Why do new Gmail signups or new email templates have low open rates?

Key findings

• Initial low open rates: New Gmail signups and new email templates frequently experience unusually low open rates, often in the 1-3% range, which is significantly below typical engagement levels.
• Sudden recovery: After an initial period, which can last for a few sends or weeks, open rates for these segments or templates often abruptly jump to normal, healthy levels (e.g., 30% and above).
• Widespread phenomenon: This behavior has been observed across a multitude of clients, different ESPs, and various mail transfer agents (MTAs), indicating a broad trend rather than isolated incidents.
• Gmail's conservative approach: A leading theory suggests that Gmail's machine learning algorithms are inherently conservative with new elements, whether it's a new email stream, a redesigned template, or recent subscriber data.
• Image prefetching impact: The way Gmail handles image prefetching may also contribute to observed discrepancies in open rates, particularly for new templates where images (and tracking pixels) might not be preloaded initially.

Key considerations

• Reputation building: Gmail's systems need time to assign (or correctly assign) a reputation to new recipients or content streams. Initial lower open rates might reflect a cautious initial placement (e.g., promotions tab or spam) until sufficient positive signals are received.
• Engagement as a driver: For new segments, engagement signals (opens, clicks, replies, moving out of spam) are paramount for building trust. Subsequent emails that receive positive engagement will help normalize deliverability and open rates.
• Template impact: New templates, even with existing good sender reputation, can be treated as 'new' content by filters, leading to a temporary dip until engagement patterns are established for that specific template. This is why new templates can affect deliverability.
• Monitoring new segments: It is essential to closely monitor the performance of new Gmail signups and emails sent with new templates to understand their initial inbox placement and engagement trends.
• Gradual warm-up for new lists: When onboarding new Gmail subscribers, a gradual warm-up approach, sending smaller volumes initially and scaling up based on positive engagement, can help establish trust with their systems.

Key opinions

• Consistent observation: Marketers widely report seeing unusually low (1-3%) open rates for recent Gmail signups, contrasting with normal performance for older subscribers.
• Template sensitivity: New email templates are also observed to have lower open rates compared to established ones, suggesting that even content changes can trigger cautious filtering.
• Prefetching theories: A common theory among marketers is that Gmail's image prefetching or caching mechanisms might be at play, where images (and thus tracking pixels) are not loaded for new senders or templates, impacting reported open rates.
• Gmail's conservatism: There's a strong belief that Gmail is highly conservative with new emails, treating new recipient segments or initial sends with extreme caution until positive engagement signals are built.
• Engagement is key: Marketers frequently emphasize that ongoing engagement from subscribers is the primary factor that unlocks better inbox placement and higher open rates over time.

Key considerations

• Monitoring new data: Marketers should segment new signups and monitor their deliverability closely, as initial low open rates might be a temporary phase.
• Content and personalization: Even with initial caution from ISPs, highly relevant and personalized content can encourage engagement, which is vital for improving sender reputation over time.
• List hygiene: An unclean or old email list can exacerbate low open rates, bounces, and spam complaints, especially with new subscriber additions.
• Adaptation to ISP algorithms: Understanding that ISPs like Gmail are constantly evolving their filtering based on machine learning means that what worked before might need adjustment for new segments.
• Troubleshooting methodology: If new templates are causing issues, it is worth exploring why email open rates drop after a template redesign and how this impacts broader deliverability.

Key opinions

• Machine learning conservatism: Deliverability experts agree that machine learning engines, like those used by Gmail, are designed to be extremely conservative with any 'new' elements: new mail streams, new templates, or newly acquired recipients.
• Image loading practices: It is speculated that Gmail may intentionally avoid loading images for new recipients or with new templates until a certain level of trust or engagement is established, directly impacting measured open rates.
• Trust building phase: The initial low open rates are seen as a 'test' period where Gmail assesses the sender's legitimacy and the recipient's interest, before granting full inbox placement.
• Engagement as the catalyst: The consensus is that positive engagement is the critical factor that helps new email streams or templates overcome initial filtering and achieve better deliverability.
• Systemic behavior: Experts acknowledge that this pattern is not an anomaly but a consistent behavior of Gmail's filtering systems across various senders.

Key considerations

• Gradual warm-up strategies: For new subscriber lists or significant changes like new templates, a measured warm-up strategy (gradually increasing volume and diversity of content) can help build trust.
• Focus on engagement metrics: Beyond raw open rates, experts advise focusing on secondary engagement metrics like clicks, replies, and forwards, as these are strong signals to ISPs.
• Sender reputation is paramount: The long-term health of sender reputation dictates how new email initiatives will be received. A consistently good reputation can mitigate initial dips.
• Patience and persistence: Experts suggest that the 'pop' in open rates after a few sends indicates a learning period for Gmail's algorithms, implying that consistent, good sending practices are eventually recognized.
• Data-driven insights: Deep investigation into specific open rate behaviors, as some experts are undertaking, can provide valuable insights into the nuances of Gmail's filtering.

Key findings

• Reputation-based filtering: ISPs (like Gmail) rely heavily on sender reputation to determine inbox placement. Any new element (template, recipient, sending pattern) effectively starts with a neutral or cautious reputation.
• Engagement as a signal: Documentation confirms that strong user engagement (opens, clicks, replies, moving emails from spam) is a primary positive signal that helps build trust and improve inboxing.
• Low engagement red flag: Consistently low open rates indicate to ISPs that recipients are not interested, which can lead to continued filtering to spam or the promotions tab.
• Authentication standards: Proper implementation of email authentication protocols (SPF, DKIM, DMARC) is a baseline requirement, but not a guarantee, for good deliverability; engagement is the next critical layer.
• Algorithmic adjustments: ISP filters are constantly learning and adjusting. New inputs require time for the algorithms to reassess and stabilize deliverability.

Key considerations

• Maintain list quality: Regularly cleaning email lists and ensuring new signups are legitimate and engaged helps prevent negative signals that harm overall sender reputation.
• Monitor deliverability metrics: Documentation encourages using tools (like Google Postmaster Tools) to track spam rates, IP reputation, and domain reputation, especially when introducing new elements.
• Consistent sending practices: Sudden spikes in volume or drastic changes in content/template can be viewed suspiciously by filters, necessitating a consistent and gradual approach for new initiatives.
• Responsive design: Ensuring emails are mobile-friendly and render well across all clients can enhance the user experience, indirectly boosting engagement and positive signals to ISPs.
• Transparency and clarity: Clear sender identity, relevant subject lines, and expected content can help recipients recognize and engage with your emails, reducing the likelihood of them being marked as spam.