Email Analytics

What is Einstein Metrics Guard in Marketing Cloud Next Your email metrics are lying to you. Apple Mail's auto-opens, security scanners, and bots are inflating your open rates and skewing your analytics - making it impossible to measure true campaign performance. Einstein Metrics Guard fixes this by using AI to filter out fake engagement and show you what's actually happening with real humans. This deep-dive explains why bots and security scanners exist (spoiler: Apple's Mail Privacy Protection pre-fetches emails), how Einstein uses time-series analysis and predictive models with confidence scores (0=bot, 100=human) to identify genuine engagement, and the simple toggle in Email Feature Settings to activate it. If you're making decisions based on email analytics, you need this feature enabled. Your A/B tests, automated journeys, and strategy depend on accurate data. https://lnkd.in/gnzd7JFE

My email got an open rate of 83% and CTR of 42% instead of usual 50% and 22%. What I found out next shocked me totally- I was thrilled and patting myself on my back only to be taken into deep shock when I started analysing what did I do right. I noticed my email platform (Brevo) has filters for "Apple Mail Privacy Protection" and "bot activity." I was unaware of them so clicked them out of curiosity. Real opens dropped to 39% and CTR of 1.14% ( 3.53% if we take open rate as the base). Only a few people have clicked on my link. That's a 60% inflation in my open rates. 😶🌫️ I had no idea Apple pre-loads emails and bots scan them, both counting as "opens." Have I been optimizing for a meaningless metric this whole time? My actual engagement rate is 3.6%, not the 83% open rate I thought I had. Now I'm deep-diving into the data: 📍 Analyzing click heatmaps - WHERE are those people clicking? 👥 Exporting emails of actual clickers - WHO are our true readers? 🎯 Planning remarketing campaigns - targeting ONLY engaged subscribers 🧹 Considering a list purge - do I remove the ones who never engage? 📊 Building segments - "clicked in 30 days" vs "ghosts" I feel like I've been marketing to phantoms. Apple pre-loads emails. Bots scan them. Both count as "opens." I've been fooled. Questions for my marketing network: What's your REAL open rate after filtering? Do you delete inactive subscribers or try to re-engage them? Which metrics actually matter in 2025? Has anyone cracked the code on improving click rates? Currently planning to A/B test everything, focus on clicks over opens, and maybe say goodbye to dead weight on my list. Am I overthinking this? Under-thinking it? Drop your brutal honesty below. 👇 #EmailMarketing #DataAnalytics #MarketingMetrics #DigitalMarketing #MarketingStrategy

Open rates are the most misleading metric in sales. They make you feel like you’re getting traction but reality, the data is completely broken. Here are 4 reasons why (and what to actually measure): 1. Email clients handle open tracking differently Gmail and Outlook handle tracking pixels in totally different ways. Send the same email and Gmail might show 60% opens, while Outlook shows 40%. That’s a 20% delta — if the pixel even fires at all. 1. Apple Mail killed open tracking Apple’s Mail Privacy Protection preloads emails, images, and pixels before a user even sees the message. So your platform logs an open… but the person never read it. This impacts every iOS user so….basically everyone. 1. Bots and security scanners inflate opens Enterprise security tools scan inbound emails for threats which includes opening and parsing them. This triggers your tracking. Now you think your subject line crushed it, but half your opens were bots. Nobody read it. 1. Pixel blocking tools everywhere The opposite is also true: real opens that don’t get tracked. Chrome extensions, ad blockers, and privacy tools can all suppress pixels entirely. So someone could open your email, read it top to bottom, maybe even forward it and your platform will show zero engagement. Here’s what you should measure instead: 1. Reply rate This is the single most important metric in the entire game. It answers the only question that matters: Did a human engage? Every reply is good. Yes. No. Even “stop emailing me.” They show Google and Microsoft that humans are responding to your emails. That you're not just some bot dumping generic outreach into the void.  No replies = you're either in spam, or your message is irrelevant. 1. Bounce rate A bounce means the email address is dead or fake. If your bounce rate is above 1%, you’re seen as a spammer. And that flag doesn’t just apply to one campaign, it pulls down your sender score across the board. Even your best emails stop reaching inboxes. If you don’t fix your list, you're just spraying garbage. 1. Opt-out rate This one tells you whether you’re hitting the right audience. When someone unsubscribes or worse, reports you, what they’re saying is: “You’re not relevant. I don’t want to hear from you.” And they’re not wrong. If your targeting was on point, if your messaging was contextual, if your outreach spoke directly to their pain they wouldn’t be opting out. Even if they don’t respond right away, they’d read. They’d stay in your pipeline. They’d keep the door open. This is usually a result of lazy ICP work. Either you’re going too broad, or your criteria are completely misaligned with what the market actually looks like. ——— We built the entire Forge stack to solve exactly this: → Leadsforge to source clean, qualified data → Salesforge to execute multichannel outreach at scale → Warmforge to protect your domain health behind the scenes Open rates don’t build pipeline. Replies do.

Ever looked at your email click data and thought "there's no way one person clicked my link 40 times"? You're probably right – they didn't. Those inflated click numbers are almost always bot clicks from security scanners, not super-engaged subscribers. Corporate email systems and providers like Microsoft automatically "click" every link to check for malware before the recipient even sees your email. Telltale signs you're looking at bot activity: → Clicks happening within seconds of delivery → Identical click counts across multiple contacts → Every single link clicked (not just one or two) → Unusually high numbers from a single person Before you reach out to that "highly engaged" contact, cross-reference with your website analytics to see who actually landed on your page. Email metrics are powerful – but only when you know what you're actually measuring. Pro tip: 1. Add an invisible link - usually white font - to your email and see how many clicks that gets. 2. See if your email platform allows you to exclude bots or Apple MPP.

The hidden reason 90% of outbound campaigns die after 30 days (and it's not what you think). It's not deliverability issues. It's not terrible offers. It's not bad copy. It's that most teams never build feedback loops. They launch a campaign, send it for a month, and when results plateau, they blame the list. Then they start over with new: Copy. Targeting. And sequences. And the cycle repeats itself. Here's what we learned after running outbound for 120+ companies: Your best-performing campaigns are hiding in your current data. You're just not listening to it. At ColdIQ, we treat every reply as intelligence. Prospects' feedback should be leveraged into better campaigns: 1. Tag Every Single Reply We use three categories in Instantly.ai: → Positive (interested, asking questions, booking calls) → Negative (unsubscribes, "not interested," objections) → Neutral (out of office, wrong person, timing issues) But we go deeper. For positive replies, we track: → Which email in the sequence hooked them → Which subject line did they respond to → Which value proposition resonated → Which persona/role they hold For negative replies, we track: → Budget concerns by role → Common objections by industry → And timing pushbacks by company size 2. Analyze Patterns Weekly Every Friday, we pull campaign data from Instantly and Clay. We look for: → Which industries respond best to specific messaging → Which angles get the most positive replies → Which CTAs drive the most meetings Example from last month: CTOs at Series A companies responded 40% better to efficiency messaging than to ROI messaging. So, we built a separate sequence just for that segment. 3. Build Iteration Workflows Based on weekly data, we create new email variations using Claude. But we don't rewrite entire campaigns. We test micro-improvements: → New subject lines for low open rates → Different pain points for cold segments → Alternative CTAs for warm prospects We use Instantly's A/B testing to run these variations against control groups. 4. Create Campaign Evolution Rules When a campaign hits certain thresholds, we automatically evolve it: → If positive reply rate drops below 2% after 500 sends, we test new angles → If objections cluster around budget, we add ROI-focused follow-ups → If timing pushbacks exceed 30%, we build nurture sequences 5. Feed Insights Back Into New Campaigns Every insight gets documented in our Clay database. When we build campaigns for new clients, we start with proven patterns: → Subject lines that work by industry → Pain points that resonate by role → CTAs that convert by company size We're not starting from scratch each time, but building on what already works. The result? Average positive reply rates improve 30-40% between month 1 and month 3. Feedback should guide your strategy. Treat outbound like a conversation where you actually listen and optimize accordingly. Questions? 👇

𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝘆: 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗘𝗺𝗮𝗶𝗹 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗳𝗿𝗼𝗺 $𝟰𝟵𝗞 𝘁𝗼 $𝟯𝟬𝟬𝗞 𝗶𝗻 𝟵𝟬 𝗗𝗮𝘆𝘀 Initial Situation and Challenges: The client was struggling with a stagnant email marketing performance: Open Rates: 7% Click Rates: Less than 0.2% Inbox Placement: Around 60% across major ISPs Spam Rates: Above 0.4% at Gmail, and 0.1% - 0.5% at other ISPs These figures highlighted significant deliverability issues, with a considerable portion of emails not reaching the inbox, affecting engagement and revenue. 𝗦𝘁𝗲𝗽 𝟭: 𝗔𝗻𝗮𝗹𝘆𝘇𝗶𝗻𝗴 𝗦𝗲𝗴𝗺𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲. 𝗧𝗼 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝘁𝗵𝗲 𝗿𝗼𝗼𝘁 𝗰𝗮𝘂𝘀𝗲𝘀, 𝘄𝗲: 1. Studied Unsubscribes and Soft Bounces: Determined that certain segments and content types had higher unsubscribes and soft bounces. 2. Content Performance Review: Found that concise content (no more than 2 scrolls) with a CTA within the first scroll had higher engagement rates. Actionable Insights: Shorter emails with prominent early CTAs drove better conversions. 𝗦𝘁𝗲𝗽 𝟮: 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 We executed multiple tests to refine content: 1. Layout and Image Alterations: Changed email layouts and image-to-text ratios to see their impact on deliverability. 2. Footer Disclaimers and Content Changes: Tweaked footer disclaimers which led to better inbox placement, especially in Gmail. Results: Improved Gmail inboxing rates and engagement. However, these changes did not significantly impact Yahoo and Hotmail. 𝗦𝘁𝗲𝗽 𝟯: 𝗜𝗦𝗣-𝗦𝗽𝗲𝗰𝗶𝗳𝗶𝗰 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗮𝗻𝗱 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 1. Revenue and Click Analysis by ISP: Discovered Yahoo and Hotmail had better conversion rates than Gmail, indicating higher engagement from these ISPs. 2. Hotmail Focus: Despite low inboxing (45%), Hotmail drove more revenue than Yahoo. We liaised with Microsoft for three weeks to resolve IP blocking issues, doubling the volume sent to Hotmail. 3. Yahoo Adjustments: Improved inboxing to 80% by targeting users who had engaged (opened emails at least 10 times and clicked once) in the last 60 days. 4. Gmail Strategy: Implemented content changes and special segmentation strategies, boosting inboxing to 70% and reducing spam rates below 0.2%. Outcome: ISP-specific strategies led to improved inbox placement and engagement across the board. Step 4: Results and Impact Inboxing Improvements: Gmail: Increased to 70% Yahoo: Improved to 80% Hotmail: Resolved IP issues and doubled volume. Open Rates: Grew to an average of 15% in 90 days Revenue: Increased from $49K to $300K per month within 90 days. Continued in the comment section... #email #emailmarketing

I am not in #MarketingOps but this looks promising! 🔥 "Email - New Bot Open & Click Rate" 𝐖𝐡𝐚𝐭 𝐢𝐬 𝐢𝐭? 📧 ↳ HubSpot is adding visibility on bot-included engagement Rates. On the email post-send page, HubSpot will now show open and click rates which both include and exclude recognizable bots. ↳ The bot-included rates may be similar to what some customers see in other marketing softwares which do not use bot filtering at all. 𝐖𝐡𝐲 𝐝𝐨𝐞𝐬 𝐢𝐭 𝐦𝐚𝐭𝐭𝐞𝐫? 💡 ↳ This helps provide a more reliable view of human interaction with your emails. ↳ HubSpot customers will now have a comparative view between bot-included and excluded rates, helping measure the real state of their email campaigns. 𝐇𝐨𝐰 𝐝𝐨𝐞𝐬 𝐢𝐭 𝐰𝐨𝐫𝐤? ⚙️ ↳ When bot filtering is on, the primary open and click rate excludes bot activity, showing the percentage of opens/clicks estimated to be made by humans. HubSpot believes these are more reliable metrics than those you may see from email service providers which do not filter bots. ↳ When bot filtering is off, the primary open/click rate includes bot activity. This is a less reliable metric but may be similar to how other marketing software which does not filter bots measures open/click rate. ↳ In each case, users will see both metrics. #hubspot  #revops  #hubspottipsandtricks

Your newsletter's click rates might be inflated. And it's not your fault. Over the past two years, many of my clients started to notice something weird: Click rates were 5-10x higher than expected on certain links. Some saw exceptionally high clicks on nearly every link in their emails. The culprit? Security bots. As phishing attacks have skyrocketed (SlashNext reported that they increased by 703% in the second half of 2024!), email security platforms have ramped up their defenses. They click on links in emails to verify they're safe before they reach inboxes. To be clear: These are good bots that are keeping the inbox safe for all of us. But the side effect? Your click data is getting messy. If you're sending to business, .gov, or .edu addresses, you're far more likely to see inflated clicks. Omeda, one ESP, has seen months where 70%+ of clicks on newsletters are from bots. (If you're sending to non-work email addresses, like Gmail, the impact maybe be smaller.) So what should you do? 🔵 Talk to your ESP to see if they can filter out these bot clicks. If not, look to a tool like Glueletter (https://lnkd.in/eFPBeGAc) to filter out these clicks. (That’s what I’m using to filter out clicks for my newsletter.) 🔵 Be proactive with your advertisers. Make sure they know about bot behavior and ask them to share links with UTMs so they can track results on their end instead of relying 100% on your ESP’s data. 🔵 Set up proper authentication (SPF, DKIM, DMARC) to prove your emails are legitimate. (I’ve got an article walking through the steps her —> https://lnkd.in/eDMTrisH) Here's the silver lining: This is an opportunity to be transparent and build trust. The newsletter operators who proactively educate their partners about what's really happening will be miles ahead of their competitors. Email isn't broken — but you do need to stay on top of trends like this to make sure you (and your partners) understand what’s happening in the inbox. ——— 📷 That’s a screenshot of a Glueletter report on a recent Inbox Collective newsletter. On some of these links, bots were 8x more likely to click on a link than a human. But because I filtered out these bot clicks, I was able to see how my audience actually behaved.

Did you know your Klaviyo account is overreporting CTR & sales from bot clicks? Here's how to fix it 👇 1. Open Analytics & Click on Custom Reports 2. Tap on Create From Scratch 3. Select Single Metric & Chose "Click Email" as the metric 4. Click on "Add Filter" and change it to “Clicked Bot” and set it to “is false.” 5. Save the Report and now you'll only see real clicks in the report 6. If you need to analyze the data further, export the report. Click the “Export” button and choose your preferred format (CSV, Excel, etc.). 7. Cross-check with Campaign Data Go to the “Campaigns” tab. Select a specific campaign you want to analyze. Use the report you’ve created to cross-check the real clicks against the total clicks in the campaign. 8. Automate the Process To automate this process for future campaigns, set up a recurring report. Go to the “Reports” tab, select your saved report, and click on “Schedule Report.” Choose how often you want the report to be generated and emailed to you (daily, weekly, monthly). Hope this helps & now you're able to eliminate bot clicks

I audit 5+ cold email campaigns every week. Here's my exact process: First, I look at reply rates: Below 1%? Infrastructure/deliverability problem. 1-3% but no meetings? Offer/copy problem. This tells me where to focus. For deliverability issues, I check: - Spintax added for variability? - Copy free of spam trigger words? - Signature has spintax? - No longer than 3 step sequence? - Adjusting start/end times daily? For technical infrastructure: - Each domain in its own tenant? - Low inbox count per tenant? - Using multiple providers? - Sending volume per inbox appropriate? - Domain went through 2-week warmup? - Redirect is working? - DNS records properly setup? - Warmup didn't get turned off for sending accounts? For lead list quality: - SMTP validation via Bouncer completed? - Catch-all emails separated and validated? - Company name formatting cleaned up? - Too many enterprise security systems in your list? - Minimum of 2500 leads in the campaign? For copy and offer issues: - Subject line looks internal (lowercase preferred)? - Using soft CTA instead of direct meeting ask? - Includes relevant social proof? - Has personalization elements? - Avoids overselling? - No links or attachments? For offer quality: - Is it "cold traffic ready" with low perceived risk? - Helps prospect make or save money? - Solves a massive pain point? - Includes risk reversal/guarantee elements? For targeting: - Prospects match your ICP exactly? - Company size appropriate for your offer? - Targeting actual decision makers? Most campaigns fail because they skip the fundamentals. Fix the foundation first. Then optimize from there. P.S. What's your biggest cold email challenge right now?