Contact Center Optimization: Strategy to Improve Customer Service by Implementing Generative AI

Strategy for applying AI in the Contact Center


How can we transform Contact Centers (CC) with generative AI? CC services are one of the best sources of information and knowledge about our business: their job is literally to interact with customers and prospects. CC agents end up receiving information about what our customers want and what they don’t want, what we explain well and what we communicate poorly, what value they perceive in our proposal and what problems can be sources of frustration.

  • At the same time, it is a difficult environment to analyze: because of the volume, the medium, the sensitivity…. From the outside, the CC is seen as a black box from which it is very difficult to obtain information and to know what happens in each call. It is only possible to get a rough idea by doing punctual listening and manual audits on call samples.
  • On the other hand, agents can respond quite well to a limited number of questions, but it is impossible for them to know the answer to all the queries that will be posed to them.
  • Finally, there is a group of issues or tasks that customers could solve in self-service mode, without the need to reach an agent, which is a costly resource in time and money.


With the existing technology until recently it was impossible to address the problem diagnosed above, but with the recent takeoff of AI and its different aspects, a service can be created to solve the needs mentioned above. This service is based on Generative AI and connects to each company’s current systems to extract and process the information.

Thanks to Generative AI and LLMs (Large Language Model) we can know what is happening at all times and have the Contact Center monitored, to extract Business Insights and to perform Quality Audits on the calls.

On the other hand, we can offer conversational tools to operators that translate into a more economical service for the company. Fewer operators, but more efficient. Using Generative AI to support Contact Center operators provides greater efficiency and better quality. We are talking about call time reductions of 20%.

We can also offer similar tools to customers to solve some types of queries autonomously. In this case we can drastically reduce the traffic to the Contact Center. Depending on the type of service, these savings can reach up to 70 or 80%.

Use Cases

Some of the main use cases we have developed are:

  • Advanced analytics:

    – Business Insights: Dashboards with information from Contact Center call transcripts, allowing business decisions to be made to optimize service based on real customer feedback.
    -Call quality audit: Comparison of the script proposed by the company with the agent’s audio transcript, Sentimental Analysis of the conversation, NPS (Net Promoter Score), etc.
  • Copilot for agents: Conversational tool that helps operators to be more efficient and provides them with real-time information to give a better and faster response to customers.
  • Self-service copilot for customers: Conversational service included in the private area of the customers’ web site to help them solve the most frequent queries autonomously.
April 18, 2024

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