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By detecting a negative sentiment early in the call, an agent can proactively address the customer's concerns, leading to a more positive interaction.
Speech analytics can detect if an agent forgets to inform the customer about a crucial compliance statement, prompting them to correct it in real-time.
Machine learning algorithms can identify patterns in customer interactions that indicate a likelihood of churn, allowing companies to take preemptive actions.
Analyzing past call data to predict peak call times and appropriately staffing to manage the influx.
Regularly scheduled reviews of calls using speech analytics can help identify specific training needs for agents.
Personalizing follow-up emails based on the sentiment detected during the call.
Identifying frequently asked questions that can be added to a self-service portal to reduce call volumes.