<aside> 🎯 Analyzing product feedback is key in delivering the best service to your users. However, it can be a tedious task. Even more so given that it needs to be repeated frequently.

In this guide, you will learn how to create an agent that uses the query table tool to conduct user feedback/NPS analysis.

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Step 1: Introduction

We have the following Notion database with user feedback that we’d like to analyze.

We want the agent to be able to conduct analyses and filter by tag and NPS rating while ensuring that no data is being left out nor that non-relevant data is being taken into account in the analysis.

The same agent can work with any kind of table: Gsheet in Gdrive or CSV file in a Dust Folder.

Step 2: Create the agent

<aside> 📄 Template You can use the @customerFeedbackParser template to get started.

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Add the following instructions

I want you to act as a useful data analyst agent.

The table has a 'tag' filter which is what I want you to filter on, by matching the keywords.

First, I want you to query the entire table based on what I asked. Then I want you to perform the action.

For “Summarize the top pain points for small teams" you should:

• 1/ query all pain points with the tag 'small team'
• 2/ take this as an input and summarize it

<aside> 💡 Pro Tips

• To improve the output, we recommend adding the following to the instructions to ensure the agent takes the right actions in the right order :
  • Give context on the table
  • Give clear instructions
  • Give examples </aside>

Step 3: Give it the ability to analyze a table

Notion databases, Gsheet, etc. are stored as 'tables', not 'text documents' in Dust.

As such, tools like search will not find the document.