Email tracking isn’t what it used to be. Privacy changes, spam filters, and shifting technologies have made open and click rates unreliable. In this episode of Content Logistics, host Baylee Gunnell sits down with Jacob Brain, Director of Operations at Marketers in Demand, to unpack why traditional email metrics are failing—and what marketers should track instead.
Jacob explains how email tracking works at a technical level, why Apple’s Mail Privacy Protection and evolving spam filters have disrupted accuracy, and why relying on opens and clicks alone leads to misleading insights. He breaks down alternative ways to measure engagement, such as website tracking, multi-touch attribution, and intent-based data, offering a smarter approach to email marketing.
The conversation also explores how marketers can build a modern tech stack, integrate tools like Factors and Clay, and use data to support sales teams effectively. If you’re looking to improve email marketing without outdated metrics, this episode is a must-listen.
Featured Guest
Name: Jacob Brain
What he does: Director of Operations
Company: Marketers in Demand
Noteworthy: Expert in data-driven marketing and email deliverability strategies.
Featured Guest
Key Insights
Traditional Email Metrics Are No Longer Reliable
Privacy updates and spam filters have made open and click tracking less accurate. Jacob Brain explains how email tracking originally worked—using invisible pixels and redirect URLs—but how modern security measures, like Apple’s Mail Privacy Protection and aggressive spam filtering, now generate false signals. Many opens are triggered before a user even sees an email, and clicks can be flagged as spam, distorting engagement data. While these metrics once helped marketers measure success, relying on them today leads to misleading conclusions. Instead of focusing on these outdated metrics, marketers should shift their approach to more reliable data sources that offer a clearer picture of engagement.
Smarter Ways to Measure Email Marketing Success
Instead of chasing open rates, marketers should focus on downstream engagement. Jacob highlights alternative ways to measure email success, such as tracking website visits, monitoring buyer intent data, and using tools like Factors and Clay to identify company-level engagement. These insights provide a fuller view of how prospects interact with content beyond email. By analyzing patterns across campaigns—rather than relying on single-point data—marketers can better assess lead quality and refine their outreach strategies. The key is to adopt a holistic approach, integrating multiple data sources rather than relying on one flawed metric.
Aligning Marketing Data with Sales for Better Results
A fragmented view of engagement hurts both marketing and sales. Jacob discusses the importance of building a centralized data repository, or “TAM Manager,” that consolidates engagement signals across platforms. This allows marketing teams to identify high-intent prospects and pass valuable insights to sales. Instead of sales teams cold-calling random leads, they can prioritize prospects who have interacted with multiple touchpoints—emails, ads, and the website. This alignment not only improves conversion rates but also strengthens collaboration between marketing and sales. By shifting focus from vanity metrics to meaningful engagement, businesses can drive better decision-making and more effective marketing campaigns.
Episode Highlights
The Technical Breakdown of Email Tracking
Jacob Brain dives into the technical mechanics behind email tracking, explaining how it originally worked. He details how open tracking relies on a hidden pixel embedded in emails, while click tracking depends on redirect URLs. These mechanisms were once reliable but have since been disrupted by privacy-focused updates. Jacob breaks down why marketers should understand these fundamental changes before rethinking their measurement strategies.
“So from a technical standpoint, without getting too far into the weeds, just at a high level, OpenTracking, the way it works is a tiny little pixel, so like a one by one pixel image, is added to an email that we send… When that pixel is fired or the image for that pixel is pulled from a server, that’s a trigger that someone opened it.”
The Growing Role of Spam Filters and Privacy Updates
Jacob discusses how spam filters and privacy policies have reshaped the accuracy of email tracking. Many email clients now preload images—firing open pixels before a user even reads an email. Spam filters also simulate clicks on links to test for security risks, inflating click metrics. These shifts mean that even legitimate marketing emails can be misclassified, forcing marketers to rethink their measurement tactics.
“So, like Apple’s Mail Privacy Protection, they preload a lot of the images in emails to speed things up, but what happens is if you’re preloading images in an email that you haven’t opened yet, that’s going to fire that open. So if you send emails to a bunch of people using Apple Mail, they’re all going to look like they opened it, when in reality, they didn’t.”
The Shift Toward More Reliable Data Sources
With email tracking becoming less reliable, Jacob emphasizes the importance of newer data sources that offer better insight into engagement. He discusses tools that track website visits, company-level interest, and multi-touch attribution. These allow marketers to see a bigger picture of prospect behavior instead of relying on individual clicks or opens.
“There are tools like Factors that track individual companies that come on the site. And these tools weren’t available historically. Now that we’re getting these technologies that allow us to gather different types of information, it’s like we lose one here and we gain some over here.”
The Case for a Centralized Marketing Data System
Jacob introduces the concept of a TAM Manager (Total Addressable Market Manager), a centralized system for tracking marketing data. By consolidating engagement signals—email, website visits, paid ads, and sales interactions—marketers can identify warm leads and improve collaboration with sales teams.
“So, we set up a database where we track a couple different things. We’re collecting all the data from emails, paid campaigns, LinkedIn DMs—whatever we’re running. We associate those interactions with contacts and companies, allowing us to build a much more robust dataset of who’s engaging and who’s not.”
