GenAI “coaching” leads to 50% growth in customer engagement

About the client

The client is the first fintech specialized in import solutions for businesses in Brazil and Latin America that offers financial solutions in credit, financing, and currency exchange, along with technology solutions that simplify, streamline, and unify services on a single platform. The company stands out through three fundamental pillars:

• Technology: A team of programmers specialized in innovative solutions.
• Financial Expertise: Financial knowledge to identify the best products and maximize results.
• Import Focus: Founded in international trade with a long history in one of Brazil’s leading trading companies.

The challenge

The company operates through Sales Development Representatives (SDRs) who create business opportunities by contacting clients through various channels, including direct phone calls with leads. 

The business challenge was to extract quality metrics from these calls and ensure optimal use of the sales pitch, improving SDRs’ operational quality and increasing business opportunity conversion.

Previously, all call analysis to identify service improvement points, pitch adjustments, and service quality assessments were conducted manually by the manager, who would listen to each call’s audio and perform evaluations. To help generate automated reports for analyzing these calls, e-Core offered support with a custom artificial intelligence solution using AWS resources.

The solution

The solution begins by using the SDRs’ phone call recordings with leads. The first step was to create a processing pipeline to convert the recordings into text. With the transcribed audio, we used Generative AI to evaluate the call. We developed a prompt to assess the dialogue between the SDR and a lead, analyzing aspects such as pitch adherence, communication skills, and presentation of the company’s product and services.

The final analysis result provides constructive feedback focused on areas for improvement, development, and motivation for the SDR. We used a Generative AI model to automatically transform call transcriptions into structured data with Amazon Bedrock, extracting and organizing essential fields, and generating constructive feedback to improve SDR performance. The resulting file is stored in an AWS S3 bucket and sent to the manager’s area on the company platform via an AWS SQS queue. Below is the architecture of the custom solution developed by e-Core.

The outcomes

The call analysis process, which previously required considerable time and effort from the manager, is now automated, enabling immediate feedback for both the SDR and manager right after each call. The solution’s scalability allows processing of 200 audios in just 2 minutes, something unachievable through manual efforts.

Additionally, the cost of the automated solution is lower than having someone perform the same task manually. Automation not only reduced the average call analysis time but also enabled detailed metrics for all calls, such as average call duration, call quality, and SDR productivity.

With feedback for all calls, the average call duration increased by 50%, indicating greater customer engagement, and call effectiveness improved by 20%. These results directly impact service quality and business opportunity conversion, solidifying the company as an innovative and efficient fintech in the import sector.