AI-driven email warmup and spam prevention

“Email isn’t working like it used to.” Sales leaders tell me this all the time. Their teams are struggling to hit quota, blaming email. But a few simple questions reveal why. — Sending from? "Outreach / Apollo / HubSpot" — Main domain? "Yes." — Emails per rep/day? "250." (8-15 reps) — Signature? "1 image, 4 links." — Copy? "Calendar link, hard CTA, use case link." — Who handles deliverability? "No one. IT when accounts get suspended." — Tracking opens/clicks? "Of course! How else would I know deliverability is bad?" — Warming up mailboxes? "What’s warm-up?" — Data source? "Apollo’s "verified" data." 🚩 A major red flag walking. This worked in 2019, maybe early 2023. But now? → ESP filters are brutal → Reps are torching their main domains → Their emails scream automation and get filtered instantly → They’re tracking opens/clicks—metrics that died with Google & Outlook → They’re not even warming up mailboxes → Their data is the same overused, hammered-to-death junk And the worst part? They don’t even realize it. Here’s what actually works: Use secondary domains – Protect your main one. ↳ Buy on Cloudflare Track only replies – Opens/clicks kill inboxing. ↳ Turn off anything that isn't reply rate Cap sending at 30/day per mailbox – More domains, lower volume. ↳ Stop sending too many emails per mailbox/domain Warm up mailboxes ↳ Bare minimum: Instantly.ai. Best: Warmy.io - Email channel. Reliable. Double-verify lists. Bad data = bad reputation. ↳ Use LeadMagic and Emailable Use an SEP built for TODAY’s deliverability – Not outdated playbooks. ↳ Go with Instantly.ai, Smartlead or EmailBison — Cancel Outreach/Salesloft Worried about CRM Data sync? ↳ Let OutboundSync update your Hubspot or SFDC automatically No links. No images. Plain text only. – Avoid spam filters. ↳ Get into the inbox first, that's all that matters Email still works. Just not the way it used to.

I spent 300 hours researching 1,500+ software. Here's how to upgrade your tech stack with AI: 1️⃣ Use AI apps for building leads lists Your ability to put the message in front of the right person is the biggest predictor of your outreach campaign's success. Some AI applications make the process easier by helping you: - Build lead lists - Deeply research prospects - Segment & score prospect Examples include: - Relevance AI Prospect Researcher and Enrichment agents - Clay’s AI Agent and Integration with 100+ data platforms. - Exa’s AI Research & Data Sourcing Agent 2️⃣ Use AI to orchestrate complex workflows Running cold email campaigns used to be fragmented across several platforms and involved moving around .csv files from one tool to another. Workflow builders & AI agents now help you: - Build a list  - Score your leads - Find their Emails - Verify these Emails - Personalise your messaging with AI - And import to leads to a sales engagement platform … all that from a single tool. Examples for these tools include Clay, Relevance AI, Common Room & Unify. 3️⃣ Use AI to improve your deliverability A message that doesn’t get read, doesn’t get replied to. Every year, deliverability is getting harder to crack. Thankfully, a few sending platforms are leveraging AI to help with: - Secondary domains & mailboxes setup - Automated Spintaxxing - Email warm-ups Examples include: Instantly.ai, lemlist & Woodpecker.co. 4️⃣ Use AI to help close your deals We’re still far from seeing AI successfully replacing humans in Google Meet. But the AI bots are already listening to these sales conversations. They already help by: - Taking notes from convos - Surfacing insights from individual conversations - Surfacing aggregate insights from MANY conversations For example, one thing I like to do is ask Attention what our prospects have asked most in our latest 100+ sales conversations. Once I know that, I can address these points in our messaging. P.S: Any unheard-of use case you’ve seen with AI applied to go-to-market?

Smartlead and Instantly.ai integrating inbox spam tests has changed how we are monitoring email deliverability at Growth Engine X. Here’s an overview of what we are doing. First, for those that don’t know, an inbox placement test is when you send a test email to a group of emails that will report back to you where the email landing. Primary, Promotions, or Spam? Now it’s not perfect because your spam filter learns from what emails you mark as spam and obviously these inboxes have never marked anything as spam. So you should know that but I still find these tests useful enough to run now that they are integrated with the platforms. We are now running a test daily at 11 pm EST on all active campaigns and getting the inbox placements. Then, every Tuesday and Friday we will use an internal API to call to list out all inboxes that landed in spam, remove them from campaigns, and tag them so we don’t use them again. We always keep extra inboxes warming for our customers so we will push in the extra fresh inboxes as we remove the ones landing in spam. Everything can be done automatically except selecting the inboxes we will use to replace the ones in spam which I’m not sure is even worth automating. Hopefully, this gives something to think about for those that also don’t use open tracking and need a way to track email deliverability in their cold email campaigns!