You can gain greater insight into customer feedback with chat rating, which adds a small thumbs up/down icon to the chat widget allowing customers to rate their chats.
Although chat rating is useful on its own to highlight particularly bad chats, coupling this feature with Analytics lets you monitor customers happiness across longer periods and discover which factors affect CSAT.
Let’s say you notice a dip in your CSAT. What do you do?
Head over to Analytics and select Satisfaction in the dropdown menu on the right.
This will immediately show you the peaks and troughs of your CSAT. For example, on 7 April, between 6 pm and 7 pm, your satisfaction rates dropped significantly.
Drill down to Agent Reports
In order to find out more about what happened at that time, you can open Agent Reports.
It seems that while 10 agents were logged in that day, only 3 were actively serving chats (as seen in the Activity Breakdown table).
We can also see that Samantha served 11 chats, receiving a CSAT of 100%. In contrast, Andy served 15 chats, with a CSAT of 60% and, Samuel served 24 chats, with a CSAT of 50%.
Individual agent profile
Naturally, we’d want to find out why Samuel and Andy had such low ratings. To find out, bring up the individual agent profile by clicking on the little magnifying glass beside their names.
If the customer left a comment with their rating, you can see why the chats were rated good or bad. For example for the two negative ratings given to Samuel, one of them was due to a misdirected customer and the other, customer confusion.
Together with the help of chat rating, Analytics lets you discover why customers were unhappy during a particular chat interaction and if your agents were a contributing factor.