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Home Blog App Marketing Case study: How To Develop a Health Tracking App

Case study: How To Develop a Health Tracking App

Aug 31 2021

health apps promotion

In the fast-paced life, we lack time to visit doctor ever so often for checking on our health. And sometimes, Health issues which need daily monitoring makes a challenge for patients and doctors. Here, Health tracking Apps plays a vital role in providing self-service tools at the ease of a few button taps.

In a time of unprecedented stress for so many of us, health apps have never been more useful in managing and reshaping our lives. Whether you want to sleep more, nail a new skincare routine, develop better eating habits, or find a moment of peace, there’s a health app out there that’ll help you reach your goals.

Maintaining a balanced lifestyle that includes working out, eating fruits and vegetables, and finding time to meditate is harder than it seems. That's why there are hundreds of apps that claim to make all this easy—and sifting through the load can be overwhelming.

To help you figure out the ones that are worth the download, we turned to doctors, registered dietitians, and other experts to share their favorite health apps.

 

Global health tracking app market overview


Increasing inclination towards fitness and weight reduction, increasing prevalence of diseases such as diabetes and rising popularity of using smart bands and watches are driving the growth of the market. According to the article published by World Economic Forum in September 2020, the global downloads of health and fitness apps increased by 46% because people are becoming health conscious and adopting healthy life style for example eating healthy and organic food instead of junk food.

 

Moreover, increasing penetration of internet and smart phones, increasing product development and increasing awareness among people are providing growth opportunities to the market. The increase in the number of people taking online fitness training for example In June 2020, Healthifyme has launched health and nutrition app that offer live and interactive workout sessions.

However, the paid app features and high risk of security can hamper the growth of the market. Health and Fitness apps are based on cloud services so there are higher chances of loss of personal data which can adversely affect the growth of the market.

 

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Segmentation analysis


The global health and fitness app market is segmented based on type, platform, device, and geography.

Health app market by type

• Diet & Nutrition
• Activity Tracking

Based on Type, the market is bifurcated into Exercise & Weight Loss, Diet & Nutrition And Activity Tracking. The Exercise & Weight Loss segment accounted for the largest market share due increasing instances of obesity and increasing awareness regarding the health impacts of obesity including diabetes, cancer and other diseases.

Health and fitness app market by platform

• Android
• iOS
• Others

Based on Platform, the market is bifurcated into Android, iOS and others. The iOS segment accounted for the largest market share due to increasing the adoption of devices which uses iOS operating system and increasing consumer purchasing power.

Health and fitness app market by device

• Smart Phones
• Tablets
• Wearable Devices

Based on Device, the market is bifurcated into Smart Phones, Tablets and Wearable Devices. The Smart Phones segment dominated the highest market share due to increasing the penetration of smart phones and internet, increasing disposable income and growing adoption of advanced technologies such as AI and IoT.

Health and fitness app market by geography

• North America
• Europe
• Asia Pacific
• Rest of the world

On the basis of Geography, the Global Health and Fitness App Market is classified into North America, Europe, Asia Pacific, and Rest of the world. North America held the largest revenue share and is expected to maintain the lead throughout the forecast period owing to growing awareness about health and increasing the adoption health and fitness apps, changing life style and increasing product development.

Insights and challenges


Several studies have used data from commercial apps and wearables to characterize health behaviors and their potential influence on health indicators, like weight and cognitive performance. 

For example, our group has analyzed data from over 700,000 users of a smartphone app (Argus, Azumio, Inc.) for tracking physical activity. We analyzed minute by minute step counts estimated automatically using the smartphone’s onboard inertial measurement unit (IMU) in individuals from over 100 different countries. This analysis revealed that inequality in how physical activity is distributed between individuals in a country is a stronger predictor of obesity rates than average activity levels in a country. By connecting activity tracking results to a database of city walkability scores, we also showed that higher walkability scores are associated with lower activity inequality in U.S. cities.

Analyzing data from consumer users of apps and wearables has allowed researchers to characterize health indicators, such as blood pressure variability, and points to promising new avenues of research, such as focusing physical activity interventions on the activity poor segment of a population. 

We also see that external factors, such as the walkability of a city and social pressures preventing sleep, can have a strong influence on health behaviors. This supports the findings of previous, more traditional studies and with the larger subject numbers in consumer app datasets, we can quantify associations between external factors and health behaviors across different age and gender groups. 

Analyzing these large datasets can also help improve the design of apps and wearables. Multiple studies show that social influence and gamification are associated with increases in healthy behavio and that gender is an important covariate. Predictive models could help apps that promote physical activity become more effective by, for example, guiding friendship recommendation algorithms or creating effective groups for activity competitions. 

Users’ goals and how individuals use health apps can be variable, but the data available about a user’s interactions with an app (even in the first few days) can predict much of this variation. Using this knowledge, app designers could create more engaging and personalized apps that are more effective in achieving behavior change.

Challenges and opportunities


Reviewing this literature and reflecting on our own experience analyzing these large-scale datasets reveal several common challenges and potential sources of error. Since these datasets are not generated to test a specific hypothesis, the data is almost always “messy” and difficult to analyze for a variety of reasons. 

Measurement error can arise from the inaccuracy of sensors in estimating quantities of interest (e.g., steps or sleep) and such errors can be systematic. 

Some of the studies analyzing sleep, steps, and physical activity, conduct their own experiments, cite validation studies in the scientific literature, and/or compare values and trends to previous literature and datasets. Missing data is another challenge, since individuals do not always wear their device or carry their phone.

Selection bias can also occur, as individuals who use apps and wearables may not represent the gender, age, geographic location, socioeconomic status, and/or race/ethnicity of the population of interest. 

Most studies acknowledge these issues and several conduct sensitivity or robustness testing. Handling very large datasets can also be challenging with a typical computer and traditional methods, particularly for researchers with limited expertise in machine learning and data science. Forming academic-industry data sharing partnerships has also been a major limiting factor in the number of studies conducted thus far.

Access to data remains a significant barrier to research. Vast amounts of data have been and are being collected by smartphones and wearables, but they are largely siloed at individual companies. A few strategies might unlock more of these data for analysis by researchers to uncover new ways to monitor and improve health. 

We encourage users to release anonymized data to advance research and, at minimum, there should be better means for users to download their own data and donate it for research, if they wish to do so. 

Going a step further, researchers can also leverage the growing movement toward citizen science, where researchers engage individuals in the process of collecting and analyzing data and then employing the results to effect changes in their community.

For example, Rodriguez and colleagues recently showed that using a citizen science mobile app called the Discovery Tool (which allows participants to take geo-coded photos and describe barriers to and enablers of healthy living in their local environments) increased engagement in a safe routes to school program along with rates of walking and biking to school. 

To protect user privacy, we need better standards and algorithms for anonymizing activity data. Government, health care, academic, and industry partnerships and consortiums around app and wearable data sharing and analysis are also needed.

The research community needs more gold-standard population level data against which to compare. Initiatives like the UK Biobank have conducted large cohort studies that provide a valuable resource, including wearable data, along with medical records, imaging, genome, and other measures. Another area of interest is identifying the relationships between activity, sedentary time, and sleep over the full 24-hour day. 

Data from commercial apps and wearables could provide insights into these relationships, but better algorithms and sensors are needed to accurately differentiate between these activities. Additionally, the research community needs transparency. 

Understanding how algorithms are computing quantities of interest—like steps or activity counts—is vital for researchers to understand sensitivities and limitations of their datasets. We encourage companies to share the details of their algorithms with researchers when possible.

Types of health tracking apps


Today several health tracking apps are available and they are becoming widely popular among users. A study by marketing charts showed that every 1 in 5 people prefers to use health trackers to monitor their health. Further, Health tracker apps were found common in the age group of 18-34 yrs followed by 34-55 yrs.

Fitness tracking app

 

Fitness Tracking Apps keep a track of physical activities in a day of a user. Whether a user is engaged in an extensive workout or is indulged in walking, Fitness tracking apps help him in keeping a record of how many calories he has burnt, or how many steps he has taken in a day. Such applications also collect and save user information of how many pushups, cycling distance, stairs climbed, Swimming Strokes, and hours slept in the form of graphs and charts to help users analyze their routine and do necessary changes for a healthy lifestyle. This graphical presentation shows daily progress to help set fitness targets.

Health conditions monitoring apps


These applications monitor chronic conditions like diabetes, blood pressure. These apps count Blood Glucose, Heart Rate, Respiratory rate, and other health measurements. These metrics are used to track and to raise an alert to the doctor and family members when the health is degrading.

These Apps are not just for patients but also for doctors to monitor their patients’ health conditions without visiting them. This makes health services process faster and eliminates queues in the clinics.

Diet tracking apps


Diet tracking apps help users keep a track of their diet- The information it gathers includes daily nutrition intake of biotin, vitamins etc. The entire information provides users with an analysis of what they are consuming and how much is required by their body. As per Statista, 26% of 18-to 30-year-olds use applications to track their nutrition regularly, while 23% of people of similar age group use these apps occasionally.

Diet Tracking Applications allow users to set goals they desire to reach in terms of losing weight or gaining strength. These apps are also useful for nutritionists to know what their patients eat every day.

Women health tracking apps


The most in-demand type of Women Health Tracking Apps is Period and Pregnancy tracking. Such apps produce reliable information based on the data provided and it assists women in tracking their cycle and measure their fertility. These apps produce data based on specific algorithms for estimated ovulation day, a fertile window of five to six days, and the body’s health to provide next prescriptions. Applications in this category assist ladies on their body and provide them with expertise on various health problems.

Mental health tracking apps


Mental Health is a sensitive subject and is increasingly gaining importance among people and medical providers around the globe. Many medical providers are applying their knowledge and experience in the development of mental health apps to support the issue. App development for this cause requires a detailed study of user behaviour to be able to develop a useful app.

Mental Health Applications assist users to track mental health, calm themselves down in anxiety and get of it slowly with day to day exercises. These apps help survive hectic issues and usually focus on more interaction with the user. In case of emergency, it raises alert to doctors, police and family members.

So, the above-mentioned apps are the most popular in mHealth Development. You must research and gather data of the mHealth market to determine your category of application

Let’s now move on to the most popular and competitive Health Tracking Apps available in the market and combination of features to get the best results.

Must have features of health tracking apps

 

Onboarding


To get users onboard you will have to ensure that the app is convenient for them. For this, you have to make a login and sign up process easy. You can either use the standard email and password approach to get users to sign up for the app, or opt for social media/ third-party integration with which users can access your app account. Make sure your app defines what services your users are going to get with minimalistic illustrations.

Detailed health profile


After registration, the next important feature in an app is the user profile. Allow users to create a simple user profile by filling in basic health details that the application uses. Collect only important information and do not overboard with unnecessary questions. Collect data from users which required such as height, weight, ailments, allergies and period date.

App tracking indicators


The main reason people have installed the app is for self-managing the health. Thus, do not compromise on the main feature. Provide tracking features with a good interface that delivers accurate data and maintain user record.

Social media and community features integration


This feature is very crucial for a fitness tracking app as it serves two purposes.

Firstly, using it the user can register in the app with just a few taps. Secondly, authorizing your app using Facebook will make the process of searching for friends easier for your users thereby building a larger audience. The users will spread the word about your app and will help in building an app audience for you.

Reminders and notifications


Reminding users about their health ensures they remain engaged. Giving reminders to fill regular logs, reminders to take medication and levels they have to achieve which they have set for themselves genuinely help users to improve and live a healthy lifestyle. In order to enhance the usability of your application, based on the review of the activities and information received, you can build in functionality to alert users about potential health concerns.

Symptom tracking and analysis


Having a symptom tracker helps users find out about the symptoms and risk associate with it. Users can regularly monitor their symptoms and patterns regularly to improve their health. The app must regularly track user symptoms and provide accurate suggestions on that. Modern technologies like AI and machine learning are used in collecting user data while also offering customized insights into safety for each user. By adding wearable support in your app, your users can automatically add health data to their everyday logs while providing you with better data to analyse.

Digital consultation


To provide users with a reliable communication channel, you can provide them with digital consultation. When the user-health drops, he can contact a health care professional and share the records with them. It is simple and realistic to get help online. You can partner with medical professionals who offer advice and treatment plans or allow patient’s professionals to provide advice through your app via message or voice calls.

Use gamification to motivate your app users


Gamification is one such technique that motivates your users to use your app to complete the task and achieve their fitness goals. By rewarding them with medals, stars, badges or giving some virtual money during each phase of progress in your health application, will not just help your users achieve their goals faster but you can also increase your app engagement rate which in turn will help you increase your app revenues.

Trending technology used in healthcare apps

 

Telemedicine


What if someone wants to consult a doctor urgently, but he is not in town, or what if the problem is not that big that one has to go to the clinic for a checkup. For this situation, the telemedicine programs work great and have revolutionized the health maintenance industry. These apps allow users to remotely contact the doctors and dieticians without visiting their vicinity, which helps them when the world is facing such flu/pandemic like COVID-19. It is an easy accessibility to professional doctors.

So if you are searching for a women’s or men’s health maintenance application, then make sure that you look for the one with doctors on-demand or telemedicine facility to meet them virtually on behalf of the commission. And if you are someone planning to build an app for health maintenance, this is a beneficial technology to keep in mind while deciding the features.

Blockchain technology


This technology is a decentralized data technology that preserves the patient data from all kinds of threats and vulnerabilities concerning security. It allows open access of information to all the stakeholders with all rights reserved within an organization. The technology controls access through secure encryption and prevents any type of data theft. It is the safest road to protect a patient’s data under all rights reserved Claus when using this digital media evolution.

Thus, if you use this technology, your online audience will be ensured about their information security, and your women’s or men’s health app will never question its credibility. You will also earn your share of commission, online goodwill, and brand recognition by taking into account such technology.

Internet of things (IoT)


IoT describes the connectivity between multiple computers over the internet. This technology can reshape the development of a health maintenance application. A developer has to integrate a particular medical device or even a Fitbit to the mobile phones, which could help users and doctors monitor data glance, side history, contacts, fingertips, videos, pictures, and photos of glasses more accurately. Insulin pen-like Gocap and InPen already use this technology to keep track of the user’s healthyout and give alerts about the bodily changes instantly.

The provider and payor apps integrated with Apple's HealthKit


The vast majority of the apps integrating with HealthKit are fitness-oriented trackers. But one of the things that Apple leaned on the most when they announced HealthKit was that the platform could also be used to improve healthcare, which they illustrated via their partnerships with Epic and the Mayo Clinic. Our analysis found 15 apps that interfaced with providers and another three related to payers and employers.

Limitations and future work


The tools we used to get the information from the Google Play Store only returned the top 250 apps related to our keyword search, so we could not extensively and exhaustively cover all apps. For our preliminary results, we only covered the apps in Google Play and not in iOS. 

Although we identified 159 apps to be self-tracking, we only conducted a detailed analysis of 15 so far, which may not fully encompass all trends in apps. There is also the possibility that we may have missed some relevant apps
due to the keywords used. 

If this analysis were repeated, the results may differ due to the Google Play market changing frequently. Lastly, we primarily focused on free content in our more detailed analysis; it is possible that some features that are lacking are behind a pay wall. We intend to address some of these limitations by investigating iOS apps, conducting a content analysis of more apps, and including paid features and apps in the analysis.


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