Addressing Non-Human Engagement in B2B Pharma Email Marketing

In the world of B2B pharmaceutical marketing, email remains a cornerstone for reaching healthcare professionals (HCPs). But recent years have brought a growing challenge: non-human engagement.

As enterprise-level email security solutions become more advanced, they increasingly interfere with our ability to measure true human interaction. Emails appear to be opened and links clicked—sometimes within seconds of being sent—yet the intended recipient may never have laid eyes on the message.

The result? Inflated metrics, confused attribution models, and misleading signals about campaign performance. It’s time to talk about how we fix this.

Many HCPs work within large hospital networks, health systems, or academic institutions that rely on robust security platforms like Proofpoint, Mimecast, Barracuda, and Microsoft Defender for Office 365. These tools are designed to protect inboxes from phishing, malware, and spam. But they do so by:

• Pre-fetching images, which triggers the open pixel
• Auto-clicking links, to scan for threats
• Executing bot-like behavior, often from shared proxy IPs

What this creates is a paradox for marketers: the more secure your audience’s environment, the more difficult it is to trust your performance metrics.

Here’s a quick breakdown of what these platforms do and how it affects marketers:

Security Feature	Impact on Metrics
Image pre-fetching	Triggers false opens
Link scanning	Inflates click rates
Bot-based routing	Masks true user identity and behavior
Proxy IPs	Impairs geo and device-based segmentation

False positives are especially common with links tied to “Request a Rep,” “Contact Us,” or form submissions—calls-to-action that security bots often flag due to anchor tags or specific URL patterns.

At Ascender, we’ve implemented a multi-layered strategy using Marketo, Google Analytics 4 (GA4), and manual analysis. Here’s how we’re reducing noise and regaining clarity:

1. Marketo Bot Activity Filters

• IAB Bot Filtering: Excludes known bot IPs
• Proximity Pattern Detection: Filters out opens/clicks occurring <3 seconds post-send

2. OS-Based Suppression

• Linux Click Suppression: Many email scanners use Linux environments—filtering activity from this OS helps isolate bot behavior.

3. Honeypot Links

• Invisible links only bots will click. These serve as red flags that help us tag and suppress bot traffic in reports.

4. Time-Based Flagging

• Opens/clicks that happen within 3–4 minutes of delivery are manually reviewed, especially if they match patterns like:
  • Clicking only anchor links
  • Clicking all links in rapid succession
  • Zero scroll or time-on-page

5. GA4 Zero-Second Sessions

• Sessions with a 0-second duration are another strong indicator of bot activity. While easy to spot, filtering these from broader engagement analytics remains a work in progress.

We’ve had to pivot away from vanity metrics like opens and clicks and focus on downstream, high-intent actions, such as:

• Engaged website sessions (scroll depth, time-on-page)
• File downloads (e.g., prescribing info or product brochures)
• Form completions (especially “Request a Rep” or demo forms)
• Video interactions (play, pause, completion rates)

These pull-through metrics provide a truer picture of HCP interest and help us differentiate between bots and real human behavior.

Other B2B marketers—especially in sectors like tech, finance, and enterprise SaaS—are dealing with similar challenges. Emerging strategies include:

• Header analysis to detect non-standard user agents
• JavaScript fingerprinting on landing pages to verify human activity
• Real-time link wrapping that delays URL resolution until click-time
• AI-powered tagging of suspicious patterns across campaigns

One promising direction is the use of AI classifiers that analyze time, sequence, source, and behavior patterns to flag anomalies. We’re exploring this at Ascender as a future-proof way to improve report fidelity (pending internal feasibility conversations).

As we continue refining our approach, we’re actively asking:

• What triggers security software to click anchor links? Is it the presence of #anchor, or the CTA language (e.g., “Request Info”)?
• Could A/B testing URL formats reduce false-positive clicks?
• Can we design engagement forms that require subtle human behaviors (e.g., scroll depth or field interaction) before submission?
• Are platforms like Marketo or Salesforce Marketing Cloud evolving their native tools to keep up?

Non-human engagement is here to stay, and so are the bots. As security systems become more aggressive, we must become more adaptive.

The future of email marketing—especially in regulated, high-barrier industries like pharma—is not about chasing opens or clicks. It’s about real interactions, real actions, and real results.

At Ascender, we’re reimagining how B2B pharma marketers can track success in a way that reflects human behavior—not just firewall noise.