Non-Human Interactions (NHI) and Email Metrics

Source: M3AAWG Exploring the Impact of Nonhuman Interactions on Email Send Metrics, November 2020 (M3AAWG-136; the document self-references m3aawg.org/sites/default/files/nhi.pdf). The original queue URL now 404s on m3aawg.org; retrieved via the Wayback Machine (snapshot 2025-12-11).

NHI — "automated clicks" — is the automated handling of received email by software rather than the recipient. It typically occurs during security scans by a mailbox provider's antivirus/security software: the system follows the links in an email and visits the target site to analyze content (hunting for malware and phishing pages), registering a "click" or an "open" for the campaign and polluting website analytics along the way. Patterns are deliberately non-obvious so bad actors can't circumvent the scanning. Symptoms range from clicks on a subset of links to every link in every email to a domain clicked in quick succession.

What began as a statistical anomaly has become "a major issue affecting email campaign metrics in a massive way"; senders who relied on open and click rates to measure performance may need additional success metrics. (NHI on clicks is the sibling of Apple MPP/Gmail prefetch inflating opens — see Metrics & Benchmarks.)

Measured impact (M3AAWG benchmark study)

Methodology: benchmark data from large and small ESPs, B2B and B2C senders across the industry, in some cases spanning several years of send/click/open data; goals were to test whether browser user-agent strings could reliably identify NHI and whether NHI could be reliably filtered to recover a true click rate.

Segment	NHI impact on metrics	Notes
B2C	Generally < 10%	Large volumes to a smaller set of large consumer inbox providers; consistent throughout the research; weaker impact for more reputable brands
B2B	20–80%	Enterprise anti-spam software is stricter on inbound; range correlated with recipient engagement — lower engagement at an inbox provider → higher probability of NHI scans

It was not possible to meaningfully break out NHI level by vertical market segment. A summary industry-wide effect is hard to quantify because filter agents and ISPs actively mask detection (necessary so filters aren't circumvented) — any filtering effort leaves a margin of error in "NHI-adjusted" rates. The strong correlation found: reputation ↔ NHI — M3AAWG recommends building and maintaining positive reputation to lessen NHI's impact on open and click rates.

Business impact

• E-commerce: automated clicks/opens can trigger marketing automations and follow-up emails; unreliable metrics degrade ROI/return-on-ad-spend planning — opportunity cost more than direct revenue loss.
• Media/content marketing: clicks and site visits are often the direct conversion metric; strategies based on guaranteed clicks, opens, or article views can no longer rely on them — direct reduction in advertiser/subscription revenue and threat to lead-gen-based marketing revenue. M3AAWG advises strengthening form and email verification to keep list quality high.
• Brand/ESP reputation: as engagement indicators degrade, engagement-based segmentation and recipient sunsetting get harder, list quality declines, lowering domain reputation via lower real engagement. ESPs hosting click-tracking links on their own domains are also exposed.
• List hygiene: NHI causes false-positive "engagement" — last-activity-based list cleaning can keep addresses on the list that were only ever 'active' because of NHI, defeating re-engagement series and unengaged-removal policies (List Hygiene & Sunset Policies).
• Recipient harm: NHI may trigger actions the recipient never consented to — completing double/confirmed opt-in, confirming details, adding to a new list, removing from a current list, or registering interest in items they don't care about — leading to additional unwanted mail, abuse complaints, and brand damage.

Best practices that reduce NHI (from the research)

• Use HTTPS exclusively for all links. Mixed secure/non-secure tracking links appear disproportionately targeted — an HTTP advertiser link behind an HTTPS tracking link "seems to trigger the most unwanted behavior."
• Separate campaigns for confirmed-engaged vs. non-engaged recipients, especially where inbox placement at certain domains is an issue.
• Monitor content quality — at the link level and beyond (image-to-text ratio, etc.). "Aggressive" marketing (emoticons in subject lines, large catch words, and the like) tends to attract more NHI.
• Sender reputation matters: NHI is considerably lower for senders with highly engaged recipients.

Plus the standing guidance: follow the Senders BCP (deliverability and engagement) and the Email Authentication BCP (lets providers attach reputation to the sender brand); content best practices reduce NHI impact.

Conclusions — the honest limits

• There is no definitive mitigation guide; the study's data covers only interactions that could be identified as NHI, not 100% of it.
• Scanners use simulated behavior designed to be indistinguishable from natural human interactions; identification is already very difficult and "will become nearly impossible in the future."
• Removing NHI changes the numbers, but a sender can never be sure it caught everything, and the effort may not be worth it; if every ESP filters NHI differently, metric comparability degrades further.
• Takeaway: NHI has measurable, significant consequences — re-evaluate the use of engagement data when determining mailing frequency or segmentation, and be aware of the inflation when reading click/open dashboards.