Tag Archives: Software

Machine Learning Unlocks Quantum Potential: A Paradigm-Shifting Partnership

November 1, 2023Artificial Intelligence & Machine LearningAI, Artificial Intelligence & Machine Learning, Development, ML, Smart, Software, Technologyadmin

In the modern world, technology has revolutionized the way we work, carry out our tasks, and interact with one another. These technological transformations have come into existence due to the application of various scientific discoveries and computing power advancements. In recent years, Machine Learning and Quantum Computing have both evolved to become game-changers, taking their place in the revolutionary field of computer science. This blog will discuss the effects of machine learning on Quantum Computing, and how the models and algorithms derived in machine learning can be applied to enhance the power of quantum computing.

Machine learning has been a hot topic in the world of computer science, with its ability to analyze and make predictions from vast amounts of data. This has led to significant advancements in various fields such as healthcare, finance, and transportation. On the other hand, quantum computing has sparked excitement with its potential to solve complex problems that are impossible for traditional computers.

The Impact of Machine Learning on Quantum Computing

Machine learning and quantum computing are two powerful technologies that have the potential to complement each other. The combination of these two fields can create a cutting-edge technology that can solve some of the most complex problems known to humankind. One of the key areas where machine learning has shown its impact on quantum computing is in the optimization of quantum algorithms.

Quantum computers are known for their ability to process large amounts of data in a fraction of the time it would take traditional computers. However, implementing quantum algorithms can be challenging due to the complexity involved. This is where machine learning comes into play. By using machine learning models and algorithms, scientists and researchers can optimize these quantum algorithms to work more efficiently and accurately. This not only saves time and resources but also improves the overall performance of quantum computers.

Another area where machine learning has shown its potential in enhancing quantum computing is in error correction. As with any technology, errors are inevitable. In quantum computing, these errors can significantly impact the accuracy and reliability of calculations. By utilizing machine learning techniques, researchers have been able to develop algorithms that can detect and correct errors in quantum systems. This has greatly improved the stability and efficiency of quantum computers, making them more viable for practical use.

Exactly How is Machine Learning Impacting Quantum Computing?

Quantum computing, on the other hand, is a unique form of computing that employs quantum-mechanical phenomena such as superposition and entanglement to manipulate information. Unlike classical computers, where information is represented in bits (0s and 1s), quantum computers use qubits to represent information. This allows them to handle and process multiple calculations simultaneously, making them incredibly powerful.

The integration of machine learning with quantum computing has opened new avenues for the development of more sophisticated algorithms and models that can solve complex problems. Machine learning techniques such as neural networks and deep learning are being applied to quantum computing, allowing for enhanced data processing and analysis. This has led to a better understanding and utilization of quantum properties, resulting in improved performance and accuracy in solving complex problems. The potential of this partnership is immense, and it has the potential to shape the future of computing.

Challenges and Opportunities

While the partnership between machine learning and quantum computing offers many opportunities, there are also some challenges that need to be addressed. One major challenge is the limited availability of quantum hardware. Quantum computers are still in their early stages of development, and only a few companies and research institutions have access to them. This can hinder the progress of using machine learning techniques in quantum computing.

Additionally, there is a shortage of experts who possess both machine learning and quantum computing knowledge. Both fields require a deep understanding of complex mathematical concepts, making it challenging to find individuals with expertise in both areas. As such, there is a need for more interdisciplinary training and collaboration between these fields to bridge this gap.

Machine Learning and Quantum Computing Effects

Machine learning and quantum computing have significant positive effects when used together. Machine learning can help quantum computing to identify, react, and handle large volumes of data quickly and efficiently. Both technologies rely on deep mathematical connections, and when combined, they can improve the precision and accuracy of quantum computations. This will enable quantum computers to solve complex problems much quicker than before. Additionally, machine learning can help in reducing the sensitivity of quantum computers to errors and noise, which are common in these systems. This will lead to improved stability and reliability of quantum computers, making them more practical for solving real-world problems.

Moreover, the integration of machine learning with quantum computing can also aid in the development of new quantum algorithms. These algorithms can be used in various applications such as optimization problems, simulation, and machine learning. The combination of these two technologies has the potential to transform various fields, including finance, drug discovery, and climate modeling.

Some Examples of Companies using Machine Learning for Quantum Computing

Several companies use machine learning and quantum computing to improve their processes and services such as: IBM, Google, Microsoft, Rigetti and Anyon Systems.

IBM: IBM Quantum is at the forefront of research and development in quantum machine learning algorithms. They’ve launched the Qiskit Machine Learning library, enabling users to implement quantum machine learning models on IBM’s quantum computers.

Google: Known for its Quantum AI lab, has been exploring the acceleration of machine learning tasks using quantum processors, particularly in the development of quantum neural networks.

Rigetti: Rigetti has been actively using quantum computers for machine learning applications. They offer the Quantum Machine Learning (QML) toolkit, which implements machine learning algorithms on quantum hardware.

Microsoft: Microsoft has been actively researching quantum machine learning and has integrated quantum computing capabilities into their Azure cloud platform, providing resources for quantum machine learning research.

Anyon Systems: Anyon Systems, a quantum software company, explores the application of quantum computing to machine learning and optimization problems, providing software tools for quantum machine learning research.

It’s worth noting that the field of quantum computing is rapidly evolving, and new companies and developments are emerging continually.

Future Possibilities

The combination of machine learning and quantum computing holds immense potential for the future. As both technologies continue to advance and evolve, their integration will lead to groundbreaking innovations in fields such as drug discovery, finance, materials science, and more. With the ability to process vast amounts of data quickly and efficiently, quantum computers powered by machine learning will revolutionize problem-solving and decision-making processes. This will have a profound impact on various industries, leading to the development of new products and services that were previously unimaginable.

Here are some future possibilities and effects of the synergy between machine learning and quantum computing:

Faster Optimization: Quantum computers excel at solving optimization problems, which are prevalent in machine learning. They can significantly speed up tasks like hyperparameter tuning, portfolio optimization, and feature selection, making machine-learning models more efficient and accurate.

Quantum Machine Learning Models: Quantum machine learning algorithms may become a reality, utilizing the inherent properties of quantum systems to create novel models capable of solving complex problems.

Improved Data Processing: Quantum computing can enhance data preprocessing tasks like dimensionality reduction, clustering, and pattern recognition. Quantum algorithms can efficiently handle large datasets, potentially reducing the need for extensive data cleaning and preparation.

Enhanced AI Training: Quantum computers could expedite the training of deep learning models, which is a computationally intensive task. This could lead to faster model training and the ability to tackle more complex neural network architectures.

Quantum Data Analysis: Quantum computing can facilitate the analysis of quantum data, which is generated by quantum sensors and experiments. Quantum machine learning can help in extracting meaningful insights from this data, leading to advancements in physics, chemistry, and materials science.

Drug Discovery and Material Science: Quantum computing combined with machine learning can accelerate drug discovery and materials research. Quantum simulations can accurately model molecular structures and properties, leading to the development of new drugs and materials.

Quantum-Assisted AI Services: Cloud providers may offer quantum-assisted AI services, allowing businesses and researchers to harness the power of quantum computing for machine learning tasks via the cloud, similar to how cloud-based GPUs are used today.

Improved Security: Quantum machine learning can contribute to enhancing cybersecurity by developing more robust encryption and security protocols. Quantum-resistant encryption algorithms are being explored to safeguard data against quantum attacks.

It’s important to note that the full realization of these possibilities depends on advancements in both quantum hardware and quantum algorithms, as well as the integration of quantum computing into existing machine learning workflows. While quantum computing is a promising technology, it is still in its early stages, and practical applications may take several years to become widespread.

Additional Benefits of Machine Learning on Quantum Computing

With machine learning, quantum computing can quickly recognize patterns and anomalies, which can lead to improvements in supply chain logistics and customer service. Additionally, it has the potential to aid breakthrough research in cancer treatments and other scientific issues that currently require significant amounts of time and effort. Using machine learning with quantum computing could generate the solutions more efficiently. Moreover, as quantum computers continue to scale, the applications and potential benefits will only increase. It’s an exciting time for both fields, and the future possibilities are limitless. Combining these two technologies will pave the way for groundbreaking discoveries and advancements that will shape our society in unimaginable ways.

Machine Learning has led to significant improvements in many sectors, and in recent years, Quantum Computing has begun to change how various industries process and analyze data. The effects of machine learning on Quantum Computing can enhance computing efficiency and precision and lead to groundbreaking research. As we continue to explore the possibilities of machine learning and quantum computing, the future is looking increasingly bright for the integration of these two innovative technologies. The application of machine learning to quantum computing has the potential to transform how we conduct research, and it is exciting to think about what changes will come about in the not-too-distant future. The possibilities are endless, and the integration of these two fields is just beginning. We can only imagine the advancements that will be made through this synergy and eagerly await what’s to come. So, it is essential to continue learning about both machine learning and quantum computing, staying updated on new developments, and exploring potential applications in various industries. By doing so, we can fully embrace and harness the power of machine learning and quantum computing, leading to a more advanced and innovative future. So, let’s keep learning and exploring the possibilities together!

In conclusion, machine learning and quantum computing are powerful technologies on their own, but when combined, their potential becomes even greater. As we continue to make advancements in both fields, it is crucial to explore and embrace the possibilities of their integration.

Mystic Media Announced as a 2022 Local Excellence Award Winner by UpCity!

May 17, 2022Android Development, Digital Marketing, iOS DevelopmentApp, B2B, Development, Digital, Marketing, Mobile, Software, UpCityadmin

For more than a decade, UpCity’s mission has been—and continues to be—to help businesses find B2B service providers they can trust. The UpCity Recommendability Rating was developed to determine a service provider’s credibility and recommendability, giving UpCity the confidence to recommend them to the more than 2 million businesses that visit their site.

Each year, UpCity analyzes and scores more than 70,000 service providers based on their UpCity Recommendability Rating and acknowledges the top national and local providers with an UpCity Excellence Award. The results are in, and we won!

We are proud to announce that the Mystic Media team has been recognized as one of the top B2B service providers of 2022 in the Salt Lake City area by UpCity!

Joe Banks, SVP of Engineering at UpCity, had this to say about Mystic Media:

“The team at Mystic Media brings decades of combined experience and quality that helps them stay ahead of the curve in all things digital. We are proud to recognize them with a 2022 Local Excellence Award. Congratulations!” —Joe Banks, SVP of Engineering, UpCity

This recognition has been driven in large part by our 4.9-star review rating on UpCity. Here are a few of our favorite pieces of feedback we’ve received from our incredible customers:

- - “This was a joint effort where we developed the hardware interface between our controller and Mystic Media developed the iOS app. Consequently, there was a lot of information exchange and testing during the process. The basic user interface was completed by Mystic Media in very short order. The rest of the development was the implementation of the various inputs and outputs. The interface retrieves and passes to the door controller via an RS485 communication port. The commands the app sends to the controller via the interface are in hexadecimal. I was very pleased with the speed and efficiency of the development and the ‘can do’ attitude of Mystic Media. They are very professional, respectful, and easy to work with. I would use them again.” – Carl Goodman, June 2021

- - “We hired Mystic for a large and complex project and are very happy with our experience. We were well out of our element with only an idea and a rough one at that. Their creative and knowledgeable team took our idea and pulled us into a process that was efficient and truly felt like a partnership. They care and want to help us see our vision through. We are currently very close to completion and I look forward to them being a valuable part of our journey forward!” – Russell Taylor, June 2021

Throughout the changes our industry has seen, the one thing that never gets old is seeing our clients succeed. We are so grateful for the collaboration opportunities we’ve had over the years and are honored to receive this recognition.

Learn more about the UpCity Excellence Awards.

Stay Ahead of Your Competition with the Top Digital Marketing Trends of 2022

May 10, 2022Digital MarketingAds, Advertising, AI, Algorithm, Analytics, App, Commerce, Customer, Data, Digital Marketing, eCommerce, Game, Gaming, In-Game, Interactive, Personlization, Social, Software, TikTok, Youtubeadmin

In an era of rapid technological acceleration, every year brings new avenues to market services and methods to boost sales. While the metaverse lurks on the horizon, it’s still in the developmental stage. Meanwhile, the current digital marketing landscape has evolved significantly within the past few years. Software developers and business owners must keep up on the latest trends in order to ensure that they don’t fall behind their competitors.

Here are some of the biggest trends in digital marketing today:

PERSONALIZATION

Success in digital marketing is increasingly dependent on how companies collect data and leverage it toward personalized ads. Studies show personalization can deliver five to eight times the ROI on marketing spend.

Personalization at its most basic level entails targeting users based on their demographic or location. For example, Guinness created a hyper-localized ad campaign which incorporated a unique Facebook ad for every Guinness venue in the UK and Ireland. Over 30,000 localized video ads for over 2,500 bars were updated dynamically based on the rugby matches playing at a given time.

Personalization relies on three tenets: data discovery, automated decision-making, and content distribution. Major corporations like Amazon leverage more extensive data with automated decision-making dictated by robust AI algorithms. Netflix’s complex viewing algorithms determine what users may like to view next based on their past viewing habits. The result is not only improved user experience, but a more personal relationship with the brand.

SOCIAL COMMERCE

Projections from Accenture show social commerce will reach $1.2 trillion globally by 2025—about 300% faster than traditional ecommerce. Gen Z and Millennials will be the biggest spenders, accounting for 62% of social revenue by 2025. Platforms are working behind the scenes to improve customer experience by creating payment methods without leaving social media apps. Two major social platforms to watch are TikTok and Youtube.

TikTok usage has risen rapidly and reached 1 billion users and counting. Engagement has been titanic with users in the United States spending up to 850 hours per month on the app. It was the top earning non-gaming app in 2021 with $110 million spent by users and its potential will only grow as influencers earn huge amounts through sponsorship deals. TikTok is not just for Gen Z, it’s a rapidly growing network and brands are taking advantage by offering influencers huge amounts of money for branded content.

As brands move their investment in traditional TV models toward streaming, one platform which stands to benefit is Youtube. Global revenue for the video streaming channel soared to $29 billion, a 46% increase from 2020. Youtube is beginning to attract more traditional TV advertisers and consequentially, their ad business is nearly matching Netflix in revenue. While revenue is ascending, there remains significant headroom for major brands to up their investment in Youtube advertising as traditional cable models phase out.

IN-GAME ADVERTISING

Just over 50% of global revenue in the gaming industry is driven by mobile games. With gaming reaching a growth rate higher than all other entertainment industries, brands are looking to in-game advertising as a way of reaching a larger audience.

The gaming demographic has recently reached a 50-50 split between men and women. Contrary to most preconceptions, in-game advertising will help you reach a wider audience of both men and women. In-game advertising not only reaches a wider audience, it makes it easy to track click-throughs and analytics. Extensive analytics enable brands to collect very precise data about their customers and foster a deeper understanding of their habits.

Playable ads have arisen as a major hallmark for brands to market their games. Playable ads are interactive and encourage the user to try a snippet of functionality from the game. Check out the examples in the video below by Vungle.

CONCLUSION

Brands need to move as fast as the times if they hope to stay on the forefront of their industry. In the era of big data, the bigger your brand, the more possibilities digital marketing entails. As AI becomes more accessible, businesses of all sizes are wise to take advantage of the digital landscape and find ways to offer a more personal experience for their customers.

How Apple & Google Are Enhancing Battery Life and What We as App Developers Can Do to Help

March 7, 2022Android Development, iOS DevelopmentAndroid, Apple, Application, Battery, Developer, Development, Device, Google, Graphene, Guide, Hardware, IOS, Lithium, Optimization, Software, Trend, Wake Lockadmin

In 1799, Italian physicist Alessandro Volta created the first electrical battery, disproving the theory that electricity could only be created by human beings. Fast forward 250 years, brands like Duracell and Energizer popularized alkaline batteries—which are effective, inexpensive and soon become the key to powering household devices. In 1991, Sony released the first commercial rechargeable lithium-ion battery. Although lithium-ion batteries have come a long way since the 90s, to this day they power most smartphones and many other modern devices.

While batteries have come a long way, so have the capabilities of the devices which need them. For consumers, battery life is one of the most important features when purchasing hardware. Applications which drain a device’s battery are less likely to retain their users. Software developers are wise to understand the latest trends in battery optimization in order to build more efficient and user-friendly applications.

HARDWARE

Lithium-ion batteries remain the most prevalent battery technology, but a new technology lies on the horizon. Graphene batteries are similar to traditional batteries, however, the composition of one or both electrodes differ. Graphene batteries increase electrode density and lead to faster cycle times as well as the ability to improve a battery’s lifespan. Samsung is allegedly developing a smartphone powered by a graphene battery that could fully charge its device within 30 minutes. Although the technology is thinner, lighter, and more efficient, production of pure graphene batteries can be incredibly expensive, which may inhibit its proliferation in the short-term.

Hardware companies are also coming up with less technologically innovative solutions to improve battery life. Many companies are simply attempting to cram larger batteries into devices. A more elegant solution is the inclusion of multiple batteries. The OnePlus 9 has a dual cell battery. Employing multiple smaller batteries means both batteries charge faster than a single cell battery.

SOFTWARE

Apple and Google are eager to please their end-users by employing techniques to help optimize battery life. In addition, they take care to keep app developers updated with the latest techniques via their respective developer sites.

Android 11 includes a feature that allows users to freeze apps when they are cached to prevent their execution. Android 10 introduced a “SystemHealthManager” that resets battery usage statistics whenever the device is unplugged, after a device is fully charged or goes from being mostly empty to mostly charged—what the OS considers a “Major charging event”.

Apple has a better track record of consuming less battery than Android. iOS 13 and later introduced Optimized Battery Charging, enabling iPhones to learn from your daily charging routine to improve battery lifespan. The new feature prevents iPhones from charging up to 100% to reduce the amount of time the battery remains fully charged. On-site machine learning then ensures that your battery is fully charged by the time the user wakes up based on their daily routines.

Apple also offers a comprehensive graph for users to understand how much battery is being used by which apps, off screen and on screen, under the Battery tab of each devices Settings.

WHAT APPLICATION DEVELOPERS CAN DO

App developers see a 73% churn rate within the first 90 days of downloading an app, leaving very little room for errors or negative factors like battery drainage. There are a number of techniques application developers can employ in their design to reduce and optimize battery-intensive processes.

It’s vital to review each respective app store’s battery saving standards. Both Android and Apple offer a variety of simple yet vital tips for reducing battery drain—such as limiting the frequency that an app asks for a device’s location and inter-app broadcasting.

One of the most important tips is to reduce the frequency of network refreshes. Identify redundant operations and cut them out. For instance, can downloaded data be cached rather than using the radio repeatedly to re-download it? Are there tasks that can be deferred by the app until the device is charging? Backing up data to the cloud can consume a lot of battery on a task that is not always time sensitive.

Wake locks keep the phone’s screen on when using an app. There was a time where wake locks were frequently employed—but now it is frowned upon. Use wake locks only when absolutely necessary—if at all.

CONCLUSION

Software developers need to be attentive to battery drain throughout the process of building their application. This begins at conception, through programming, all the way into a robust testing process to identify potential battery drainage pitfalls. Attention to the details of battery optimization will lead to better, more user-friendly applications.

Part 3: Techniques to Keep Users Coming Back & Increase Retention

February 8, 2022Android Development, Gaming & Monetization Strategies, iOS DevelopmentApplication, Content, Design, Development, Feature, Follow, Friend, Gamification, Notification, Push, Retention, Social, Software, Updateadmin

How Gamification Can Boost Retention on Any App Part 3: Techniques to Keep Users Coming Back & Increase Retention

The Mystic Media Blog is currently endeavoring on a 3 part series on how gamification mechanics can boost retention on any app—not just gaming apps but utility apps, business apps and more. In this third entry, we explore additional techniques to keep users coming back and increase retention.

Your users have downloaded your app and are acclimated with its features. You’ve perfected your core loop to ensure users can complete meaningful actions in the app on a daily basis. Now the question becomes—how can you retain ongoing usage? The average cost to acquire a mobile app user is $4, yet retention rates can quickly drop from there. Statistics show that a 5% increase in retention can boost profitability by up to 75%.

There are a variety of techniques employed by mobile games that app developers can use in their non-gaming apps to keep users engaged long after the application ends.

INVEST IN THE FUTURE

An optimized application development process requires thinking about how your product can evolve beyond the initial release. Often this is due to schedule and budgetary constraints. It is natural in any creative endeavor to have more ideas than time and money to complete them. However, thinking long-term can be an advantage. New features entice users to continue using the application after download and to allow push notifications for fear of missing out on updates.

Mobile games often have to confront this since the amount of content they offer is finite—a certain amount of levels, achievements, and unlockables which can be completed. Games can offer additional modes and levels to entice users to come back. Similarly, non-gaming apps can offer new content—such as informative blogs, new features, and new product lines.

During the development process, plan out multiple phases and deliver new features and content updates on a regular basis. If you have a blog, host it on your application and keep users coming back for content updates.

IMPLEMENT SOCIAL FEATURES

Game developers know that “Socializers”, or users who thrive on social interaction, constitute one of the most important Bartle Types. Social features are crucial not only to retaining interest and daily usage of an application, but as a marketing technique to encourage users to engage with one another and spread the word. Once your userbase is established, implementing social features will increase engagement.

Consider implementing the following social features in phase 2 of your application:

Customizable user profiles: Enabling usernames, profile pictures, bios and other user customization features help users feel more connected to the app vis a vis their profile.
Rewarded social sharing: Encourage users to spread the love by rewarding them with discounts and reward points when they share to social media.
Likes and comments on products: Implementing comments and likes not only gives users another avenue for engagement, it creates a platform for automated push notifications that will likely result in more daily opens.
Follow and friend other users: Allowing users to connect can result in meaningful social relationships which will increase their connection with your application.
Rewarded actions: Encourage users to complete an action for the first time by offering them some kind of reward.

PUSH NOTIFICATIONS STRATEGY

Push notifications are integral to every app developers’ retention strategy. They are the most effective vessel for delivering timely reminders and relevant notifications about new features on applications. Users can disallow push notifications at any time, so developers need to pick their spots or risk losing one of their most prized tools.

When developing your push notification strategy, consider the following:

Timing: Rather than sending push notifications all at once, target users based on their time zone. Make sure the timing of your notifications makes sense based on the message.
Personalization: Optimize UI by tracking app usage data and leveraging it for personalized push notifications. Personalize push notifications based on a user’s behavior such as their purchase history to help build app loyalty and keep notifications relevant.
Prudence: If you bombard users with irrelevant notifications, the decision to unsubscribe to push notifications becomes easy. Exercise restraint when sending push notifications and only send valuable information and reminders.

Users are always looking for value and discount—which is why delivery and transportation applications often use push notifications to send discount codes. Shopping apps can also send push notifications which notify users when they have items left in their cart—a timely prompt to finish the purchase can directly lead to revenue.

KEEP INNOVATING

The app development process does not have to end with an apps initial release into app stores. Rolling out new features to maintain engagement with your audience and bolster your application will result in improved retention.

Part 2: Optimize Onboarding with Gamification

January 19, 2022Android Development, Gaming & Monetization Strategies, iOS DevelopmentAndroid, App, Application, Business, Design, Development, Experience, Gamification, Gaming, Interface, IOS, Mechanics, Mobile, Onboarding, Registration, Software, Tutorial, UI, User, UXadmin

How Gamification Can Boost Retention on Any App Part 2: Optimize Onboarding with Gamification

The Mystic Media Blog is currently endeavoring on a 3 part series on how gamification mechanics can boost retention on any app—not just gaming apps but utility apps, business apps and more. In this second entry, we explore how to refine and gamify your onboarding process to keep customers coming back.

ONBOARDING

Your app has been downloaded—a hard-fought battle in and of itself—but the war isn’t over; the onboarding process has just begun.

App onboarding is the first point of contact a user has within an application. It’s one of the most crucial parts of the user experience. Situating users in your application is the first step to ensuring they come back. Twenty-five percent of apps are only opened once after being downloaded. Many apps simply do not make it simple enough for users to understand the value and get the hang of the application—step one in your retention process.

Here are the top tips for smooth onboarding:

MINIMIZE REGISTRATION

A prolonged registration process can turn off new users. Users do not always have time to fill out extensive forms and can quickly become resentful of the pacing of your app. Keep registration to a minimum, minimize required fields, and get users going faster.

We recommend enabling user registration altogether with “Continue as Guest” functionality. Games typically employ this and it enables users to get hands on with the application before they undergo the tenuous account creation process. Hook them with your app, then let them handle the administrative aspects later. Account creation with Google, Facebook, or Twitter can also save quite a bit of time.

Gamification is all about rewarding the user. Offer users an incentive to create their account to positively reinforce the process and you will see more accounts created. If they haven’t created an account, make sure to send prompts to remind them of what the reward they are missing out on. As we detailed in our last entry, FOMO is a powerful force in gamification.

TUTORIAL BEST PRACTICES

When a user enters your application for the first time, they generally need a helping hand to understand how to use it. Many games incorporate interactive tutorials to guide the user through functionality—and business apps are wise to use it as well. However, an ineffective tutorial will only be a detriment to your application.

Pacing is key. A long tutorial will not only bog the onboarding process down, too much information will likely go in and out of the user’s brain. Space your tutorial out and break it into different sections introducing key mechanics as they become relevant. On-the-go tutorials like the four-screen carousel below by Wavely help acclimate users quickly and easily.

And don’t forget to offer a reward! Offer users some kind of reward or positive reinforcement upon completing tutorials to encourage them to continue using the application.

AVOID DEAD ENDS AND EMPTY STATES

An empty state is a place in an application that isn’t populated with any information. For example, favorites, order history, accomplishments, etc.—these pages require usage in order to be populated for information. New users will see these pages and become confused or discouraged. Many applications will offer self-evident statement such as “No Favorites Selected”. Or, in the case of UberEats below, no message is displayed.

It’s confusing and discouraging for users to see these statements. Avoid discouraging your users by offering more information, for example: “Save your favorite restaurants and find them here.” Check out Twitter’s exemplary message for users who’ve yet to favorite a tweet below.

CONCLUSION

Onboarding is the first and most crucial step to building a relationship with your userbase. One of the major things business apps can learn from gaming apps is that time is of the essence when it comes to capturing a user’s attention. Keep it short, punchy, and to the point.

How Gamification Can Boost Retention on Any App Part 1: The Starbucks Test and Appointment Mechanics

December 7, 2021Android Development, Gaming & Monetization Strategies, iOS DevelopmentAndroid, App, Appointment, Badge, Bonus, Business, Currency, Development, Discount, Gamification, Gaming, IOS, Login, Mechanics, Mobile, Monetization, Retention, Rewards, Software, Starbucks, System, Testadmin

When creating any application, retention is a vital part of ensuring users are engaged and continuing to use the app months and years after downloading. Mobile games have been on the forefront of developing advanced retention mechanics, but regardless of whether your app is a game or serves an entirely different purpose, retention is the key to enriching your app’s relationship with its customers and engraining usage into the user’s life.

With that in mind, the Mystic Media Blog will endeavor on a 3 part series on how gamification mechanics can boost retention on any app—not just gaming apps but utility apps, business apps and more. In this first entry, we will explore how appointment mechanics can boost engagement and the importance of passing the Starbucks Test.

THE STARBUCKS TEST

Can your users have a meaningful experience with your application in the time it takes for a barista to make a caramel machiatto—roughly two minutes? That’s the challenge that Nicolas Lovell and other app developers put forth known as The Starbucks Test. We’ve covered it previously in several of our blogs on Gaming and Monetization strategies.

The goal of the Starbucks Test is to encourage users to use the application at any point in their day. When an application becomes a regular part of a user’s life, it puts game developers in the catbird seat to extract revenue through ads and/or in-app purchases. For business apps, it means users are going to be familiar with the app’s interface and ready to use it when they need it most.

With the firm goal of adding features which will pass the Starbucks Test in mind, the question becomes: What can your app offer users within 2 minutes?

The answers vary wildly depending on the application. Some mobile games are designed for the user to complete a full core loop within the Starbucks Test, while others offer side tasks which can be swiftly completed. Shopping applications can prompt users to view new products and time-sensitive price updates while business apps can offer short informative articles or reward users for completing their profile on the app. The key is to not only put forth an action that can be completed swiftly, but to offer users something in exchange for the user’s actions.

CREATE A REWARD SYSTEM

In order to gamify an app, you need to not only create tasks but incentivize the user to complete them by offering some kind of reward. For games, this is easy as almost all games incorporate some kind of level or point system. For non-gaming apps, you have to get creative. Consider these three common rewards:

Discounts: Offer a direct discount for services, products, or in-app purchases in exchange for completing an action in the application. Discounts that are time-sensitive will add urgency and create FOMO (Fear of Missing Out). Many apps offer some type of discount in exchange for providing reviews on app stores.
In-App Currency: Offer an in-app currency reward for completing an action in the application. For example, loyalty points help keep customers engaged and incentivize them to shop with you. The Starbucks app employs a profuse gamification strategy using it’s loyalty point program on their mobile app.
Badges: Some apps employ badge systems to great effect. For example, Alamo Drafthouse patrons receive credit toward a badge system every time they visit the theater. Badges give users the feeling of status and strengthen a user’s identification with brands while incentivizing them to continue using the app to attain new badges.

APPOINTMENT MECHANICS

Once you have a rewards system, the time comes to create tasks that can be completed on a daily basis without infringing on the user’s time. Many mobile games use appointment mechanics—a concept that can extend beyond the gaming sphere. Appointment mechanics are time-based incentives that reward users and create FOMO. If the user does not complete the action in time, they miss out on a reward.

Often appointment mechanics refresh after a specific time interval—hourly, daily, weekly, etc. One commonly used appointment mechanic is a daily login bonus. All the user has to do is login to receive a reward—be it loyalty points or in-app currency. Take it a step further, and you can offer consecutive daily bonuses which accrue as the user completes daily logins. Consecutive daily bonuses can be applied to any action—for example, rewarding users with double loyalty points for using your app to order a product or service on consecutive days.

Mindfulness apps like Headspace take appointment mechanics to the next level by asking the user when they’d like to be reminded to use the app on a daily basis. These regularly refreshing mechanics keep a fresh reward in front of users at all times.

In our next entry, we will explore optimizing the onboarding process to foster long-term relationships with your users.

HL7 Protocol Enhances Medical Data Transmissions–But Is It Secure?

August 31, 2021HealthcareClinical, Data, Developer, Health, Healthcare, HL7, Medical, Protocol, security, Software, Technology, Vulnerabilityadmin

In our last blog, we examined how DICOM became the standard format for transmitting files in medical imaging technology. As software developers, we frequently find ourselves working in the medical technology field navigating new formats and devices which require specialized attention.

This week, we will jump into one of the standards all medical technology developers should understand: the HL7 protocol.

The HL7 protocol is a set of international standards for the transfer of clinical and administrative data between hospital information systems. It refers to a number of flexible standards, guidelines, and methodologies by which various healthcare systems communicate with each other. HL7 connects a family of technologies, providing a universal framework for the interoperability of healthcare data and software.

Founded in 1987, Health Level Seven International (HL7) is a non-profit, ANSI-accredited standards developing organization that manages updates of the HL7 protocol. With over 1,600 members from over 50 countries, HL7 International represents brain trust incorporating the expertise of healthcare providers, government stakeholders, payers, pharmaceutical companies, vendors/suppliers, and consulting firms.

HL7 has primary and secondary standards. The primary standards are the most popular and integral for system integrations, interoperability, and compliance. Primary standards include the following:

Version 2.x Messaging Standard–an interoperability specification for health and medical transactions
Version 3 Messaging Standard–an interoperability specification for health and medical transactions
Clinical Document Architecture (CDA)–an exchange model for clinical documents, based on HL7 Version 3
Continuity of Care Document (CCD)–a US specification for the exchange of medical summaries, based on CDA.
Structured Product Labeling (SPL)–the published information that accompanies a medicine based on HL7 Version 3
Clinical Context Object Workgroup (CCOW)–an interoperability specification for the visual integration of user applications

While HL7 may enjoy employment worldwide, it’s also the subject of controversy due to underlying security issues. Researchers from the University of California conducted an experiment to simulate an HL7 cyber attack in 2019, which revealed a number of encryption and authentication vulnerabilities. By simulating a main-in-the-middle (MITM) attack, the experiment proved a bad actor could potentially modify medical lab results, which may result in any number of catastrophic medical miscues—from misdiagnosis to prescription of ineffective medications and more.

As software developers, we advise employing advanced security technology to protect patient data. Medical professionals are urged to consider the following additional safety protocols:

A strictly enforced password policy with multi-factor authentication
Third-party applications which offer encrypted and authenticated messaging
Network segmentation, virtual LAN, and firewall controls

While HL7 provides unparalleled interoperability for health care data, it does not provide ample security given the level of sensitivity of medical data—transmissions are unauthenticated and unvalidated and subject to security vulnerabilities. Additional security measures can help medical providers retain that interoperability across systems while protecting themselves and their patients from having their data exploited.

Top Mobile Marketing Trends Driving Success in 2021

March 16, 2021Android Development, Digital Marketing, iOS Development6 second ads, Ads, App, Bidding, Install, Mobile, Playable, Real-Time, Retention, Rewarded, ROI, Short, Software, Waterfalladmin

Mobile app marketing is an elusive and constantly evolving field. For mobile app developers, getting new users to install games is relatively cheap at just $1.47 per user, while retaining them is much more difficult. It costs on average $43.88 to prompt a customer to make an in-app purchase according to Liftoff. An effective advertising strategy will make or break your UI—and your bank. In 2019, in-game ads made up 17% of all revenue. By 2024, that number is expected to triple.

2020 was a year that saw drastic changes in lifestyle—mobile app users were no exception. What trends are driving app developers to refine their advertising and development tactics in 2021? Check out our rundown below.

Real Time Bidding

In-app bidding is an advanced advertising method enabling mobile publishers to sell their ad inventory in an automated auction. The technology is not new—it’s been around since 2015 when it was primarily used on a desktop. However, over the past few years, both publishers and advertisers have benefited from in app-bidding, eschewing the traditional waterfall method.

In-app bidding enables publishers to sell their ad space at auction. Advertisers simultaneously bid against one another. The dense competition enables a higher price (CPM) for publishers. For advertisers, bidding decreases fragmentation between demand sources since they can bid on many at once. In the traditional waterfall method, ad mediation platforms prioritize ad networks they’ve worked with in the past before passing it on the premium ad networks. In-app bidding changes the game by enabling publishers to offer their inventory to auctions which include a much wider swath of advertisers beyond the traditional waterfall.

Bidding benefits all parties. App publishers see increased demand for ad inventory, advertisers access more inventory, and app users see more relevant ads. In 2021, many expect in-app bidding to gain more mainstream popularity. Check out this great rundown by AdExchanger for more information on this exciting new trend.

Rewarded Ads Still King

We have long championed rewarded ads on the Mystic Media blog. Rewarded ads offer in-game rewards to users who voluntarily choose to view an ad. Everyone wins—users get tangible rewards for their time, publishers get advertising revenue and advertisers get valuable impressions.

App usage data from 2021 only increases our enthusiasm for the format. 71% of mobile gamers desire the ability to choose whether or not to view an ad. 31% of gamers said rewarded video prompted them to browse for products within a month of seeing them. Leyi Games implemented rewarded video and improved player retention while bringing in an additional $1.5 million US.

Facebook’s 2020 report showed that gamers find rewarded ads to be the least disruptive ad format, leading to longer gameplay sessions and more opportunities for content discovery.

Playable Ads

Playable ads have emerged as one of the foremost employed advertising tactics for mobile games. Playable ads enable users to sample gameplay by interacting with the ad. After a snippet of gameplay, the ad transitions into a call to action to install the game.

The benefits are obvious. If the game is fun and absorbing to the viewer, it has a much better chance of getting installed. By putting the audience in the driver’s seat, playable ads drive increased retention rates and a larger number of high lifetime value (LTV) players.

Check out three examples of impactful playable ads compiled by Shuttlerock.

Short Ads, Big Appeal

As we are bombarded with more and more media on a daily basis, finding a way to deliver a concise message while cutting through the clutter can be exceptionally difficult. However, recent research from MAGNA, IPG Media Lab, and Snap Inc. shows it may be well worth it.

Studies show short-form video ads drive nearly identical brand preference and purchase intent as 15 second ads. Whereas short form ads were predominantly employed to grow awareness, marketers now understand that longer ads are perceived by the user as more intrusive, and they can get just as much ROI out of shorter and less expensive content.

Check out the graph below, breaking down the efficacy of 6 second vs. 15 second ads via Business of Apps.

Conclusion

Mobile advertisers need to think big picture in terms of both their target customer and how they format their ads to best engage their audience. While the trends we outlined are currently in the zeitgeist, ultimately what matters most is engaging app users with effective content that delivers a valuable message without intruding on their experience on the app.

For supplementary reading on mobile marketing, check out our blog on the Top Mobile Ad Platforms You Need to Know for 2021

How to Optimize GPS and Background Processes for Android Oreo

May 10, 2018Android DevelopmentAndroid, Android O, API, App, Background Processes, Battery, Developer, Geolocation, GPS, How To, Location, Location Services, Notifications, Oreo, OS, Programming, Softwareadmin

As our past article Android Oreo Serves Up the Sweets will show, Android Oreo lived up to expectations upon release and gave both consumers and app developers plenty of enhancements to enjoy.

However, for app developers, enhancements to the UI aimed to conserve battery life affect GPS services and require changes to the code in order to optimize pre-existing apps for the new OS. Specifically, Android Oreo restricts apps that are running in the background with limited access to background services. Additionally, apps can no longer use their manifests to register for most implicit broadcasts. When an app is in the background, it is given several minutes to create and use services, but at the end of that time slot, the app is considered idle and the OS will stop running background services.

These changes directly affect apps with geolocation functionality. Android Oreo limits how frequently apps can gather location in the background. Background apps can only receive location updates a few times each hour. The APIs affected due to these limits include Fused Location Provider, Geofencing, Location Manager, Wifi Manager, GNSS Measurements and GNSS Navigation Messages.

Apps that currently use location services in previous Android OS’s will require an update to optimize for Android Oreo. Apps that use location services range anywhere from navigational apps like Waze and Google Maps to social media apps like Twitter, and food apps like Yelp and Seamless.

For apps that require frequent location updates, increasing the usage of the app in the foreground will ensure that the app gets frequent access to location information. In order to program this, developers must implement startServiceinForeground() instead of startService() in Activity class.

In Service class in onStartCommand(), developers can use the following code:

Via StackOverflow

When foreground services running in the background consume high energy, Oreo fires an automatic push notification to the user informing them of the battery-consuming service. With the push notification in place, app users are more likely to uninstall apps that track location without conserving battery life, putting the onus on software developers to deliver battery-efficient apps. One of the biggest issues facing some app developers is ensuring that battery life is not sucked as a result of tracking location in apps. Check out our full rundown of how to build battery-efficient geolocation apps for supplementary reading.

The results of the limits put in place with Android O are increased battery life for the user and the necessity for app owners to consider how their apps interact with location information. Retaining a thorough understanding of how location information will be retrieved and used through out the development process ultimately benefits both software developers and consumers with better UI and more energy efficient processes.