This report is used to just get a high level understanding of how many issues the agent is handling in the period
agent - agent email ID
num resolved - number of times the agent marked conversations resolved
num unique resolved - unique conversations the agent marked resolved
(ratio gives indication of how often there were reopens for that agent)
Helps you manage your resources at different points of time in the day.
hour by hour - used to get a sense of how many conversations are actively in progress in any "hour of the day"
time of day: 0=12-1am, 1=1 to 2am, and so on
messages: number of messages exchanged in that hour
unique conversations: number of unique conversations that were active in that hour
If a conversation started at 3:58 and continued till 4:15, it will get counted in both 3-4 and 4-5. so it is just about how many conversations were active in that period and can be used for figuring out how you want to staff up in various times of the day.
day summary - just a high level of how many unique users engaged and how many times those conversations were marked resolved.
This report is mostly used to track what kind of users are engaged - what percentage are users who transacted, what percentage of users who engaged went on to buy something or convert to premium, etc. It also helps you understand if you have to send a survey or reach out to these users in a different way.
users_contacted - a list of all unique users who sent a message in that period
konotor_id - our internal identifier for that user
name - name as set with us
email - email as set with us
app_user_id - user id as set with us by the business (external ID)
conversation_id - identifier to go look at the conversation from the user (can type into URL)
This report can be used to pivot on to take average by agent, etc and measure first response in different times of the day, etc as well. it has all raw data needed to do analysis on first response times in many ways.
first response app_id - redundant
conversation_id - ID for that conversation
conversationstart_millis - timestamp in milliseconds at which that specific interaction started (you can have multiple rows for the same conversationid with different start_millis for people who come back after you mark resolved, etc)
conversationstart_timestamp - same as millis, but in human readable time format
firstresponse_messageid - just an identifier for the message, not required
firstresponse_millis - time in milliseconds for the first response since epoch (edited)
time_to_firstresponse - time in seconds from the time of the first message from user in that interaction to the first response from an agent
time_to_firstresponse_timestamp - in a readable format as hours, mins, second
firstresponseby_email - email id of agent who did the first response
resolution - same as 5 but instead of first response, it does for resolution
resolution category and sub category as entered by the agent are also present in the report
report 6 also now has the CSAT related information on it.
It shows a trend of what time of the day more users try to start conversations. This report is similar to report 2, but counts each conversation only once - the first ever time it came in during that period
This is the all encompassing report - has CSAT star rating, CSAT issue resolved or not, CSAT feedback message, time of CSAT, message channel name, time to last response before resolution (even if an agent takes time to resolve, what matters is the last message before the agent has hit the 'resolve' button).
'Handle time to resolve' is the time between that last message and the time it has taken before the agent hit the 'resolve' button.
How was the message assigned - did the message come in when the business hours feature was turned on (YES) or not(NO).
time to assign - it is the total number of messages from agent versus total number of messages from user.
conversation_id: This is the ID that is present in the URL for that conversation. Can be used to refer the conversation and to know more.
conversationstart_millis: This is raw data for the start time of the conversation.
conversation_start_timestamp: This is the readable timestamp for the start time of the conversation.
message_id: This is an internal id or a unique identifier for the message. This can be ignored.
business_hours_on: “YES” signifies that the conversation initiated after working hours.
resolution_message_id: This is again an internal id or a unique identifier for the resolution message sent by the agent. This can be ignored.
csat_issue_resolved: Was this issue resolved? YES/NO. When clicked YES by customer it will show “t” and when user clicks NO it will show “f” in the report.
csat_response: This is the comment the user adds. This is not mandatory for the customer so field may be blank.
csat_rating: These are the star ratings the customer gives 1-5. In case of 0, if "csat_issue_resolved" column is “t” it means user evaded the rating by clicking back or closing the app. Also in the case of “f” it will be 0.
csat_createdtime: The time when the user clicks YES/NO for the question "Was this issue resolved?"
resolution_millis: This is the raw data for the time when the resolve button was clicked.
resolution_timestamp: This is the readable timestamp for the time when the resolve button was clicked( conversation was resolved).
time_to_resolve: Time in seconds between start time and resolution time for the conversation.
time_to_resolve_formatted: Time in HH:MM:SS format between start time and resolution time for the conversation.
resolvedby_email: Agent who resolved the conversation.
messagechannel_name: The message channel in which the conversation was initiated
resolution_category_name: Label that is attached to the conversation once it is resolved.
resolution_subcategory_name: Sub-category of the label that is attached to the conversation once it is resolved.
firstresponse_message_id: This is an internal id or a unique identifier for the first response message sent by the agent. This can be ignored.
firstresponse_millis: This is the raw data for the time when the first response message was sent to the customer.
firstresponse_timestamp: This is the readable timestamp for the time when the first response message was sent to the customer.
time_to_firstresponse: Time in seconds between start time and first response message time for the conversation.
time_to_firstresponse_formatted: Time in HH:MM:SS format between start time and the first response message time for the conversation.
firstresponseby_email: Agent who sent the first response message.
lastresponse_message_id: This is an internal id or a unique identifier for the last response message sent by the agent. This can be ignored.
lastresponse_millis: This is the raw data for the time when the last response message was sent to the customer.
lastresponse_timestamp: This is the readable timestamp for the time when the last response message was sent to the customer.
time_from_lastmessage_to_resolution: Time in seconds between the last response message to the resolution time( basically between the last message sent by agent and time it took to click the resolve button).
time_from_lastmessage_to_resolution_formatted: Time in HH:MM:SS format between the last response message to the resolution time (between the last message sent by the agent the and time it took to click the resolve button).
lastresponseby_email: Agent who sent the last response message to the customer.
assignment_message_id: This is an internal id or a unique identifier for the assigned message. This can be ignored.
assignment_time_millis: This is the raw data for the time when the conversation was assigned to an agent.
assignment_timestamp: This is the readable timestamp for the time when the conversation was assigned to the customer.
time_to_assign: Time in seconds between the conversation start time and assignment time( basically the time taken from first customer message till assignment of the conversation to an agent).
time_to_assign_formatted: Time in HH:MM:SS format between the conversation start time and assignment time( basically the time taken from first customer message till assignment of the conversation to an agent).
assignedby_email: Agent who assigned the chat (when A assigns chat to B, here it will track A). It will be "auto assign" if intelliassign assigns it to the agent.
user_message_count: Number of user messages exchanged in the whole conversation (from start time to resolution time)
agent_message_count: Number of messages exchanged by agent from start time to resolution time.