 follow-up emails to send to various leads that showed interest in the past but then went cold.
The conversion rate of the follow-up for these kinds of leads drastically goes up if you do some account research, researching their company and how your offer relates to them.
This is not something I want to do for 30 leads every day, because even throwing them into ChatGPT, it takes a few minutes per lead on average.
This kind of tool does the account research for you and has a knowledge base of your company, so it's able to automate that process and you can then just proofread the email and send it.