Speech Analytics Market Size

Speech Analytics Market Analysis

The Speech Analytics Market size is estimated at USD 3.13 billion in 2024, and is expected to reach USD 6.47 billion by 2029, growing at a CAGR of 15.61% during the forecast period (2024-2029).

Speech analytics solutions can convert call recordings to actionable data and then translate the data into valuable, effective insights across the enterprise. These solutions are primarily utilized to handle a broad range of customer interactions. Enterprises globally have incorporated speech analytics through a combination of internally recorded data and externally syndicated data to generate a cutting-edge solution to understand customer requirements and comprehensively reduce churn.

• Speech analytics provides actionable insights that boost corporate value and motivate data-driven decision-making to improve individual agent training methodologies. To improve customer satisfaction, it is critical to measure contact center efficiency. As a result, using speech analytics, users can uncover issues that may be trending across several calls but were not identified as a major concern at the time. Companies can use speech analytics tools to comprehend unexplained consumer behavior better and gain customer insights into intent and satisfaction level.
• During the COVID-19 outbreak, the potential end-user industries were adopting cutting-edge technology-enabled speech analytics solutions, further boosting market growth. While call centers have long been a great frontier of workplace automation, the pandemic accelerated the overall process. Also, AI and machine learning have massively upscaled the speed at which companies may segment conversations into relevant categories through speech analytics to understand what's happening in a conversation.
• One of the critical components of speech analytics solutions is transforming audio data into text. Text is much easier to share and search than audio to prove regulatory compliance, conduct an audit, or enable the discovery process in the event of litigation. The data is available for anyone who needs it in an easily found format within the organization. In January 2022, Meta AI released data2vec, a high-performance self-supervised algorithm that applies to multiple modalities, including separate applications onto speech, text, and images. It was identified to have outperformed industry-standard single-purpose algorithms for computer vision and speech.
• Moreover, the market is witnessing efforts from vendors toward product innovation and various partnerships to provide businesses with better solutions. For example, Cogito has developed a real-time conversation-analysis tool based on behavioral science and deep learning. The company's AI listens to conversations for both content and tone. Cogito claims that it may detect mimicking, change in volume, pitch, etc., to gain real-time insight into how customers are exactly feeling and how all company calls are going. It also provides real-time suggestions to customer service representatives to improve the call and evaluate performance.
• One of the first extensive tests of Cogito's system was done at the insurance company Humana during a six-month trial which involved a total of 200 agents' calls, thereby making use of the system resulted in a 28% improvement in net promoter scores, a 6% improvement in resolution of the issues, and fewer callers asking to speak to a manager. Cogito claims that its system reduces callbacks by 10% and increases customer satisfaction by 28%.
• The rapid explosion of demand for speech-to-analysis software and platforms has heralded the growth of several startups in the field, including a few companies that recorded nearly 10x growth. For instance, SuccessKPI, a quality monitoring and speech analytics tools provider, recorded a 200% increase in demand for their platform due to the growing digitization of operations in North America and their expansion into Latin America, Europe, and Asia-Pacific. The growth invited a USD 33.0 million investment from Banneker Partners in January 2022 to enable the rapid expansion of customer success, product, partner, marketing, and sales teams globally.
• However, the market studied is witnessing challenges in deploying voice-based communications. It is more challenging for a computer system to deal with voice interactions than chat on a purely technical level. Background noise, unusual speech patterns, different accents, and poor pronunciation make it hard for an AI to translate voices into text.