Human Agents + Chatbot, it is crucial to track key metrics, continuously improve chatbot performance and free up Human Agents from mundane tasks.
This section we would focus on 15 key metrics which will help us track the performance of Chatbot and Human Agent. Then we focus on how we can use the detail Chatbot failure report to improve the bot's performance.
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Bot Performance Reports helps to look at total number of request severed by the bot successfully and all the different reasons why the chat was transferred to an human agent.
Tip: This graph is measured in “number of request” and not “number of chats”. A single chat session can server multiple request to a customer.
Tip: A chat session for a web channel ends when customer / bot / human agent closes the chat.
Tip: The details on all the different reasons why a chat got transferred to an human agent with all the details regarding chat can be found under “Chatbot Failure Report”
Comparison between chats handled between Bot and Human Agent. Human Agents handles chat only when it is transferred from Bot due to some failure.
The below graph provides the agents with a quick analysis of the chat traffic spread across the date range selected as part of the filter.
This provides the distribution of chat traffic with respect to Web, Mobile and Tablet.
Departments are mapped with “Purpose of conversation” under the conversation builder. Departments can added through the Live Chat Software settings.
This provides a snapshot of chat traffic per department for Bot, Human Agent and Total.
Request type are identified by the intent name provided as part of the intent node or from the value of the top level menu shown through a UI Control. Read more on naming the request type here.
This provides a snapshot of chat traffic per request type for Bot, Human Agent and Total.
This provides a snapshot of chat closed by Visitor, Agent and total Handover chats.
This provides a comparison snapshot of chats initiated Proactively vs User Initiated. Proactive chats are where chat proactively gets launched depending on parameters set under Live Chat Software.
Average Handle Time (AHT) is a metric that measures how long it takes bot / agent to complete a chat session.
Bot Average Handle Time (AHT) is calculated for all successful request handled by Bot and doesn’t consider the request that were handovered to Human Agents.
Human Agent Average Handle Time (AHT) is calculated from the time the Agent accepts the chat till the chat is closed either by Visitor / Agent.
This provides a snapshot of Average Handling Time (AHT) broken down per department for Bot, Human Agent and Overall for a chat session.
This provides a snapshot of Average Handling Time (AHT) broken down per request type for Bot, Human Agent and Overall.
This provides a snapshot of wait time between chat handovered by bot and Human Agent accepting the chat. This also provides the longest wait time for a customer in the date range selected.
This provides a snapshot of number of chats handled per human agent.
This provides a snapshot of Average Chat Time in Minutes per human agent.
A quick snapshot of chat metrics including:
Chat bot failure report is one of the crucial report for improving Bot performance and reducing the number of handover happening to Human Agents. This is a detail snapshot of information providing all the details regarding the failure and why the Bot transferred a chat session to Human agent. This report can be downloaded for further analysis in formats like CSV and PDF.
There are four high level reason for bot failure to handle a request
The Bot failure reports consists of:
|Input Variable||Invalid variable value||Bot is not able to understand the input entered by the customer or the validation check under the Input Parameter node for the input type fails.|
|Input Variable||Handover - Invalid variable value retry limit reached||Max retry limit is reached and the handover is initiated by Bot to Human Agent.|
|Intent||Intent detection failed||Intents nodes help the bot to identify customer intent by parsing the English statement. When Bot is unable to understand what customers is trying to say, it could be because of the missing training example or the bot is not designed to handle those request.|
|Intent||Handover - Intent detection failed and retry limit reached||Max retry limit is reached and the handover is initiated by Bot to Human Agent.|
|Trigger||Handover - Trigger status failure||Successful status check for the trigger fails|
|Trigger||Handover - Trigger timeout||The HTTP API / Service URL that the trigger is trying to consume timeout|
|Trigger||Handover - Trigger validation failure||Validation provide under the trigger fails|
|Input Variable||Handover - Info not available||When customer says that I don’t have a particular information handy or available, those failures are captured here.|
|Trigger||Chat Closed - Trigger status failure||Chat closed indicates that Human Agent support is turned off. Successful status check for the trigger fails.|
|Trigger||Chat Closed - Trigger timeout||Chat closed indicates that Human Agent support is turned off. The HTTP API / Service URL that the trigger is trying to consume timeout.|
|Trigger||Chat Closed - Trigger validation failure||Chat closed indicates that Human Agent support is turned off. Validation provide under the trigger fails.|
|Input Variable||Chat Closed - Invalid variable value retry limit reached||Max retry limit is reached and the chat is closed as Human Agent support is off.|
|Intent||Chat Closed - Intent detection failed and retry limit reached||Max retry limit is reached and the chat is closed as Human Agent support is off.|
|Input Variable||Chat Closed - Info not available||When customer says that I don’t have a particular information handy or available, those failures are captured here. In this particular case the chat is closed by bot as Human Agent support is off.|
Select the date range and click on “Search” button to populate the different analytical information. All the graphs except the Active chat metrics are with respect to the below date range selected.
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