Automating Email Marketing Campaigns

We analyzed 4 million recruiting emails sent through Gem. Most get opened. But only 22.6% get replies. Half those replies are "thanks, but no thanks." We dug into what actually works. Here are 8 factors that drive REAL responses: 1. Strategic timing beats everything else - 8am gets 68% open rates. 4pm hits 67.3%. 10am lands at 67% - Most recruiters blast at 9am when inboxes are flooded - Avoiding peak times alone can boost your opens by 7-10% 2. Weekend outreach is criminally underused - Saturday/Sunday emails get ≥66% open rates consistently - Why? Empty inboxes. Zero competition. Candidates actually have time - Yet few recruiters send on weekends. Their loss is your gain 3. Keep messages between 101-150 words - Shorter feels spammy. Longer gets skimmed - You need exactly 10 sentences to nail the essentials - Every word beyond 150 drops performance 4. Generic templates kill response rates - Generic templates: 22% reply rate - Personalized outreach: 47% increased response rate - Even adding name + company to subject lines boosts opens by 5% 5. Subject lines need 3-9 words - Include company name + job title for highest opens - "Senior Engineer Role at [Company]" beats clever wordplay - 11+ words can work if genuinely intriguing, but why risk it? 6. The 4-stage sequence is optimal - One-off emails are dead. Send exactly 4 follow-up messages - You'll see 68% higher "interested" rates with proper sequencing - After stage 4, engagement completely flatlines. Stop there 7. Get the hiring manager involved - Having the hiring manager send ONE follow-up boosts reply rates by 50%+ - Yet most recruiters don't use this tactic - Weekend advantage: Minimal competition for attention 8. Leadership involvement is a cheat code - Role-specific timing (tech vs non-tech) matters - Technical roles: 3 of 4 best send times are weekends - Engineers check email differently than salespeople. Adjust accordingly TAKEAWAY: These aren't opinions. This is what 4 million emails tell us. Most recruiting teams are stuck in 2019 playbooks wondering why their reply rates won't budge. Meanwhile, recruiters who implement these 8 factors see dramatically better results. The data is right there. The patterns are clear. The only question is: will you actually change how you operate? Or will you keep sending the same tired emails at 9am on Tuesday? Your call.

I set up 37 AI Agents for our $6M ARR outbound agency. These are the 6 AI Agents we deploy across our >$10M ARR clients. I used to spend HOURS trying to figure out what makes a cold email work. Which pain points hit hardest. What signals show someone is ready to buy. When to reach out. How to segment my lists without losing my mind. Now? I run everything through a squad of AI agents (built in n8n) that do the heavy lifting for me. Here’s the team: → 1. COMPANY_ANALYST Analyzes your website, case studies, and G2 reviews. Finds what problems you solve, what ROI you deliver, and what makes you different. Outputs: • Top pain points (ranked 1-10) • Customer impact metrics • Differentiation hooks • Real customer language → 2. PAIN_EXPERT Takes those insights and builds a Pain Point Matrix. Scores each pain by: • Frequency • Financial impact • Time savings • Risk reduction • Emotional relief • Urgency Then ranks them-so you know what matters MOST. → 3. SIGNAL_HUNTER Searches for digital breadcrumbs showing a company feels that pain. Looks at: • Tech stack • Website copy • Job posts • Social posts • Event attendance • Review activity Even gives you ready-to-use Boolean search strings for LinkedIn. (Yes, you get a literal playbook for signals.) → 4. SEGMENT_STRATEGIST Breaks your market into micro-segments (100-200 companies each). Maps the most intense pain for each. Defines how to spot them, what triggers that pain, and what NOT to target. Helps you focus on the best-fit group first. → 5. TRIGGER_SPECIALIST Watches for buying signals in that top segment: • Researching solutions? • Budget approved? • Leadership change? • Tech stack updates? Sets up real-time alerts and tells you exactly when/how to reach out. → 6. CAMPAIGN_BUILDER Takes all this and builds 3 outbound campaigns you can launch. For each: • Campaign name • Target audience • Trigger event • Messaging • Data sources • Personalization fields • Target KPIs • A/B test plan • Launch checklist If you want to see how these AI agents actually work in a real outbound workflow (step-by-step) - I'll be putting together an entire SOP over the weekend, let me know if you want it!

I cut my $300K marketing team down to one person. Revenue went up 40%. Here's the AI system that made this possible. An old-school marketing team is expensive and slow. Not because the people aren't talented, they are. But because every project requires constant back-and-forth. "Tom, what's your take on this campaign?" "Can you review this copy?" "What stories should we use here?" "How do we position this for your audience?" Even the best marketers need guidance to capture your voice and vision. The solution? We built AI systems that give my team instant access to my knowledge. Now my one marketing person works like they have my entire brain available 24/7. Here are the 5 AI systems we built: 1. Audience Intelligence AI Trained on years of Impact Theory podcast data. Knows exactly what our audience struggles with so we can create more valuable content. 2. Ad Copy AI Trained on our most successful campaigns. Gives my team proven messaging frameworks. I can test 20 angles in the time it used to take to write one. 3. Social Media AI Trained on my highest-performing posts and audience data. Shows my team what hooks work and what stories resonate. We pick the best variations instead of starting from scratch. 4. Story Bank AI Trained on stories I've told across hundreds of podcasts. Finds the perfect story for any message instantly. I focus on new stories while AI handles the proven ones. 5. Coaching Insights AI Trained on years of my business coaching calls. Knows which frameworks solve specific problems. My team builds content based on real customer transformations. The result? My marketing person doesn't need to interrupt me for every decision. They get expert-level guidance instantly. When they do need me, it's for high-level strategy, not basic questions. Most marketing bottlenecks happen because teams need constant guidance. AI eliminates the guidance delays. Your best people get to focus on creativity and strategy instead of waiting for approvals. While your competitors are still stuck in revision cycles, your team is already testing the next campaign. Come to my free AI masterclass and I'll show you how to leverage AI to start your business with confidence: https://buff.ly/57ouBTK

𝐀𝐈’𝐬 𝐧𝐞𝐰 𝐫𝐨𝐥𝐞 𝐢𝐧 𝐢𝐦𝐩𝐫𝐨𝐯𝐢𝐧𝐠 𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐞𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞𝐧𝐞𝐬𝐬 𝐚𝐧𝐝 𝐑𝐎𝐈. AI has already proven to be a valuable tool in increasing #advertising efficiency, helping brands plan better, work smarter and save time. But can AI also drive measurable impact and increase #marketing effectiveness? Nielsen has recently measured over 50,000 #AI powered brand campaigns on YouTube and over 1 million performance campaigns on Google to uncover ROAS and sales effectiveness. The results from those MMMs showed that Google AI-powered advertising solutions consistently outperformed manual campaigns in both #ROAS and sales effectiveness: 🚀 Google AI-powered video campaigns on YouTube deliver 17% higher ROAS than manual campaigns. 💪 Google AI-powered VRC for Efficient Reach + VVC delivers 23% higher sales effectiveness than VRC for Efficient Reach alone. ✔️ Adding Google AI-powered Demand Gen to Search and Performance Max campaigns delivers 10% higher ROAS and 12% higher sales effectiveness than those without Demand Gen. It's already clear that #AI isn’t just a fad or a futuristic planning tool – it’s a performance driver in #advertising.

When I was working for the edutech company, we ran campaigns regularly to generate leads for Special classes. Once, we launched a campaign optimized for user registration for the same. However, we didn't get the planned number of conversions after spending a large budget for three days. A landing page is the problem, our team said. The bounce rate was high, leading to a low lead conversion rate. Campaigns were optimized for 'Maximize conversion.' We checked with the product team. They said the design used on the landing page is the same as in previous campaigns, and their conversion rate was three times higher than. It had become a two-way tussle between the product and marketing, the yin and yang of growth. The marketing team complained about the bad landing page experience & registration flow. The product team was complaining about wrong traffic & poor targeting. When we checked the targeting, it was perfect. Relevant in-market and interest audiences, similar and lookalike audiences, and proper retargeting audiences. We were at a crossroads. Already, one-third of the campaign period was over. The Cost per registration (CPR) was five times what we planned. We had to act fast to get it corrected. Finally, we found the issue and corrected it. What exactly happened? We used to optimize campaigns for reach and clicks in the initial stage. It helps in gaining early scale-up and traction. Eventually, we transition them to conversion-based bidding and optimization. However, since the introduction of 'Maximize conversion(MC)', we no longer do that as the MC campaign will do the two-step process in one. It helps gain faster scale-up without wasting the budget. However, giving the campaign the right and enough conversion events is vital here. One grave mistake you can make here is giving the wrong or no conversion at all. Ecen today in an automated campaign, if you don't provide any conversions or enough conversions, the campaign will continue sending different types of traffic and wait for a conversion to occur. Suppose it didn't receive any; it will keep sending different types of users, leading to a low conversion rate. This is precisely what was happening in our campaign. The conversion event was set up incorrectly, thinking that we always start with clicks and view optimization. The platforms received no conversions. So, the random traffic gave a one-third conversion. It was a simple but unacceptable mistake. After we corrected this, our CPR came down by 50% the next day, and eventually, we achieved the planned numbers. Adjusting your process for the new campaign type is essential to avoid losing money in the campaign.

A client came to me recently, frustrated. 🗣"Justin, our LinkedIn Ads were killing it at $10K a month. We scaled to $25K… and our cost per booked call shot up. What’s going on?" This is a common mistake. Scaling a campaign isn’t just about increasing the budget—it’s about adjusting the strategy. When you push past a certain spend, the best prospects have already engaged. The remaining audience is either less active or seeing the ads too often, which drives up costs without increasing conversions. Instead of blindly increasing spend, we made three key adjustments: ✔ Expanded into new job titles to reach fresh decision-makers. ✔ Tested industries with untapped demand. ✔ Refreshed creative to keep engagement high. Within weeks, performance stabilized, and we were scaling profitably again. Scaling isn’t just about spending more—it’s about evolving the approach. If you’ve hit this wall before, what did you do to push through?

𝗧𝗼𝗼 𝗺𝗮𝗻𝘆 𝗯𝗿𝗮𝗻𝗱𝘀 𝘁𝗿𝗲𝗮𝘁 𝗪𝗵𝗮𝘁𝘀𝗔𝗽𝗽 𝗹𝗶𝗸𝗲 𝗦𝗠𝗦. 𝗜𝘁’𝘀 𝗻𝗼𝘁. That's a criminal misuse of WhatsApp that’s quietly killing retention for both D2C and B2B brands. Brands get access to the WhatsApp API, upload a list, and hit “Send to All.” It feels efficient. But it creates what we call the broadcast trap, a pattern that burns through customer trust fast. 𝗪𝗵𝘆 𝗶𝘁 𝗗𝗼𝗲𝘀𝗻’𝘁 𝗪𝗼𝗿𝗸: Without enough personalization, messages feel generic and irrelevant. Customers start ignoring future messages after 1–2 interactions. Engagement and repeat purchase rates drop significantly. We’ve seen this across hundreds of brands before they changed their strategy to: → 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝘁𝗮𝗿𝗴𝗲𝘁𝗶𝗻𝗴: Messages are sent based on user actions, such as abandoned carts, product views, or purchase inactivity. → 𝗦𝗲𝗴𝗺𝗲𝗻𝘁-𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻: Returning customers, first-timers, and high-LTV buyers each get a different experience. → 𝗧𝗶𝗺𝗲𝗹𝘆 𝘁𝗿𝗶𝗴𝗴𝗲𝗿𝘀: Instead of one big push, messages are sent at the right moment — like 2 hours after a missed checkout, or 1 day before an offer expires. → 𝗣𝗿𝗼𝗴𝗿𝗲𝘀𝘀𝗶𝘃𝗲 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀: Each interaction builds on the last instead of restarting from scratch → 𝗖𝗹𝗲𝗮𝗿 𝗼𝗽𝘁-𝗶𝗻𝘀 𝗮𝗻𝗱 𝗽𝗮𝗰𝗶𝗻𝗴: Customers feel in control, not spammed. → 𝟮 -𝘄𝗮𝘆 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻𝘀: Hooking each message with contextual chatbots that continue the conversation. 1-way announcements don’t work, 2-way chats do. Here’s what changes when the 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘁𝗵𝗲 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝘆: Higher conversion rates Better repeat purchase rates Dramatically fewer unsubscribes and spam reports That’s the power of doing WhatsApp 𝘳𝘪𝘨𝘩𝘵. And for those wondering how brands manage this kind of personalization at scale? They use tools that make it effortless (we built one we’re pretty proud of 😉).

Want to scale your Meta Ads without wasting ad spend? Here’s the framework I use to turn chaos into performance: ✅ 𝟭. 𝗠𝗶𝗻𝗶𝗺𝗶𝘇𝗲 𝗪𝗮𝘀𝘁𝗲𝗱 𝗔𝗱 𝗦𝗽𝗲𝗻𝗱 𝘄𝗶𝘁𝗵 𝗮 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗖𝗕𝗢 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 • Create a CBO (Campaign Budget Optimization) campaign for prospecting. • Launch ads in packs (4–6 creatives), each as a new ad set. • Facebook will automatically allocate spend to top performers. • If you need to force budget to an ad, use ad set spending limits—but go slow ($10/day max to start). • This creates a competitive testing environment that naturally filters top creatives. ✅ 𝟮. 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁 𝗮 𝗣𝗿𝗼𝗽𝗲𝗿 𝗦𝗰𝗮𝗹𝗶𝗻𝗴 𝗠𝗲𝗰𝗵𝗮𝗻𝗶𝘀𝗺 • Graduate winning creatives into a dedicated scaling campaign. • This campaign should be broad targeting only, minimal to no restrictions. • Do NOT pause the winning ads in the testing campaign - let them run in both places. • Scaling campaigns should eventually have 5–10 top creatives, with growing budgets over time. • Monitor performance and grow budgets methodically. ✅ 𝟯. 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗬𝗼𝘂𝗿 𝗔𝗰𝗰𝗼𝘂𝗻𝘁 𝘄𝗶𝘁𝗵 𝗖𝗹𝗲𝗮𝗿 𝗦𝘄𝗶𝗺 𝗟𝗮𝗻𝗲𝘀 • Segment your campaigns into: • Prospecting (100% net-new customers) • Retargeting (site visitors / add to carts who haven't purchased) • Retention (existing customers / purchasers) • Use custom audience exclusions and CRM lists (e.g., from Klaviyo) to enforce clean segmentation. • Each lane should have distinct budgets, KPIs, and expectations. ✅ 𝟰. 𝗦𝗽𝗲𝗻𝗱 𝗠𝗼𝗻𝗲𝘆 𝗪𝗵𝗲𝗻 𝗬𝗼𝘂’𝗿𝗲 𝗠𝗼𝘀𝘁 𝗟𝗶𝗸𝗲𝗹𝘆 𝘁𝗼 𝗠𝗮𝗸𝗲 𝗠𝗼𝗻𝗲𝘆 • Analyze performance data by day of week, platform, placement, age, and landing page. • Use data from Meta Ads, Google Ads, and Shopify together. • Increase weekend spend if data shows higher conversions (e.g., Fri–Sun). • Rebalance weekday budgets downward accordingly. • Re-assess performance every 4 weeks. 🔁 𝗕𝗼𝗻𝘂𝘀 𝗧𝗶𝗽𝘀 & 𝗥𝗲𝗺𝗶𝗻𝗱𝗲𝗿𝘀 • Never pause a working ad - always duplicate into new campaigns. • Data-led decision-making beats intuition. Let Meta do the heavy lifting. • Use Shopify data to validate ad platform insights. • Track graduation timing and only assess ad success from that time onward. #PerformanceMarketing #MetaAds #GrowthMarketing #EcommerceMarketing #CustomerAcquisition #ROAS #Meta

“My ROAS has dropped, so I’m looking for new channels to spend on,” said a brand last week. I said, “Let’s audit your conversion funnel first.” “When you click on your ads, where do you land?” The Head of Digital looked at me blankly and I realised they’d fallen into the same trap as many before: Too focused on what’s out of their control - the black box of Meta and Google’s AI and neglecting what is in their control, their website and product. Here’s what we found: A conversion rate of 1.5%, well below the industry average of ~3%. “Imagine if you doubled your conversion rate, what would that do to your ROAS?” I asked. I didn’t even get into the concept of CMOAS yet. Instead, we talked about: – Landing pages that didn’t align with ad creative – Broken size curves being prioritised in product feeds – Add to cart buttons out of view on mobile – A lack of UGC and lifestyle imagery creating friction It’s now one week since the call and the team implemented Profit Peak. Conversion rate has climbed to 2%. Contribution profit is up 35%. And I can’t wait to see what next week brings for a brand now focused on fixing what’s within their realm of control. Don’t overlook the low-hanging fruit. Don’t get distracted by the Google and Meta optimisation hype in your inbox from coaches and experts.

I analyzed the best performing sites on Wix. Out of 289 million users, this is what's really working in terms of conversion. 1. Your CTA Might Be Too Direct The highest-converting landing pages don’t always have the most to the point CTAs, they prime the user emotionally first. Good: "Buy Now" Better: "Start Your Journey →"Buy Now" 2. The 3-Second Rule 🚨 If your website takes more than 3 seconds to load, you're losing leads, sign ups, you name it. Your website’s speed is your conversion rate’s best friend. Make sure your LPs don't have bloated images, useless animation, 3rd party scripts or follow any other less than best practice when it comes to site performance. 3. The idea that people Don’t Scroll is a Lie! They do scroll, you need to give them a good reason to do it. So don't cram everything above the fold. - Use subheads that push the reader forward - Design visual breaks (images, icons, bold text) - Make scrolling feel natural with the right effects 4. Stop Obsessing Over Your Homepage With few exceptions, your homepage is NOT your most important page when it comes to customer acquisition. Your landing pages and checkout flows drive conversions/sales. Make sure you are focusing on the right assets when you are looking for conversion optimization. 5. A/B Testing is Overrated It's not that you shouldn't do it, its that many markerters depend too heavily on them when there are big fixes you can make without the need for an A/B test. For example, fix obvious UX issues and use customer interviews to identify friction points. And if you do A/B test, then test significant changes not just a button color. You want data with actionable insights. Want to hear more insights on how to improve conversions, check out the link in the comments.