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Today, I will share my thoughts on the immense potential of voice call analysis for the business sector, particularly in the context of Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP) systems. Despite the prevalence of chatbots and other text processing technologies, only 3% of business solutions currently utilize the potential of voice interaction analysis.
Our team analyzed 100,000 voice queries from clients to a company. Our goal was to answer the question: 'Can we understand how to communicate with a lead before the first call, having only basic information about them, to increase the chances of conversion?' From the entire database of calls, we clearly identified 10 tones of conversation (see screen in the article). By correlating this with information about the client's future conversion or loss, as well as previously known information about them, we built a model that currently provides sales recommendations on how to better converse with a lead. Just imagine :)"
Now, let's discuss more technically how this and similar services can be applied:
One of the key aspects often overlooked is the analysis of customers' voice tone during calls. Utilizing machine learning algorithms to cluster customers based on their tonal characteristics can provide companies with valuable insights. For example, grouping customers with a positive voice tone can help preemptively identify successful interactions and sales strategies.
Voice call analysis can also be integrated into CRM systems for automating the assessment of customer inquiries. This not only improves the process of quality handling but also allows for the detection of trends and the anticipation of customer needs. The application of deep learning technologies to recognize customers' emotional states opens up new possibilities for personalized service.
In the context of ERP systems, voice data analysis can help optimize internal processes. For example, identifying stressful situations in employee conversations can indicate problems in work organization or training. This creates opportunities for timely corrections and enhances enterprise efficiency.
We will not tire of stating that chatbots and ChatGPT represent only 1% of the productivity potential of AI/ML in business solutions, and we will continue to showcase the excellent work of my team.
