Introduction

I have recently had a few conversations with customers about reporting and statistics in Live Assist for Dynamics 365 so I wanted to share on here what I have shared with them. The July 2018 iteration release of Live Assist for Dynamics 365 is introducing a new entity type called Chat Queue Statistics which will record in Dynamics 365 various data about the individual skills you have configured.

Our article on how to set this up can be found here: Chat Queue Statistics, so I will cover how this data can be used to produce useful reports. You can also see our article on the API provided by Dynamics 365 here: Chat Queue Statistics API.

The first item to note is that LAD365 does not provide its own Data Visualisation tool. We provide the data and you will need to utilise your favourite tool to analyse and display the data how you want. An example tool for this is Power BI by Microsoft, but there are plenty of others out there as well.

Live Assist for Dynamics 365 Data

The data from LAD365 is stored directly in the Dynamics 365 data model. There are currently 2 records that contain our data:

1. Chat Activity - This contains data about a specific chat
2. Chat Queue Statistics - This contains data about a skill queue

Chat Activity Data

• Name: Chat Activity
• ID: cxlvhlp_chatactivities

The Chat Activity has been around since the initial release of LAD365. A Chat Activity is created for each chat conversation that is held and the data stored in the chat activity is specific to that chat. I will not list all of the data elements stored in the Chat Activity as they can be easily seen in your Dynamics 365 solutions install, but some highlights are:

1. Source Page URL - cxlvhlp_SourcePageURL - Analyse how much chat traffic different web pages are generating.
2. Chat Duration - cxlvhlp_duration - Analyse how long different agents spend on chats
3. Co-Browse Sessions - cxlvhlp_NumberOfCobrowseSessions - Analyse where and when cobrowse is being used to enhance your customer service
4. Post Chat Survey - Analyse customer satisfaction through your post chat surveys

Chat Queue Statistics

The Chat Queue Statistics are new in the July 2018 release (package version 3.2.0.3).

• Name: Chat Queue Statistic
• ID: cxlvhlp_chatqueuestatistics

This entity will capture historical data about a specific skill queue. Each instance of the entity will represent a 5 minute window and new instances will be created on an hourly basis automatically by LAD365 if a chat occurred during the window. The number of Chat Queue Statistic entities created in a one hour window for each skill will therefore equate to the number of 5 minute windows that a chat occurred in.

Examples:

• Chat Occurs every minute for 1 skill = 12 x 1 = 12 Chat Queue Statistic Entities created in a 1 hour period
• Chat Occurs every 10 minutes for 1 skill = 6 x 1 = 6 Chat Queue Statistic Entities created in a 1 hour period
• Chat Occurs every minute for 5 skills = 12 x 5 = 60 Chat Queue Statistic Entities created in a 1 hour period
• Chat Occurs every 10 minutes for 5 skills = 6 x 5 = 30 Chat Queue Statistic Entities created in a 1 hour period

The data stored in the Chat Queue Statistic entity can be inspected easily in Dynamics 365, so again here are some highlights:

1. Average Available Slots - cxlvhlp_averageavailableslots - Average number of available agent slots. Agents can of course handle more than 1 chat at a time, so if an agent is configured to handle 5 concurrent chats and are on average engaged in 2, then they will have 3 slots available.
2. Average Queue Size - cxlvhlp_averagequeuesize - Average number of visitors waiting in the queue
3. Chats Abandoned - cxlvhlp_chatsabandoned - The number of chats abandoned. (Abandon: A visitor starts a chat, enters a queue but closes the chat before it is answered)
4. Total Wait Time Before Abandonment - cxlvhlp_totalwaittimebeforeabandonment - The total amount of seconds visitors spent in a queue before abandoning

Calculating Statistics

With this information stored in Dynamics 365, it is possible to calculate different statistics. Here are some examples:

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