How to Create Safe Sample Data for Product Demos
Published October 7, 2026 · By Kate Steinmeyer · AI Demo Creation
Safe sample data for a product demo is fictional, internally consistent, and sufficient to show the workflow. Build the example around the starting state and result the viewer needs to understand. A realistic-looking dataset is not useful if it accidentally contains a customer name, implies a measured result, or changes between scenes.
This is an editorial and production workflow, not a claim that any particular synthetic dataset meets legal or security requirements. Follow your organization’s policies for public demo material.
Design the record backward from the outcome
Suppose a hypothetical demo shows a request moving from “submitted” to “approved.” Write the final state first: a fictional request with an approver and an approved status. Then define the earlier states needed to explain how it got there. You may only need a requester, request title, date, reviewer, and status—not hundreds of records.
Create a small data sheet before recording:
| Field | Example to invent | Check |
|---|---|---|
| Organization | Fictional company name | Does it resemble a real customer? |
| People | Fictional requester and reviewer | Do names and roles stay consistent? |
| Object | Fictional request or project | Is the task understandable? |
| State | Submitted, in review, approved | Does the sequence match the product? |
These are planning fields, not a recommendation to use the example values as if they were real customer evidence.
Inspect everything the capture may reveal
The main record is only one surface. Check the sidebar, account switcher, browser tabs, URLs, notifications, filenames, avatars, search history, and earlier states visible during transitions. A blur added in editing may miss a frame or appear in only one export. Starting with a clean demo workspace is easier to maintain.
If AI drafts callouts or narration from the screen, review the generated text too. It may convert a fictional value into a claim such as “teams save two hours,” or imply that the pictured organization uses the product. Remove invented outcomes and label illustrative examples when context could be mistaken for evidence.
Keep the sample reusable
Store the source data and the purpose of each record with the demo’s owner. When a screen changes, a replacement capture can use the same fictional people and states. Check that dates still make sense and that the final state matches the narration.
Run a final review on the published output, not only the editor. Open the public link, watch the export, and inspect thumbnails or social previews. Interactive demo governance covers the broader ownership and review process.
FAQ
Is anonymized customer data safer than fictional data?
Fictional data is a simpler default for a reusable public demo. Use real customer material only when your organization has approved the specific use and checked that the anonymization is sufficient.
How realistic should sample data be?
Realistic enough to explain the task and the state change. Extra detail creates more surfaces to review and maintain without necessarily helping the viewer.
Can AI make the sample dataset?
It can draft fictional records, but a person should review them for accidental resemblance to real entities, internal consistency, and unsupported claims.
When you turn the safe workflow into a buyer demo, MaybeUndo’s product demo tools can help organize the story across assets.