🚰 Feedback

Present users with insights of the complete experience in a funnel. How many users moved from the landing page, to get started to converting and we should be able to show this in a funnel format. Also we should be able to sort this by duration so a user can see this data over a 7 day period, or two weeks.

Provide users with analytics on web forms like: Which field users drop off on, which fields take the longest to complete, validation errors per field, form abandonment vs completion, conversion rate per form and even friction signals such as multiple clicks.

I am struggling with importing GA4 goals from our Server-Side Tracking (SST) property. In the past, I successfully imported the Purchase goal and Add-to-Cart event from our GA4 Client-side property. However, with the new SST GA4 properties, the Add-to-cart event is not available as an import option in Convert. Additionally, I cannot differentiate between the Revenue properties of the old client-side and new server-side properties, making it difficult to identify which is which.

We would appreciate a feature that sends email alerts when AB test traffic stops. This would help us quickly address any issues with our tests and ensure they are running smoothly.

When deploying wins or taking actions, confirmation overlays appear at the top right of the screen, obstructing the 'Status' drop-down. This requires waiting for them to disappear before proceeding. Repositioning these overlays to the center or another location would streamline the workflow.

We are trying to map our purchase number with another tool, and it would be helpful if we could change the Convert dashboard timezone to EDT. This would ensure consistency across different platforms and make data comparison easier.

This is introducing AI agents using Node/JS and Python SDKs. So we need an effective agent with efficient and real-time agent performance analytics. Some key possibilities should be; Automated Hypotheses Generation & Variant Creation: That is, the Agent should be able to analyze historical user data to provide or suggest hypotheses and variations. Real time and Dynamic optimizations. So using elements we already have like MAB, the agents should be able to auto allocate user traffic. Personalization at Scale: So the agent can segment audiences into groups and deliver tailored test variations to these segments.

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