Meetings by Signature Playbook metric tracks the number of meetings scheduled through a specific Drift playbook, indicating the playbook's effectiveness in generating leads and guiding prospects towards conversions.
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 Meetings by Signature Playbook using Databox, follow these steps:
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.
The Contacts metric in Drift tracks the number of unique people who have engaged with your chatbot or been contacted by a team member, providing insight into customer interactions.
Sent by Chat Playbook refers to the number of times a particular playbook has been initiated by a user to start a conversation with a visitor on the website or app using the Drift chat feature.
Emails Captured by Chat Playbook is a metric that tracks the total number of unique email addresses collected through automated chat conversations within a specified playbook.
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 Conversations by Signature Playbook metric measures the number of live chat conversations initiated by a specific Signature Playbook within a given time frame.
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.