For high-stakes activities like refugee resettlement, Golden avoids overwhelming users with all requirements upfront. Instead, it progressively distributes necessary steps and information. This makes complex processes feel manageable, preventing potential users from feeling intimidated by a 'digital stack of paperwork' and abandoning the sign-up.
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While the goal is often a frictionless experience, some friction can be a positive filter. Descript found that users willing to download a desktop app were more invested and more likely to stick around. Don't be afraid of early steps that test a user's commitment.
To increase user conviction, Golden's platform intentionally hides opportunities a user is unqualified for or that are at capacity. This prevents the negative experience of discovering a compelling option only to be rejected, ensuring a smoother journey and reducing drop-off before a user commits.
Traditional onboarding asks users for information. A more powerful AI pattern is to take a single piece of data, like a URL or email access, immediately derive context, and show the user what the AI understands about them. This "show, don't tell" approach builds trust and demonstrates value instantly.
The obsession with removing friction is often wrong. When users have low intent or understanding, the goal isn't to speed them up but to build their comprehension of your product's value. If software asks you to make a decision you don't understand, it makes you feel stupid, which is the ultimate failure.
To introduce powerful features without overwhelming users, design interactions that reveal functionality contextually. For instance, instead of a tutorial on zooming, have the UI automatically zoom out when space becomes limited. This makes the feature discoverable and its purpose immediately obvious.
A one-size-fits-all onboarding process is ineffective. Customers have varying levels of technical proficiency; a power user may find excessive handholding annoying, while a novice needs it. The process must be flexible and tailored to the individual to avoid creating a frustrating experience.
Effective user onboarding focuses on helping users achieve small, tangible victories that lead to the product's core value. Instead of generic feature tours, use in-app messages triggered by specific user behaviors (or lack thereof) to guide them to the next "micro-yes," like sending their first Zap in Zapier.
Instead of a broad onboarding, focus the entire initial user experience on achieving one specific, "brag-worthy" value event as quickly as possible. Structure this as a sprint: define the event, remove all friction, design a "click, click, value" path, and use alerts to nudge users along to that singular 'win'.
Open-ended prompts overwhelm new users who don't know what's possible. A better approach is to productize AI into specific features. Use familiar UI like sliders and dropdowns to gather user intent, which then constructs a complex prompt behind the scenes, making powerful AI accessible without requiring prompt engineering skills.
The most effective AI user experiences are skeuomorphic, emulating real-world human interactions. Design an AI onboarding process like you would hire a personal assistant: start with small tasks, verify their work to build trust, and then grant more autonomy and context over time.