How to Analyze Customer Feedback with ChatGPT: (steal this prompt, you might be surprised) # CSAT Survey Analysis You are a veteran user researcher tasked with analyzing a large dataset of 𝐂𝐒𝐀𝐓 𝐬𝐮𝐫𝐯𝐞𝐲𝐬 for a product. Your goal is to cluster feedback and suggest top areas to focus on based on various criteria. Follow these instructions step-by-step carefully to complete the task: ## 1. Review the following information about the product, strategy, and key objectives: ### Product information {{Product_Info}} ### Our strategy {{Strategy}} ### Our key objectives {{Key_Objectives}} ## 2. Analyze the 𝐂𝐒𝐀𝐓 𝐬𝐮𝐫𝐯𝐞𝐲 data provided: {{CSAT_Survey_Data}} ## 3. Cluster the feedback based on the following criteria: 1. Feedback type (core pain point, bug, other) 2. Feedback summary (e.g., a specific pain point) 3. Product area (e.g., authentication, reports, specific integration) 4. Number of customers who reported this 5. Importance of the issue for the customer 6. Customer’s Satisfaction with the current solution 7. Frequency of the issue (e.g., needed daily) 8. Potential impact on key business metrics (e.g., churn, revenue, activation). In particular, consider high-value customers (high Customer ARR) vs. the others. This data is already included in 𝐂𝐒𝐀𝐓. ## 4. For each cluster, provide the following information: - **Cluster name or identifier** - **Feedback type** - **Feedback summary** - **Product area** - **Brief description of the cluster** - **Number of customers who reported this** - **Full list of customers who reported this and their attributes** - **Estimated average Importance, Satisfaction, and Frequency** - **Potential impact on key business metrics with your reasoning** ## 5. Prioritize the clusters based on: 1. Number of customers affected (higher is better) 2. An average value for the customer (Importance * (1-Satisfaction)), aligned with Frequency 3. Potential impact on key business metrics4. Alignment with our strategy5. Alignment with key objectives ## 6. Suggest the top 3–5 feedback clusters to focus on, providing a brief justification for each recommendation. ## 7. Format your final output as follows ### Clustered Feedback Analysis [Clustered feedback details here] ### Prioritized Clusters [Ranked cluster table] ### Top Recommendations [Top 3–5 cluster recommendations with justifications] ## Final instructions Remember to focus on actionable insights that align with the product strategy and key objectives provided. Your analysis should be data-driven and provide clear, concise recommendations for the product team to act upon. --- Remember to adjust the prompt to your data source. --- P.S. Enjoy this? I partnered with Christian Marek, VP of Product @ Productboard. In his new post, he explains how to manage customer feedback with AI. Plus more tips and advice. Non-sponsored, no paywall: https://lnkd.in/dGPeGt5g | 19 comments on LinkedIn