There are a few reports that we can wait for a while, but then there are a few reports we need hourly. That is why we have released new reports that you can avail hourly about monitoring chats and agents.
The goal of introducing these reports is to reduce the reporting downtime.
How are Hourly Chat Reports different from existing reports?
These newly introduced reports offer a distinct set of insights compared to our existing ones. Moreover, they seamlessly integrate into clients’ individual data analytics systems, ensuring their dashboards remain functional and dynamic. These reports are designed to provide information at two levels:
- The chat level
Allowing for a granular understanding of customer interactions.
Which Reports you have Hourly?
How to Enable Hourly Reports
Reach out to CSMs to enable hourly reports
Go to admin.verloop.io > Allow Hourly reports> ON/OFF
How to Schedule Hourly Chat Reports?
- Admin will go to Platform > Settings > Chat Reports
- Click on New Report and then select Hourly Chat reports
- Add the name of the report
- Add the email recipients which can be added by comma to get the reports via email. The admin can edit recipients.Add a webhook URL endpoint to which this report will be delivered once generated.
This automatically sets the last 1 hr report, which will be delivered at the 10th minute of the next hour.
Example: a report at 11:10:00 AM will show data from 10:00:00AM -10:59:59 AM. (Admin’s timezone)
There can be only one raw report per report type and frequency
- Chat report
- You can also click on the link and download it.
- The scheduling duration interaction will be changed, you have to select the hourly.
- You cannot create an ad hoc report for this.
Columns in the Report
- RoomCode is a sequentially generated unique integer identifier that is assigned to each conversation.
- Room code is unique for every user.
RoomUrl is a hyperlink to a chat room on the Verloop.io platform. It provides the ability to see all the messages in a chat room at once.
RoomStatus indicates the status of a chat room.
- RESOLVED is when the conversation is complete & the room has been closed.
- OPEN is when the bot or the agents are in contact with the user.
ChatStartTime time indicates the date and time when the bot receives the first message from a user.
- A chat is sent to the queue while the agent awaits the user for the preceding messages.
- QueuedAt is the date and time the chat was sent to the queue.
- QueueTime shows (duration) time in hh:mm:ss about how long a chat room has stayed in the Queue.
- Example: If the chat went into Queue at 10:00:22 AM and then assigned to an agent at 10:02:33 AM, then the QueueTime will be 00:2:11
- ChatEndTime is the date and time when either the bot, the user or the agent marked a conversation as complete and the chat room got closed.
- LastInteractionAt denotes the date and time of the last message which was sent by either a bot, an agent or the user in a chat room.
- ClosingComment reveals the remarks made when a chat room was being closed.
- The chat room is either closed by the bot or the agent.
- When a conversation is complete, and the bot closes the chat room, it leaves a comment, “Closing now”.
- CSAT stands for customer satisfaction, the feedback given by the user is stored under this variable.
- This CSAT score identifies the level of satisfaction a user had while using the bot, also it signifies whether the user’s problem is solved.
- It is basically estimated between 1 to 5, where 1 is the lowest and 5 is the highest CSAT score.
It captures detailed comments or remarks from users regarding their experience with the bot.
The “CsatTriggeredAt” KPI indicates the timestamp when the Customer Satisfaction (CSAT) survey was triggered and made available to the user for feedback.
The “CsatSubmittedAt” KPI denotes the recipe for which the customer submitted their response to the Customer Satisfaction (CSAT) survey.
- Chat autoclose denotes if a room was closed automatically by the bot.
- If the room was closed by the bot, it shows as TRUE else FALSE.
ClosedBy indicates the name of the bot or agent that closed the chat room.
- AgentStats displays the number of messages the bot, and the agent have sent in the chat room
- Sometimes there can be multiple agents involved in a chat room.
- This is seen in the order MYBOT: x, AGENT1: x, AGENT2: x
It is the email which is given by the agent, our bot saves that into this variable.
Quantifies the total count of messages generated and delivered by the bot during a given interaction or session.
The total count of messages sent by the user during an interaction or session.
The total count of messages sent by the agent during an interaction or session.
- BotFirstResponseTime indicates the time span in hh:mm:ss for the bot to respond after ChatStartTime.
- Example: If a chat starts at 10:00:00 AM and the bot replies at 10:00:02 AM, then the BotFirstResponseTime is 00:00:02.
- AgentFirstResponseTime indicates the time span in hh:mm:ss for an agent to respond after a chat is assigned.
- Example: If a chat is assigned to an agent at 10:00:00 AM and they reply at 10:02:00 AM, then the AgentFirstResponseTime is 00:02:00.
- UserFirstResponseTime indicates the time span in hh:mm:ss for a user to reply after a chat is started.
- Example: If a chat is started by the bot or an agent at 10:00:00 AM and the user replies at 10:02:00 AM, then the UserFirstResponseTime is 00:02:00
- FirstAgentAssignmentTime indicates the time span in hh:mm:ss for the agent to get assigned after a request for an agent was made by the user.
- Example: If a request for an agent was made by the user at 10:00 AM and the agent got assigned at 10:02 AM, then the FirstAgentAssignmentTime is 00:02:00
AgentAssignmentTimestamp refers to the exact timestamp, including date and time, when an agent was officially assigned to a user’s request or query.
FirstAgentResponseTimestamp signifies the precise timestamp, including both date and time, when the initially assigned agent provided their first response to a user’s query or request.
There can be multiple departments for a client, first assigned department ID is the ID of the department to which the chat room was first assigned
There can be multiple departments for a client, First assigned department name is the name of the department to which the chat room was first assigned
There can be multiple departments for a client. The last assigned department ID is the ID of the department to which the chat room was last assigned.
There can be multiple departments for a client. The last assigned department name is the name of the department to which the chat room was Last assigned
LastAssignedAgentName refers to the name or identifier of the most recent agent who was assigned to handle a specific user interaction or query.
LastAssignedAgentEmail pertains to the email address of the most recently assigned agent who took charge of a specific user interaction or query.
- Recipe Id is the ID of the recipe, This recipe ID helps in determining the updated recipe from the list of recipes.
- These IDs help in identifying the WhatsApp recipe as well as a web recipe.
The recipe name is the name given to the recipe, so whenever the recipe update is required by the clients. If a new recipe is created it is standardized with the checkbox checked in the recipe menu followed by the recipe name.
It’s the ID which helps in the identification of the unique users versus the repetitive users, user ID is allotted to every user who interacts with the bot, the number of times a bot is engaged with a user it will have that unique ID only.
User Phone number is the number which is given by the user, our bot saves that into this variable.
User name is the name which is given by the user, our bot saves that into this variable.
User Email is the Email which is given by the user, our bot saves that into this variable.
User Email is the Email which is given by the user, our bot saves that into this variable.
User Ip Address is the Ip Address which is used by the user, our bot saves that into this variable.
User OS is the OS which is used by the user, our bot saves that into this variable.
User Browser is the Browser which is used by the user, our bot saves that into this variable.
ChatChannel refers to the communication platform or channel through which a chat interaction between a user and a bot or agent takes place like WhatsApp, website, etc.
Chat Tags’ are labels you add to chat sessions to help you categorize and sort your website’s chat sessions.
- Recipe flow indicates the flow of conversation through different blocks.
- A conversation goes through multiple blocks in a chat flow. Recipe flow displays the name of the blocks separated by a delimiter “->”
- Example: Block A -> Block B -> Block C
- These are the names of the bocks that the conversation has gone through separated with delimiter ‘->
Custom variables are user-defined data points or attributes that can be set and utilised within a chat or messaging system. These variables provide a way to store and access specific information unique to each user or conversation. Custom variables are user-defined data points or attributes that can be set and utilised within a chat or messaging system. These variables provide a way to store and access specific information unique to each user or conversation.
Recipe variables refer to dynamic data points that can be set and used within a recipe. These variables enable the recipe to capture, store, and utilize specific information unique to each interaction.
The name of the agents.
The email address of the agents
It is the total number of chats assigned to the agent for the duration of the report.
Example: If a report is generated from March 1 to March 20 and the # chats assigned column has a value of 200 against the Agent name, this means that 200 chats have been assigned to the Agent within 20 days.
It is the total number of chats assigned to the agent, but transferred to another agent. Example: If a report is generated from March 1 to March 20 and the # chats transferred column has a value of 17 against the Agent name, this means that the Agent transferred 17 chats out of all the chats they received within 20 days.
- It is the total number of chats assigned to the agent, which they resolved successfully.
- Example: If a report is generated from March 1 to March 20 and the # chats resolved successfully column has a value of 190 against the Agent name, this means that the Agent resolved 190 chats out of all the chats they received within 20 days.
- Chats resolved will be credited only to the last person to close the chat who actually resolved, all the remaining stakeholders/agents in the same chat will get no credit for resolving the count.
It is the average or mean value of all the CSAT ratings received by the Agent.
It is the median value of all the CSAT ratings received by the Agent.
- Avg first response time is the average value of first response time in hh:mm:ss of all the chats an agent was assigned.
- Example: If an agent was assigned 3 chats and the first response time was 1000, 2000 and 10500 milliseconds, then the Avg first response time will be the sum of all response times divided by the count of response times
- Median first response time is the median value of first response time in hh:mm:ss of all the chats an agent was assigned.
- Example: If an agent was assigned 5 chats and the first response time was 1000, 2050,1500, 2500 and 30000 seconds, then the median first response time would be the mid value of all the first response times arranged in ascending or descending order. i.e. 2050 milliseconds
Available For Chat
Number of the agents if available appears here,
Not Available For Chat
Number of the agents not available appears here.
The Number of agents who have logged out here, appears here.
Effective Handling Time
Effective Handling Time refers to the duration it takes for a support agent to effectively resolve a customer’s query or issue
Aux status, short for “Auxiliary status,” refers to the secondary or additional states that a support agent can be in while using a customer support system. These states are separate from the primary status of being available to take customer inquiries. Common aux statuses include “Break,” indicating that the agent is temporarily unavailable.
The concurrency will show the average number of simultaneous engagements handled by an agent. This metric aids in assessing the proficiency of agents in managing concurrent chat interactions.
Occupancy is an important metric in any contact centre. It represents how busy your contact centre agents are. Occupancy rate refers to the percentage of time that agents spend directly dealing with customers.
Calculations in the Report
For calculating Chat Counts
Various conversation scenarios are tracked at the backend, and when specific events within these scenarios are triggered, they are assigned a value of 1 in the corresponding KPI columns. For instance, in the conversation scenario depicted below, each event that occurs during the conversation is recorded in the rows, and the associated KPIs are indicated in the columns. When an event such as chat start or bot reply occurs, the corresponding column is marked, and these values are aggregated in the final calculation.
For Calculating Different Chat Duration
Different conversation scenarios are monitored in the backend, and when a particular event takes place, a true value is assigned to the corresponding metric/KPI listed in the columns. The time duration between two consecutive true events represents the final value for that specific KPI.
For instance, consider the scenario shown below. In Scenario 1, a conversation begins at 12:00:00, resulting in true values assigned to the associated KPIs in the columns. Subsequently, when the bot responds at 12:01:00, a true value is assigned to the relevant KPI, such as FRT (First Response Time). The time elapsed between these two events determines the final value of the KPI. In this example, the FRT is 00:01:00.
Audit trail reports will be available for the following scenarios:
- Report scheduled
- Report name changed
- Report deleted
- Added recipients
- Removed recipients
- Downloaded reports via links