Speech Recognition technology sounds attractive as it is a step forward to automated voice processes. Whether that is partly or fully as yet, voice automation is a technology journey that has made harnessing speech data much easier than in previous decades. Multiple industries are looking for efficient ways to mine data from voice processes, as they generate millions of bytes, which should not be left untouched.
A way to get ahead is adopting a speech analytics platform, testing its viability for your market-population mix, and generating adequate functional responsibilities based on the insights generated from individuals and demographic segments.
Speech analytics gives call agents a head start, with the quality of data that is more individualistic than before. Besides improving the analytical output, speech-based capabilities also ease the burden on agents, analysts, and management personnel in consumer-driven organizations.
Let’s look at the factors driving adoption in recent years.
The rise of virtual assistants
In many consumer-driven markets, the recent trend of auto-response interactive services, or chatbots, is still prominent. However, in the voice process, businesses are asking if a similar revolution is already happening. The typical requirement of cutting-edge customer service is lower costs and higher analytical value, especially as customers grow. Thus, speech recognition is essential in the technology mix for contact centers. Besides offering easier, inexpensive ways to deal with queries, it offers data from speech that can help machines trigger processes, optimize the workflows, and help executives respond effortlessly.
The need for contact centers to prove their endurance
With lack of technological innovation in most contact centers, they have had the reputation of turning into cost centers. Technology is expected to drive automation, but voice data always seemed to be complicated for machines. Improving agents’ performance or customer experience, or both requires knowing attitudes, the explicit and implied opinions of customers, their intentions implied through conversation, and thus, a technology which can capture audio bytes in high resolution.
Reduced complexity and cost of sales operations
Sales-call strategies are often required to be based on complex analysis, which relies on online data. With business intelligence, sales strategies became easier to develop, but the results were not that easy to predict. However, sales calls requiring high compliance, speech technology offering succinct menu-driven programs, and machines having the capacity to trigger calls, targeting can be more accurate.
Better research and access to speech technology
Over the recent years, due to better data processing and storage capacity, research in the area of audio data-mining has flowered to feasible implementation. It has given businesses the opportunity to filter essential elements like unsaid emotions and interest in specific products, besides the ability to detect multiple languages. Filtering milliseconds of audio bytes to detect voice patterns is an advanced capability contact centers can now use to “listen” to their customers’ intentions.
The ever-growing need and applications of data
If companies have speech capabilities, they will have the opportunity to mine more information, individually, about their customers at large. Competitive advantage through more depth in data is the reason why speech analytics is becoming an important technology. In consumer markets, languages, cultures, demographic trends, and geographical factors vary. Responding too can become an unprecedentedly simpler task using multi-lingual, dialect-recognition voice technology as part of a cloud-based business analytics system.
It is important to understand that fetching the best value from a Speech Analytics product has much to do with optimizing the workflow and operations. Using the valuable data, organizations have proved under-a-year ROI is achievable.
Click to access our whitepaper publication which talks about how easy it is for enterprises to deploy and operate Speech Analytics.