How do AI assistants and MPP impact email open rates, and what are better metrics to measure outbound campaign effectiveness?

Key findings

• Inflated metrics: MPP and some AI assistants pre-load email images, causing open rates to appear higher than actual human engagement.
• Two opens: It's possible to see two 'opens' for a single email, one from MPP and another from an AI agent, without human interaction.
• Inaccurate reflection: Image loads have historically been an unreliable indicator of whether a recipient actually read an email, a problem exacerbated by new technologies.
• Questionable validity: The reliability of open rates as a primary KPI for email campaigns is increasingly being questioned. For more insights into this, refer to our guide on whether email tracking is dead.

Key considerations

• Shift focus: Marketers should pivot away from open rates as a standalone measure of campaign success.
• New metrics: For outbound campaigns, especially in B2B, metrics like positive reply rates, click-through rates, and conversions are more meaningful. Learn more about alternative email engagement metrics.
• User agent analysis: Analyzing user agent data in event logs can help distinguish between human and automated opens.
• Define effectiveness: Clearly define what 'effectiveness' means for your specific campaign goals to select the most appropriate metrics. For additional perspectives, explore a Salesforce article on why email open rates remain relevant.

Key opinions

• Questioning validity: Many marketers now question the overall validity of relying on open rates due to artificial inflation.
• AI assistants mimic MPP: There's a growing understanding that AI assistants track opens via pixels, similar to how MPP operates, leading to similar data inaccuracies.
• Outbound campaign focus: For B2B outbound campaigns, marketers are realizing that vanity metrics like open rates don't accurately measure success.
• Shift to replies: There's a strong inclination to prioritize positive reply rates as a more reliable indicator of campaign effectiveness.

Key considerations

• Adapt strategies: Marketing strategies need to adapt to the new reality where open rates are less reliable, focusing on content and calls to action that drive true engagement.
• Beyond vanity metrics: Marketers should move beyond superficial metrics and delve into deeper engagement indicators. Our article on how opens should be used offers more guidance.
• Refining effectiveness: The definition of 'effective' in email marketing now heavily leans on direct responses and conversions rather than simple message receipt.
• Leverage other data: Explore other data points like website visits, demo requests, or CRM updates to get a holistic view of campaign success. A Quora discussion also highlights inaccurate email open rates.

Key opinions

• Dual opens: Experts confirm the possibility of multiple 'opens' (e.g., one from MPP, one from an AI agent) for a single email, even without human interaction.
• AI pixel tracking: AI email assistants, like Superhuman, often use pixels to track opens, operating similarly to conventional methods, not with 'superhuman' insights.
• Long-standing issue: The inaccuracy of image loads as a true indicator of human engagement has been a known problem for many years, only amplified now.
• Redefining effectiveness: The definition of an 'effective' email campaign must evolve beyond open rates to focus on more tangible outcomes. Explore our discussion on good email marketing metrics for B2B.

Key considerations

• Holistic view: Assess campaigns based on a variety of metrics that reflect actual user interaction and desired outcomes, rather than just opens.
• User-agent analysis: Utilize full event logs and user-agent information to differentiate between automated and genuine human opens where possible.
• Focus on replies: For outbound sales, concentrate on metrics like positive reply rates, which directly indicate interest and potential conversion. Our guide on increasing email click-through rates provides complementary strategies.
• Educate marketers: It's crucial to educate email marketing teams on these changes and guide them towards more meaningful KPIs. For deeper insights, consider articles like Stop obsessing about open rates.

Key findings

• Pixel preloading: Apple MPP preloads tracking pixels on its proxy servers, resulting in artificially inflated open rates.
• Privacy enhancement: MPP's primary function is to prevent senders from knowing if an email has actually been opened by a human.
• Impact on metrics: This preloading leads to incorrect metrics, including inaccurate open rates, making traditional open rate analysis unreliable. For more details on this impact, see our page on how MPP affects tracking.
• Bot activity: Beyond MPP, general bot activity can also open emails and click links, further skewing metrics.

Key considerations

• Adjusting analytics: Email analytics platforms must adjust their reporting to account for MPP and similar privacy features, providing more accurate insights.
• Focus on reliable KPIs: Marketers should concentrate on other KPIs that are not as easily manipulated by preloading or bot activity, such as clicks, conversions, and direct replies.
• Understanding limitations: It's critical for marketers to understand the inherent limitations of open rate tracking in the current privacy-focused email environment. Our article on measuring open rates accurately offers solutions.
• New strategies: Email marketing strategies must evolve to focus on engaging content that drives deeper interactions rather than just aiming for a high 'open' count. MoEngage's user guide on MPP and email analytics provides further technical context.