Cereba - AI Powered Onboarding Setup

Scalable AI onboarding built for clarity, speed, and user trust.

What is Cereba?

A SaaS platform that helps businesses and agencies create AI-powered sales and marketing campaigns. Onboarding is the first impression and step to training the users AI on brand tone, goals, and audience.

Role: Head of Product & UX
Company: Early-stage AI SaaS startup
Timeline: MVP launch to ongoing iterations

Challenge

Building user trust in AI-generated content from the outset.

Designing a quick yet customizable setup process.
Managing diverse user knowledge levels and content quality.
Creating distinct, non-confusing entry paths for different user types.

My Contribution

Defined and implemented onboarding flows and microcopy.

Collaborated with engineering on state logic and user pathways.
Conducted user testing to identify and address drop-off points.
Developed internal tools and dashboards to inform future improvements.

Goal

Reduce onboarding friction and uncertainty.

Enable users to establish a personalized AI setup in under five minutes.
Cater to both individual and agency users with tailored experiences.

The Design Process

1 Understand

We launched with what we thought users wanted: a rich, thorough onboarding experience. It asked 25+ questions about their company, industry, tone, and goals, everything the AI needed to perform.

What We Saw

Drop-off at the AI personality step
Tracked via Google Looker Studio. Users exited during the point where they were asked to build a tone and audience profile for the AI.
User feedback on support and onboarding calls
“This is working great! But do I have to go through all that again for each campaign?”
Increased onboarding support volume
Early-stage users consistently reached out for help within the first few minutes of setup.

What We Measured

Funnel completion rates and drop-off at each step
Conversion rates into campaign creation
Ticket tags and onboarding-related help requests

What Surprised Us

Low urgency to complete onboarding
Many users started but didn’t finish setup in a single session. Some would return days later. Others said they weren’t “ready” to use AI or didn’t know how it would help.
Misaligned user assumptions
We initially designed for GoHighLevel users and digital agencies. In reality, most users were small business owners without websites or CRM tools. Some didn’t yet have a clear marketing process, which shaped their perception of AI’s usefulness.

What We Learned

Users needed a better understanding of what the AI setup would do for them
We need to focus on AI education, not just efficiency

First personality creation experience.

Google Looker data visual.

User personas for individual and agency.

2 Sketch

We explored three onboarding directions, each with a different take on speed, clarity, and control. The goal was to uncover the right balance between automation and user guidance, one that worked for both individual users and agencies.

We Explored Possibilities

1. Chatbot
A conversational interface that felt novel, but users didn’t know what they could say, and many were confused about what it was doing with their responses.

2. Express Setup
This 45-second version scraped content from a website to auto-generate an AI profile. It was fast, but users dropped off at the paywall, unsure of the value they had just created.

3. Guided Flow (Final Direction)
We designed a custom, step-by-step path using short, tailored questions. It maintained speed while giving users clarity, light control, and a growing sense of value at each step.

Other Key Focuses

Tone and personality selector to shape AI behavior
Progress indicator to reduce anxiety around completion
Branching logic for individuals vs. agencies

These were tested using low-fidelity flows and live prototypes with engaged customers. Feedback shaped our direction quickly — helping us align the experience with different user types and expectations.

Examples of the different design concepts

3 Decide

After testing three onboarding flows, the guided, question-based version emerged as the clear winner. It performed better across all key metrics and also delivered a smoother, more intuitive experience that users consistently described as confident and easy to follow.

Why the Guided Flow Won

Higher completion rates and fewer drop-offs at the paywall
More positive user feedback during testing: users felt “confident” and “in control”
Reduced confusion — each question focused attention and lowered cognitive load
Improved accuracy — responses were more consistent and meaningful
Better perceived value — users understood what they were building and why it mattered

The step-by-step model helped demystify AI onboarding for users who initially found the idea overwhelming.

How We Prioritized

We used a mix of:

Stakeholder input
User testing feedback
Live A/B test results (Guided vs. Express vs. Classic)

We also refined scope using feedback from onboarding support sessions and real usage friction.

What We Cut or Delayed

Manual knowledge base setup was removed from onboarding. Instead, the AI auto-generates it and users can edit it later.
Redundant questions (like campaign engagement prompts) were consolidated. Asking the same thing twice — even in different contexts — felt repetitive to users.
Typing-heavy inputs were minimized in favor of smart defaults and one-click answers, speeding up the flow without sacrificing data quality.

Guided onboarding user journey map

Does the New Onboarding Work?

It was time to test them in the real world. We built interactive experiences in Bubble.io and A/B tested our onboarding flows to see which approach drove the most engagement and conversions.

Each onboarding path was tailored to different user needs:

Express – A quick-start option for users eager to dive in.
Standard – A guided, step-by-step walkthrough.
Done For You – A premium service with a 1-on-1 onboarding call for hands-off setup.

By tracking real user behavior, we fine-tuned the flow to eliminate bottlenecks and refine our strategy based on how users actually engaged.

Continuously Measuring the Impact

Our goal was simple: Make onboarding seamless and increase conversions.

We focused on two key metrics:

Increase purchase conversions
Improve onboarding completion rates

Here’s what happened:

✔ Introducing a paywall boosted purchase conversions by 60%.

✔ Over 90% of users successfully completed onboarding.

✔ Refining the Done For You path led to a ~80% user conversion after their complementary setup call.

This confirmed that structured, personalized onboarding directly impacted user engagement, retention, and revenue.

Not everything worked perfectly the first time. Through two rounds of iteration, we uncovered key takeaways:

What we learned from testing & iteration

Iteration 1 Findings:

Done For You adoption stalled at 15%—users didn’t see the value.
Express Flow was too fast, leaving users uncertain about what they were getting.
Missed premium upsell opportunities in the Express Flow.
Paywall lacked perceived value, leading to hesitation.

Paywall Iteration 1

Iteration 2 Improvements:

✔ Refined Done For You messaging → 30% ROI increase.
✔ Added a 2-week free trial (with credit card capture) → Conversions jumped 40%.

These adjustments transformed onboarding into a high-performing conversion engine, ensuring users reached their "aha" moment faster and with less friction.

Paywall Iteration 2