A List in Microsoft Power Pages is a data-driven configuration that displays a collection of records on a webpage in a grid format. Lists can be used to present business data on a website and can be integrated with pages or forms to build web applications. To learn how to add a list in Power Pages, please refer to this documentation.
The AI Summary to List feature transforms dense tables into visually appealing summaries and chart representations. By providing concise insights and intuitive visualizations, this feature enhances efficiency and empowers users to analyze data with ease. Whether you’re working with large datasets or looking for quick takeaways, the AI Summary feature ensures that extracting value from data becomes a seamless experience.
Here’s a Use Case
Imagine a restaurant with a personalized website hosted on Power Pages portals. This platform features a dedicated feedback section where patrons can share their dining experiences. Now, envision the restaurant owner enhancing this experience by presenting the overall feedback and ratings, capturing sentiments about the food, ambiance, and service, in an engaging and visually appealing format.
Solution-
Using the AI Summary List, the customers visiting the restaurant’s website can easily view and understand its ratings on their devices. They can understand patrons’ views on the Restaurant’s ambiance, food, and more through these articulate visual charts.
Let’s enable the AI Summary List with these steps-
Step 1: In the Power Pages Design Studio, redirect to Power Pages List configuration and Click on the ‘Edit List ‘option of the list to open the ‘List settings’
Step 2: Within the ‘Set up’ section, as seen in the screenshot, check out the option to enable ‘AI Insights’, turn on the toggle, and activate the AI Summary List Feature.
Following this, add the Customer Feedback table from Dataverse. The Customer Feedback table is customizable in the restaurant system that contains feedback from the customers. With Active Feedbacks, the view contains columns such as customer, rating, suggestion for improvements, phone number, and what you like the most. After adding the table, click on Done. You will see the AI Insights window appear above your list.
Configuration Settings for AI Insights
To configure more options for AI Insights in the list, click on the Insights window. Selecting the Insights option the configuration window will be open where you can find the following options:
- Title: Change the title of your summary card.
- Additional Instructions: Provide instructions to AI Insights on what to include in the insights or data visualizations.
- Chart Types: Choose from various AI Insights chart types, such as Bar charts, Line charts, etc. that work best for your data.
Hit “Sync” to save your list configurations and preview your website seamlessly. Upon loading Power Pages, AI Insights takes center stage, analyzing data from your chosen source with precision. It then generates concise summaries, intelligently tailored to the configuration options you specified during the AI Insights setup process.
For our implementation, we leveraged the Customer Feedback table to highlight the standout features of the restaurant. This includes customer ratings and the most cherished aspects, such as ambiance, service, and food variety, accompanied by the customers’ names. The AI Summary’s insights are elegantly visualized below through a pie chart and a column chart.
Notes:
- Virtual Tables: Virtual Tables are not yet supported in the AI Preview List.
- Minimum Data Requirement: The selected view must contain at least five columns to generate meaningful data.
Conclusion
Understanding complex data tables has long been a challenge for professionals and businesses. Traditional table formats demand considerable time and effort to derive valuable insights. The AI Summary feature for lists simplifies this process by turning dense datasets into actionable insights and clear visualizations. This powerful tool makes data analysis seamless and efficient, enabling users to focus on decision-making instead of interpreting data.