Call Centre

Perform automatic speech recognition to transcribe, analyse and provide insights to how users are interacting with your business. We tap into the human element and leverage call data to optimize your operations.

Some key use-cases include:

1
Speech recognition
  • Automatic speech recognition solutions transcribe telephonic conversations into text so that they may be easily searched and organized. More sophisticated systems may split the conversation by speaker, detect emotion as well as analyse the content of the conversation tocategorise the type of conversation.
  • Another way AI is improving call centres is by incorporating smarter interactive voice response to streamline the call and improve the customers experience. This can assist those in the call centres by handling users that have requests that are manageable through simplerule based systems so they can be fully present when taking on the more difficult tasks.
2
Insight generation
  • AI that transcribes, conversational flow and monitors the emotional state of both the user and operator can provide valuable insights. Call centre AI solutions allow unstructured datato be used in predictive call routing to match users to specific service agents, compliance & coaching of agents reactions, and generate leads. This system may also be usedto optimize call centre operations by identifying top performing agents, provide scriptchanges based on emotional responses and optimize limited agent capacity to better achieve the objectives of the call centre.
Relevant Case Studies
Marketing Services Provider

Mobile Marketing Company

Automated data intergation and reporting platform to facilitate real-time reporting across the organization.

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Lead Generation Company

Major Lead Generation Company

Created a decision-making system to evaluate the likelihood of a scheduled marketing message generating a lead, and hence determine whether the message should be sent - all in real-time.

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Australia Awards

Government

Automatically review thousands of scholarship applications using machine learning. Highly accurate and highly explainable models helped staff reduce the number of applications requiring manual review and understand applicants better.

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