User Trust +
Explanations
Strong UX fuels user trust and business growth—boosting sales, loyalty, and retention. Better usability drives revenue while reducing churn for your AI products.
Want to drive discussions, speed iteration, and avoid pitfalls?
How to define user trust in a product’s context?
Defining user trust starts with understanding what trust means for your audience and how it’s built, maintained, or lost in your product’s context.
We identify factors—like transparency, reliability, and user control—that influence trust, assess risks of over- or under-trusting AI, and create strategies to measure and strengthen trust across the product lifecycle.
Why is user trust important in AI product design?
User trust is vital for AI adoption—without it, even powerful features may be ignored. Trust ensures users feel confident, informed, and in control when interacting with AI.
At BrandRx, we design transparent, intuitive experiences that explain AI outputs, set clear expectations, and provide recovery paths for errors. Our approach builds lasting trust, driving engagement, satisfaction, and product success.
When should the system provide explanations?
Explanations should be offered when they help users make informed decisions, build trust, or understand AI behavior—especially for critical, unexpected, or low-confidence outcomes.
We design context-aware explanation triggers that give clarity without overwhelming users, ensuring transparency while maintaining a smooth and efficient experience.
What you will get
Achieving Your Vision
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