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.
With Databox you can track all your metrics from various data sources in one place.
Used to show a simple Metric or to draw attention to one key number.
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 Contacts using Databox, follow these steps:
Drift dashboard template which gives you insights about new and closed conversations, reply times by team members and more.
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.
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.
The Meetings Booked by Chat Playbook metric measures how many meetings were scheduled as a result of utilizing specific chat playbooks.
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.