How should I handle email profiles with unusual high engagement rates that may be bots?

Summary

Addressing email profiles with unusually high engagement rates requires a comprehensive strategy considering that such activity can be bot-driven, spam filter related, or even genuine. Recommended approaches include analyzing engagement patterns for anomalies, using honeypots to identify automated sign-ups, implementing CAPTCHAs and double opt-ins to prevent bot registrations, segmenting and monitoring high-engagement profiles, examining subscriber signup sources, analyzing IP addresses and user-agent strings, and considering on-site behavior. Regular list cleaning and continuous monitoring of engagement metrics, coupled with advanced bot detection tools, are crucial. Remember that spam filters might mimic bot behavior and active users on the site should not immediately be treated as bots. The goal is to balance effective bot mitigation with minimal disruption to legitimate user engagement.

Key findings

  • Diverse Origins: High engagement can stem from bots, spam filters, or genuine user activity, requiring careful differentiation.
  • Behavioral Analysis: Analyzing engagement patterns (e.g., rapid clicks, unrealistic open times, consistent timings) is key to bot identification.
  • Technical Measures: reCAPTCHA, double opt-in, IP/user-agent analysis, and rate limiting help prevent and mitigate bot traffic.
  • Honeypot Effectiveness: Honeypots effectively identify bots that automatically scrape and sign up.
  • Source Matters: Analyzing the source of subscribers can identify potentially suspicious or bot-driven signup origins.
  • Holistic View: Considering on-site behavior and purchase activity alongside email engagement provides a more complete picture.

Key considerations

  • False Positives: Avoid incorrectly identifying genuine users or spam filters as bots.
  • User Experience: Balance bot mitigation with a positive user experience; minimize friction for legitimate users.
  • Data Compliance: Ensure compliance with data privacy regulations when analyzing user data.
  • Continuous Adaptation: Regularly update bot detection rules and monitoring techniques to stay ahead of evolving bot tactics.
  • List Hygiene: Prioritize regular list cleaning to remove identified bot accounts.
  • Impact on Analytics: Bots can skew email analytics; accurate data requires filtering out bot-generated activity.

What email marketers say
11Marketer opinions

To handle email profiles with unusually high engagement rates that may be bots, a multi-faceted approach is recommended. This includes analyzing engagement metrics for patterns indicative of bot activity (e.g., rapid clicks, unrealistic open times, same timings between actions), implementing honeypots to identify bots signing up automatically, using CAPTCHAs and double opt-ins to prevent bot subscriptions, segmenting and monitoring highly engaged profiles, analyzing subscriber sources, considering site activity alongside email engagement, continuously monitoring and updating bot detection rules, and regularly cleaning email lists. Filtering out bot traffic is crucial for maintaining list hygiene, improving email deliverability, obtaining accurate engagement analytics, and protecting sender reputation.

Key opinions

  • Engagement Patterns: Analyze engagement metrics for patterns indicative of bot activity (e.g., rapid clicks, unrealistic open times, consistent timings between actions).
  • Honeypots: Implement honeypots (email addresses not linked anywhere) to identify bots signing up automatically.
  • Subscription Prevention: Use CAPTCHAs and double opt-ins to prevent bots from subscribing in the first place.
  • Segmentation: Segment and monitor highly engaged profiles to isolate potential bots.
  • Subscriber Source: Analyze the source of subscribers to identify suspicious sources more likely to contain bots.
  • Site Activity: Consider site activity alongside email engagement, treating active site users as active for mailing purposes, regardless of email engagement.

Key considerations

  • List Hygiene: Filtering out bot traffic is crucial for maintaining list hygiene and avoiding skewed analytics.
  • Deliverability: Suppressing bots improves email deliverability and protects sender reputation.
  • Analytics Accuracy: Implement strategies to filter out bot activity to get a more accurate view of subscriber engagement.
  • Continuous Monitoring: Continuously monitor engagement metrics and update bot detection rules to stay ahead of evolving bot technologies.
  • Regular Cleaning: Regular list cleaning is essential for removing bot accounts and maintaining email list health.
Marketer view

Email marketer from HubSpot explains that you should analyze the source of the subscribers. If a large number of subscribers came from an unknown or suspicious source, they are more likely to be bots. Remove these subscribers to protect your sender reputation.

January 2024 - HubSpot
Marketer view

Email marketer from Email Geeks suggests looking for purchase activity driven by email to those addresses.

April 2022 - Email Geeks

What the experts say
4Expert opinions

Handling email profiles with unusually high engagement rates that may be bots requires careful analysis. Such behavior can stem from spam filters mimicking user engagement or from actual bots attempting to game the system. To differentiate, experts recommend analyzing engagement patterns (rapid clicks/opens), signup metadata (IPs, query data), and non-email site activity. Implementing honeypots can identify automated sign-ups. However, keep in mind that some high engagement might come from legitimate, valuable users or automated spam filters.

Key opinions

  • Spam Filter Activity: High engagement rates may originate from spam filters scanning for malicious content, especially in corporate, educational, or governmental contexts, so don't immediately assume it's a bot.
  • Engagement Pattern Analysis: Analyze engagement patterns for very rapid clicks/opens to potentially identify bots.
  • Metadata Examination: Investigate signup metadata like IPs and query data to understand user behavior and identify potential bots.
  • Honeypot Implementation: Honeypots (unused email addresses embedded in code) can effectively trap and identify bots that automatically scrape and sign up.

Key considerations

  • User Validation: Not all high engagement is malicious; some may be legitimate users or spam filters.
  • Behavioral Analysis: Correlate engagement patterns with signup and site activity data for a more comprehensive bot identification approach.
  • Data Privacy: Ensure compliance with privacy regulations when analyzing user data for bot detection.
  • Non-Email Behavior: Focus on non-email behavior to determine if the bot is negatively impacting other systems.
Expert view

Expert from Word to the Wise explains that you can identify bots by analyzing engagement patterns such as very rapid clicks or opens immediately after the email is sent. Correlate this data with other metrics to confirm bot behavior.

February 2023 - Word to the Wise
Expert view

Expert from Email Geeks shares that high engagement rates can be from spam filters, especially in corporate/educational/government sectors, looking for malicious content, so they may be real users.

November 2024 - Email Geeks

What the documentation says
3Technical articles

To address email profiles exhibiting unusually high engagement rates potentially caused by bots, documentation from various sources suggests several technical measures. Implementing reCAPTCHA on signup forms helps differentiate between human users and automated accounts. Analyzing IP addresses and user-agent strings for suspicious activity can detect and mitigate bot traffic, complemented by rate limiting to prevent rapid, automated requests. Furthermore, utilizing double opt-in confirmation ensures that subscribers are genuine by requiring them to verify their email address before being added to the list.

Key findings

  • reCAPTCHA Implementation: reCAPTCHA on signup forms distinguishes between human users and bots.
  • IP/User-Agent Analysis: Analyzing IP addresses and user-agent strings detects suspicious bot activity.
  • Rate Limiting: Implementing rate limiting prevents rapid, automated requests from bots.
  • Double Opt-In: Double opt-in confirmation ensures subscribers are genuine by verifying their email address.

Key considerations

  • Integration Effort: Implementing reCAPTCHA, IP/User-Agent analysis, rate limiting, and double opt-in requires technical integration.
  • User Experience: Consider the impact of reCAPTCHA and double opt-in on user experience; minimize friction for legitimate users.
  • Ongoing Monitoring: Regularly monitor the effectiveness of these measures and adapt to evolving bot tactics.
  • False Positives: Address the potential for false positives (e.g., legitimate users flagged as bots) with appropriate handling mechanisms.
Technical article

Documentation from SparkPost explains that you should analyze IP addresses and user-agent strings for suspicious activity to detect and mitigate bot traffic. Implement rate limiting to prevent rapid, automated requests.

March 2024 - SparkPost
Technical article

Documentation from Mailchimp explains that using double opt-in confirmation helps ensure that subscribers are genuine and not bots. This process requires new subscribers to verify their email address before being added to the list.

December 2024 - Mailchimp