Quick Answer
For search, voice, and "just tell me what to do".
Most product descriptions describe features when they should sell transformations. AI can generate descriptions that speak to buyer psychology - addressing fears, painting outcomes, handling objections - while maintaining your brand voice. The difference between a description that converts and one that doesn't often comes down to structure: leading with outcomes, supporting with features, and closing with confidence.
Key Takeaways:
- Descriptions should sell, not just inform
- Buyers care about outcomes more than features
- AI can optimize for conversion patterns
- Structure matters as much as content
- Every description is a mini sales page
Playbook
Analyze high-converting descriptions in your market
Train AI on conversion patterns and your brand voice
Lead descriptions with outcomes and transformations
Support with features that validate the promise
Test and iterate based on actual conversion data
Common Pitfalls
- Listing features without connecting to benefits
- Writing for search engines instead of buyers
- Using generic language that could apply to any product
- Ignoring objections buyers have before purchasing
Metrics to Track
Conversion rate by description version
Time on product page
Add-to-cart rate
Bounce rate from product pages
Customer feedback on product expectations
FAQ
How long should product descriptions be?
Long enough to answer key questions and handle objections. Simple products need less; complex products need more. Test length against conversion.
Should I optimize for SEO or conversion?
Both, but conversion first. A description that ranks but doesn't convert is useless. Write for buyers, then optimize for search without hurting readability.
How do I maintain brand voice with AI?
Provide AI with examples of your best writing, style guidelines, and brand voice descriptions. Review and edit outputs until AI learns your patterns.
Related Reading
Next: browse the hub or explore AI Operations.