The Bounces by Email Playbook metric tracks the number or percentage of bounced emails sent through a specific playbook or automated sequence. This can help identify issues with email deliverability or the effectiveness of the playbook's messaging and targeting.
With Databox you can track all your metrics from various data sources in one place.
Used to show comparisons between values.
Databox is a business analytics software that allows you to track and visualize your most important metrics from any data source in one centralized platform.
To track Bounces by Email Playbook using Databox, follow these steps:
This dashboard tracks the traffic levels of visitors using chat for assistance, along with the overall performance of Drift Campaigns.
New Conversations is a metric that tracks the number of new chats or conversations initiated by website visitors or customers within a certain timeframe.
The Average Time to Close (ATC) metric measures the average duration from initial contact to final resolution for a closed deal or opportunity, helping track and improve sales team efficiency.
Conversations by Chat Playbook measures the number of chat conversations initiated by users interacting with specific chat playbooks on a website or messaging platform.
The Meetings Booked by Chat Playbook metric measures how many meetings were scheduled as a result of utilizing specific chat playbooks.
The Sent by Email playbook metric tracks the number of chat invitations or links sent via email by the Drift playbook, helping to measure the effectiveness of email campaigns in driving chat engagement and conversions.
The Unsubscriptions by Email Playbook metric measures the number of recipients who unsubscribe from your email marketing communications following the implementation of an email playbook.
Open % by Signature Playbook is a metric that measures the number of times signature playbooks are opened by visitors on a website, indicating interest and engagement levels.
CQL (Concept Drift Quantification) is a metric that measures the amount of change in the underlying concept of data over time, enabling drift detection in machine learning models.