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AI Tools: Report Builder

Good example prompts to try

  • list top 10 retail products sold in 2025. Use revenue account with retail in its name
  • list all the members who terminated last month, include the reason they terminated and any note provided on the status change
  • histrogram data by age bracket of current members
  • top 10 staff members who sold the most 'shoes' last month. use 'shoe' in the revenue account
  • Report of membership termination reasons by month, grouped by reason, #withDateFilter
  • compare average weekend checkins counts to average weekday counts checkins by hour. use columns for hour, weekday, weekend. Take the average of the total check-ins by using the number of days in the date rage #withDateFilter
  • list all customers who terminated last month and their 1 month, 3 month, and 6 month visits counts. include reason for termination, status notes, last visit date
  • list top 20 customers who purchased the most shoes in 2025. Report customer, quantity, and revenue. Use 'shoe' revenue account
  • list all currently frozen members, their date of freeze, and the # of months they've been frozen. Use the date of their most recent freeze status to compute the # of frozen months. Ignore programs

Important Tips

  • We have provided knowledge of the database structure to the AI model, but we have not provided your data.  So the model knows you have customers and invoices, for example, but it does not know you have a revenue account called 'retail' or your rental shoes are called 'Rental Rock Shoes'.  So when asking for this that requires specific knowledge of your data, provide it in the prompt.   An example would be "List all the customers who purchased a product with a description containing 'Rock Shoes' yesterday"

  • Use 'New Chat' to start over: If you are going down a rabbit hole, start over.  If you are changing the nature of the chat, start over.

  • Be specific: “Sales by month in 2023” is better than “Tell me about sales.”

  • Add filters: e.g., “Purchases of product description containing 'grigri'  in the last 30 days.”

  • Ask for formats: “Purchases of product description containing 'grigri'  in the last 30 days, grouped by age bracket,” “Top 10,” “Sort descending.”

  • Correct it's mistakes: If you get unexpected results, communicate it back to AI, such as "the sales column amount seemed to high"

  • Natural dates work: “last quarter,” “past 7 days,” “year to date.”

  • Start simple, refine later: Begin broad, then filter/group.

  • Be clear on ambiguous terms: Specify “july” vs. “july 2025”

  • Check the SQL shown: Verify results and learn your data structure.

  • Rephrase if needed: Small changes in wording improve accuracy.

  • Know the limits: Complex queries may need manual SQL editing.

  • Lastly: Use the Hashtag Helpers to add additional information to your saved custom report.

 

 

 

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