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3 Simple steps to improve customer satisfaction

Up until now, expensive, and mostly inaccurate post incident surveys were the only way to track and measure customer satisfaction. If you are using Jira Service Management for customer support then customer satisfaction can now be effortlessly improved utilising automated AI driven natural language processing (NLP).

Here are 3 simple steps to leverage AI to improve customer satisfaction

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Step 1: Get the complete CSAT story with AI driven real-time analytics

The tendency of unsatisfied customers to express themselves, while satisfied customers remain silent can be countered utilising AI natural language analysis.

Rather than gather feedback from a minority utilising post-incident surveys, utilise AI to analyse all customer and agent sentiment in real-time and do away with intrusive surveys.

Step 2: Create a culture of intervention instead of repair

Real-time feedback opens up new opportunities for action. If dissatisfaction is detected as soon as it appears, agents can intervene and prevent escalation and mitigate the risk of customers leaving dissatisfied.

Leverage real time sentiment analysis to enable agents to identify, intervene and repair interactions where negative customer sentiment has been detected.

Step 3: Automate customer satisfaction monitoring with AI driven alarms and notifications

Customer sentiment alarms allow agents and managers to watch customer satisfaction metrics and receive notifications when satisfaction scores fall below configured thresholds.

Get notified in real-time and stay up-to-date with all your customer satisfaction metrics to enable you to take action when required.

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AI Insights is available on the Atlassian Marketplace - Take your customer support to the next level and automate your CSAT workflow. Try the app for free, get in touch with us for a demo and make sure to watch this channel to hear more about how AI transforms the way we work together.

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There was a lot of useful information in this post.

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