StampedIQ: Insights Analysis

StampedIQ: Insights Analysis feature allows the content of all collection reviews being analyzed by our A.I., which in turn is converted into an overview of various topics based on keywords and their sentiment level.

*Available on Professional plan

Supported languages:

  • Chinese (Simplified)
  • Chinese (Traditional)
  • English
  • French
  • German
  • Italian
  • Japanese
  • Korean
  • Portuguese (Brazilian & Continental)
  • Russian
  • Spanish

In This Guide


Introduction To Insights Analysis


You can access Insights Analysis feature by heading over to Analytics > Insights


Overview of Insight Analysis

The sentiment score runs between -100 to 100, with 0 to -100 being negative scores, and 0 to 100 being positive. Here are examples of each type of scoring:

This gives you a sense of what customers are saying for each topic and review, which allows you to make smarter business decisions. For example, when there's a downtrend in terms of sales, you can filter the topics based on date period, then look for topics with the most negative sentiment and make adjustment to your business accordingly.

There are 3 additional buttons revealed when a topic is moused over, as shown in the first example:

- Eye icon: Hide the topic from showing up in the results, which will be moved to the "Hidden" tab.

- Heart icon: Tag the topic as favourite, which will then show up under the "Favourites" tab.

- View products: Redirect to new page with more detailed breakdown of the topic, which will be covered in the next section.


Detailed Breakdown of Individual Topics

You can get a detailed breakdown of each topic in Insights Analysis, which provides you with even more data to make an informed decision.

  • Reviews: Provides you with the review content containing the keywords.

  • Top Related Topics: List of other related topics picked up within the same reviews.

  • Overtime: Showcases the trend of the topic over a period of time.

  • Products: List down all the products containing the topic and their individual sentiment score.