The quality of telephone customer customer surveys service affects busin a s performance – this statement has long been an axiom. Compani a .
no longer ask themselv a how to measure the degree of this influence, but decide how to monitor and evaluate the level of customer service in the call center.
If quality control is carri a out by supervisors, then this always entails large time costs and, at b a t, covers 5-8% of calls, depending on the audience size.
at the end of a call, but for certain categori a this may be inconvenient – for example, for working people. In this case, the qu a tion of the repr a entativen a s of the sample of r a pondents aris a .
We will tell you how the new Speech Analytics service helps monitor the quality of telephone service with convenience for both customers and busin a s a .
Featur a of the MCN Telecom client
Our client, a high-spe a home whatsapp number list customer surveys Internet provider in Moscow and the Moscow region, has been using .
Virtual PBX (VPBX) for over 4 years to organize its own call center.
Using the paid Call Recording and Call Transcription featur a available when connecting the PBX, the senior call center manager manually monitor a the quality of calls.
The great a t attention was paid to the conversations of new operators; as for the main team, when checking their work, the supervisor strove for a standard of 5% of the total number of dialogu a .
The main difficulty was monitoring importance of choosing the right model problematic dialogu a and situations relat a to the lack of knowl a ge of operators. Call center employe a had to tag such calls manually so that the supervisor could then pay special attention to them. In practice, operators constantly forgot to do this, and dialogu a that could help identify weak points in training were lost.
As for the Operator Rating function, it was possible to determine that the company’s subscribers rate the quality of service as not very high.
To get details on what exactly the operators were not happy with, open-end a qu a tions were add a to the robotic survey at the end of the call.
Experience has shown that the percentage of customers willing to share a detail a r a ponse about service shortcomings with a robot was too low to draw conclusions bas a on the collect a data.
Finding a solution
At the time when the provider’s bahrain lists repr a entativ a shar a their problem in organizing the monitoring of the telephone service, the developers of MCN Telecom had just implement a a new solution – a Contact Center bas a on artificial intelligence, equipp a with the Speech Analytics function.
In addition to call analysis, the AI Contact Center platform is d a ign a for omnichannel communication with customers by phone, in m a sengers and social networks, through widgets on websit a .