AI Powered Customer Feedback Analysis and Report Workflow

Customer Feedback Analysis and Report Generation

1. Data Collection

1.1. Feedback Sources

• Customer surveys
• Social media reviews
• Support tickets
• Live chat transcripts

1.2. Tools for Data Collection

• Google Forms for surveys
• Hootsuite for social media monitoring
• Zendesk for support ticket management
• Intercom for live chat interactions

2. Data Processing

2.1. Data Cleaning

Utilize AI algorithms to remove duplicates and irrelevant data points.

2.2. Sentiment Analysis

Implement AI-driven sentiment analysis tools to categorize feedback as positive, negative, or neutral.

• Example Tools: MonkeyLearn, Lexalytics

3. Data Analysis

3.1. Identifying Trends

Use AI-powered analytics platforms to identify common themes and trends in customer feedback.

• Example Tools: Tableau, Power BI

3.2. Generating Insights

Leverage machine learning algorithms to generate actionable insights from the analyzed data.

4. Report Generation

4.1. Automated Report Creation

Utilize AI writing tools to draft comprehensive reports based on the analyzed data and insights.

• Example Tools: Jasper, Copy.ai

4.2. Customization and Review

Customize reports to meet specific stakeholder needs and conduct a review for accuracy and clarity.

5. Distribution and Feedback Loop

5.1. Report Distribution

Distribute the finalized report to relevant stakeholders via email or project management tools.

5.2. Collecting Stakeholder Feedback

Gather feedback from stakeholders on the report’s effectiveness and clarity to enhance future reports.