An AI product explanation should help a buyer understand what the product does in a real workflow. Technical terms may matter to specialists, but most viewers first need a clear picture of the problem, the input, the output, and what happens next.
Lead with the user's problem
Begin with a specific task or decision the audience recognizes. Avoid opening with a list of model capabilities. Explain the setting and the friction in plain language, then introduce the product as one part of the workflow.
Show the workflow, not just the promise
Make the sequence visible: what information goes in, what the product does, what result the user sees, and what action follows. Use a real or representative interface where possible. Label a visual metaphor clearly if it is a simplified explanation rather than a literal view of how the system works.
See how product stories are presented in the Sonar AI explainer and UniDesk product introduction. For another finance-related product story, explore the DankStocks platform explainer.
Be precise about the product's role
Separate what the software automates from what a person reviews, edits, approves, or decides. If outputs can vary, make that clear. Avoid absolute claims such as “always accurate” unless the business can substantiate them and explain the conditions.
- Use everyday language first; define necessary technical terms.
- Show a representative example that matches the product today.
- Mention relevant review or approval steps.
- Check claims with product and legal stakeholders before publication.
Keep the explanation focused
A short explainer does not need to cover every feature or technical detail. Choose one audience, one use case, and one next step. Put deeper specifications, security details, and documentation on pages designed for those questions.
The same structure can guide a SaaS explainer video script. For help shaping the story, see how to write a SaaS explainer video script.
Check the explanation with a new viewer
Show the script or storyboard to someone who does not already know the product. Ask them to describe the problem, what the product does, and what they would do next. If their answers differ from the intended message, simplify the story before production.
