Crimson
UX Design
As part of our HCI course, we consider why and how women track their menstrual cycles, examining their experiences to uncover design opportunities and develop solutions that cater to these young adults. We design 'Crimson' which enables menstruating women to track their period in a personalised manner by adapting to their needs.
View Live →View Report →View Code →View Prototype →We found that women use physical calendars, their own memory & period tracking apps to track their periods. Digitising their personal informatics comes with a lot of benefits of getting detailed analysis, better predictions and ease in sharing with doctors and loved ones. Even so, there are still lot of inhibitions in using the existing period tracking apps mainly due to lack of accurate predictions, exclusion of people with hormonal disorders and overly feminine interface designs.
Menstruating women of the ages 18-22 trying to track or predict periods and related information feel frustrated due to lack of an accurate and personalised method.
"Crimson" enables menstruating women to track their period in a personalised manner by adapting to their needs and letting them enter details that suit their lifestyle, thus giving more accurate cycle predictions.
We designed an extensive set of onboarding questions to know the user better. It involves general demographic information, lifestyle and period specific questions. Obviously, it's not mandatoy, but helps Crimson make better platform for the user.
The user starts personalising the app from the onboarding itself, choosing features they want. Based on the questions, the app itself tweaks the home screen with widgets. The home screen can be customised with widgets as per user's choice. They also get contextual tips after adding their data.
Many users like to keep a tab of their data and see rudimentary analysis themselves. Some prefer to share detailed reports with their doctors and loved ones. Crimson helps both kinds of user, seamlessly analyse and share their data.
Looking back at my design process, I had some key takeaways while working on this project.
We found that women use physical calendars, their own memory & period tracking apps to track their periods. Digitising their personal informatics comes with a lot of benefits of getting detailed analysis, better predictions and ease in sharing with doctors and loved ones. Even so, there are still lot of inhibitions in using the existing period tracking apps mainly due to lack of accurate predictions, exclusion of people with hormonal disorders and overly feminine interface designs.
Menstruating women of the ages 18-22 trying to track or predict periods and related information feel frustrated due to lack of an accurate and personalised method.
This was our final problem statement we arrived after many iterations. As every design process, this also was iterative. We had to focus on our user segment because we had limitations on conducting our research and also the domain of menstrual tracking is huge and a global phenomenon. Hence we focused on young adults aged 18-22. During our research we fixed on the problem faced by these women to period predictions and tracking.
Doing a competitive analysis helps us identify current practices used in Period Tracking (referred as PT henceforth) apps, collate the best features and think about the shortcomings. It also helps as a starting point for further research and design. We chose three competitors to represent a fair share of the segment of PT apps. The compititors are :
A detailed competitive analysis can be found here.
Goals:
Process: We interviewed 11 people (5 semi-structured and 6 contextual) out of which I conducted 3 interviews. My 3 participants, will henceforth be identified as U1, U2 and U3. U1 gave a semi-structured interview whereas U2 & U3 gave contextual interviews.
After our initial draft of questions we conducted pilot studies and edited the questionnaire depending on the answers we got.
The interviews were preceded by casual everyday conversation to establish neutral grounds. The semi-structured interview started with some general questions about the interviewee to make them feel comfortable and afterwards I asked questions from our questionnaire set. For the contextual interview I again asked a few general questions and then introduced a PT app. They downloaded the app on their mobile and started using it while describing whatever they were thinking.
‘I usually forget when I had my last period, so it helps me be prepared for it’ - U1
‘Does it predict things based on my previous tracks? If I don’t add data, can it know that maybe there’s something else’ - U2
‘Why does it need so much of data? What does it do with it?’ - U3
The users talked about things that we had earlier missed in the competitor analysis, such as the remarks made by U2, and U3 above. Talking to the users helped usunderstand better why they left using PT apps or thought of them as not being helpful..
Now with all the data we had, we set forth to analyse it and make meaningful connections between them. Here are images of the affinity and scenario maps but you can also see the maps in further detail by clicking on this link. You may have to resize the board from the bottom navigation.
As at each step we’re building on top of previous results, we worked on top of the themes defined by our affinity mapping. We made 3 users which will help us define our product further. Personas allow for interdisciplinary knowledge sharing and help to understand more about personas and their use of the proposed design.
Both the Information Architectures can be explored in further detail at this link. You may have to resize the board from the bottom navigation.
As at each step we’re building on top of previous results, we worked on top of the themes defined by our affinity mapping. We made 3 users which will help us define our product further. Personas allow for interdisciplinary knowledge sharing and help to understand more about personas and their use of the proposed design.
Process
Our group conducted 10 user evaluations. Due to covid-19 restrictions we could not go out physically and conduct these tests, so instead we conducted them online through Google Meet. I conducted 2 evaluations which I’ll refer to as E3 and E4 (Figure 22 & 23).
I chose these people because both provided a good mix to the pool of evaluators. E3 is a Literature Major with Art background. E4 is a Junior pursuing engineering.
To conduct the evaluations, we took consent to click photographs & screen record and then, we shared our prototype link with the users and told them to share their screen. I kept a note of what they were saying. E3 liked the app a lot but also gave valuable feedback regarding the colour of the app. She said ‘Red is associated with powerful emotions and hence I’d like some other colour in my app’. She further asked during add data, 'Can I add my symptom on my own, which isn't here'. This made us rethink the placement of the add button, which wasn’t very accessible. E4 also added, 'I'm not able to figure out what each kind of box represent'. This sheds light to a fundamental problem for new users, and hence we proposed to add tutorials at the start of the app to help new users get accustomed to the interface.
Summary
Till now we scoped the problem, defined user’s goals and motivations, sketched out the design and finally made the prototype. This step I believe is the most crucial out of all as here we actually took our app and let real users test it. We got some interesting feedback regarding visual design, placement of buttons, some regarding the flow as well and we intend to incorporate all those in our revised design. A more abstract learning that I got was from people telling how useful it can be for them. 'When I go to my doctor, I don't remember most of the things from my previous cycles, this would help me a lot.' - E3. This I believe is the strongest learning of user centered design, users actually liking what you made, and you can have a small but significant impact on their lives.
Looking back at my design process, I had some key takeaways while working on this project.
We found that women use physical calendars, their own memory & period tracking apps to track their periods. Digitising their personal informatics comes with a lot of benefits of getting detailed analysis, better predictions and ease in sharing with doctors and loved ones. Even so, there are still lot of inhibitions in using the existing period tracking apps mainly due to lack of accurate predictions, exclusion of people with hormonal disorders and overly feminine interface designs.
Menstruating women of the ages 18-22 trying to track or predict periods and related information feel frustrated due to lack of an accurate and personalised method.
This was our final problem statement we arrived after many iterations. As every design process, this also was iterative. We had to focus on our user segment because we had limitations on conducting our research and also the domain of menstrual tracking is huge and a global phenomenon. Hence we focused on young adults aged 18-22. During our research we fixed on the problem faced by these women to period predictions and tracking.
Doing a competitive analysis helps us identify current practices used in Period Tracking (referred as PT henceforth) apps, collate the best features and think about the shortcomings. It also helps as a starting point for further research and design. We chose three competitors to represent a fair share of the segment of PT apps. The compititors are :
A detailed competitive analysis can be found here.
Goals:
Process: We interviewed 11 people (5 semi-structured and 6 contextual) out of which I conducted 3 interviews. My 3 participants, will henceforth be identified as U1, U2 and U3. U1 gave a semi-structured interview whereas U2 & U3 gave contextual interviews.
After our initial draft of questions we conducted pilot studies and edited the questionnaire depending on the answers we got.
The interviews were preceded by casual everyday conversation to establish neutral grounds. The semi-structured interview started with some general questions about the interviewee to make them feel comfortable and afterwards I asked questions from our questionnaire set. For the contextual interview I again asked a few general questions and then introduced a PT app. They downloaded the app on their mobile and started using it while describing whatever they were thinking.
‘I usually forget when I had my last period, so it helps me be prepared for it’ - U1
‘Does it predict things based on my previous tracks? If I don’t add data, can it know that maybe there’s something else’ - U2
‘Why does it need so much of data? What does it do with it?’ - U3
The users talked about things that we had earlier missed in the competitor analysis, such as the remarks made by U2, and U3 above. Talking to the users helped usunderstand better why they left using PT apps or thought of them as not being helpful..
Now with all the data we had, we set forth to analyse it and make meaningful connections between them. Here are images of the affinity and scenario maps but you can also see the maps in further detail by clicking on this link. You may have to resize the board from the bottom navigation.
As at each step we’re building on top of previous results, we worked on top of the themes defined by our affinity mapping. We made 3 users which will help us define our product further. Personas allow for interdisciplinary knowledge sharing and help to understand more about personas and their use of the proposed design.
Both the Information Architectures can be explored in further detail at this link. You may have to resize the board from the bottom navigation.
As at each step we’re building on top of previous results, we worked on top of the themes defined by our affinity mapping. We made 3 users which will help us define our product further. Personas allow for interdisciplinary knowledge sharing and help to understand more about personas and their use of the proposed design.
Process
Our group conducted 10 user evaluations. Due to covid-19 restrictions we could not go out physically and conduct these tests, so instead we conducted them online through Google Meet. I conducted 2 evaluations which I’ll refer to as E3 and E4 (Figure 22 & 23).
I chose these people because both provided a good mix to the pool of evaluators. E3 is a Literature Major with Art background. E4 is a Junior pursuing engineering.
To conduct the evaluations, we took consent to click photographs & screen record and then, we shared our prototype link with the users and told them to share their screen. I kept a note of what they were saying. E3 liked the app a lot but also gave valuable feedback regarding the colour of the app. She said ‘Red is associated with powerful emotions and hence I’d like some other colour in my app’. She further asked during add data, 'Can I add my symptom on my own, which isn't here'. This made us rethink the placement of the add button, which wasn’t very accessible. E4 also added, 'I'm not able to figure out what each kind of box represent'. This sheds light to a fundamental problem for new users, and hence we proposed to add tutorials at the start of the app to help new users get accustomed to the interface.
Summary
Till now we scoped the problem, defined user’s goals and motivations, sketched out the design and finally made the prototype. This step I believe is the most crucial out of all as here we actually took our app and let real users test it. We got some interesting feedback regarding visual design, placement of buttons, some regarding the flow as well and we intend to incorporate all those in our revised design. A more abstract learning that I got was from people telling how useful it can be for them. 'When I go to my doctor, I don't remember most of the things from my previous cycles, this would help me a lot.' - E3. This I believe is the strongest learning of user centered design, users actually liking what you made, and you can have a small but significant impact on their lives.
Looking back at my design process, I had some key takeaways while working on this project.
