What is Average Handle Time (AHT)?
AHT (Average Handle Time o Average Handling Time) is a metric used in call centres, customer service and help desk operations to measure the average amount of time an agent spends on a customer interaction, including talk time and post-call work time. It is calculated by adding up the total time spent on all calls, chats, emails or any other customer interaction and dividing that figure by the number of interactions handled by the agent.
AHT is an important metric for customer service operations because it provides insight into the efficiency of agents and the overall process. It is used to identify areas where improvements can be made to reduce handling time, such as streamlining processes, improving technology or providing additional training to agents. In addition, a low AHT can improve customer satisfaction, as it often indicates that customers spend less time waiting for assistance and receive faster resolution to their problems.
How to reduce the average handle time?
The voice biometrics solution from Veridas, a leading company in the development of solutions for digital identity verification, makes it possible to reduce the average handle tiem (AHT) and authenticate users with:
- 3 seconds of voice, regardless of text and language.
- With more than 99.9% accuracy, evaluated by the National Institute of Standards and Technology (NIST).
- Maintaining maximum privacy: Veridas does not store customer data at any time; all our technology is under a strict data privacy policy, complying with GDPR and CCPA.
Veridas already has end-users in countries such as Spain, Germany, Holland, Japan, and Mexico, among others. Our technology is used in the Contact Center platforms of some of the world’s leading companies, such as BBVA, Deutsche Telekom, Prosegur, and the leading Spanish energy company. Embracing from the financial or telecommunications sector to the alarm or energy sector.
How to calculate Average Handling Time (AHT)
The TMO is calculated by dividing the total time spent on calls by the total number of calls handled. The process is broken down here:
- Add up the total time for all calls: This time includes both the time the agent is talking to the customer (talk time) and the post-call time (time spent recording information about the call after hanging up).
- Counts the total number of calls handled: This includes all calls that have been answered and handled by agents during the measurement period.
- Divide the total call time by the total number of calls handled: This will give you the TMO.
The formula is:
TMO = Total call time/Total number of calls.
Call Centers: authenticate the user in real-time while conversing with an agent
Implementing a solution like Veridas’ in a Call Center environment would enable cost reduction, improved user experience, and increased security.
Cost Optimization: Reduced Average Handling Time (AHT) and Increased First Call Resolution Rate (FCR)
Until now, authenticating a user in a call center environment required a lengthy process, lasting 30 to 60 seconds, based on personal questions, which makes security questionable. With the Veridas solution, the user can be verified while speaking naturally with the agent, completely eliminating the time spent on authentication. This dramatically reduces the Average Handling Time (AHT).
Considering the average error rate in knowledge-based authentication, over 10-15%, implementing a solution like Veridas’, with an accuracy of over 99%, would reduce the associated costs in support calls.
Better user experience: any language and text, increased Net Promoter Score
In addition, it is a solution that makes the authentication process an accessible and inclusive process: no more passwords, no need for SMS or email verification to validate a transaction, no more lengthy question-based processes… and the user’s password becomes what makes him unique, his voice, significantly improving the user experience.
Maximum security: fraud reduction
Moving from knowledge-based elements (Knowledge-Based Verification – KBV – or passwords) or possession elements (OTPs) to inherence elements (voice) generates a much more robust solution to prevent and detect identity fraud. In addition, the Veridas solution enables active and passive detection of prerecorded or synthetic voices.
Veridas voice biometrics: forget about choosing between security, savings, and user experience.
Voice biometrics solutions require the end-user to complete two steps for use. First, the user must enroll his or her voice and then authenticate with that enrollment. During enrollment, biometric engines transform the voice into a voice vector. And it is in this process that Veridas stands out from other solutions available on the market.
Veridas’ solution works based on artificial intelligence and neural networks, requiring only 3 seconds of voice in any language and without the need to repeat a specific phrase to create a voice vector, which is irreversible.
It is also multiplatform by design; our solution is designed in such a way that it can be easily integrated into any existing platform. As a result, we continue to consolidate a network of partners that allows us to be present in countries worldwide.
Finally, committed to quality assessment to certify its performance, Veridas is the only company in the world present in the NIST facial verification (1:1), identification (1:N), and voice recognition evaluations and in compliance with state and European regulations.
