Improving sign ups (mobile app)

Low-quality sign-ups were rising, and internal teams needed more data to properly vet experts. Working closely with product, legal, and ops, we redesigned the registration experience to balance data needs with a better user experience. I quickly prototyped and tested the form with real users, uncovering key friction points and streamlining the journey, before any code was written. Clearer fields, smarter verification, and a stronger foundation for quality sign-ups.

Challenge

Initially experts were allowed to sign up directly through the app, however we saw a rise in low-quality registrations, and in some cases, users attempting to sign up multiple times to game the system. We needed a registration process that would attract legitimate experts and capture the right data to assess their suitability.

The challenge? Internal teams required a large number of data points to verify quality, making the form long and potentially off-putting.

Project goal: Redesign the registration flow to capture essential data, without overwhelming users.

The original registration form

Defining what we needed

The project kicked off with a session led by the PM, bringing together key stakeholders to agree on the essential data points we needed to collect at sign-up. This included operational requirements as well as legal and compliance considerations.

We also confirmed that the business wanted to integrate, a third-party identity verification tool, to ensure users were who they claimed to be. This added complexity to the flow, as we now had to map where verification would sit in the overall journey.

Early discovery sessions to define required data points for sign up.

Visualising the problem

Once we had the full list of required fields (fourteen in total 🫣), it became clear this would be a heavy lift for a mobile form.

Rather than debate the theory (sulk), I quickly built a working prototype using an AI prototyping tool. This gave the team something tangible to interact with, rather than relying on static mockups or spreadsheets of field names.

Creating a prototype using AI tooling

Validation

With the prototype ready, I tested it internally and with a small group of users to evaluate form length and overall experience. Feedback showed the number of fields wasn’t a major issue thanks to autofill, but we uncovered usability problems like unclear labels and unintuitive inputs.

We refined the form, removing friction-heavy fields like date of birth, which Persona could collect later and other non-essential inputs.

Crucially, early testing surfaced issues before development, saving time and rework.

Collating User feedback

Mapping the flow

With the feedback incorporated, I mapped the full sign-up journey, including all key stages of the 3rd party verification process. This helped us clearly visualise the entire user experience, from entering details to completing identity checks, and identify potential drop-off points.

Is it just me? or does anyone else really enjoy the process of mapping a user journey.

Mapping the user flows for both sign up and the external validation

UI design

With the flow locked in, I moved into high-fidelity UI design, focusing on layout clarity, validation states, and mobile responsiveness. The goal was to keep the experience smooth and manageable, even with a higher number of fields.

Working out the required functionality for each form field

Results (pre-launch)

✅ Rapid user validation

Using AI prototyping, we gathered meaningful user feedback within hours, not days. Greatly accelerating validation.
✅ Functional issues caught early

Testing surfaced interaction issues before build, saving time, effort, and rework during development.
✅ Clear team alignment

The prototype aligned stakeholders early, giving the team confidence and clarity on what we were building.
Note: I was unable to provide data findings for this project as i left the company before the project was released.

💡Key learnings

Prototyping early saves time later

Quickly building a functional prototype with AI helped us catch usability issues before development began, saving rework down the line. A vast improvement on basic clickable prototypes.

Not all data needs to be collected upfront

Questioning each data point (like date of birth) led to a more streamlined experience without compromising data quality.

Mapping complex flows early

Helps to prevent ambiguity during development and ensures a smoother handoff to engineers.

🥵 Challenges

High number of required fields

Balancing business, compliance, and platform requirements meant the form comprised of a number of mandatory fields. This risked overwhelming users, especially on mobile, so simplifying where possible was essential.

Multiple stakeholders

Legal, compliance, product, and ops teams all had input on what data to collect. Aligning priorities and agreeing on what was essential took time and diplomacy.

UI design for the form and also confirmation screens

Role: Senior product designer

Project duration: 3 weeks

Team: Project manager, Development and Product designer.

Responsibilities: Discovery • Ideation and prototyping • Journey mapping • User testing • UI • Interaction design

Tools: Miro • Bolt AI • Figma