SentiTalk use natural language processing (NLP) and machine learning algorithms to analyze text data from customer interactions, such as emails, chat logs, and call transcripts, and provide insights into customer sentiment and behaviors.
Analyze leads sentiment
Analyzing the sentiment of customer statements provides insights into customer attitudes and behaviors, which helps sales reps tailor their communication and sales approaches to better meet the needs and expectations of their customers.
Check what you know and what your customers say
By measuring most common queries on the sales conversations you will know the exact needs of your customers and measure their satisfaction level after your sales team offers.
Big team, one brain
By combining all sales conversations data, you are able to conclude what is the current market need and how’s your sales team performing versus that.
Benefits
Improved communication
Tailor Sales communication to better meet the needs and expectations of the customers.
Optimization
Identify most common mistakes during the Sales communication using machine learning.
Feedback
Analyze concerns and objections about your products and services.
Reporting
Report on Sales Efficiency using KPIs you’ve set vs sentiment of your Sales Team voice.
A/B testing
Challenge different Sales techniques with advanced SentiTalk Analytics.
Opportunities identification
Identify opportunities to upsell or cross-sell related products or services.