Response Time (Office Hours) metric measures the average time it takes for a Help Scout user to respond to a customer during office hours.
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 Response Time (Office Hours) using Databox, follow these steps:
Resolved Conversations is a metric that measures the total number of customer support conversations that were resolved by your team within a given time period.
The Replies Sent metric measures the number of responses or messages sent by a Helpscout user in a given time frame, indicating the overall efficiency and engagement of customer support.
The Replies Sent per Day metric measures the average number of replies that are sent per day to customer inquiries or tickets in Helpscout. It provides insight into the efficiency and productivity of the support team.
The First Response Time metric measures the time it takes for a customer support agent to respond to a customer's initial request or inquiry.
The Happiness Score by Team Member metric measures the satisfaction level of customers after interacting with a specific customer support team member. It helps to identify the best-performing team members and areas for improvement in customer support.
The Happiness Score by Happiness Ratings metric measures customer satisfaction by assigning a numerical value to feedback ratings. It helps teams track customer sentiment and identify areas for improvement.
The Conversations by Tag Name metric allows you to track and analyze customer conversations that have been assigned a specific tag, helping you understand and optimize the types of issues your customers are raising through those tags.
The Replies per Day per User (%) metric measures the average number of replies a user sends per day as a percentage compared to the teams average. It helps understand each users contribution to the teams overall performance.