For any new technology to gain global adoption, it is critical that it is capable of resolving serious business issues at scale. It must be able to make operations more efficient, faster and affordable for the adopters. That is where conversation intelligence platforms have rapidly emerged as the tool of choice for contact centers across industries and geographies.
About a decade ago when AI conversation intelligence started taking shape, it was expected that it would be mostly about chatbots. However, the modern SaaS companies building conversation intelligence solutions have expanded the capabilities far beyond that to cover 100% of conversations across voice, chat and email. For instance, Mihup offers products that can handle as many as 25 languages, and dialects thereof. This makes the platform highly useful for a linguistically diverse country like India.
This has been made possible by combining the developments in the natural language processing arena with AI and creating solutions that accurately comprehend the words being spoken during a conversation between an agent and a customer. These tools can also understand customer sentiments through a real-time evaluation of various parameters such as tonality, silence on the call, threat words etc. Deploying such solutions is easy and fast as they are cloud-based and do not require significant investments or alterations in hardware that is available with contact centers. In fact, a leading platform can seamlessly work with major diallers. These abilities enable the conversation intelligence platforms to resolve major operational challenges faced by contact centers globally.
The customer service experience delivered by contact center agents is paramount to the growth of a business and maintaining good market reputation. That’s where conversation intelligence solutions have managed to increase agent efficiency by up to 50%. They achieve this through real-time support in the form of cues to agents on their screens, and automation of routine processes which leads to reduction in time spent on each call. The real-time agent-assist system can suggest the next best step to an agent and pull-out relevant information from the CRM automatically to reduce the effort. Further, it can offer live transcription, note making and automatic call summary generation. By being able to revisit these notes later, agents are not only able to respond faster and with greater accuracy, but also spend less time on other routine activities. This leads to a greater experience for the customers, and less fatigue for the agents.
Further, conversation intelligence solutions can also undertake automatic backend call analytics. These systems can fill the QA sheets with scores at a faster pace and provide data through integrated dashboards that can be accessed for further evaluation or generation of reports for strategic decision making. Contact centers making such holistic usage of conversation intelligence have seen 20% higher sales conversions. The additional revenue generation alone justifies the investments made apart from the goodwill generated in the market.
Another major benefit that conversation intelligence offers is the advancement of mobility. In vehicles that come with embedded conversation intelligence tools, drivers can simply use voice commands for operating in-vehicle systems such as air-conditioning and music or to make phone calls. Further, advanced voice assistance solutions can also observe the driver’s behaviour and create personalization on various parameters.
Conclusion
The conversation intelligence market is registering a CAGR of 20% year-on-year, and is expected to go past $30 billon by 2030. This high rate of growth is fuelled by several transformational improvements it has brought about. Smart mobility and AI-driven sales and customer service are going to be two of the key pillars of the future ecosystem, and conversation intelligence has already started delivering significant improvements in both areas. The day is not far when we will see custom solutions that will make it possible for humans and machines to seamlessly converse, understand and collaborate with each other.
(The author is Mr. Bhaskar Mishra, Head of Product, Mihup, and the views expressed in this article are his own)
