Tag Archives: Mobile

The Real Power of Artificial Intelligence

Technological innovations expand the possibilities of our world, but they can also shake-up society in a disorienting manner. Periods of major technological advancement are often marked by alienation. While our generation has seen the boon of the Internet, the path to a new world may be paved with Artificial Intelligence.

WHAT IS ARTIFICIAL INTELLIGENCE

Artificial intelligence is defined as the development of computer systems to perform tasks that normally require human intelligence, including speech recognition, visual perception, and decision-making. As recently as a decade ago, artificial intelligence evoked the image of robots, but AI is software not hardware. For app developers, the modern-day realization of artificial intelligence takes on a more amorphous form. AI is on all of your favorite platforms, matching the names and faces of your friends. It’s planning the playlist when you hit shuffle on Apple Music. It’s curating the best Twitter content from you based on data-driven logic that is often too complex even for the humans who programmed the AI to decipher.

MACHINE LEARNING

Currently, Machine Learning is the primary means of achieving artificial intelligence. Machine Learning is the ability for a machine to continuously improve its performance without humans having to explain exactly how to accomplish all of the tasks it has been given. Web and Software programmers create algorithms capable of recognizing patterns in data imperceptible to the human eye and alter their behavior based on them.

For example, Google’s autonomous cars view the road through a camera that streams the footage to a database that centralizes the information of all cars. In other words, when one car learns something—like an image or a flaw in the system—then all the cars learn it.

For the past 50 years, computer programming has focused on codifying existing knowledge and procedures and embedding them in machines. Now, computers can learn from examples to generate knowledge. Thus, Artificial Intelligence has already permanently disrupted the standard flow of knowledge from human to computer and vice versa.

PERCEPTION AND COGNITION

Machine learning has enabled the two biggest advances in artificial intelligence:  perception and cognition. Perception is the ability to sense, while cognition is the ability to reason. In a machine’s case, perception refers to the ability to detect objects without being explicitly told and cognition refers to the ability to identify patterns to form new knowledge.

Perception allows machines to understand aspects of the world in which they are situated and lays the groundwork for their ability to interact with the world. Advancements in voice recognition have been some of the most useful. In 2007, despite its incredibly limited functionality, Siri was an anomaly that immediately generated comparisons to HAL, the Artificial Intelligence in 2001: A Space Odyssey. 10 years later, the fact that iOS 11 enables Siri to translate French, German, Italian, Mandarin and Spanish is a passing story in our media lifecycle.

Image recognition has also advanced dramatically. Facebook and iOS both can recognize your friends’ faces and help you tag them appropriately. Vision systems (like the ones used in autonomous cars) formerly made a mistake when identifying a pedestrian once in every 30 frames. Today, the same systems err less than once in 30 million frames.

EXPANSION

AI has already made become a staple of mainstream technology products. Across every industry, decision-making executives are looking to capitalize on what AI can do for their business. No doubt whoever answers those questions first will have a major edge on their competitors.

Next week, we will explore the impact of AI on the Digital Marketing industry in the next installment of our blog series on AI.

How To Design Battery-Efficient Geolocation Apps

The ability for smartphones to offer location services fostered major opportunities for app developers looking to create new apps and enhance functionality of existing apps. Tinder, FourSquare, & Waze use geolocation in the center of their functionality to great success. In combination, these three apps can help a user determine a dinner companion, restaurant of choice, and route to the restaurant. By delivering location-sensitive information to users regardless of where they are in the country, these apps appeal to massive audiences.

Programming geolocation services into an app will have a major impact on the overall quality of the app—and it’s easier said than done. Inefficient geolocation services drain device battery life and deliver inaccurate location data. When apps drain battery life, users uninstall them. In order to determine the best method of programming geolocation services, it is vital for app developers to know who is going to be using the app and how they are going to use it.

Location can be determined by a smartphone in a number of ways. The most widespread include:

GPS: All modern iOS & Android smartphones are equipped with GPS technology. GPS can use at least four satellites to determine a user’s location within about 60 feet.

Cell ID: When GPS isn’t available, phones can use Cell ID, information from cellular towers, to determine location. Cell ID is ideal in big cities with vast amounts of cell towers. Serial fans should be familiar with how cellular tower information can be vital in identifying one’s location. GPS & Cell ID can also work in conjunction to deliver a more precise GPS location.

Wi-Fi: Devices can detect Wi-Fi networks in the same way they can detect cellular towers, but Wi-Fi is more precise as Wi-Fi networks cover smaller regions. Devices can use RSSI (Received Signal Strength Indication) to refer signals from the phone with Wi-Fi points database. Devices can also use the user’s frequently visited places, a profile or wireless fingerprint based on locations in Wi-Fi networks frequented by the user. Wi-Fi can identify a user’s position within 2 meters of accuracy.

The decision of how an app should prioritize these three methods to determine location is a vital one. If users are located in the city, that means both dense Wi-Fi router and cell tower coverage will open up options. If the app is being used primarily in a domestic situation, Wi-Fi might be both the most accurate and efficient method. Apps designed for rural areas may have to use Wi-Fi due to lack of cell towers.

Geofencing Graphic from Applidium

GEOFENCING

Geofencing utilizes a device’s GPS to determine a user’s distance from a particular point. Geofencing can sense when a user enters within a set radius defined by the coordinates of its center. Geofencing will sense when users are inside or outside of a retailer and offer action prompts for either space. There are three types of geofencing:

Static geofencing is based on a user’s position in relation to a specific place. For example, a retailer app sends a message to users who pull into the parking lot of a mall containing the retailer.

Dynamic geofencing takes into account both a user’s location and a changing data stream. For example, a parking app sends the user a message about a recently evacuated parking space that the user is approaching.

Combined geofencing determines when a user enters into a location in relation to other users. For example, apps like Yelp, Facebook, or FourSquare send notifications if a friend checks into a nearby merchant .

CREATING BATTERY-EFFICIENT APPLICATIONS

Making a geolocation app battery-efficient is one of the biggest challenges  app developers face in the programming stage. Developers must create a comprehensive strategy based on their audience.

ACTION THRESHOLDS: Defining accurate action thresholds and use-cases for an app’s geolocation services will dictate its level of battery-efficiency. The more precise your location accuracy requirements, the greater the battery drain. Action thresholds and use-cases define how an app is intended to be used, allowing a framework for developers to enact an efficient model of internal processes for location determination.

COMPREHENSIVE TESTING: Testing the app aggressively to gather a large amount of data is the only way to know the most efficient action thresholds. The more the developer understands how an app is being used, the more they can refine their programming. After release, continuing to gather analytics from user behavior and refine tactics based on how users are getting value from the app becomes a crucial ongoing process.

POLLING FREQUENCY: One of the major variables dictated by action thresholds is polling frequency. The more an app polls for locations, the better its location accuracy. The necessary level of location accuracy varies depending on the app. The precision of location accuracy necessary for an app to be functional can vary. A restaurant app, for example, might be able to get away with accuracy from 200 meters to a few kilometers, while an app that locates friends might need accuracy within 10 – 20 meters.

Evaluating the most efficient polling frequency requires thorough use-cases and some creativity. Programmers can design algorithms to reduce polling frequency if an app hasn’t changed locations for several minutes. Programmers can also analyze the speed of the device and use this data to change polling frequencies. A developer may elect to increase polling frequency as a car accelerates to ensure they maintain location accuracy within a selected radius.

DEFERRING TO OS: Many major mobile platforms will share geolocation information at an operating system level. As a result, any app that is listening can receive location updates requested by other apps. By deferring to other apps already polling for location data, apps can minimize battery drain while still retaining acceptable location data.

Check out Apple and Android’s developers’ sites for more information on best practices for programming location services.

Everything You Need to Know About Machine Learning

A calculator can solve complex problems which would take even the most savvy mathematicians an incomparable amount of time. Artificial intelligence has become one of the most hotly debated and highly funded aspects of technology because the speed at which machines can process information yields innumerable possibilities and applications which can and will benefit humanity. One of the first popular incarnations of AI is Machine Learning.

Machine Learning is the ability for a computer to learn without being explicitly programmed. Machine learning focuses on computer programs which can identify patterns and create its own algorithms when exposed to new data. It is used in self-driving cars, in newsfeed algorithms on social media, in evaluating job candidates, in recognizing faces on your phone, and more.

The most powerful form of machine learning currently active is called “deep learning”. “Deep learning” builds a complex mathematical structure known as a neural network out of vast quantities of data. Machine learning’s ability to handle mass amounts of data makes it crucial to the advancement of IoT. The IoT collects enormous amounts of data which require computers with machine learning to recognize patterns and create algorithms.  In self-driving cars, IoT cameras and sensors in each autonomous vehicle absorb their surroundings and turn them into huge amounts of data. The data is then sent to the cloud where it is accessible to all autonomous vehicles on the road. Thus, when one self-driving car makes a mistake, all of them learn. In conjunction with the Internet of Things, machine learning will be vital to the building of a smartworld.

TOP PROGRAMMING LANGUAGES

Machine learning requires a great deal of statistical analysis; it demands an intelligent programming language which can process a number of complex issues and general paradigms.

R: Considered a statistical workhorse, R has emerged as one of the top programming languages for machine learning. R is intended for advanced users because of its complex nature and wide learning curve.

Python: A rising star for machine learning, Python is a data science book which has been in use in the manufacturing industry for awhile. Python gives users direct access to predictive analytics, making it the foremost data science language. Developers turn to Python when they are looking to frame better questions or expand the capabilities of their existing machine learning systems.

MATLAB/Octave: Millions of engineers are already using MATLAB, a matrix-based language, to analyze and develop cutting edge systems. MATLAB has emerged as the simplest way to demonstrate computational mathematics.

MACHINE LEARNING AND iOS 10

Machine learning laid much of the groundwork for the biggest upgrade in iOS 10. It is very difficult for computers to comprehend the intricacies of the human language. Machine learning has enabled iPhones to sense contextual clues with increasing confidence, improving iMessage’s ability to autocorrect and for Siri to understand the particulars of your vernacular. In the iPhone 7 camera, machine learning allows the device to separate the background from the foreground to achieve amazing portraits once possible only with DSLR cameras.

MACHINE LEARNING AND ANDROID

Google is among the dominant forces in machine learning. Much of Google Search’s prominence is owed to advances in the machine learning field. In November 2015, Google released TensorFlow, an open-source software library for machine intelligence. TensorFlow effectively simulates “deep learning” neural networks across different computer hardware and offers a straightforward way for users to train computers to perform tasks by feeding them large amounts of data.

Google uses Tensorflow in many of their internal processes, including RankBrain for information retrieval, image classification, SmartReply, and more.

MAXIMIZING MACHINE LEARNING IN MOBILE APPS

Now that mobile devices have the high productive capacity level to perform tasks to the same degree as a traditional computer, the question of what machine learning can offer apps has arisen. Large retailers like Amazon and eBay use machine learning in their mobile apps to improve customer experience with smarter product search and recommendation features, along with the ability to forecast buying trends with analytics.

While Machine Learning algorithms require a high level of programming experience and a ton of data to be effective, integrating apps with Siri & iMessage for iOS 10 allows developers to take advantage of the vast deep learning neural networks embedded into Apple’s 1st-party apps.

While the future of machine learning  on a commercial level remains to be seen outside of tech titans like Facebook, machine learning algorithms will be crucial in conjunction with the IoT in building a new SmartWorld with unparalleled predictive capabilities.

How Mobile Commerce Is Changing Retail Sales

Smartphones have brought about unparalleled convenience in our daily lives. We are constantly connected to our rolodex of contacts with a variety of methods of communication. We can access all the information available on the world wide web anytime. Consumers looking to make purchases on the go can find the nearest store with ease. For businesses, the mobile platform represents not only a major avenue for advertising, but an opportunity to give customers the ultimate convenience when purchasing products.

According to Internet Retailer, mobile commerce represents 30% of all US e-commerce and rose by 38.7% from 2014 to 2015. Mobile commerce drives sales, and businesses lacking a mobile strategy are missing out on a major opportunity to increase revenue. Here are the top mobile commerce trends for 2016:

INTEGRATING PHYSICAL WITH DIGITAL

Although the digital world is virtually omnipresent in households, the appeal of immediately receiving one’s purchases by shopping in store remains attractive. Retailers are increasingly offering a variety of online + in-store options to capitalize on the convenience of digital and the immediacy of making a physical purchase.

Apps like Curbside have partnered with Target & Kroger’s to enable customers to reserve their purchases and skip the line when picking up products.

Beacon-enabled features like geo-targeted offers and loyalty rewards are becoming more and more popular. Geo-targeted offers can drive in-store traffic when delivered effectively. According to Target Marketing Magazine, 85 of the top 100 retailers are planning to adopt beacon technology by the end of 2016. Business Insider has predicted beacons will directly influence over $44 billion in US retail sales in 2016.

PERSONALIZED MOBILE PAYMENTS DRIVE LOYALTY

Although services such as Apple Pay and Android Pay were once hailed as the future, they have had a hard time receiving mass adoption. While mobile payment services haven’t gained popularity, the mobile wallet has made a major impact on commerce. Starbucks drives 16% of transactions through its mobile app. Walmart Pay arrived in December 2015, and now Target is next in line to develop their own payment app.

WEARABLES ON THE RISE

According to Arc, there will be a 61% growth in wearable ownership in 2016. App developers and retailers are still plotting on how to capitalize on wearables. Many anticipate a hands-free shopping experience in which one can simply walk out with their purchases and have automatic charges through wearable devices. Malls and large stores like Walmart may use wearables to make it easier for consumers to navigate stores. Wearables represent a major avenue for retailers to create innovative strategies and dictate trends to come.

THE MOBILE WEB DRIVES PURCHASES

While about 85% of time spent on mobile devices occurs in apps, the mobile web has actually proven to be a more successful in driving website traffic. While app usage is prevalent, consumers spend 80% of their app time on their top 3 apps. The mobile web drives twice the amount of site traffic than mobile apps. With 82% of smartphone users looking to their phones in stores when deciding what to buy, many anticipate the mobile web to surpass apps as the largest revenue driver in the next few years.

HOW CAN MOBILE COMMERCE HELP YOUR BUSINESS?

With technology in constant flux, the potential to drive revenue with a refined mobile strategy is constantly growing. Mobile strategies must be created, enacted and reevaluated with every new OS and device. Mobile is an ongoing investment. Understanding the value of a mobile strategy and how each device can enrich a customer’s interaction with your business will lead to long-term revenue growth.

5 Essential Mobile Game Monetization Strategies to Keep Your Pockets Full

A recent study by Venture Beat showed that less than 1% of mobile game players contribute 48% of total revenue to game publishers. Inability to effectively capitalize upon this hyper-concentrated group of revenue drivers leaves many mobile game developers in the red. The rise of the Freemium model has essentially killed the paid gaming app, leaving many developers scratching their heads on how to turn a profit out of their passion. Here are some of the best methods for mobile game monetization:

1. SEGMENTATION Without a price to download, app publishers can no longer rely on a single method of monetization. Thus segmentation, the division of profit streams, is key to any mobile game monetization plan. App monetization revenues stem from three major categories: in-app purchases, subscription-based premium upgrades, and ad revenue. Highly-successful games can also bring in money through sponsorships, merchandise, and even big-budget Hollywood movies, but the bulk of app developers generate revenue from inside the phone. Experienced mobile game developers use their understanding of each of these revenue streams and how they relate to their target audience to leverage multiple revenue streams within their games.

2. REWARDED AD FORMAT Ads and in-app purchases are both great assets to mobile game developers looking to monetize, but what if you could play them off each other to increase both sources of revenue? That’s the idea behind the rewarded ad format. In exchange for watching full ads during breaks in gameplay, users receive in-game rewards, power-ups, lives, etc. The incentive increases video completion rate, as well as ad revenue, and preview premium features to entice more in-app purchases. While the rewarded ad format can lead to a surge in both in-app purchases and ad revenue, it still requires strategy. Keeping the audience in mind by ensuring the user base will find the content of the ad interesting will increase completion rate. Strategic rewarded ad placement is also key to keeping users engaged. Rewarded ad overkill will alienate users and prevent them from playing the game.

3. FREEMIUM The popular Freemium monetization method entails developers offering a free download of the most basic form of the app to entice the user, then premium services and features available for purchase or through a subscription fee. The Freemium model drives revenue through in-app purchases, premium features available through subscription fees, and ads. Apps like Tinder and Candy Crush have capitalized on their massive user base by enticing users to make in-app purchases and update to premium accounts. Candy Crush also uses social media to allow users to receive premium features in exchange for sharing with their friends.

4. NATIVE ADS Native ads are advertisements designed to match the form and function of their surroundings. TwitterFacebookGoogle, and Instagram all offer native ads and tools to help developers create and customize their ads. Native ad placement increases the chance of engagement by seamlessly blending the design of the ad in with the UI of the app. While many ads stand out in the context of a mobile app, native ads look like they are a part of the app rather than an advertisement. Some say native ads are unethical and deceptive, while others praise the improved customer targeting and enhanced content. Effective native ads blend seamlessly with the surrounding UI. The number one rule of native ads is to know your audience. If the developer can incorporate relevant content rather than ads for products that do not interest the user, native ads can appear to become more of an enhancement than an interruption.

5. FEEDER APPS Feeder apps are simple games with addicting gameplay which app developers utilize to spread brand awareness. Feeder apps often feature such simple gameplay, in-app purchases and ads would feel intrusive. Instead, push notifications and links in the main menu redirect users to their company website or another one of their games in iTunes. Many mobile development companies develop a network of feeder apps as a part of their publication and monetization strategy. By utilizing a well-integrated native ad for the company or game the developer intends to monetize, developers can turn viral feeder apps into profits. This comprehensive article by Scientific Revenue offers a great example of how feeder apps can function effectively. ZeptoLab cross-promotes their featured app King of Thieves through their feeder app Cut the Rope.

CONCLUSION Succeeding in the world of mobile gaming requires the same intense flare for competition which fuels mobile gamers. Experienced game developers know the stakes and come out swinging, ready to capitalize on every strategy they can to create a revenue stream. With the right combination of smarts, app developmentpromotion and strategy, mobile game developers can capitalize on their user base to rake in the big bucks.

Sink or Swim: Why Google Needs Andromeda to Compete with Apple

Andromeda summed up in a graphic (Via thehackernews.com)

App developers commonly cite device fragmentation as one of their biggest peeves about the Android platform. While Apple keeps a stronghold on all iOS devices, Android allows third-party developers to create hardware for the platform. With a number of different devices all with different screen sizes, tech specs and OS capabilities, developers cannot efficiently optimize the end user experience of their apps for all devices as they can with iOS. However, Google is making a major move to create a more streamlined app ecosystem with Andromeda.

Rumors of Andromeda began when multiple independent sources revealed it would be announced at Google’s October 4th announcement. When October 4th turned out to be hardware-focused, the heat died down on Andromeda. However, in the big picture, Andromeda represents a necessary move in order to prevent Google from losing potentially billions of dollars to Apple in the years and decades to come.

WHAT IS ANDROMEDA?

The idea of Andromeda is to combine Google’s laptop OS (Chrome OS) and their mobile and tablet OS (Android). Chrome OS is not Google Chrome, the web browser you may or may not use every day, but their desktop operating system which works with Chromebooks. For the skinny on Chrome, check out this awesome breakdown:

Rather than integrate Android features on Chrome OS, Andromeda will do the opposite and enable mobile devices with Chrome OS features. Mobile devices will begin to feel like an extension of one’s desktop. Rumored features include file organization, multi-modal windowing and compatibility between mobile and desktop apps. While the details have yet to be revealed, the concept behind Andromeda makes it a huge, necessary step for Google’s long-term future in the OS market.

WHY IT’S IMPORTANT

Andromeda will put Google in direct competition with the Mac OS X and Windows platforms. Apple has long been focused on device Continuity, the interchangeability between iOS devices. Their mobile (iOS) & desktop (OS X) operating systems are optimized to work together. By merging Google’s mobile platform with their desktop OS, Google increases cross-device functionality  and creates a strong incentive for consumers to keep all their devices within the Google brand.

THE INTERNET OF THINGS MAKES THIS SINK OR SWIM FOR GOOGLE 

The good news for app developers is in Andromeda’s long-term potential. Andromeda will enable developers to create apps which seamlessly function across devices: smartphones, tablets and desktops. As the IoT becomes domesticated, having a unified OS will mean big bucks for software companies looking to capitalize on home automation and commercial IoT products. In 10 years, consumers will be incredulous if they can’t control their coffee machine, change the channel on their TV and lock their doors on any of their devices. They want cohesive simplicity. If Google loses the OS battle with a less cohesive strategy than Apple, they will also lose the smartphone, tablet, TV and laptop.

CONCLUSION

Dennis Jones, CEO of payments technology company Judopay, put it this way for Developer-Tech: “Andromeda will be the foundation for omnipresence for Google-powered hardware, similar to Apple’s ecosystem… Andromeda is the foundation to enable this omnichannel world.”

Without Andromeda, Google would be dead in the water against the future omnichannel world Apple has been developing over the years. Who will execute better? Until the public sees Andromeda in action, the answer remains to be seen.

Apple Brings the Internet of Things Home with HomeKit & iOS 10

Anyone engrossed in the tech scene knows the Internet of Things is one of the trendiest technology topics on the web. The IoT is shaping our world and building fortunes for innovators, futurists and top app development companies. However, in the common household, the IoT has yet to break through to the mainstream. The biggest company in the world is now looking to enact change.

Tim Cook, in his September Announcement, declared that iOS 10’s HomeKit update is the first time home automation has been integrated with a major platform. While Apple introduced HomeKit in 2014 with iOS 8, iOS 10 comes with a dedicated app called Home that controls all home automation devices.

HOME IS A HOME RUN

Home Apple App via Wareable

Home combines IoT technology with the masterful UI of iOS. Previous iterations of iOS and HomeKit required the user to manage each interface separately. So if a phone had 20 HomeKit apps, they would have 20 user interfaces to manage. The Home app unifies HomeKit apps, creating a central control center for all home automation applications.

With over 1 billion active Apple devices across the world, Home enters the market with giant global reach. Virtually every major manufacturer of home automation devices now supports HomeKit. Accessories cross all major categories, from lights and air conditioners to window shades, locks and home security. Commercial IoT companies now have massive domestic reach, and iOS users have more incentive to update their homes than ever before.

HAVE SIRI SET THE SCENE

Siri Scenes via Next Market

One of the coolest features of Home is the Siri integration. Users can control Home from both the Control Center and Siri, but Siri can work at the speed of your language. Siri’s ability to handle multiple requests means users can accomplish their ideal environmental preferences in the speed of a sentence. Apple refers to these combination commands as “scenes” and users can give “scenes” a nickname. A rambunctious user might say “Hey Siri, let’s get funky,” prompting Siri to lock the doors, dim the lights, put Barry White on the speakers at a reasonable volume and provide the most apt customized ambience for the user to rock out.

THE APPLE TV IS THE HEARTH

The fourth generation Apple TV can also act as a hub for the Home app, with the Siri Remote making it easy to control your home on the go. Apple TV’s seamless integration with HomeKit and other iOS products makes it the ultimate smart TV for a smart home, providing yet another reason for consumers to consistently buy iOS products.

BUILDING COMMERCIAL IOT FROM THE GROUND UP

The Home Automation page on the Apple website is a clear indicator of Apple’s intentions to not only be a household name, but to be the name on your household. The company already has a major market share of phones, tablets, computers, TVs and watches. They are rumored to be looking to acquire McLaren as a part of Project Titan. Apple understands that the ubiquity of the iOS platform makes them the most appealing platform for manufacturers of smart devices. Apple also announced that leading home builders, including Brookfield Residential, KB Home, Lennar Homes and R&F Properties, are integrating many HomeKit devices into new homes.

With the Apple Home potentially on the horizon, one can only wonder how much of Apple’s vision of the smarthome will be realized in the next 5-10 years.

Game Design Techniques: Significantly Increase Ad Revenue with a Sharp Core Loop

Due to the budgetary, software and hardware limitations of mobile games, developers must hook audiences with a well-built game incorporating layers of psychological strategy. The core of any mobile game is the Core Loop. The Core Loop is the main facet of gameplay. It’s the beating heart upon which all progress is precipitated. In sports games, it’s the matches. In Angry Birds, it’s launching the birds to destroy the pigs. In Candy Crush, it’s the levels. The Core Loop is the obstacle that users willingly take on with the intention of overcoming in exchange for a feeling of accomplishment. While retention techniques can reinforce that feeling and can add to the experience, no game can survive a poor Core Loop. In some cases, a great Core Loop doesn’t need any sort of extravagant retention technique. Flappy Bird, which took 3 hours to make, can accrue $50,000 a day in ad revenue purely off the Core Loop.

THE BASICS

A good Core Loop for a mobile game generally entails a simple, enjoyable, repetitive action which triggers a reward when executed properly. This reward is something in-game which triggers a dopamine rush for the user. The rewards can be anything from gaining points, getting lives, advancing levels, power-ups, unlocking characters and items, and so forth. These rewards are tiered and the dopamine rush should vary depending on the level of accomplishment. For instance, the main action of Fruit Ninja is slicing fruit. Slicing one fruit triggers a dopamine rush, but clearing a level of fruit triggers a larger dopamine rush, and getting on the high score list triggers yet a larger one, etc. Retention tactics can dictate how these rushes are tiered, but the action which produces the rush is the most important thing: the Core Loop.

LOOPING

Rule number one of the Core Loop for mobile games is to actually loop. After one loop completes, another loop begins. The user completes a level and begins at the next level with their score intact, or they fail to complete the level and begin at the start of the same level with their score reset. Even rewards apps for retail stores rely on Core Loop to hook users. Console games are monetized through retail, so they can craft larger budget, more intimate single-player experiences, but mobile games are generally monetized through the Freemium model, which means ad-revenues will make up the bulk of their profits. Ads come at the end of the Core Loop, so the more loops per user, the better. Thus, mobile developers generally invest in simple but rewarding, well-crafted, repetitive gameplay systems.

PROGRESSION AND REPETITION

Pac Man Level 1 Vs. Level 2 via GitHub

While a Core Loop must loop, it also must instill a sense of progression. If the user doesn’t feel like they’re making progress, they will likely quit. Users want the satisfaction of accomplishment, and both satisfaction and accomplishment require a sense of finality. Arcade games are popular on mobile devices because they thrive on repetition. Level 2 of Pac-Man is not much different from Level 1, but it is different, and that minor difference instills a sense of progression; the sense that a new challenge must be conquered with skills accrued in past gameplay experience. Memories unconsciously become technique. In games like the aforementioned Flappy Bird, the goal is simply to get a high score. There are no levels, but a sense of progression is still built purely through how one’s high score builds. If the high score weren’t displayed, Flappy Bird would still have a Core Loop, but nobody would play it since one couldn’t measure one’s progress. It wouldn’t feel like a game. The beauty of high scores is they represent a single player game with a social release, which is also great for social media promotion.

SESSION LENGTH

Session length is a vital aspect of the Core Loop. The Starbucks Test entails that the user should be able to have a meaningful experience with the game in the time it takes the barista to make them coffee. A concise session length will get users coming back often in the empty pockets of their day.

DUAL LOOP

The Dual Loop is an advanced game development technique that can deeply enhance gameplay. At the end of the first loop, the Dual Loop technique offers the user the option to stop their session and enter into a mini-loop which enhances the next loop, which is a continuation of the first. When you play Clash of Clans, you can battle, which is the main loop, but you can also collect resources or build and train your army in between battles. The dual allows the user to add quick 30-second interactions which pass the Starbucks Test and increase their investment in the competition.

One of the best ways to enhance your ability to develop a Core Loop is to play and analyze other games. A well-designed Core Loop can lead to mobile gaming success on minimal budgets, and massive success on larger budgets.

Monetizing IoT: How the Internet of Things Builds Fortunes

A man sits in a restaurant and orders “The John Candy Burger” (a double cheeseburger with four strips of bacon and a fried egg) through a touch screen embedded into the table. As he gives the waiter his order, his smartwatch vibrates. He checks a push notification which tells him he should not order “The John Candy Burger” based on information gathered from a sensor in his body which has been monitoring his blood pressure and cholesterol among other notable health measurements in a constant stream of data for 15 years with infallible predictive capabilities. It tells him this specific cheeseburger from this specific restaurant will increase his risk of a heart attack on his daily run by 8%. He doesn’t understand how, but he accepts it the way one accepts that the earth is round and the Great Pyramid of Giza existed in 2540 BC.

In the above fictional example, the Internet of Things took the man’s order, evaluated the average nutritional content of the burger based on data gathered through sensors embedded into a smart grill, and transmitted it to the smartwatch where it analyzed nutritional content in the context of over 15 years of health data gathered on the man to inform him on the potential risk of his decision. The Internet of Things is bigger than money. It’s a new world where planes don’t crash and  smartphones can tell their users the location of the nearest empty parking spot to minimize travel time and ensure the city is maintaining optimum functionality. A pregnant wife is gently guided through a safe 9-month path to the newest addition to her family. The edges of the world are being smoothed out by data. The Internet of Things is leading the human race toward new levels of efficiency, productivity and effectiveness.

“Show me the money”

As a major technological evolution takes place, many businesses are looking to monetize it. Although the world has yet to see the full impact of the Internet of Things, it has already revolutionized process improvement for everything from manufacturing to health care, product enhancement, and safety. For the developer eager to enter a burgeoning field with infinite possibilities, here are some of the common techniques for monetizing IoT applications.

ONE-TIME PAY + FREE APP

The most basic monetization method entails creating a simple product with everyday applications, like Jawbone and the Phillips Hue Connected Bulb for example, and offering the equipment for purchase which works in conjunction with a connected app for iOS & Android. This method is most effective for products where the manufacturing cost to market ratio is kept low.

SUBSCRIPTION-BASED

One of the major issues with the IoT is the amount of data generated regularly by their devices. The amount of data and possibilities are so staggering, it’s vital to understand and decide upon relevant metrics and analysis tactics. For developers, it means that the cost of maintaining many IoT apps calls for a constant stream of revenue. Companies like Audi offer a hotspot subscription, ranging from 6 to 30 months, for Audi Connect, their hotspot navigation system utilizing Google Earth and Voice to offer real-time alerts, weather and traffic. In some applications, data plans will likely emerge as a another way of tiering subscription-based purchases.

WHITE LABEL SERVICES

Perhaps the most profitable and complex option, monetizing IoT applications through white label services entails having the foresight to identify the future of the technology and the necessary human & financial resources to act upon it effectively through the creation of a template offering which businesses can rebrand as their own. Jasper Technologies created the Connected Car Cloud as a cloud-based turnkey solution for developing smart-cars with real-time diagnostics, safety, security, and more.

Acquired by Cisco for about $1.4 billion in March, Jasper is one of the big success stories of IoT monetization and a model for future innovators looking to capitalize on the business opportunities brought about by the Internet of Things.

Learn more about IoT through this awesome article with advice from early adopters via Computer World.

The Secret to Monetizing Mobile Games: Retention

In the Freemium era, retention is perhaps the most important measurement of a mobile game’s success. While console games are sold in boxes, rely on marketing, and profit primarily from sales (in addition to ongoing online content/purchases), the bulk of mobile games are free and must begin generating revenue after they have been installed. In-app purchases and advertising revenues make up the vast majority of revenue. The average in-app purchase is made 12 days after first launching an app. During that time the user is likely generating revenue primarily through in-game advertising.

The great FTP (Free-To-Play) game monetization expert Nicholas Lovell (a consultant on Angry Birds Go—the very first FTP game from the conception on) breaks down the FTP game design process into a pyramid of three games which play off of each other: Core Loop, Retention, and Superfan games.

FTP Pyramid Via Game Sparks

CORE LOOP: The Core Loop is active gameplay: playing matches in Madden, clearing a level in Candy Crush, catching a Pokemon and battling in Pokemon GO. The Core Loop is the heart of the game. Without an engaging Core Loop, a game has nothing on which to build.

RETENTION: The Retention Game revolves around the Core Loop and is everything that instills the user with a sense of progression toward an overarching goal to keep them  coming back. It is the scoring mechanisms, the levels, the mechanics which establish progression (commonly the game maps), the narrative in Single Player games like Grand Theft Auto and Assassin’s Creed, the achievement system, and the leaderboards. Retention reinforces positive feelings and a sense of accomplishment from the Core Loop experience. Without an effective Retention game, users will not see any point to the game and will not receive an sense of accomplishment or progression toward a greater goal, and the Core Loop will seem insignificant and fade out.

SUPERFAN: The Superfan gameplay mechanics are catered to those who have developed a significant relationship with the game. They are premium subscriptions, extravagant in-app purchases, add-ons for  game’s die-hard fanatics.  Many mobile games are designed for casual play and no Superfan game, while other high-budget multiplayer games, like Clash of Clans and Pokemon GO, have very established brands and use Superfan methods to capitalize on their fervent fandom.

While having an addictive Core Loop is the most important building block, Retention reinforces positive feelings about the game, instills a sense of progression toward both immediate goals and overarching goals, and ensures users are feeling rewarded by the time they put into gameplay. Core Loop will get them in the door, while Retention will keep them in the house and lubricate their wallet.

Here are four of the best guidelines for developing retention, including specific methods, for mobile games:

SEDUCE THE USER WITH AN INTRODUCTION

In the highly competitive market for mobile games, games must engage from the introduction. Games with bland introductions will not retain users. An investing opening cut scene, an aesthetically appealing title screen and awesome music/SFX will pay off when they seduce users from the outset to play on and enter the Core Loop.

MAKE THE GAMEPLAY ACCESSIBLE

If a game is too easy or too hard, it won’t be worth the user’s time. It’s important to specify a game’s audience, decide what level of gamer they will be, and make it accessible to them.  Tutorials can help introduce game concepts, but when they are too long or restricting, they hurt more than they help. Offering users tips and tricks during loading screens and through push notifications are a clever way of increasing accessibility to new users without infringing on the Core Loop.

REDUCE AVERAGE LENGTH OF SESSION

The STARBUCKS TEST has become common terminology in game developer circles. If the user can’t have a meaningful experience in the time it takes for a barista to make your drink, then the game loop is too long. In mobile games, which are primarily played in the pockets of time where the impatient smartphone owner must wait, it’s vital to have a short Core Loop which the user can complete quickly and come back to throughout the day.

INSTILL A SENSE OF PROGRESSION

While some games, like Flappy Bird, are simple and fun enough to succeed on an arcade level with only high scores, most mobile developers are unable to achieve the same level of competition and must instill a sense of progression in order to retain the user. Whether it’s unlocking new levels or characters or progressing along a game board, the game must congratulate the user frequently in order to reinforce positive feelings about the game. Many games enlist achievement systems in order to give the user tangible goals with rewards outside of the main objectives of the Core Loop.

Read more on Achievement systems here via Gamasutra

Learn more about retention in the YouTube lecture below by Lovell. At 1:11:00, Lovell explains how prototyping the retention game outside of the Core Loop to see if it still feels effective is a great way of testing how effective retention methods.

Ultimately, the two biggest factors which will lead to uninstalls for mobile games are boredom and frustration. The game designer must battle these factors both in the immediacy of the Core Loop and the overarching retention strategies.