The first 30 seconds: how to show value in AI product onboarding

Why the pre-signup experience matters more than ever — and how to design onboarding flows for AI-driven products that feel tailored, deliver outcomes, and convert.

In the world of product design, “onboarding” is the critical first handshake between a user and your platform. It’s a broad term, covering everything from basic tutorials to complex, compliance-driven flows. Despite the variety, most onboarding strategies rely on a mix of three recurring patterns: educational (guiding users toward mastery), regulatory (ensuring a secure and trustworthy setup), and sales-driven (highlighting features to encourage conversion).

These approaches don’t exist in isolation, and they aren’t confined to a particular stage of the user journey. In many cases, they appear both before and after signup, overlapping in subtle and strategic ways. But there’s something especially high-stakes about the pre-signup phase: it’s the first real test of whether the product resonates, whether it earns a user’s attention, and ideally, their intent to continue.

That’s the focus of this article. Not onboarding in the general sense, but the very beginning of it: the pre-signup flow, where users have the least patience and the most potential to walk away. And specifically, how two forces — personalization and perceived value — shape that moment and determine whether someone decides to take the next step.

Why onboarding Mmatters: beyond feature walkthroughs

In the past, most pre-signup onboarding flows were short and feature-focused, designed to show users how things work as fast as possible. However, this approach often fails to give users a real reason to stick around, as they might understand how the app works but not why it matters to them personally.

It’s time to think about onboarding differently — as a motivational experience, not just a walkthrough of features. Onboarding isn’t just another step; it sets the entire tone for what comes after. The numbers support this: RevenueCat’s report indicates that 80–90% of all trials occur on Day 0, and Wyzowl found that 86% of customers become more loyal with a great onboarding experience. These statistics highlight the crucial nature of those first few minutes; missing that initial momentum means users won’t stick around.

Building motivation: understanding user psychology

Before diving into design, it’s essential to understand what truly motivates people. When you’re genuinely excited to try something new, it’s rarely because you received a perfect step-by-step manual. Instead, something “clicked”.

• Personal Relevance: The experience felt personal and directly relevant to you, solving something real in your life.
• Emotional Connection: It stirred up a range of emotions — from curiosity and relief to excitement and a positive kind of fear. Emotional friction can be a powerful push.
• Confidence: You felt capable of handling it; a sense of “Yeah, I can do this” goes a long way.
• Timing: The initial spark of interest fades quickly, so there’s a short window to act before the moment is gone.

While personal relevance, emotion, confidence, and timing all matter, none of them lands without quality. This isn’t just about clever copy or flashy visuals, but a product that knows its purpose and follows through. A sharp promise, a seamless experience, transparent pricing, and a helpful UI all work together to deliver something real. If any piece is off, users will feel it, and no amount of onboarding psychology can compensate for a product that doesn’t hold up once people are inside.

The power of personalization

When designing onboarding that converts, personalization is the first thing to consider, as it directly affects engagement and retention. A personalized experience makes the product feel relevant from the start, adapting to who users are and what they want to achieve, increasing the chances they’ll stay long enough to see value.

Beyond the first impression, personalization in product design creates an opportunity to gather structured, voluntary input. During onboarding, users are often willing to share details like goals, roles, and use cases that would be difficult or unethical to extract later. This data can then be used to segment users, detect patterns, understand what’s working, and even follow up with users who drop off. Therefore, personalization isn’t just about making users feel understood; it’s about building a data foundation for continuous improvement, especially crucial for AI-powered products.

With this foundation, the next step is to understand how personalization works in practice for AI-driven products — what effective onboarding looks like and how to tailor it without adding complexity or overwhelming new users. Let’s break down the key emerging patterns.

Start small and simple

Effective onboarding in AI-driven apps should begin with minimal friction. A simple, high-level question, such as asking for a user’s name or preferred nickname, can create a sense of personalization without demanding much effort. The goal at this stage is to make the experience feel human and approachable, not overwhelming.

While some products start by asking for an email address to enable follow-ups and direct outreach, the timing of that request is critical. Many users abandon the flow if they’re asked for personal details before understanding the product’s value. Even minor obstacles can have a measurable impact.

In one product I had a chance to work on, a simple 3-second video transition between two steps caused a noticeable drop in completion at that exact point. It was a small delay, but enough to break momentum.

This underscores the importance of carefully testing early steps. If you plan to request contact information upfront, A/B test the placement and framing. A few seconds — or a poorly timed question—can make all the difference.

Design your questions with purpose

The questions you ask during onboarding do more than collect data; they shape how users perceive the product from the start. Well-designed questions signal that the product is built around the user’s goals and help configure an immediately relevant experience. From a product perspective, this is about front-loading value; by guiding users through early personalization, you reduce the amount of setup needed later. There’s also a psychological benefit: users who invest effort in customizing something are more likely to engage with it further, leading to stronger trial activation and better-qualified users.

The structure and complexity of your questions should match the product’s nature. For simple products with narrow use cases, a single onboarding path may suffice. However, for products with multiple user types or broad functionality, a branching flow, where questions adapt based on earlier responses, is typically more effective, allowing you to present only the most relevant features and keep the experience focused and personalized.

Every question must justify its presence; ask only what’s necessary to improve the experience. Avoid filler questions or vague prompts that lack a clear functional or strategic purpose, as each additional step introduces friction, so it must earn its place. This approach improves early engagement and can reduce churn. For example, Canva increased retention by replacing generic product tours with goal-based onboarding paths, surfacing relevant features faster.

As a general rule, the more flexible your product, the more critical it is to design purposeful, adaptive, and user-specific onboarding flows.

Build logical, context-aware question flows

A well-designed onboarding flow should demonstrate an understanding of the user, not just in what’s asked, but in how each question connects to the last. Every step should feel like a natural continuation of the user’s previous input. If questions feel random or disconnected, the experience quickly becomes mechanical, and the sense of relevance is lost.

It’s also important to subtly and intelligently remind users that the experience is being shaped around them. That doesn’t mean announcing it explicitly or leaning on generic buzzwords — it means reinforcing, through phrasing and interaction design, that the system is responding to their input in ways they can clearly perceive.

For example, if a step is optional, avoid a generic label like “Skip.” Instead, use phrasing like “Skip personalization” to subtly reframe the action — and to reinforce that what follows is directly influenced by the user’s choices. Small, deliberate language choices like this help users stay aware that the experience is being shaped around them, without overexplaining or coming off as performative. Done well, this kind of feedback builds trust. It signals that the product isn’t just collecting data — it’s actively using it to tailor the experience in real time.

Keep momentum: reward with value

The number of steps users will tolerate during onboarding is directly tied to their motivation. In high-motivation contexts, such as mental health, financial relief, or career advancement, users will push through surprisingly long flows. BetterHelp’s onboarding, for instance, spans over 40 steps, functioning more like a clinical intake form than a signup flow, yet completion rates remain high because the motivation is intrinsic and urgent; users are seeking a result, not casually exploring.

In low-motivation contexts, that tolerance disappears; users haven’t committed yet, and every additional step becomes a reason to leave. Here, the structure of onboarding becomes critical. Long sequences must be broken into thematic sections, each with a clear sense of progress, using visual milestones, contextual cues, and micro-interactions to help users feel momentum.

However, momentum only lasts if users believe they’re moving toward something valuable. Many onboarding flows fall short by requiring effort without providing anything meaningful in return. To sustain engagement, onboarding has to show value immediately, not eventually.

This is where personalization plays a strategic role. When onboarding adapts to the user, asking the right questions, reacting to inputs, and surfacing relevant features, it stops feeling like a generic setup and starts feeling like progress. The more the product reflects the user’s goals, context, or language, the clearer and more immediate its value becomes.

This feedback loop between effort and reward is essential. The best onboarding flows create small, repeatable moments of value, whether through personalized suggestions, relevant insights, or emotional reassurance. Each interaction validates the user’s input and reinforces that they’re building toward something real.

When onboarding feels static or extractive, users disengage; but when each step is supported by a tangible return, however small, it becomes easier for users to stay committed and complete the flow. The goal isn’t just to reduce friction; it’s to make the effort feel worth it.

Let users control personalization

In many AI-driven business tools, personalization extends far beyond basic setup questions. Users are encouraged to connect existing systems (CRMs, calendars, internal documentation) or upload proprietary files and notes. These inputs become training data that directly shape how the AI behaves and what it understands.

With just a few actions, a user can transform a general-purpose model into a highly contextual assistant that understands their domain, terminology, workflows, and internal logic. This isn’t cosmetic personalization; it’s foundational, enabling the system to operate with knowledge unique to a specific team or company.

The critical shift is control. Instead of forcing users into rigid templates, the product invites them to define what matters. The more the system reflects their reality, the more likely it is to integrate into their day-to-day work.

Personalization becomes a feedback loop: the more a user invests, the more relevant — and ultimately indispensable — the product becomes. This turns onboarding into more than a starting point; it becomes a strategic setup phase that builds long-term value.

This is the direction AI tools are heading: toward closed, organization-specific agents that accumulate domain knowledge and evolve into internal infrastructure that is intelligent and deeply aware of context, priorities, and language. Relevance will be the differentiator; generic models won’t compete.

Presenting value: promise and realization

The old approach to onboarding primarily focused on presenting product features, showing users what to expect after installing the app with lists like “Quick invoicing” or “Habit tracking”. While this strategy still exists to some extent, users often don’t care. For this approach to work, the product needs to be well-known, and the user highly motivated from the start; otherwise, flat lists of features lead nowhere.

Effective onboarding should lead the user through a process of product personalization. The more the experience is tailored to specific goals or contexts, the higher the chances for conversion and long-term retention. But what about the product’s actual features? This doesn’t mean the old way of presenting value is completely useless.

Promise and reassurance

Presenting value can’t just be about capabilities; it has to show users the outcome they’re moving toward. For example, instead of a workout app saying it offers “100+ different workouts,” it could, after personalization questions, say, “You’ll gain 5kg of muscle mass in the next 6 months. Here’s your starting plan”. The underlying system is the same, but it’s framed as a result. Similarly, a mental health app could show an example of a habit-building notification, emphasize that users who activate them build habits 40% faster, and then ask if they want to turn them on.

These moments are more than marketing; they create forward motion, and the key enabler is the personalization step itself. The questions asked early on aren’t just setup; they’re fuel, providing the context needed to present value in a tailored and relevant way. When onboarding connects a specific promise to a clear next step, and that promise is visibly shaped by what the user just shared, value isn’t abstract — it’s felt. That’s what creates momentum.

Let users create real value during onboarding

Some products go beyond simple personalization by guiding users through a core use case during onboarding, so the result isn’t hypothetical but real. Instead of showcasing capabilities, they walk users through actually using the product to create something meaningful, tied directly to its core value. This approach flips the standard trial experience: rather than “here’s what you could do,” the product says, “you’ve already done it — do you want to go further?”.

That shift matters; the user has invested effort, seen a result, and is no longer just exploring — they’re in motion. The value isn’t promised; it’s earned, happening before the user ever reaches the dashboard.

In an AI-powered music app, for example, onboarding might involve writing lyrics, picking a genre, and generating a fully produced demo within minutes. That song becomes the user’s first meaningful interaction with the product. A low-bitrate version might be free, with a paywall introduced only when the user wants to export or upgrade. The paywall isn’t a blocker; it’s a continuation of momentum.

This model dramatically shortens time-to-value. It doesn’t just show users what the product can do; it involves them in doing it. They’re not watching a demo; they’re participating in creation. Especially in products where the goal is creativity, execution, or rapid utility, users don’t want onboarding tours or long tutorials; they want results.

In that context, onboarding shouldn’t feel like setup or orientation; it should feel like doing the thing the product is built for. Guiding users into a focused, hands-on experience from the very first screen is one of the most effective ways to establish relevance and convert curiosity into commitment.

Chatbot assistants

An increasingly common pattern in AI-driven products, particularly on the web, is the use of chatbots as part of the onboarding experience, though it’s less common on mobile due to UI constraints.

Some products offer an AI assistant to support users during onboarding, allowing them to ask questions as they progress through setup. This is especially useful for complex tools where users may have questions beyond typical onboarding flows. In this scenario, the chatbot acts as a supplementary layer, clarifying, assisting, and guiding in real time.

In other products, onboarding is led entirely through a chatbot interface. Users interact directly with the bot, which collects information, introduces features, and simulates the core product experience. This is an appealing idea: delivering immediate interaction, personalization, and value all in one place.

However, there are caveats. In one product I worked on, we experimented with a model where users engaged with a lightweight, onboarding-focused chatbot immediately before signing up. The idea was to collect input and offer a preview of how the product worked, all while making the experience feel personalized. While it made sense on paper, users misunderstood the flow. Many assumed the limited chatbot was the full product, and were frustrated when it didn’t support deeper or more advanced queries. The result wasn’t engagement — it was disappointment.

This doesn’t mean chatbot-led onboarding has no future, but it is highly context-dependent. Its effectiveness relies on users’ expectations, technical maturity, and awareness of how AI works. If the experience isn’t clearly framed or the assistant falls short of user expectations, it can easily backfire. Chatbots can be powerful onboarding tools, but only when they support, not misrepresent, the actual product experience.

Conclusion

Effective onboarding is more than just a tutorial; it’s a carefully crafted motivational experience that sets the stage for long-term user engagement and loyalty. The core principles revolve around two intertwined pillars: personalization and value.

Personalization is essential from the first interaction. Starting small, asking purposeful questions, and building logical, context-aware flows help users feel understood and make the experience immediately relevant. This approach not only gathers valuable input for improving AI-driven products but also builds early user investment. When users can control personalization by connecting their own systems or data, the product evolves from a general tool into a deeply contextual assistant.

Equally important is how value is presented and delivered. Instead of listing features, effective onboarding shows the outcomes users can achieve, creating a clear, motivating promise. The strongest flows let users experience that value early, guiding them through a meaningful use case before they’ve fully committed. This shifts the experience from a passive preview to an earned result, dramatically reducing time-to-value. Chatbot assistants can support this well, but only if expectations are clearly managed; when misunderstood, they risk undermining the broader product experience.

Ultimately, the goal of modern onboarding is to make the user’s effort feel inherently worthwhile. By focusing on personal relevance, fostering a sense of confidence, and rewarding each step with tangible progress, products can convert initial curiosity into lasting commitment, ensuring users not only understand how the product works but, more importantly, why it matters to them.

References I recommend going through:

• How to retain more users with value-based onboarding by Robbie Allan for Intercom
• State of Subscription Apps 2025 by RevenueCat
• Growing public concern about the role of artificial intelligence in daily life by Alec Tyson and Emma Kikuchi for Pew Research Center
• 5 ways to personalize your user onboarding experience by Katryna Balboni for Appcues
• Effort Justification: Valuing Experiences More Due to Effort Invested by Aslan Patov for Renascence.io
• How Canva’s growth team improves activation +10% by Ty Magnin for Appcues
• The magic of microcopy by John Saito
• The Dopamine Loop: How UX Designs Hook Our Brains by Arushi
• AI Agents Simplified: How AI Agents Answer Questions Using Domain Knowledge by Shawn Shi
• Framing Your Way to a Better User Experience: A Guide for UX Designers by Hadrik Dewra
• The one trick to improve your user onboarding by Roman from Onboarding.pro

The first 30 seconds: how to show value in AI product onboarding was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

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