Hello Community members!

We know lengthy wait times can easily cause customers to abandon their call or communicate less effectively with an agent, ultimately resulting in poor customer satisfaction, loss of goodwill, business, and reputation for a company. Being able to predict how long an incoming interaction might have to wait until it is transferred to an agent is key in ensuring a customer's experience is positive and successful.

Re-introducing Estimated Wait Times

In a complex contact center setting, service times are often affected by factors that change often and based on specific situations. Queue abandonment, agent efficiency, concurrent interaction handling, agent availability and more, makes it difficult for Estimated Wait Time (EWT) calculations to be accurate unless the most recent historical samples are taken in.  Genesys Cloud's new EWT takes queuing theory and couples it with machine learning to deliver greater accuracy in wait time calculations.

Key Benefits:

• Take on shared queue environments – Sometimes agents can handle more than 1 queue at a time. Genesys Cloud's new EWT calculation looks at recent data to create more accurate estimates that support multi-skill environments.
• Continuously improving calculations – A machine learning mechanism takes into account the transient state of the queue at any time to help arrive at more accurate estimates every time.
• Say goodbye to padding – With greater precision, feel comfortable building a call flow with an EWT request without having to add additional time on the calculation.

 

The new EWT algorithm will come in effect on December 9^th, 2020. Learn more about how the New Estimated Time Calculation is done in our article, or comment below to get assistance on specific questions.

#Telephony

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Marcela Areiza
Product Marketing/Management Manager
Genesys - Employees
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Thanks for the note!!

Is there any way we can send an SMS to abandoned callers then create a callback for them using Architect?



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Sherif Sherra
NCR Corporation, Dubai
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Original Message:
Sent: 12-01-2020 09:20
From: Marcela Areiza
Subject: ⚠️ [IMPORTANT] ⚠️ New Estimated Wait Time Algorithm Coming Dec. 9th!

Hello Community members!

We know lengthy wait times can easily cause customers to abandon their call or communicate less effectively with an agent, ultimately resulting in poor customer satisfaction, loss of goodwill, business, and reputation for a company. Being able to predict how long an incoming interaction might have to wait until it is transferred to an agent is key in ensuring a customer's experience is positive and successful.

Re-introducing Estimated Wait Times

In a complex contact center setting, service times are often affected by factors that change often and based on specific situations. Queue abandonment, agent efficiency, concurrent interaction handling, agent availability and more, makes it difficult for Estimated Wait Time (EWT) calculations to be accurate unless the most recent historical samples are taken in.  Genesys Cloud's new EWT takes queuing theory and couples it with machine learning to deliver greater accuracy in wait time calculations.

Key Benefits:

• Take on shared queue environments – Sometimes agents can handle more than 1 queue at a time. Genesys Cloud's new EWT calculation looks at recent data to create more accurate estimates that support multi-skill environments.
• Continuously improving calculations – A machine learning mechanism takes into account the transient state of the queue at any time to help arrive at more accurate estimates every time.
• Say goodbye to padding – With greater precision, feel comfortable building a call flow with an EWT request without having to add additional time on the calculation.

 

The new EWT algorithm will come in effect on December 9^th, 2020. Learn more about how the New Estimated Time Calculation is done in our article, or comment below to get assistance on specific questions.

#Telephony

------------------------------
Marcela Areiza
Product Marketing/Management Manager
Genesys - Employees
------------------------------