QKS Group reveals a Speech Analytics market projected valuation of $2.86 billion by 2030, growing at a CAGR of 14.20% from 2025 to 2030.
Speech analytics can be broadly categorized into real-time speech analytics and post-call speech analytics based on the time required for audio data analysis. Real-time speech analytics enables analysis during ongoing voice conversations, providing agents with instant actionable data, trends, and metrics to enhance service quality. It also offers insights into customer sentiment, tone, and patterns, guiding agents in real time to improve the customer experience. Post-call speech analytics focuses on learning from concluded conversations, recognizing keywords, and creating personalized text categorization models to inform future customer support processes and strategies. The adoption of predictive analytics using ML algorithms and data enables businesses to forecast outcomes in customer interactions, transcending from reactive to proactive and preventative strategies. Holistic contact center analytics consolidates all interaction data, including voice, text, and email, and provides a comprehensive 360-degree view of customer journeys, offering deeper insights and opportunities for cross-channel optimization.
Quadrant Knowledge Solutions defines speech analytics as a technology that analyzes customer conversations from live or recorded audio data to derive deep insights, trends, and metrics from each conversation. It uses AI technologies such as NLP, speech recognition, and transcription to evaluate agent performance, assess customer experience, and monitor organization-wide strengths and shortcomings in every voice interaction.
Key questions this study will answer:
What is the current state of competition in the Speech Analytics market?
What is the market share held by major vendors in this market?
What are the key competitive dynamics in the global and regional markets for Speech Analytics?
Who are the leading vendors in the global and regional markets?
Are there vendors specializing in specific industries?
How do different vendors compare in terms of their offerings of cloud-based versus on-premises solutions?
What competitive factors impact the market positioning of different vendors?
What are the relative strengths and challenges of the vendors operating in this market?
How do different vendors position themselves competitively across customer segments, from SMBs to large enterprises?
Fig. 17 Market Share of Speech Analytics Manufacturing, 2025
Fig. 18 Market Share of Speech Analytics Hospitality, 2025
Fig. 19 Market Share of Speech Analytics On-premises Deployment, 2025
Fig. 20 Market Share of Speech Analytics Cloud Deployment, 2025
Fig. 21 Market Share of Speech Analytics SMB Customers, 2025
Fig. 22 Market Share of Speech Analytics Large Customers, 2025
Fig. 23 Market Share of Speech Analytics Enterprise Customers, 2025
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