Context: Understanding customer satisfaction is important for our business, however, today's approaches are too imperfect:
Survey: asking users directly.
Response rate low (1-3%) and polarized (super happy or frustrated)
Not representative of all messages or conversations. This can be disrupting and
Time-consuming for the receiver. Can be delicate to ask
Manual reporting: support agent or RM logging the sentiment of their customers takes time, is hard to scale and hard to get accurate.
Low volume: difficult to get enough customer survey responses for meaningful CSAT reporting
Request: Get real-time satisfaction insights (~CSAT) across every conversation, without introducing a change in behavior or new software.
We would like to know customer satisfaction :
at different levels
Message
Conversation
Contact
Account: "Account Health" type scoring --- ex, if someone writes in 6 times over the year, what's the sentiment of all those conversations (whether they are by the same person or from different people within the same company)
at different time
Real time → to adapt workflows (SLA, escalation, tone …)
Specific time (First inbound, at the end (resolution))
Over-time
Actions:
Making the (AI) customer satisfaction ratings visible in analytics would be another way of getting insights into quality of communications.
be able to drill down into conversations where the satisfaction is low.
reporting on satisfactions
create a workflow based on satisfaction