Re-designing symptom logging for casual and power users at Flo Health

Inflexible symptom logging meant users often felt underrepresented and insights remained shallow, while vague boundaries between free and Premium features hindered Flo’s ability to drive engagement, revenue and retention.

Inflexible symptom logging meant users often felt underrepresented and insights remained shallow, while vague boundaries between free and Premium features hindered Flo’s ability to drive engagement, revenue and retention.

Role

UX/UI designer

Company

Flo Health

Femtech

Time Frame

6 weeks

Skills

Product strategy

Content design

UX/UI design

Explore the prototype

Background

Expanding features, blurred value

With ~280M users worldwide and unicorn status, Flo has become the most-used health and fitness app globally for menstrual cycle and fertility tracking. But despite broad adoption and a strong brand, user feedback indicated that navigation, logging, and feature clarity weren’t always keeping up with expectations.

Challenge

Restrictive logging & low feature awareness

User interviews revealed two pressing issues:

Constrained symptom tracking — users lack the options to fully represent their experiences or track symptom nuances.

Low awareness of app features — both free and Premium users struggled to understand the app’s full value, undermining satisfaction and revenue.

Solution

Flexible logging and guided feature discovery

I designed:

A more flexible, representative logging flow to suit both casual and power users.

A feature discovery experience that gently surfaces app features, distinguishing between free and Premium to encourage Premium adoption.

When the leader already leads, what’s left to improve?

As the undisputed leader in its category, competitive and secondary research showed that Flo's strength was breadth, but this risked cascading into scope bloat and unclear value.

Optimising existing flows mattered more than adding new ones

Premium transparency was key to building revenue and trust

Many pain points could be tested with low-stakes A/B tests vs full-scale re-designs

User interviews revealed two distinct user mindsets, with very different usage behaviours

Through interviews with free and Premium users, I identified two distinct user archetypes:

Power users

Investigative Indias

Curious, detail-oriented users who track symptoms related to suspected or diagnosed health conditions; they value data, education and insights.

Casual users

Empowered Esmes

Quick, “in and out” users; just want to know cycle phase, log flexibly, and efficiently find information if and when the need arises.

At first, the needs of casual and power users felt at odds. But on closer inspection, they wanted many of the same things.

To anticipate and gain control over cycle-related symptoms

“It's important for me to track things so that when I have an appointment I can say, this is when it's been really bad and this is when it's been better.”
-Investigative India
“I use the app to track my symptoms and moods and then look at my own patterns without paying for Premium.”
-Empowered Esme
“Usually if I’m logging it’s because I’ve been a bit mood swing-y and I want to see when and why that's happening.”
-Investigative India
“Before tracking with Flo, I don't think I had a solid understanding of where in my cycle I'm most affected."
-Empowered Esme

“It's important for me to track things so that when I have an appointment I can say, this is when it's been really bad and this is when it's been better.”
-Investigative India
“I use the app to track my symptoms and moods and then look at my own patterns without paying for Premium.”
-Empowered Esme
“Usually if I’m logging it’s because I’ve been a bit mood swing-y and I want to see when and why that's happening.”
-Investigative India
“Before tracking with Flo, I don't think I had a solid understanding of where in my cycle I'm most affected."
-Empowered Esme

“It's important for me to track things so that when I have an appointment I can say, this is when it's been really bad and this is when it's been better.”
-Investigative India
“I use the app to track my symptoms and moods and then look at my own patterns without paying for Premium.”
-Empowered Esme
“Usually if I’m logging it’s because I’ve been a bit mood swing-y and I want to see when and why that's happening.”
-Investigative India
“Before tracking with Flo, I don't think I had a solid understanding of where in my cycle I'm most affected."
-Empowered Esme

Flexible, accurate symptom logging

“My symptoms aren't always at the same level. So to be able to put intense, medium, light, or whatever, that would be really helpful."
-Empowered Esme
“There's all these options that you can add, like how much water you've drunk, your weight and your temperature. I don't want to do any of that.”
-Investigative India
“They don't have pelvic pain as an option, so I just put it down as 'Abdominal pain'."
-Investigative India
“The pain logging options are a bit limited. I usually put ovulation pain under “back pain”, even though it’s not, but I know what it means."
-Empowered Esme
"Using an app that doesn't have the symptoms I want to track isn't great."
-Empowered Esme

“My symptoms aren't always at the same level. So to be able to put intense, medium, light, or whatever, that would be really helpful."
-Empowered Esme
“There's all these options that you can add, like how much water you've drunk, your weight and your temperature. I don't want to do any of that.”
-Investigative India
“They don't have pelvic pain as an option, so I just put it down as 'Abdominal pain'."
-Investigative India
“The pain logging options are a bit limited. I usually put ovulation pain under “back pain”, even though it’s not, but I know what it means."
-Empowered Esme
"Using an app that doesn't have the symptoms I want to track isn't great."
-Empowered Esme

“My symptoms aren't always at the same level. So to be able to put intense, medium, light, or whatever, that would be really helpful."
-Empowered Esme
“There's all these options that you can add, like how much water you've drunk, your weight and your temperature. I don't want to do any of that.”
-Investigative India
“They don't have pelvic pain as an option, so I just put it down as 'Abdominal pain'."
-Investigative India
“The pain logging options are a bit limited. I usually put ovulation pain under “back pain”, even though it’s not, but I know what it means."
-Empowered Esme
"Using an app that doesn't have the symptoms I want to track isn't great."
-Empowered Esme

Transparent Premium vs. Free value proposition

“My subscription is about to run out. I was going to see what the app is actually like without it, because I can't remember what I get extra.”
-Investigative India
“I wish they’d be like, this is what you get on a premium account, and this is what you don't get, just being really upfront about it.”
-Empowered Esme
“Erm... there’s the advice… and there’s the community features… I don't know what other Premium things there are.”
-Empowered Esme
“Why don’t I upgrade to Premium… well, I'm not sure what else it gets you. So I think one thing is, I'm lacking knowledge of all the things you get.”
-Empowered Esme

“My subscription is about to run out. I was going to see what the app is actually like without it, because I can't remember what I get extra.”
-Investigative India
“I wish they’d be like, this is what you get on a premium account, and this is what you don't get, just being really upfront about it.”
-Empowered Esme
“Erm... there’s the advice… and there’s the community features… I don't know what other Premium things there are.”
-Empowered Esme
“Why don’t I upgrade to Premium… well, I'm not sure what else it gets you. So I think one thing is, I'm lacking knowledge of all the things you get.”
-Empowered Esme

“My subscription is about to run out. I was going to see what the app is actually like without it, because I can't remember what I get extra.”
-Investigative India
“I wish they’d be like, this is what you get on a premium account, and this is what you don't get, just being really upfront about it.”
-Empowered Esme
“Erm... there’s the advice… and there’s the community features… I don't know what other Premium things there are.”
-Empowered Esme
“Why don’t I upgrade to Premium… well, I'm not sure what else it gets you. So I think one thing is, I'm lacking knowledge of all the things you get.”
-Empowered Esme

Restrictive symptom logging and hidden tools left experiences untracked and features untapped

This combination of limitations surfaced a wider experience problem: valuable tools were present, but underused due to how they were framed and accessed.

Collectively, these insights revealed an experience gap that called for reframing, shaping the core design questions:

How might we make symptom logging accurate and flexible, yet simple — so users feel represented and supported, and the app gains more valuable data to drive engagement?

How might we clearly show Premium benefits in a simple, relevant way — so free users see the value of upgrading and paying users know how to get the most from their subscription?

Balancing impact and effort to land on product improvements that would serve both user groups

Using the MoSCoW method, I assessed which features would best:

Provide value for both personas
Balance impact vs. effort

The must-have features became:

A redesigned logging flow with more flexibility, symptom options & severity ratings

A re-onboarding quiz and targeted feature walkthrough to clearly introduce relevant features

See user flows

Content-first, confusion last: Designing flexible symptom logging flows

With the feature set established, I employed a content-first approach, listing out the content that would be required for each symptom category, and assessing how to structure the hierarchy to be clear and intuitive.

Key content design decisions

Which new symptoms to add (based on what users told me they felt was missing)

Renaming symptom categories to be clearer and more discrete (e.g. dividing “symptoms” into high level categories like “pain and discomfort”, “digestion and stool”)
A severity rating system that worked regardless of category (i.e. “low, medium, high” worked for states e.g. "motivation" while “mild, moderate, severe” worked for symptoms e.g. "abdominal cramps"

Key UX, UI and product considerations

Avoid overwhelm → progressive disclosure, chunking, collapsible sections, progress tracking, user control and customisation, accordions, tabs, quick actions and content layering

Evolve within Flo’s UI → reuse patterns (chips, accordions, cards) while simplifying layouts
Balance user + business goals → surface features through useful context, not intrusive upsells

Below are my initial paper sketches exploring different layouts for the original symptom log, which I saw as the most complex aspect of the re-design. These sketches include a redesigned homepage, which is the entry point for logging symptoms.

Midfi explorations: validating paths through user preferences

To minimise bias, I created two mid-fidelity versions of each screen then ran an unmoderated preference test with 41 users.

All 41 users were asked to choose their favourite version of the dashboard, symptom log category screen, and feature discovery screen, as shown below.

To minimise bias, I created two mid-fidelity versions of each screen then ran an unmoderated preference test with 41 users.

All 41 users were asked to choose their favourite version of the dashboard, symptom log category screen, and feature discovery screen, as shown below.

To minimise bias, I created two mid-fidelity versions of each screen then ran an unmoderated preference test with 41 users.

All 41 users were asked to choose their favourite version of the dashboard, symptom log category screen, and feature discovery screen, as shown below.

Then, depending on their preferred symptom log category screen, users were shown two versions of each consecutive screen in the flow. This branching logic meant that the sample size providing feedback on the symptom log screens was smaller– but nonetheless valuable.

Under each preference selection, I asked users why they had chosen the design they had.

Under each preference selection, I asked users why they had chosen the design they had.

Under each preference selection, I asked users why they had chosen the design they had.

Some results were split 50/50, indicating that both designs had merit

In those cases, I took forward the designs that:

A) Most closely correlated with user interview data

B) Would have a more significant negative impact if not implemented, based on users' responses as to why they had chosen the design they had

Where feasible, I made small tweaks to the chosen design that incorporated commonly appreciated aspects of the non-chosen design. For instance, several users liked that the minimal edit home screen (see above) showed the days until next period, so I added this into the re-design.

Other designs showed clear winners, and these informed the hi-fi design direction

Midfi explorations: validating paths through user preferences

To minimise bias, I created two mid-fidelity versions of each screen then ran an unmoderated preference test with 41 users.

All 41 users were asked to choose their favourite version of the dashboard, symptom log category screen, and feature discovery screen, as shown below.

Simulating A/B conditions to test visibility and engagement

The redesigned dashboard, accordion-based symptom log, and tooltip feature re-onboarding were taken forward into testing.

The re-onboarding flow was embedded directly within the symptom log screen, encouraging users to explore and interact with elements that naturally caught their attention as they progressed.

As Empowered Esme's rarely explore beyond the symptom log or calendar, I hypothesised that embedding the re-onboarding within the logging flow would better encourage discovery.

This setup mirrored the conditions of a live A/B test, allowing visibility of the card and the likelihood of organic engagement with the re-onboarding experience to be assessed without prompting.

“More useful and more representative”: 100% log success, with 80% re-onboarding CTR

Using the chosen hi-fidelity symptom log, I asked users to show me how they would log their symptoms and mood.

Before completing the test, users were asked which app features they were aware of. They were asked again at the end of the test.

What worked well

100% successfully completed the new logging flow without aid

100% found the re-design more useful than the original

100% found the re-design more representative than the original

60% reported feeling more inclined to log than with the original

80% clicked into the re-onboarding flow without prompting

Overall, user feedback was extremely positive

What needed improvement

Only 50% of those who clicked into re-onboarding engaged with the feature walkthrough tooltips

All users expressed a preference for a full list of features over a walkthrough

Feature recall was the same as baseline, even amongst users who has engaged with the tooltips

2 users thought it could be clearer how the inner and outer portions of the mood wheel worked

Iterating with small fixes and strategic upgrades

I prioritised changes based on impact vs effort:

Quick wins → Rename ambiguous "Edit" label on log category screen to clarify it managed categories, not logged data
Fill-ins → rename “edit” button, add inline definitions for customisable categories
Bigger projects → replacing the mood wheel with emojis, full feature list (free vs Premium) + no credit card free trial A/B test

Feature re-onboarding before

This iteration explored whether embedding re-onboarding within the logging flow could increase awareness of under-used features among log-only users.

Feature re-onboarding after

Feature discovery was repositioned to better support exploration over time, while remeainign easy to access when needed.

Mood log before and after

The mood logging experience was redesigned to better support both quick check-ins and more reflective emotional tracking, without compromising text accessibility.

Final solution

The final solution delivers a more flexible, representative logging experience alongside clearer feature discovery, supporting both quick check-ins and deeper tracking while improving transparency around Flo’s full value.