An African finance house needed to reduce costs and improve service. Learn how Aya developed voicebots in five local dialects.
The Challenge
A major financial services company operating in seven African countries with over 6 million customers faced a big challenge: maintaining efficient and affordable 24/7 customer support. Despite using chatbots and voice recognition systems, their customer service teams were overwhelmed, leading to long wait times and unhappy customers.
To tackle these issues, the company needed a solution that could improve customer interactions and reduce the workload on their support staff.
The Solution
Aya Data partnered with industry experts to create and launch voicebots in five local African languages. Here’s how we made it happen:
1. Voice Data Collection: We gathered thousands of hours of voice recordings in different dialects and carefully labelled them.
2. Model Development: We used this data to train AI models to understand and respond to common customer inquiries in these dialects.
3. Voicebot Deployment: We built and implemented custom voicebots that could handle various customer requests, providing smooth and accurate responses.
The Results
The new voicebots made a noticeable impact:
- Reduced Workload: The voicebots managed about 50% of customer inquiries, significantly easing the burden on the customer support team.
- Faster Response Times: With the voicebots handling many requests, customers experienced quicker responses.
- Increased Satisfaction: Customers reported higher satisfaction due to faster and more efficient service.
By introducing voicebots that speak local dialects, the company improved customer service, cut costs, and enhanced the overall customer experience.
Looking to boost your customer service with innovative voicebot technology?
Contact us today to discover how our solutions can transform your customer interactions and improve satisfaction.
Disclaimer: Aya Data respects client confidentiality and will not share specific client details or project information. Any identifying information in our case studies may be anonymized.
