Phone Call Sentiment Analysis

SocialInbox’s AI-powered sentiment analysis evaluates phone conversations in real time, detecting emotional cues like frustration, satisfaction, or urgency. By integrating natural language processing (NLP), the system categorizes interactions as positive, neutral, or negative, enabling immediate response prioritization. For example, a customer expressing dissatisfaction during a call triggers an alert, prompting supervisors to intervene swiftly. This feature reduces churn by addressing issues before escalation and enhances customer loyalty through proactive support

When negative sentiment is detected, SocialInbox automatically generates support tickets tagged with urgency levels and context. These tickets include call transcripts, sentiment scores, and recommended actions, streamlining workflow for customer service teams. For instance, a heated complaint about delivery delays creates a high-priority ticket routed to logistics teams, ensuring rapid resolution. This automation minimizes manual oversight, reduces response times, and ensures consistent follow-up across channels like email, SMS, and social media

SocialInbox unifies phone call data with social media, reviews, and messaging platforms into a single dashboard. This holistic view lets businesses track sentiment trends across Google My Business, Facebook, and WhatsApp, ensuring cohesive brand management. For example, a negative phone review syncs with the user’s Google profile, prompting an AI-crafted public response to mitigate reputational damage. The platform also updates local SEO rankings by aggregating positive reviews and resolving inconsistencies across 50+ directories