A brand consistency assurance mechanism can be established through THEO:
- Creating Brand DNA BenchmarksUpload corporate style guides, historical quality copy, VI manuals and other materials, and the system will extract color preferences, language style and other elements to form a standardized description (e.g., "a professional but warm technology brand"). When testing, you can let the AI generate the copy and then compare the match with the enterprise's historical content.
- Dynamic Calibration SystemWhen the AI output is found to deviate, typical counter-example documents (e.g., ineffective copywriting) are added to THEO to regenerate the knowledge base. It is recommended to establish a closed-loop process of "style calibration - generation - manual review".
- Scenario-based cueing techniques: When using the knowledge base, scenario requirements (e.g., "Write Instagram posts in a relaxed colloquial style, avoiding technical jargon") should be attached to the AI conversation. Combined with THEO-generated customer profiling data, it can increase content conversion rate by 27% or more.
Best practices show that updating user feedback data once a week and supplementing it with the latest marketing examples every month keeps AI output continuously optimized.
This answer comes from the articleTHEO: A core tool for transforming business information into an AI intelligent assistantThe
May not be reproduced without permission:AI productivity tools " How to optimize the marketing team's use of AI to generate content that doesn't match the brand's tone?
