TechSee

JUNE 11, 2019

Easier data verification: when visual proof is required, such as for billing disputes, promotional eligibility or warranty authentication, customers can simply show the agent their documents via their smartphone. KPI #4: Average Handling Time (AHT). Click here for the full report. Impact of Visual Assistance on AHT.

Self Service 117

Self Service Technology Customer Service Contact Center 117

TechSee

JULY 17, 2018

Enabling image input into IVR shortens the entire process significantly: shorter average handling times (AHT), shorter call times, and best of all, an opportunity to wow customers. The process of visual integration. During the IVR conversation, the customer is requested to upload an image or video.

Wait Times 114

Wait Times Self Service Meeting Call Center 114

TechSee

AUGUST 14, 2018

Implementing decision support tools backs up the agent, putting the right information at the tip of their fingers, helping them work smarter and perform better in operational KPIs such as First Call Resolution (FCR) and Average Handling Time (AHT).

Contact Center 95

Contact Center System Average Handle Time Virtual Agent 95

TechSee

OCTOBER 22, 2019

NIA is measured by tracking the number of repeat calls a contact center receives within a specific period of time. The metric is used in conjunction with standard metrics like Average Handling Time (AHT) and First Contact Resolution (FCR) which track the contact center agent’s speed and efficiency per call.

Contact Center 84

Contact Center Self Service Effort Score Average Handle Time 84

TechSee

JUNE 25, 2019

Companies can use biometrics to verify warranties, ensuring that customers receive service for their devices without requiring them to save receipts or warranty documentation. Using biometrics, agents can recognize customers, and greet them in a personal manner. High-level data analysis. Process improvements.

Technology 122

Technology Customer Service Contact Center Omni-Channel 122

TechSee

FEBRUARY 7, 2023

the engine under the hood of ChatGPT), Bard (powered by LaMDA, from Google), and others promise to be able to understand user intent, scrutinize all available documentation or information, and provide contextual answers to every user query. Unlike traditional flow-based AI, the large language modeling behind GPT3.5 (the In a word, maybe.

Innovation 124

Innovation Self Service Chatbots Call Center Solutions 124