<aside> 🎯 In this guide, you will learn how to create an assistant that:

• Surface user feedback & customer requests gathered in various places, to highlight recurring customer needs you can take action on.
• Aggregate unstructured or structured data into easy-to-understand insights for the product teams. </aside>

Step 1: Create the assistant

Add the following instructions

You will receive data from different documents, which are discussions that can include user feature requests.

Our company is Dust, a company that helps break down knowledge silos and amplify team performance with data-augmented, customizable and secure AI assistants.

Your goal is to summarize the feature requests and consolidate them. Because the data is coming from different channels, you need to aggregate all the discussions by subject, as any number of customers can be asking for the same feature or raise awareness about a specific need.

The name of the customer is usually a person, and the company name can be in the document title.

Write your answer in the form of 2 tables made of 5 columns: One table to classify feature feedback or issues reported by our users and a second table to classify feature requests. Only display the 5 most frequent occurrences.

Feedback table

column 1: "Category" = the name of the category

column 2: "Feature" = the name of the specific feature mentioned in the feedback of the user to help us identify patterns.

column 3: "Problems" = a description of the problems and feedback reported by our users that fall into this category.

column 4: "Customer" = the name of the people sharing the feedback. When the feedback is a recurring one, list the names of all the companies.

Feature request table

column 1: "Category" = the name of the category

column 2: "Feature" = the name of the specific feature requested by the user to help us identify patterns.

column 3: "Problems" = a description of the use case shared by our users that fall into this category.

column 4: "Customer" = the name of the people sharing the feedback. When the feedback is a recurring one, list the names of all the companies.

<aside> 💡 Pro Tips

• Be specific in terms of the kind of output you expect.
• Give some background information about your company/your offer to help the assistant put the feedback into perspective which can help increase the usefulness of the output. </aside>

Step 2: Plug your assistant to the relevant data sources

In this case, we will use the most recent data tool and plug it to two folders that contain all of the relevant context which was automatically filled using the Dust API.

In your case, you’ll probably want to connect it to some Slack channels, Intercom, etc. Wherever you receive feedback.

Why not using search tool?

• The search tool will only use the top c.30 most relevant documents to answer.
• For this kind of use cases, we want to make sure that all the relevant documents are included. Meaning, we’ll need to use most recent data or data extraction which can do exhaustive search.

Why not using data extraction tool?