Automation Features in Modern Email Tools

I love having AI review specific types of emails I get to see if they're worth my time. Today I helped my friend Alec Cheung - a fellow marketer in the CMO Coffee Talk community I'm a member of - set up one of these AI automations and it turned out awesome, so I wanted to tell you about it (with his permission of course). Here's the backstory: Going through website form submissions was eating up too much marketing team time. The submissions (which have a place for open-ended inputs that make them hard to screen via traditional methods) flow through Pardot and trigger emails that required human review to figure out if they were genuine leads or just spam. Tons turn out to be junk, creating unnecessary work for Alec's team. Others are genuine leads (or actual paying clients) that a human definitely needs to follow up with. Alec posted in our CMO Coffee Talk AI channel a few weeks ago asking for ideas on how to improve their process with AI. This is a super simple automation, so I offered to help if he'd let me share what we did. He was in! Our fix was AI-powered automation using Zapier. Here's the flow: 1️⃣. A visitor submits a form on Alec's company's website. 2️⃣. Pardot sends an email with the form contents to a designated address. 3️⃣. Zapier kicks off the automation. 4️⃣. GPT-4o reads, analyzes, and categorizes the submission. 5️⃣. Based on the categorization, the automation filters the next steps. 6️⃣. If a human needs to attend to the email, it emails them (along with the appropriate categorization, directly in the flag email's subject line). If it does not require a human, then nobody is notified about the form submission. The result is a far more streamlined workflow that will save a lot of monotonous manual effort. And it's CHEAP. It looks like this automation will cost Alec around $0.10-$0.20 per day in AI usage to run - yes, cents, not dollars. It's an incredibly affordable solution for such a big time (and headache)-saver. Alec was new to using Zapier for this kind of task, so we had 2 calls. First, we planned the planned process, and I gave him some homework, and then today we finished everything. (And he gave me the okay to share with you!) While the setup is pretty straightforward, it does require a base knowledge of Zapier, and how to write solid AI prompts (this isn't something for AI newbies to take on alone). For those in CMO Coffee Talk, I'll go much deeper into this automation during our 2/19 mid-week Zoom "What Every CMO Needs to Know About How AI is Evolving in 2025: Automated Workflows, Agents, and Reasoning Models." Also - if you're a marketer and want to explore AI automations, I do get into that in my Foundations of Generative AI for B2B Marketing course (🔗 in bio). --- UPDATE: A recording of the webinar for CMOs I mentioned above is now available! More details at: https://lnkd.in/gxe9EQ69

We automated our newsletter creation in 30 minutes. Now it saves us 10+ hours every month. For months, I manually wrote every single issue of our newsletter. Every single word. Tool descriptions. Profile summaries. Post breakdowns. Subject lines. Email copy. Then we discovered AirOps and built a system around it. Each issue covers 5 categories: 1. Tool of the week - best new software we've discovered 2. Profile of the week -  a creator worth following 3. Post of the week - best LinkedIn content we've seen 4. Data source of the week - where to find valuable insights 5. Play of the week - a winning strategy or tactic Now we just input the raw data: - Tool links - Profile URLs - LinkedIn post and YouTube videos URLs And AirOps handles the rest: ✓ Writes email copy for each section ✓ Creates compelling subject lines ✓ Formats everything consistently ✓ Proofreads and polishes ✓ Generates preview text All based on the custom prompts we built for it. However, we didn't automate everything - the picks and judgment calls are on us. The human touch stays in the loop. AI can write. But it can't know what our audience needs or spot the nuance that makes a recommendation valuable. That's still our job. But the grunt work? Gone. We send to 8,000+ subscribers every week with a 45% average open rate. Here's the formula you can copy: 1. Define your structure 2. Build your prompts once 3. Let AI handle the writing 4. Keep the human judgment Automate the production. Keep the expertise. What's one task you'd automate tomorrow if you had the right system?

Matthieu Vaxelaire asked me this morning how Fintool.com manages nurturing emails after receiving a feature announcement email from us. Well… the Fintool agent does it on its own now. The old way is dead. Customer.io, Mailchimp, HubSpot... they all work the same way: segment users into buckets, write templates, and build drip campaigns with if/then logic. It’s cumbersome and not truly personalized for customers. Customers care about what’s in it for them with a new feature. They want concrete examples tailored to their actual usage. The Fintool.com agent now reads our changelog of new features (https://lnkd.in/gnvPs432) and writes a personalized announcement email to each customer. It first gathers context about their usage, preferences, memories, past conversations, watchlists, and more. Then it writes a completely unique email for each user. A portfolio manager covering semiconductors gets: “I noticed you’ve been tracking NVDA earnings. Want me to add AMD and INTC to your watchlist for a comparative view?” An analyst covering healthcare gets something completely different. No segments. No templates. No A/B testing or merge tags. The agent does all the work. This is where GTM is going. The same way AI is eating scaffolding in code, it’s eating marketing automation. Every “automation” tool is just a poor approximation of what an agent with full context can do. This works for nurturing, new lead engagement, free trials, and more

Automated emails account for just 2% of email sends but drive 37% of all email-generated revenue. On a per-message basis, automation earns about 16x more than scheduled campaigns ($2.87 vs $0.18 per email, per Omnisend's 2026 benchmark). The catch is that most ecommerce brands have three automations running (welcome, abandoned cart, post-purchase) and call it a day. The brands actually pulling in the 37% are running back-in-stock, browse abandonment, replenishment, win-back, post-purchase nurture, and re-engagement before suppression. Each one converts on its own. Together they compound. Re-engagement before suppression is the one most brands skip. Pull contacts who haven't opened in 90-180 days, send a multi-email sequence with subject line variation, and only suppress the ones who don't respond. Re-engagement campaigns recover 10-20% of inactive subscribers when run well, and your overall deliverability climbs 2-5% after the dead weight comes off. The platform you're paying for matters here. The ESPs that handle this well have a full automation library out of the box, treat every flow as a first-class workflow, and don't lock the testing tools behind enterprise tiers. Omnisend is the platform I send brands to for this. Full automation library on every plan, including free. https://lnkd.in/gMQ6Yb86

Automated doesn't mean impersonal. In fact, the 𝘳𝘪𝘨𝘩𝘵 automation ensures your most important leads get a personal, faster response than you could ever manage manually I built a system to make sure your hottest prospects don't go cold. It:  1. 𝗜𝗻𝘀𝘁𝗮𝗻𝘁𝗹𝘆 𝗮𝗻𝗮𝗹𝘆𝘇𝗲𝘀 an inbound message via BANT analysis (Budget, Authority, Need, Timeline).  2. 𝗔𝘂𝘁𝗼-𝗿𝗮𝗻𝗸𝘀 leads by bucketing into High, Medium, or Low priority.  3. 𝗥𝗲𝘀𝗽𝗼𝗻𝗱𝘀 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁𝗹𝘆 by sending a 𝘵𝘢𝘪𝘭𝘰𝘳𝘦𝘥 email based on both the inquiry and priority High-priority leads get a personalized message (like the one shown in the screenshot) setting expectations with a promise that a solutions engineer will reach out within 24 hours, and a scheduling link to pick a time that's convenient for the lead. The result? → Your sales team spends 100% of their time on high-intent buyers → Every single lead gets the 𝘳𝘪𝘨𝘩𝘵 expectation set, instantly → You scale your pipeline without hiring a massive SDR team Watch the full tutorial to see how to build it yourself (link in comments) Do you think this could be useful to your team? If so please let me know in the comments! 𝘕𝘰𝘵𝘦 𝘵𝘩𝘢𝘵 𝘋𝘪𝘨𝘪𝘵𝘢𝘭𝘖𝘤𝘦𝘢𝘯 𝘸𝘢𝘴 𝘶𝘴𝘦𝘥 𝘰𝘯𝘭𝘺 𝘢𝘴 𝘢𝘯 𝘦𝘹𝘢𝘮𝘱𝘭𝘦 𝘤𝘰𝘮𝘱𝘢𝘯𝘺 𝘧𝘰𝘳 𝘵𝘩𝘪𝘴 𝘷𝘪𝘥𝘦𝘰, 𝘢𝘯𝘥 𝘵𝘩𝘪𝘴 𝘵𝘶𝘵𝘰𝘳𝘪𝘢𝘭 𝘥𝘰𝘦𝘴 𝘯𝘰𝘵 𝘯𝘦𝘤𝘦𝘴𝘴𝘢𝘳𝘪𝘭𝘺 𝘳𝘦𝘧𝘭𝘦𝘤𝘵 𝘤𝘰𝘮𝘱𝘢𝘯𝘺 𝘱𝘰𝘭𝘪𝘤𝘪𝘦𝘴