Maia voice transcription screen Maia patient follow-up cycle cards
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Maia Health - 2025

How we increased adoption by showing less of the product.

Users didn't need to know the whole platform to get started. They needed to solve a real problem with as little effort as possible.

Project overview

Industry
Health Tech SaaS
Role
Product Designer
Timeline
December 2024 - April 2025
Outcome
+67% subscriber base in three months
Maia's new trial home on a MacBook, with transcription front and center

Context

Maia is a SaaS platform that helps healthcare professionals reduce the administrative load of clinical work, bringing electronic health records, patient management and AI tools together in one place.

Context data

Almost 2 hours a day. That's how long physicians spend, on average, on health records and clinical documentation outside working hours, according to a study of US physicians (JAMA Internal Medicine, 2022, 2019 data).


*This figure does not refer to Maia users.

Scenario

Growing new user acquisition was a business priority. At the time, the process relied on sales demos, but the sales team was struggling to get them booked.

More than 50% of scheduled demos never happened. On the other hand, among professionals who did attend a Maia demo, the reported sales conversion was above 80%.

That gap suggested the platform had a compelling value proposition, but depended on a sales process that made it hard for new users to reach the product.

>50%

of scheduled demos never happened (no-show).

>80%

sales conversion among professionals who attended a Maia demo.

Data reported by the sales team.

Healthcare professional using Maia during an appointment

Challenge

How might we get more people to discover and experience Maia's value?

Discovery

The most used feature was hidden inside the platform.

Every week I tracked Maia's usage data in Mixpanel, looking at how people used the platform, especially the most active users.

Over time, a pattern emerged: AI transcription accounted for far more usage than any other feature. Some professionals came back to Maia again and again just to use it.

Even so, transcription lived inside the health record flow. To reach it, users had to go through several steps, including creating and selecting a patient, even when they had no interest in using the health record.

Product hypotheses

01 · First contact

We believed that making transcription the first experience would increase the share of new users who actually experienced Maia's value.

02 · Free access

We believed that letting people use transcription before a sales demo would lower the barrier to entry and increase the number of professionals trying the platform.

Mixpanel analysis: AI consultation transcription had the highest event volume, with recurring use by the most active users
Usage by feature over the analyzed period.

Design decision

Get users to value before they get to know the whole product.

The Mixpanel finding opened an opportunity: turn AI transcription into Maia's main entry point.

Until then, acquisition depended on sales demos. I proposed introducing a free trial, following a Product-Led Growth (PLG) approach, in which new users could try transcription before talking to the sales team.

The design decision was to remove barriers to that first use: let users reach transcription without having to learn or set up the health record.

The other features would be introduced as users needed them, instead of competing for attention on the very first visit.

Previous layout Previous screen: new note inside the health record
New layout New screen: transcription as the first action

Experience redesign

From six steps to two.

Before, to start a transcription, users had to find or create a patient, open their health record and create an entry.

That flow made sense for people using Maia as their health record, but added unnecessary steps for those who just wanted to transcribe an appointment.

I redesigned the journey so new users could start a transcription right from the first screen, without creating or linking a patient.

Afterwards, they could copy the result into the system they already used, or assign it to a patient in Maia.

Illustrative simulation

The cost of repeating a task many times a day

Appointments per day 8

40

steps per day in the previous flow

24

fewer steps per day with the new flow

Assumption: one transcription per appointment. A step count, not time saved or an observed usage metric.

Trade-off 01

Reducing friction without giving up on health record adoption

What we gave up

Less exposure to the health record

By no longer requiring a patient to be created, we reduced early contact with the health record and the chance to build it into the user's routine.

What we gained

Faster access to value

New users could start transcribing without setting up the health record, cutting steps they didn't need for their main task.

How we balanced it

Adopting the health record stopped being a requirement and became an option.

After transcribing, users could assign the result to a patient in Maia. That kept opportunities to discover the health record without getting in the way of the first transcription.

Design Rationale

Before

  1. Create patient
  2. Use health record
  3. Transcribe

After

Transcribe Immediate value
Copy result Keep using the current system
Assign to patient Explore Maia's health record

Solution

A first experience built around what users valued most.

I redesigned Maia's first experience to put AI transcription at the center of the journey. Instead of presenting every feature at once, the new interface prioritized a single task: starting a transcription.

Figma overview: new and old home screens, microphone and format drawers, login, transcription flows and health record v2
Maia's new trial home on a MacBook: New Transcription highlighted on the left and Event History on the right

Start with what matters

The new home for trial users put transcription front and center, reducing the number of options and decisions needed on the first visit.

New Transcription: linking a patient is optional; format, audio input and text format Microphone selection Text format selection: first appointment, follow-up, dictated note, bullet summary or original text

Remove unnecessary dependencies

Transcription no longer required creating or linking a patient first. Users could complete the task and copy the result into the health record they already used.

Patient search to assign the transcription, with an option to add a patient
Appointment transcription with no patient yet, with the Assign Patient option and the Copy text button Appointment transcription assigned to the patient Rogerio Murijo

Introduce the rest at the right moment

After transcribing, users could assign the result to a patient in Maia. The health record was still there, but it was no longer a requirement for trying transcription.

Preserve the experience for existing users

Without a round of usability testing before launch, we rolled out the new experience to trial users only.

Existing subscribers kept the previous home, with access to the new transcription from the menu and support from the account team.

Trade-off 02

Redesign reach vs. the risk of change

What we limited

Reach of the new experience

Existing subscribers wouldn't get the new home, which limited early exposure to the redesign and the simplified journey.

What we preserved

Continuity of the experience

We avoided forcing an unvalidated change on subscribers' routines, while new users tried the redesigned journey.

How we balanced it

We kept the previous home, but made the new transcription available from the menu.

That way, subscribers could use the feature without having to adopt the whole new experience.

Results

More professionals trying Maia. A new entry journey in production.

In the three months after the new experience launched, we tracked the growth of trial users and subscribers.

168

new trial users — 12% above the target of 150.

11.9%

conversion: 20 of the 168 trials became subscribers.

+67%

subscriber base: from 33 to 55, a net gain of 22 customers.

These results show how acquisition and the subscriber base evolved after launch. Since there was no controlled experiment, the growth can't be attributed entirely to the redesign.

Learnings

Improving the experience doesn't always mean adding something.

The biggest lesson from this project was realizing that an existing feature could deliver more value once it stopped depending on the rest of the product.

Usage data helped spot the opportunity, but it took questioning one of the experience's assumptions: that users had to start with the health record to use Maia.

In redesigning the journey, we prioritized first value over showcasing every feature. At the same time, we preserved the experience for existing subscribers to limit the risks of the change.

Not running usability tests before launch also left an important limitation: we could track acquisition and conversion, but not directly measure how much the new journey improved usability.

If I kept evolving this experience, the next step would be to watch users complete their first transcription, identify real difficulties and measure completion of that task.

The value was already in the product. The challenge was making it easier to get to.

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