eAlicia Business Case: Speech Analytics with AI in quality audits. Transition from manual to automated model
With this reading our aim is to share our experience and the advantages of refocusing manual quality audits towards automated audits with eAlicia Speech Analytics technology using generative AI. That is why in this case study we will focus on the economic impact for the organisation providing the service and on improving the KPIs related to the Customer Experience.
Implementation of eAlicia Speech Analytics with Generative AI in Quality Audits
Background
- Low efficiency and low outreach: Manual review was a slow and laborious process, allowing only 5% of total calls to be audited.
- Limited accuracy and subjective decisions: Human subjectivity introduced variability in audit results.
- Late detection of problems: Identification of emerging issues and trends was slow, affecting the company’s ability to respond.
Objectives set for the Project
The implementation of the eAlicia Speech Analytics solution with AI had the following objectives:
- Increase audit coverage: Evaluate 25% of telephone interactions; a much more representative sample for more confident decision-making.
- Improve accuracy: Reduce subjectivity and increase consistency in quality assessments.
- Identify problems in an agile way: Detect recurring and emerging problems quickly and take immediate action.
- Impact customer satisfaction positively: Use the insights gained to optimise processes and improve the customer experience.
Proposed Solution
The proposed solution involved the implementation of eAlicia Speech Analytics with generative AI, which was incorporated into the service:
- Automatic transcriptions: Convert phone calls into text with high accuracy.
- Sentiment analysis (SAS): Assess the emotional tone of interactions and catalogue them.
- Detect keywords for our client: Identify topics and keywords relevant to our client and their quality audits.
- Customised reporting: Create automatic reports on quality metrics and trends detected that are aligned with strategic quality plans.
Benefits / Expectations of our client
- Expand audit coverage: Increase the current analysis of calls by 5 (25% of the total) to ensure that all problem areas are detected and addressed. Pursue a more representative sample.
- Increase accuracy in fieldwork: Generative AI reduces human variability, providing more consistent, accurate and unbiased assessments.
- Improve efficiency: Automating the audit process frees up time and resources, allowing quality personnel to leave those functions to become expert calibrators with higher value-added tasks.
- Increase customer satisfaction: Insights derived from the analysis would be used to better train service staff, improve internal processes and, as a main objective, increase customer satisfaction.

Results obtained
After implementing the eAlicia Speech Analytics solution with generative AI, our client achieved the following results:
- Five times the previous sample of quality audits: 25% of calls were audited, providing a complete picture of performance and potential problems previously missed with the 5% audited manually.
- Improved service quality: Recurring problems were quickly identified and corrected, improving service quality and customer perception.
- Cost efficiency: The automation of the audit process, with the same investment for our client, made it possible to multiply the sample to be analysed by a factor of 5, with all the benefits that this entails. If we had not wanted to multiply the audited sample by a factor of five, the costs would obviously have been much lower than with manual audits.
- Increased customer satisfaction: 15% increase due to improvements in service quality and faster problem resolution. In addition, service perception was improved thanks to the continuous improvement levers incorporated in the quality strategy.
Increasing KPIs
- Audit coverage: Increase from 5 to 20% of the audited sample.
- Audit accuracy: 20% improvement in the consistency of assessments.
- Problem detection time: 45% reduction in the average time to detect recurring problems by identifying a greater number of problems due to the increase in the sample to be audited.
- Operational cost efficiency: The audited sample was increased by a factor of five with the same investment in manual audits.
- Customer satisfaction: 14% increase in CSAT.
Conclusions
The transition from manual to automated quality audits (with the same investment) using the eAlicia Speech Analytics solution with generative AI has been highly beneficial for our client. Not only has it improved efficiency, increased sampling and accuracy of the audit process, but it has also enabled a faster response to the client’s needs, resulting in a significant improvement in CSAT.
Therefore, it seems that the transition is more than justified.
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