Why your email metrics don’t match your conversions (and how to fix it)

Have you ever found yourself looking at an email campaign report, but the numbers didn’t add up? For example, the opens and clicks looked phenomenal, but the conversions and sales didn’t follow?

At GetResponse, we’ve experienced this firsthand. Both with our own email campaigns and the ones we’ve run advertisements in. Even if the report said we’ve achieved an open rate of 40% and a CTR of 5% we knew the landing page would only see a portion of that traffic.

The uncomfortable truth? A significant portion of those “engaged” subscribers aren’t customers at all – they’re bots. Something we’ve known for years but never had a real way of measuring its impact. This invisible audience has been quietly inflating the metrics we depend on to measure success and justify our budgets.

Since Apple’s Mail Privacy Protection launched in 2021, this problem has accelerated, creating an industry-wide decrease in confidence in email engagement data.

That’s why we’ve built Bot Detector – a new feature that lets you see your email engagement data with more clarity. You can now view your campaigns with bot interactions included or excluded, giving you the choice between comprehensive data and human-only insights.

Understanding bot activity in email marketing

Bot clicks and opens typically aren’t malicious attacks – they’re the unintended consequence of systems designed to protect users. When security software scans your emails for threats, it automatically interacts with every link and image, generating fake engagement data in the process.

Here’s what’s creating the problem:

• Security scanning tools like Microsoft Defender automatically click every link to check for phishing sites and malware before emails reach recipients.
• Email preview systems render email content to improve user experience, triggering opens when apps preload images and scan content.
• Link validation services pre-fetch URLs to verify they work properly and don’t redirect to dangerous sites.
• Mobile carriers examine links for compliance and safety, especially when messages contain external or shortened URLs.

Data from our own campaigns at GetResponse shows that even 30-40% of recorded opens can be attributed to bots rather than real recipients. Click-through rates face similar distortion. The results may vary depending on your industry but are affecting virtually every email marketer.

For email marketers, this means the metrics you’ve relied on are contaminated with non-human interactions. You’re measuring both human and machine actions, but your strategy decisions need to be based solely on the human part.

This is why having clear visibility into both your total engagement and human-only engagement is so valuable. Even if your reports may not look as impressive as before, it doesn’t mean you’re losing effectiveness. On the contrary, you’re gaining precision and clarity in how you measure and optimize your campaigns.

Where bot activity affects your email campaigns

Bot interactions create challenges across several key areas of email marketing:

• Performance reporting: It becomes harder to accurately measure ROI and compare email performance against other marketing channels when a significant portion of your engagement data comes from automated systems.
• A/B testing: When bots interact with your test variants, your results don’t reflect actual subscriber preferences. You might choose a “winning” subject line based on automated opens rather than genuine human interest.
• Segmentation: Engagement-based segments become less reliable when bot activity inflates interaction scores. Subscribers might get categorized as “highly engaged” when they’ve never actually opened your emails, while genuinely interested subscribers appear less active.
• Automation workflows: Triggers based on opens or clicks can fire incorrectly. Re-engagement campaigns might skip subscribers who appear active due to bot interactions, while other workflows might send follow-ups to people who never actually engaged.
• Campaign optimization: When you optimize send times, content, or targeting based on inflated metrics, you’re essentially optimizing for bot behavior rather than subscriber behavior.

The good news? These challenges are solvable once you can distinguish between human and bot interactions.

Introducing the GetResponse Bot Detector

We built Bot Detector because we needed it ourselves. After seeing the disconnect between our email metrics and actual business results, we wanted to clearly understand what was really happening with our campaigns.

Bot Detector is a new feature that identifies automated interactions in your email campaigns and gives you the choice of how to view your data. You can see your metrics with bot activity included (the traditional view) or excluded (human-only engagement). It’s that simple.

The feature is available across your campaign reports, so whether you’re analyzing a recent newsletter, automation message, or autoresponder, you can choose the data view that makes the most sense for your goals.

To access it, simply go to Reports, select the message(s) you want to analyze (Newsletters, Autoresponders, Automations), and turn on the toggle “Exclude bot interactions and Apple Privacy opens”.

What you’ll see when you turn on the Bot Detector

When you first toggle on “Exclude bot interactions and Apple Privacy opens,” don’t be shocked if your numbers look different.

This is completely normal and the initial “shock” is something we’ve experienced ourselves, too.

Here’s what a typical campaign might look like:

Setting	Open rate	Click-through rate
Before (all interactions)	25%	2%
After (human only)	17.5%	1.4%

Your first instinct might be to worry about the “drop” in performance. But remember: you haven’t lost any real engagement. You’ve simply removed the automated interactions that were never going to convert anyway. That 17% open rate represents people who actually chose to read your email.

The difference between your total and human-only metrics will vary depending on your audience and campaign type. B2B senders often see larger gaps due to corporate security tools, while B2C campaigns might show smaller differences.

As an example, consider the following results we’ve seen for our own email campaigns.

For one of our lead nurturing series, we saw a 25.6% drop in open rate and only a 5.9% decrease in click-through rates.

However, the results for our newsletters looked much less impressive. We observed a 37% drop in open rates and a 46% drop in click-throughs.

Frankly, the first time we saw these results we were shocked. However, we were also relieved because it explained the differences we saw between the email campaign reports and our website traffic data.

On a personal note, we’re definitely going to revisit our own strategies and how they relate to the best practices we’ve previously shared:

• Guide to increasing your email open rates
• Guide to improving your email click-through rate

Making the most of the Bot Detector: When and how to use it

Now that you have the Bot Detector, here’s how to get the most value from both data views:

When to look at “All Interactions”

There are still times when you’ll want to see the complete picture, including bot activity:

• Deliverability monitoring: If you’re troubleshooting delivery issues or checking inbox placement, the total interaction data gives you a fuller view of how your emails are being processed by different systems and security tools
• Historical comparisons: When you’re comparing current performance to campaigns from before you had bot detection, use the “All Interactions” view to maintain consistency in your analysis
• Technical troubleshooting: If you’re working with your IT team or investigating unusual patterns, seeing all interactions — including automated ones — can help identify technical issues or security scanning behaviors

When to focus on “Human Only”

This is where the real optimization magic happens:

• A/B testing decisions: Always use human-only data when deciding which subject line, send time, or content approach performed better. Bot interactions can’t tell you what resonates with your actual audience
• Content strategy: When analyzing which types of content get the best engagement, human-only data shows you what your subscribers actually find valuable, not what security scanners happen to click
• List segmentation: Build your “highly engaged” and “at-risk” segments based on human interactions. This ensures your re-engagement campaigns target people who’ve actually gone quiet, not those who just happen to have less aggressive security scanning
• ROI calculations: When you’re measuring email marketing’s business impact or comparing it to other channels, human-only engagement gives you a more accurate picture of what’s driving real results
• Budget planning: Use human-only metrics when making the case for email marketing resources or comparing channel performance for budget allocation

How the Bot Detector works

You might be wondering: how does GetResponse actually identify which interactions are bots versus humans? After analyzing millions of email interactions across our platform, we can tell you it’s more complex than it appears.

Bot detection isn’t as simple as flagging fast clicks or blocking certain IP addresses. An excited subscriber clicking immediately after receiving a flash sale email looks very similar to a security scanner. Meanwhile, sophisticated corporate tools can spread their scanning across time to appear more human-like.

That’s why we analyze multiple signals simultaneously:

• Timing patterns are one piece of the puzzle. Security scanners often click within seconds of delivery, but humans can be quick too – especially for highly anticipated emails.
• Click behavior provides another clue. Bots frequently click every link systematically, while humans are selective about what interests them.
• Technical signatures help us identify corporate security tools, which often operate from data center IP addresses and use recognizable system identifiers.
• Geographic consistency flags when clicks originate from locations that don’t match the recipient’s typical patterns.
• Content interaction anomalies reveal telling signs – like clicks on invisible tracking elements that humans would never see, or interactions that happen without corresponding engagement signals.
• Machine learning analysis combines all these factors using advanced algorithms trained on our extensive dataset to make nuanced distinctions that simple rules couldn’t catch.

The real challenge? None of these signals work alone. We need sophisticated analysis to distinguish between a genuinely excited customer and an automated system – which is why developing accurate bot detection has taken significant time and testing.

Our goal is practical accuracy: cleaner data for better decisions, without accidentally excluding real subscribers.

Getting started with the Bot Detector

Email marketing remains one of the highest-ROI channels in digital marketing. Our recent study confirmed this, with 26.9% of marketers reporting email as their best-performing channel over the last six months. But to maintain that effectiveness, we need data we can trust.

Bot Detector doesn’t improve your email marketing better overnight, but it improves your measurement immediately. When you can distinguish between human and automated interactions, every decision becomes more informed. Your A/B tests reflect actual preferences. Your segments contain genuinely engaged subscribers. Your optimization efforts target real behavior patterns.

This isn’t about making your reports look more impressive. It’s about building email strategies on solid ground, with data that actually reflects your subscribers’ interests and actions.

Ready to discover what your engagement really looks like? Head to your Reports tab and toggle on the Bot Detector!

Note: We’re slowly releasing this feature to all our users. If you’re not seeing it in your dashboard yet, you can either wait or reach out to our Customer Success Team and ask to have it enabled faster.