The Clicks by Email Playbook metric measures the total number of clicks on links in marketing emails sent through the Drift platform.
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 Clicks 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.
MTFR is the duration between a customer's initial message and the first human response. It measures how quickly a company engages with its customers.
Clicks by Chat Playbook is a metric that measures the number of clicks on suggested responses or actions within a chatbot conversation, indicating user engagement and effectiveness of the chatbot's pre-programmed responses.
Click % by Chat Playbook measures how many times a chatbot suggestion was clicked compared to the total number of suggestions shown. It indicates the effectiveness of chatbot suggestions in guiding website visitors towards a desired outcome/metric.
The Replies by Email Playbook metric measures the percentage of automated email replies sent by Drift that receive a response from the recipient, indicating engagement and potential interest.
The Opens by Email Playbook metric measures the number of times a visitor opens an email sent through the Drift email playbook feature. It lets you track the effectiveness of your email campaigns and identify opportunities for improvement.
Opens by Signature Playbook metric measures how many times signature playbooks were opened by website visitors, providing insight into the effectiveness of personalized messaging.
Views by Signature Playbook metric tracks how many times a signature playbook has been viewed. It helps to evaluate the effectiveness of a playbook and make data-driven improvements.
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.