CamoTea

Problem Background  

Have you ever stayed up a little too late as a result of a flight or project then woke up feeling really groggy the next day? Chronic, recurrent and situational insomnia impact over 45% of the adult population which leads to exhaustion and impaired daytime functioning. The estimated indirect costs of insomnia via loss of productivity and work absences is estimated to cost $6 billion annually. 

There are currently a variety of solutions offered to treat insomnia. One popular method is Sleep restriction therapy (SRT) which is a cognitive behavioural therapy procedure designed to help reduce middle of the night awakenings. It can be a daunting process due to the number of calculations involved in adjusting the user’s sleep schedule as different metrics like sleep efficiency, average time slept, and quality of sleep need to be accounted for and considered. 

While there are existing apps that help set alarms and track user data, there aren’t very many accessible solutions for sleep restriction therapy. 

Research Insights

Camotea initially began with an idea to create a sleep restriction therapy app for users who had circadian rhythm disorder but we soon realised that there was a larger market for those suffering from sleep disorders. We decided that by targeting users with different types of insomnia, we could broaden the total addressable market.

User Pain Points

The primary pain point that we wanted to address was the exhaustion and loss of productivity that users would feel after a night of poor sleep. One’s mental and physical well-being the following day can be significantly impacted by the quality of sleep from the previous night.

Feedback

We conducted 5 usability tests of our competitor’s product and noticed a pattern in some of the issues that the users were encountering with the app. 

There were 3 key insights that we distilled from the usability tests and tried to incorporate into our product.

The first, night mode. Users preferred the darker option which was overall friendlier to the eyes and one’s circadian rhythm by reducing the amount of blue light that users are exposed to when getting ready for bed and experiencing insomnia. 

Secondly, actionable feedback. Users often received rather ad-hoc suggestions without actionable feedback to initiate sleep restriction therapy. It was easy to confuse people with contradictions. The apps trend to lack a ‘so what?. Once you have informed the user about their sleep, what then are the steps that they must take to resolve and address the issue?

Lastly, another common issue raised was the complexity of the UI. Users preferred a simpler version with fewer buttons to do the required tasks necessary.

Solution Explanation

Based on our target user’s pain points and feedback, we were able to further narrow down what the solution needed to succeed. Our target users were people struggling to fall asleep at night, of which many had developed a habit of being on their smartphones. They needed a mobile-first website they could access at the times when the problem, struggling to fall asleep, was most prevalent. Having an accessible solution to improve and address their sleep schedule would lead to improved quality of sleep and minimise loss of productivity in the following day.

Therefore, our primary focus was on developing a mobile design. For our MVP, we opted to focus on the following features:

• Provide a sleep efficiency and average sleep calculator based on user inputs of bedtime, time fallen asleep, and time woken up
• Provide a suggested bedtime based on the calculated sleep efficiency and desired wake up time of the user

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There are more features on our list that could further enhance the user experience but we chose to prioritise the above features due to time constraints. Some of the other features are briefly discussed in the ‘Future Steps’ section and hopefully something that we could incorporate in the future. 

Lofi & Hifi Mockups 

LoFi Mockups:

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AFter some iteration of the lo-fi and hi-fi designs to ensure that they met the previously determined acceptance criteria, Figma was used to create a prototype and test it with users

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HiFi MockUps:

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For our initial designs, we incorporated pages where users could also learn about different methods to try to treat their insomnia such as information pages on cognitive behavioural therapy for insomnia or how to improve one’s sleep hygiene. However, we realised that due to time constraints, we had to prioritise core features that would both benefit the user and address the core issue. 

At its core, our goal for our product was to improve access to sleep restriction therapy and simplify the calculations and data that a user would need to track. As nice as educational resources or interfaces with external apps could be, those would be additional features that didn’t address the core job to be done. 

Implementation Details

Technical implementation

The project is purely a frontend react app hosted on netlify. 

React.js and Typescript were the tech stack used to develop the product

The tech stack was selected as our developer had prior experience with this tech stack before co.lab and wanted to solidify his skillset by using this stack to implement and ship a product. This allowed him to learn more and further improve his confidence in using this tech stack,

Moreso, with the problem we are trying to solve, he felt that using react.js will be an appropriate stack that can be used to build our product as a web app that is accessible on mobile.

Technical challenges

The hardest part of development is successfully determining the most efficient algorithm to calculate sleep efficiency. 

Our team ran into an issue where current calculations of sleep efficiency necessitate the use of a formula that requires date and time inputs which complicates the inputs but we were able to resolve this by limiting the inputs to ensure that the calculated values made sense and were congruent with what the user would experience.

The key takeaway is that we were able to implement suggestions as to when a person should sleep based on the parameters the user provided while interacting with the application.

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Future Steps

Although we had a fantastic experience creating CamoTea and seeing this product end to end from ideation to shipping it, we will not be continuing with this project after our co.lab experience comes to an end. 

This is the first iteration, our MVP of the product. At its core, our goal was to improve access to sleep restriction therapy and simplify the calculations and data that a user would need to track. We completed this by calculating both the average sleep and the sleep efficiency for a user.

If we were to continue the product, there are a few features that we would like to fully flesh out in order to better support users as well as slightly varied use cases (i.e. travellers, workers on shift schedules etc). 

For example, one such change would be to better track the user's breadth of data via accounts or stored local data so that the user would be able to view their sleep journey. We could also include and track more metrics such as sleep quality, total sleep, and sleep goals. 

Another step would be to implement a more thorough SRT regimen that would further simplify and improve the user’s journey to adjust their sleep schedule. This could allow and track more user inputs such as the duration over which they would like to adjust their sleep schedule and adjust based on their perceived quality of sleep. 

There’s also a lot of potential for this app to interface with external functions on the user’s mobile device where it could reduce more steps for the user such as directly setting alarms, adjusting phone brightness/blue light filters, or even turning off Bluetooth connected lights at a predetermined time in order to optimise sleeping conditions. 

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