Case Study - Sentient Machines

Understanding customer interactions utilizing speech technology

Gaining critical insights and optimize their call center operations.

Contact centers handling high volumes of calls inevitably produce huge quantities of data, and businesses are increasingly focusing on new ways to capture and utilize this untapped wealth of information.

While the aim is usually to maximize efficiency and reduce costs, businesses can simultaneously improve the customer experience, which leads to increased sales and revenue. To do this, they must first understand their customer interactions.

Businesses seeking to use their system data to improve customer care and provide a more proactive service are turning to Natural Language Processing (NLP) and BigData analysis to gain critical insights and optimize their call center operations. This process begins with speech recognition.

Machine learning – understanding humans

Sentient Machines uses deep learning to bring an understanding of customers to the call center industry. Their cloud-based platform, Sentient Analytics, interprets calls and learns from customer-agent interactions with real-time monitoring. Using Speechmatics’ Automatic Speech Recognition (ASR) software, natural language interactions between customers and agents are transcribed and analyzed for insights into customer emotions, motivation and frustrations. Sentient Analytics investigates how to improve the customer experience by analyzing callers’ sentiments and emotional shifts – after transcribing the voice file, it interprets any hidden meaning. The software can even highlight customers who are about to leave the call in real-time, sending the agent an alert telling them why.

Maximizing data value and business benefits

With a user-friendly web-based data dashboard, Sentient Analytics presents performance metrics in a clear and easy to digest format, providing immediate, actionable customer feedback for agents while uncovering hidden trends and providing business managers with insights to improve call center services and user satisfaction. To achieve this, Sentient Analytics requires a high quality transcription solution. “We shortlisted 3 companies before choosing Speechmatics,” says Dr Damljanovic, “We need reliability and precise results, and we need them in real-time. Speechmatics is fast, accurate and clearly identifies each participant – it was by far the most robust solution for conversations featuring different accents.” After converting Sentient Analytics’ call analysis into data-driven business decisions, customer care can be improved with personalized agent training, while call center operations can be optimized, highlighting anomalies and saving time by replacing manual intervention in quality assurance.

“It’s a win-win for businesses. By recording, analyzing and therefore understanding more about call center interactions, the business can offer customers an improved, personalized journey leading to less turnover, while also gaining valuable insights into weaknesses in their processes, along with real-time information which can increase sales conversions.”

Dr Danica Damljanovic CEO and Co-Founder of Sentient Machines


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