Natural Language Interaction Insights
Transforming Typical Conversation Speech into Actionable Insights
Conversations in the day, whether in-person, via voice, video or chat, all provide rich data in naturally occurring language. We learn so much about how people communicate using these natural forms of speech, and organizations use speech analytics and natural language processing (NLP) to gain insight into user behaviour, language, and tone to evolve communication strategies.
Statswork can convert raw speech data into actionable insights based on research-backed machine learning and languageÂ
analysis to help businesses enhance engagement, decision-making and voice-enabled systems.
Conversation speech monitoring allows the capture of the audio or text data from calls, meetings or voice assistants which can determine trends in language, tone, and frustration in real-time. Using speech insights generated from AI, and machine learning, the insights gained from voice data can help improve customer experience, train conversational AI, and optimize voice interfaces.
Understand Customer Needs
Qualitative research will reveal the why behind what customers do. Once you understand this you can adopt strategies that better meet their expectations.
Spot Market Trends
Ethnography and the collection of digital data will help you spot and keep on top of developing market trends.
Improve Product Development
Feedback from focus groups and interviews used to test products and services will help you refine your offerings, as well as being in tune with how customers feel about them.
Enhance Brand Strategy
The insights that qualitative market research provides can help your intentions for advertising messages and brand positioning stay strong and clear.
More Informed Decision Making
The right combination of qualitative and quantitative data will produce deeper, more balanced, and data-led strategies.
Build Customer Loyalty
Learning what motivates your customers helps you to create a unique experience, and one they will stick with long term.
Audio and Speech Text Capture
Records and analyses verbal conversational data from all types of calls and meetings as well as voice assistants to collect and analyse interdisciplinary sampling of contextual and spontaneous speech samples.
Tone and Emotion Understanding
Enables businesses to provide AI-based emotional and tone analysis to recognize emotional inflections and nuances within spontaneous, natural speech that allow for more authentic and effective customer outreach.
Theme and Pattern Identification
Uses conversation analysis to recognize and understand patterns, topics that regularly occur, and pain points within spoken conversations that will help to gain insights for improved customer service and communication.
Contextual Language Understanding
Applied academic frameworks in Natural Language Processing (NLP) models are used here to analyse contextual language and patterns of variation to facilitate the development of smarter conversational AI and personalized interaction strategies.
Real-Time Monitoring of Conversational Interactions
Allows businesses to monitor spoken conversational interactions live for immediate feedback to the effectiveness of their communication, and to quickly troubleshoot or respond to customer’s needs.
Behaviour and Communication Insights
Transforms speech to textual data into insights to understand user prototypes and behaviour, speech patterns, and styles of communication to improve collaboration among teams and strategies for customer interactions.
Industries
Data collection allows sectors to train computer vision models, improve automation, improve diagnostics, ensure safety, and spur innovation via AI applications.
Input: This can include audio files, transcripts, call logs or API integrations
Output: This will be structured data that provides sentiment, intent, themes and speech behaviour.
Data Collection | Article
Data Abstraction | Article
Data Entry | Article
Claim your insights today and start turning everyday speech into more intelligent business decisions.
