Metric Investigation: Explaining a Sharp Fall in SendGrid's Tracked Email Opens

The open rate for email sent through SendGrid, Twilio's email delivery platform, has fallen by 35%. Walk through how you would find out why. ```hint Question the signal first An email open is never observed directly; it is inferred from something the recipient's mail client does. Work out how that inference could break before you look at senders or recipients. ``` ### Clarifying Questions - Is the 35% a relative fall in unique opens divided by delivered emails, or a fall in the raw number of opens? - Did the drop happen within a day or two, or build up over weeks, and against which baseline is it measured? - Is it platform-wide, or concentrated in certain customers, email types (marketing versus transactional) or mailbox providers? - Did anything ship recently on our side, such as changes to open tracking, the reporting pipeline or the sending infrastructure? ### What a Strong Answer Covers - Pinning down the metric's definition, the shape of the drop over time and the baseline before forming hypotheses - Separating tracking and reporting failures from real changes in what recipients do - Segmenting by mailbox provider, client, customer, email type, region and sending IP or domain to localize the drop, including mix shifts - Deliverability causes such as spam-folder placement, authentication and reputation, and external changes by mailbox providers - An investigation order with the data for each check, and the fix, customer communication and prevention once the cause is found ### Follow-up Questions - If the cause is a mailbox provider's privacy change, what would you tell customers and which metric would you steer them toward? - How would you design an alert that catches a drop like this within hours without firing on normal daily swings? - If a handful of large senders account for most of the drop, how would you tell whether it is their list quality or a platform problem?