Email Analytics

Stop tracking email open rates. Open rates are the least reliable metric in your funnel. Honestly, they are wildly inaccurate. This is because an email "open" is only considered when a tracking image pixel loads in an email. Let’s break down the 7 ways your open rate is probably wrong. Apple Mail Privacy Protection (MPP): This feature pre-loads images and content in emails, potentially registering an "open" even if the recipient hasn't actually opened the email. Image blocking is enabled by default in many email clients, which prevents your tracking pixel from loading. So even if someone reads your email top to bottom, it may never count as an open. Email Client Settings: Some email clients automatically display images in the preview pane, which can register an "open" even if the recipient hasn't fully opened the email. Tracking Pixel Issues: Tracking pixels, which are tiny images used to track opens, can sometimes fail to load due to various technical issues, including server-side problems or client-side limitations. Spam Filters: Advanced spam filters and sorting algorithms might check the email though bots, potentially skewing open rates Forwarded emails may register multiple opens from different devices or IPs, even if only one person is reading it Inflated Open Rates: Certain programs that automatically open and view emails for spam detection can also contribute to inflated open rates. And yet, marketers obsess over it. Whole campaigns are “optimized” for a number that doesn't reflect real intent, real engagement, or real outcomes. We went one step ahead of open rates at Mailmodo. We bring web-like actionable interactions within emails. Instead of measuring who opened, we focus on what they did. Inside the email. That means: A one-click poll → submitted A meeting → booked right inside the email A feedback form → feedback provided An event registration form → user registered for the event If you want to build email journeys that measure action instead of illusions, let’s talk. I can share what we’ve seen work and why open rate should never be your success metric.

Your 50% email open rate is likely closer to 18%. 💩 We analyzed various Klaviyo campaigns and found that roughly two-thirds of the reported opens were generated by Apple Mail Privacy Protection, proxies, or security tools rather than people actually opening the email. In one campaign, Klaviyo reported a 34.36% open rate. But after filtering likely machine activity, the estimated human open rate was only 11.68%. In another campaign, Klaviyo reported a 48.44% open rate. After filtering for robotic opens, the estimated human open rate was 17.62%. In both cases, the reported open rate was inflated by nearly 3x. One frustrating detail is that Klaviyo provides a filter to exclude bot activity from reporting, which is what we used to calculate the real versus robot open rates above. However, bot activity is still included in Klaviyo’s default open-rate reporting. Maybe inflated numbers make marketers feel better. But they can also hide a real deliverability problem. A fake open does not necessarily mean a fake person. The subscriber may be completely real. They simply did not open the email. Apple, a proxy server, or a security tool opened it on their behalf. It is a fake metric, not necessarily a fake contact. So if your open rates look incredible but purchase rate, revenue per recipient, and total email revenue remain weak, do not assume your deliverability is healthy. An inflated email open rate may be masking the exact problem you need to fix.

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.

Stop tracking email open rates. 🛑 Lots of talk about Gmails new banner blocking auto image downloads recently however this is not a new problem. Optimising campaigns for open rates is worse than a vanity exercise - it’s misleading and unreliable. Here’s why… Open tracking relies on an invisible image (a tracking pixel) embedded in your email. When the email is opened, the image loads, logging the open… But it’s not that simple. That pixel can also collect data like IP addresses, locations, and browser details, raising significant privacy concerns. As a result, major players like Microsoft, Google, and Apple have taken action to protect user privacy. Let’s take Gmail as an example: Since the introduction of Google’s privacy measures, reported open rates have been significantly inflated. Many of these “opens” are triggered by Google’s servers rather than genuine recipient engagement. Check out the data 📈 Chart 1: Compares open rates for Gmail against other providers like Microsoft and Proofpoint. Notably, Gmail’s open rates have consistently been higher, with a significant spike after 2018. Chart 2: Focuses on “first-minute opens” likely caused by image preloading or security scanning. Data suggests that 15-20% of emails sent to Gmail/GSuite recipients are false opens, a trend since 2018. The takeaway? Open rates are a relic. They’re inflated, unreliable and can mislead your outbound strategy. Instead, focus on metrics that reflect genuine engagement: ✅ Click-through rates  ✅ Responses ✅ Actual engagement In email prospecting, not all that glitters is gold—some of it is just glitter. Full stats breakdown link in the comments #outbound #B2Bsales #prospecting

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.

Your click-through rate is lying to you. Most brands celebrate a 3% CTR. Meanwhile, bots, accidental taps, and bored scrollers are inflating your numbers while real buyers go untracked Here's the thing: Not all clicks are created equal. A bot clicking your CTA in 0.3 seconds ≠ A customer who reads your email, clicks, browses for 4 minutes, and adds to cart. But most ESPs treat them the same. That's the problem. We just dropped a podcast episode breaking down click quality vs click quantity. Here's what actually matters: 1. Stop writing emails for "anyone" If a bot, a toddler, or a random scroller can click your CTA, it's too generic. Write for one use case. Make your CTA repel the wrong person and attract the right one. Most click bloat isn't a design problem. It's a clarity problem. 2. Not everyone is ready to "Shop Now" Build multiple intent pathways: Top funnel: "See how it works" goes to a PDP or explainer Mid funnel: "See why customers love it" goes to a reviews/UGC Bottom funnel: "Claim your 15% off" goes to a cart or quick buy Track which path your best customers take. Optimize for those clicks. 3. Build a click "quality" score Pair clicks with behavior: Bot or <3s time-on-site = 0 points Bounce = 1 point PDP view = 2 points Add to cart = 3 points Purchase = 5 points Tag users accordingly. Retarget high scorers. Re-engage or suppress low scorers. You can't scale retention if your clicks aren't converting. 4. Fix your pre-click promise Getting 100s of clicks but zero conversions? Your email is overpromising or misaligned. What you say in the email must match what they land on. Don't tease 15% off and drop them on a full-priced collection page. The bottom line: Click inflation is real. Your CTR is lying. And "more clicks" is not the answer. If you want more revenue, design emails that attract qualified, intentional, human clicks. Then track what happens after. We broke down the full framework in our latest Send It! Podcast with Chase Dimond and I.. 🎧 Listen here: https://lnkd.in/g372-bQH Big thanks to our main sponsor Omnisend and Inboox.ai for the sponsorship 🙏

Looking to filter bot traffic from analytics reports? Start with your email channel. Why email? Because it attracts a lot of hidden bot activity, inflating most metrics like CTR and on-site engagement. When you send your newsletter emails, major email providers automatically scan the links in your email for malicious content as soon as they hit users' inboxes. These scans don’t stop at the links in your email—they also follow and scan any links found on the pages those links lead to. As a result, a single link click could generate as many as 10 pageviews in your analytics. The challenge is that most of these bots don't reveal their identity. They mimic normal user behavior, using standard user agents and performing actions like scrolling through pages or clicking buttons. This makes it difficult for Google Analytics to filter them out automatically. So, how can you exclude this bot traffic? Since bots don’t label themselves, it can be challenging. Here are 2 approaches: 1- IP Blocking:  One of the most common sources of bot traffic is Microsoft Safe Links, luckily they provide a list of IP addresses used by Outlook 365. You can blacklist these IPs in your analytics reports. You could also find some of these IPs using your server logs or ask your developer for them. 2- Honeypot Trap: Another method is setting up a honeypot. A common technique involves adding a hidden link in your email footer that real users won’t click, but bots will. Any traffic associated with this link can be excluded from your reports, or even challenged with a CDN like Cloudflare. Do you use any different approach?

Many brands are making decisions based on fake email data (and don't know it).   Here's a simple Klaviyo setting that 90% of brands ignore:   Excluding bot interactions from attribution.   I've been implementing this across all my clients lately, and it's a best practice that most brands just... don't do.   Here's the problem:   Bots are clicking your emails and SMS messages.   Not real customers. Bots.   This inflates your attribution and makes you think email is performing better than it actually is.   Maybe it's competitors checking out your campaigns. Maybe it's automated tools crawling your content. Maybe it's spam filters testing links.   The fix is dead simple:   Go into Klaviyo attribution settings → exclude bot interactions from clicked email and SMS metrics.   That's it.   Now your revenue attribution reflects actual human behavior.   The difference might be small (1-2% in most cases, some as high as 5%), but the principle is huge:   Make decisions based on real data, not inflated metrics.   Your attribution should show you where real customers are actually engaging and buying.   If you're using Klaviyo and haven't done this yet, do it today.   It takes 30 seconds and gives you cleaner, more accurate performance data.

Your click rate is destroying your email data - and it's getting worse. If you're sending B2B emails and seeing 4-7% click-through rates, I have bad news: Your actual engagement is probably closer to 0.5-2%. The difference? Bots. You see, enterprise security tools are doing their job... Protecting organizations from malicious emails. But they're destroying your email data in the process. When you send an email to a B2B contact, their organization's security system: → Automatically triggers the open (this isn't new) → Clicks every single link in your email (this is the growing problem) → Sometimes even triggers unsubscribes What you think are real clicks is actually seeing bot activity. Which means you might be optimizing for the wrong metrics. You might be making strategic decisions based on artificial data. And most ESPs aren't equipped to handle this. A few are starting to report "potential bot activity," but: The methodology isn't transparent The data isn't actionable The problem keeps growing Meanwhile, you're: Misidentifying engaged subscribers Wasting budget on segments that don't actually engage Missing the real behavioral patterns in your list An entire email strategy is being built on compromised data. We developed a method to identify and segment bot traffic without suppressing real subscribers. Here's how it works: Build a custom email footer with this structure: To: [subscriber email] From: [business name] Business Address Unsubscribe | Manage Preferences Now here's the key: Make the colon in "To:" a hyperlink. Just the colon. → Link it anywhere (your website, privacy policy, the same link from your email body, etc.) → The bold, underline, and mask the styling of both "To:" and "From:" → Keep the clickable area as small as possible → Make it nearly impossible to accidentally click Why this works: Email providers can see it's a legitimate link (no red flags) Real humans won't click a single colon character Bots will click it automatically You can now track non-human interactions When someone clicks that colon link, we tag them as "possible bot/non-human interaction." Now, I don't recommend suppressing this list. Real subscribers are on it. They'll book calls. They'll make purchases. Their actual engagement is just hidden behind bot activity. Instead: Segment them out for cleaner reporting. Analyze bot-free data separately. Make strategic decisions based on verified human behavior. ----- In this week's Email OS newsletter, I'm breaking down five specific tactics to protect your list and get cleaner data - especially critical if you're in B2B. Subscribe here: https://lnkd.in/g9h83HNV ----- Have you noticed unusual click patterns in your B2B email campaigns? Drop a comment with what you're seeing - I'm curious how widespread this has become across different industries.