Contact centres have long served as a pivotal touchpoint for businesses to interact with customers. Each day, thousands of calls are made and recorded, leading to an enormous wealth of untapped data. By leveraging the power of transcription and AI, businesses can unlock the hidden value in these call recordings and generate a custom Large Language Model (LLM) to gain actionable insights and improve customer experience.
The Power of Transcription and AI in Contact Centres
Transcription is the process of converting spoken language into written text. In contact centres, this means transcribing call recordings for analysis. However, manual transcription can be time-consuming, expensive, and error-prone. This is where AI comes into play. By employing AI-driven transcription services, businesses can quickly and accurately transcribe call recordings, transforming them into a rich source of data.
The next step is using this transcribed data to build a custom LLM. LLMs are advanced AI models that can understand, interpret, and generate human-like text. By training a custom LLM on the transcribed contact centre data, businesses can gain valuable insights and predict customer behaviour more accurately.
Unlocking the Hidden Value
Training service staff with the most effective behaviour & utterances
Building an LLM on historical conversations and giving it a ChatGPT interface gives you the ultimate staff training agent because it knows what works and what doesn't and it can make suggestions for increasing sales, collecting debt more effectively or getting a commitment of some kind. The larger the LLM the better, and if it is entirely based on your businesses recorded conversations the suggestions made by the AI agent are extremely relevant.
Identify patterns and trends
By analysing the transcribed call data, AI-driven algorithms can identify patterns and trends in customer interactions. This can help businesses understand common customer concerns, preferences, and pain points. In turn, this information can be used to improve products and services, address customer issues proactively, and create more targeted marketing campaigns.
Identify Customer Pain Points
By analysing call recordings, businesses can identify common issues or problems that customers are experiencing. This information can be used to make improvements to products, services, or processes to address these pain points.
Enhance agent performance
Custom LLMs can also be used to assess and improve agent performance. By analysing call transcripts, businesses can identify areas where agents excel and areas that need improvement. This can help create tailored training programs, boost agent morale, and ultimately, enhance customer satisfaction.
Track Customer Sentiment
By analysing the language and tone used by customers in call recordings, businesses can track customer sentiment and identify patterns in customer behaviour. This information can be used to improve customer satisfaction and retention.
Automate routine tasks
AI can help automate routine tasks, such as generating responses to frequently asked questions or providing suggested solutions to common customer issues. By streamlining these tasks, contact centre agents can focus on more complex and high-value customer interactions.
Train your next service agent
AI can be used to create digital service agents using your own data extracted from the historical call recordings. The LLM model would be tuned to communicate to clients with text chat or voice in the most effective manner based on the call recording examples.
Personalise customer experience
Custom LLMs can help businesses deliver a more personalised customer experience by understanding individual preferences and tailoring interactions accordingly. This can lead to increased customer loyalty, higher retention rates, and improved customer satisfaction.
Predict and prevent customer churn
By analysing call transcripts and customer interactions, custom LLMs can identify customers at risk of churning. Businesses can then proactively address their concerns and offer incentives to retain them, thereby reducing churn rates and increasing revenue.
Conclusion
Contact centre call recordings contain a wealth of valuable information that often goes untapped. By creating a custom LLM, businesses can analyse large amounts of data in a fraction of the time it would take to listen to recordings manually. By leveraging transcription and AI to generate a custom LLM, data can unlock the hidden value in these recordings and gain actionable insights that can be used to improve customer experience, enhance agent performance, and drive revenue growth. By embracing this technology, businesses can quickly improve their product and customer service and get a competitive edge. Procrastinating, on the other hand, they can be left behind very quickly as the adoption of AI services explodes.
