Tag Archives: Analytics

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

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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 the Internet of Behaviors Will Shape the Future of Digital Marketing

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In the digital age, businesses need to leverage every possible platform and cutting-edge technology in order to get a leg up on the competition. We’ve covered the Internet of Things extensively on the Mystic Media blog, but a new and related tech trend is making waves. This trend is called the Internet of Behaviors and according to Gartner, about 40% of people will have their behavior tracked by the IoB globally by 2023.

WHAT IS THE IOB?

Internet of Behavior, or the IoB, exists at the intersection of technology, data analytics, and behavioral science. The IoB leverages data collected from a variety of sources, including online activities, social media, wearable devices, commercial transactions and IoT devices, in order to deliver insights related to consumers and purchasing behavior.

With devices more interconnected than ever, the IoB tracks, gathers, combines and interprets massive data sets so that businesses can better understand their consumers. Businesses leverage analysis from the IoB to offer more personalized marketing with the goal of influencing consumer decision making.

HOW DOES IT WORK?

Traditionally, a car insurance company would analyze a customer’s driving history in order to determine if they are a good or bad driver. However, in today’s digital age, they might take it a step further and analyze social media profiles in order to “predict” whether a customer is a safe driver. Imagine what insights they could gather from a user’s Google search history or Amazon purchases? Access to large datasets enables large companies to create psychographic profiles and gather an enhanced understanding of their customer base.

Businesses can use the IoB for more than just purchasing decisions. UX designers can leverage insights to deliver more effective customer experiences. Large companies such as Ford are designing autonomous vehicles that change based on the city, modulating behavior based on vehicle traffic, pedestrians, bicycles and more.

GBKSOFT created a mobile application that collects data from wearable devices in order to help golfers improve their skills. The application records each golf ball hit, including the stroke, force, trajectory and angle, and delivers visual recommendations to improve their swing and technique. Insights gathered through data are translated into behavioral trends that are then converted into recommendations to improve the user’s game.

The IoB is all about collecting data that can be translated into behavior which helps companies understand consumer tendencies and translate them into meaningful actions.

CONCERNS

While there is quite a bit of enthusiasm surrounding the potential impact of the IoB for B2C companies, a number of legal concerns come with it. A New York Times article, written by Harvard Business School emeritus professor Shoshana Zuboff, warns of the age of surveillance capitalism where tech behemoths surveil humans with the intent to control their behavior.

Due to the speed at which technology and the ability to collect data has proliferated, privacy and data security are under-regulated and major concerns for consumers. For example, Facebook was applying facial recognition scans in advance of the 2016 election without user’s consent. Cambridge Analytica’s use of psychoanalytic profiles has been the subject of much derision. Momentum for data privacy regulation is growing and since the IoB hinges on the ability for companies to collect and market data, forthcoming regulations could inhibit its impact.

CONCLUSION

Despite regulatory concerns, the IoB is a sector that we expect to see grow over time. As the IoT generates big data and AI evolves to learn how to parse through and analyze it, it’s only natural that companies will take the next step to leverage analysis to enhance their understanding of their customers’ behaviors and use it to their advantage. The IoB is where that next step will take place.

How AI Fuels a Game-Changing Technology in Geospatial 2.0

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Geospatial technology describes a broad range of modern tools which enable the geographic mapping and analysis of Earth and human societies. Since the 19th century, geospatial technology has evolved as aerial photography and eventually satellite imaging revolutionized cartography and mapmaking.

Contemporary society now employs geospatial technology in a vast array of applications, from commercial satellite imaging, to GPS, to Geographic Information Systems (GIS) and Internet Mapping Technologies like Google Earth. The geospatial analytics market is currently valued between $35 and $40 billion with the market projected to hit $86 billion by 2023.

GEOSPATIAL 1.0 VS. 2.0

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Geospatial technology has been in phase 1.0 for centuries; however, the boon of artificial intelligence and the IoT has made Geospatial 2.0 a reality. Geospatial 1.0 offers valuable information for analysts to view, analyze, and download geospatial data streams. Geospatial 2.0 takes it to the next level–harnessing artificial intelligence to not only collect data, but to process, model, analyze and make decisions based on the analysis.

When empowered by artificial intelligence, geospatial 2.0 technology has the potential to revolutionize a number of verticals. Savvy application developers and government agencies in particular have rushed to the forefront of creating cutting edge solutions with the technology.

PLATFORM AS A SERVICE (PaaS) SOLUTIONS

Effective geospatial 2.0 solutions require a deep vertical-specific knowledge of client needs, which has lagged behind the technical capabilities of the platform. The bulk of currently available geospatial 2.0 technologies are offered as “one-size-fits-all” Platform as a Service (PaaS) solutions. The challenge for PaaS providers is that they need to serve a wide collection of use cases, harmonizing data from multiple sensors together while enabling users to simply understand and address the many different insights which can be gleaned from the data.

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In precision agriculture, FarmShots offers precise, frequent imagery to farmers along with meaningful analysis of field variability, damage extent, and the effects of applications through time.

Mayday

In the disaster management field, Mayday offers a centralized artificial intelligence platform with real-time disaster information. Another geospatial 2.0 application Cloud to Street uses a mix of AI and satellites to track floods in near real-time, offering extremely valuable information to both insurance companies and municipalities.

SUSTAINABILITY

The growing complexity of environmental concerns have led to a number of applications of geospatial 2.0 technology to help create a safer, more sustainable world. For example, geospatial technology can measure carbon sequestration, tree density, green cover, carbon credit & tree age. It can provide vulnerability assessment surveys in disaster-prone areas. It can also help urban planners and governments plan and implement community mapping and equitable housing. Geospatial 2.0 can analyze a confluence of factors and create actionable insight toward analyzing and honing our environmental practices.

As geospatial 1.0 models are upgraded to geospatial 2.0, expect to see more robust solutions incorporating AI-powered analytics. A survey of working professionals conducted by Geospatial World found that geospatial technology will likely make the biggest impact in the climate and environment field.

CONCLUSION

Geospatial 2.0 platforms are very expensive to employ and require quite a bit of development.  The technology offers great potential to increase revenue and efficiency for a number of verticals. In addition, it may be a key technology to help cut down our carbon footprint and create a safer, more sustainable world..

AIoT: How the Intersection of AI and IoT Will Drive Innovation for Decades to Come

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We have covered the evolution of the Internet of Things (IoT) and Artificial Intelligence (AI) over the years as they have gained prominence. IoT devices collect a massive amount of data. Cisco projects by the end of 2021, IoT devices will collect over 800 zettabytes of data per year. Meanwhile, AI algorithms can parse through big data and teach themselves to analyze and identify patterns to make predictions. Both technologies enable a seemingly endless amount of applications retained a massive impact on many industry verticals.

What happens when you merge them? The result is aptly named the AIoT (Artificial Intelligence of Things) and it will take IoT devices to the next level.

WHAT IS AIOT?

AIoT is any system that integrates AI technologies with IoT infrastructure, enhancing efficiency, human-machine interactions, data management and analytics.

IoT enables devices to collect, store, and analyze big data. Device operators and field engineers typically control devices. AI enhances IoT’s existing systems, enabling them to take the next step to determine and take the appropriate action based on the analysis of the data.

By embedding AI into infrastructure components, including programs, chipsets, and edge computing, AIoT enables intelligent, connected systems to learn, self-correct and self-diagnose potential issues.

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One common example comes in the surveillance field. Surveillance camera can be used as an image sensor, sending every frame to an IoT system which analyzes the feed for certain objects. AI can analyze the frame and only send frames when it detects a specific object—significantly speeding up the process while reducing the amount of data generated since irrelevant frames are excluded.

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While AIoT will no doubt find a variety of applications across industries, the three segments we expect to see the most impact on are wearables, smart cities, and retail.

WEARABLES

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The global wearable device market is estimated to hit more than $87 billion by 2022. AI applications on wearable devices such as smartwatches pose a number of potential applications, particularly in the healthtech sector.

Researchers in Taiwan have been studying the potential for an AIoT wearable system for electrocardiogram (ECG) analysis and cardiac disease detection. The system would integrate a wearable IoT-based system with an AI platform for cardiac disease detection. The wearable collects real-time health data and stores it in a cloud where an AI algorithm detects disease with an average of 94% accuracy. Currently, Apple Watch Series 4 or later includes an ECG app which captures symptoms of irregular, rapid or skipped heartbeats.

Although this device is still in development, we expect to see more coming out of the wearables segment as 5G enables more robust cloud-based processing power, taking the pressure off the devices themselves.

SMART CITIES

We’ve previously explored the future of smart cities in our blog series A Smarter World. With cities eager to invest in improving public safety, transport, and energy efficiency, AIoT will drive innovation in the smart city space.

There are a number of potential applications for AIoT in smart cities. AIoT’s ability to analyze data and act opens up a number of possibilities for optimizing energy consumption for IoT systems. Smart streetlights and energy grids can analyze data to reduce wasted energy without inconveniencing citizens.

Some smart cities have already adopted AIoT applications in the transportation space. New Delhi, which boasts some of the worst traffic in the world, features an Intelligent Transport Management System (ITMS) which makes real-time dynamic decisions on traffic flows to accelerate traffic.

RETAIL

AIoT has the potential to enhance the retail shopping experience with digital augmentation. The same smart cameras we referenced earlier are being used to detect shoplifters. Walmart recently confirmed it has installed smart security cameras in over 1,000 stores.

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One of the big innovations for AIoT involves smart shopping carts. Grocery stores in both Canada and the United States are experimenting with high-tech shopping carts, including one from Caper which uses image recognition and built-in sensors to determine what a person puts into the shopping cart.

The potential for smart shopping carts is vast—these carts will be able to inform customers of deals and promotion, recommend products based on their buying decisions, enable them to view an itemized list of their current purchases, and incorporate indoor navigation to lead them to their desired items.

A smart shopping cart company called IMAGR recently raised $14 million in a pre-Series A funding round, pointing toward a bright future for smart shopping carts.

CONCLUSION

AIoT represents the intersection of AI, IoT, 5G, and big data. 5G enables the cloud processing power for IoT devices to employ AI algorithms to analyze big data to determine and enact action items. These technologies are all relatively young, and as they continue to grow, they will empower innovators to build a smarter future for our world.

How Artificial Intuition Will Pave the Way for the Future of AI

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Artificial intelligence is one of the most powerful technologies in history, and a sector defined by rapid growth. While numerous major advances in AI have occurred over the past decade, in order for AI to be truly intelligent, it must learn to think on its own when faced with unfamiliar situations to predict both positive and negative potential outcomes.

One of the major gifts of human consciousness is intuition. Intuition differs from other cognitive processes because it has more to do with a gut feeling than intellectually driven decision-making. AI researchers around the globe have long thought that artificial intuition was impossible, but now major tech titans like Google, Amazon, and IBM are all working to develop solutions and incorporate it into their operational flow.

WHAT IS ARTIFICIAL INTUITION?

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Descriptive analytics inform the user of what happened, while diagnostic analytics address why it happened. Artificial intuition can be described as “predictive analytics,” an attempt to determine what may happen in the future based on what occurred in the past.

For example, Ronald Coifman, Phillips Professor of Mathematics at Yale University, and an innovator in the AI space, used artificial intuition to analyze millions of bank accounts in different countries to identify $1 billion worth of nominal money transfers that funded a well-known terrorist group.

Coifman deemed “computational intuition” the more accurate term for artificial intuition, since it analyzes relationships in data instead of merely analyzing data values. His team creates algorithms which identify previously undetected patterns, such as cybercrime. Artificial intuition has made waves in the financial services sector where global banks are increasingly using it to detect sophisticated financial cybercrime schemes, including: money laundering, fraud, and ATM hacking.

ALPHAGO

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One of the major insights into artificial intuition was born out of Google’s DeepMind research in which a super computer used AI, called AlphaGo, to become a master in playing GO, an ancient Chinese board game that requires intuitive thinking as part of its strategy. AlphaGo evolved to beat the best human players in the world. Researchers then created a successor called AlphaGo Zero which defeated AlphaGo, developing its own strategy based on intuitive thinking. Within three days, AlphaGo Zero beat the 18—time world champion Lee Se-dol, 100 games to nil. After 40 days, it won 90% of matches against AlphaGo, making it arguably the best Go player in history at the time.

AlphaGo Zero represents a major advancement in the field of Reinforcement Learning or “Self Learning,” a subset of Deep Learning which is a subset of Machine Learning. Reinforcement learning uses advanced neural networks to leverage data into making decisions. AlphaGo Zero achieved “Self Play Reinforcement Learning,” playing Go millions of times without human intervention, creating a neural network of “artificial knowledge” reinforced by a sequence of actions that had both consequences and inception. AlphaGo Zero created knowledge itself from a blank slate without the constraints of human expertise.

ENHANCING RATHER THAN REPLACING HUMAN INTUITION

The goal of artificial intuition is not to replace human instinct, but as an additional tool to help improve performance. Rather than giving machines a mind of their own, these techniques enable them to acquire knowledge without proof or conscious reasoning, and identify opportunities or potential disasters, for seasoned analysts who will ultimately make decisions.

Many potential applications remain in development for Artificial Intuition. We expect to see autonomous cars harness it, processing vast amounts of data and coming to intuitive decisions designed to keep humans safe. Although its ultimate effects remain to be seen, many researchers anticipate Artificial Intuition will be the future of AI.

How to Craft the Perfect Instagram Story Strategy to Promote Your Business

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Instagram introduced the Story function to their platform in August 2016. Replicating Snapchat, the Instagram Story offers ephemeral visual content that disappears 24 hours after posting it.

As with the introduction of any new tool on social media, the first question a business must ask itself is: How can we leverage this new platform to promote our company, product or services?

Here are some tips to help you craft the perfect Instagram Story strategy:

GIVE A BEHIND-THE-SCENES LOOK

Instagram users expect the most touched-up and polished visual content to show up on the feed. Part of the appeal of the Instagram Story is that it offers a deeper, less polished look into the day-to-day life of the account.

Musicians take advantage of Instagram Stories by previewing snippets of new music on their stories. The fact that these stories will disappear activates a fan’s FOMO (Fear Of Missing Out). If they see one of their favorite artists post to their story, they feel obligated to watch it or else they will miss out on exclusive music, otherwise they may have to wait months for an official release. Thus, it both offers a behind the scenes look and incites users to return to view more stories.

FOMO

FOMO, or Fear of Missing Out, is a form of anxiety triggered by missing an opportunity. For example, when considering whether to go to an office party or a concert, one may be more driven to go because one doesn’t want to miss out on fun than wanting to enjoy the experience.

The ephemeral nature of the Instagram Story makes FOMO a major psychological factor determining whether a user elects to watch a story or not. If the user does not watch the story, they will never see the content. Businesses want to offer exclusive deals and content through their story that are not available anywhere else. Consumers who watch stories with exclusive deals and content are thereby rewarded and are more likely to watch them in the future to get more deals.

Incorporating exclusive deals will draw more users to watch your business’s Story because—well, it’ll make them afraid of missing out. Check out Psychology Today’s deep dive into FOMO.

KEEP IT FUN, KEEP IT LIGHT, KEEP IT MOVING

Take your Instagram Story on the road. Vary up the locations where you post and it will create more excitement as users will know to expect the unexpected when they view your story. Keep it light, give it some humor. Your Instagram Story should contain content that lightens the mood and makes viewers want to return.

MAKE IT A REAL STORY

Stories have a beginning, middle and end. Instagram Stories can conform to that structure as well! If an employee is going to a convention, have them document it in their story with an introduction post explaining their agenda for the day (beginning), videos of the most salient moments of the convention (middle), and a final post that wraps everything up and summarizes what they’ve gleaned (end).

Using storytelling techniques will keep users engaged in your feed and help Stories retain viewers from beginning to end.

ANALYTICS

Reviewing analytics and evaluating the metrics is a key process in evaluating your Story’s success. Use the Insights tab to see how many views your story received, how many shares, replies, profile visits, and how long users are watching your story to evaluate its success.

One of the key analytics is Completion Rate: what percentage of users watched your story from beginning to end? Evaluating completion rate, as well as Taps Forward, which shows when users tapped forward on a slide to see the next image, will help you determine whether your ideal posts per day are 2 or 12.

BE CONSISTENT

Consistency is key in social media. It takes time to develop a voice and even more time and effort to develop an audience. With a combination of a good strategy, solid content, and consistency, your business can leverage Instagram Stories to entice your customers and expand its reach.

Monetizing IoT: How the Internet of Things Builds Fortunes

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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.

App Store Optimization Part 5: Key Differences in Apple Vs. Google Play App Stores

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In an effort to emphasize the importance of App Store Optimization, The Mystic Media Blog is applying its expertise into a six-part series on ASO. In our previous entry Maximize Your Exposure by Getting Featured on the App Store, we detailed techniques on how to get featured on an App Store landing page. This week, we will explore the differences in ASO for Google Play and  Apple App Store.

App Store curators look to surface the most relevant content for users. Although the ultimate goal may be the same for both Google and Apple, their approach to achieving their goals are different. The exact details of Apple’s processes are shrouded in secrecy as they promote discovery through curation, while Google focuses more on analytics and prioritizes transparency in their processes. Check out their recent I/O speech on Getting Discovered on Google Play for a bevy of useful information. While our ASO series thus far has focused on the common ground, this chapter will delve into the differences between the two app stores and what techniques can be used to optimize for either store.

GENERAL THEMES

Google Play favors bigger mobile-focused enterprises, while Apple favors independent developers. A recent study at MobileDevHQ found independent developers generally rank higher in the Apple App Store, while Google Play is more favorable toward mobile focused enterprises. MobileDevHQ recorded the top apps for each store and found that 65% of the top apps for iPhone were independently developed, while 90% of top apps in Google Play store were developed by mobile-focused enterprises.

Granted, out-of-context, the above statistic can be misconstrued. Big mobile-focused enterprises do better on Google Play because they have the brainpower and workforce to analyze the statistics which factor heavily into Google Play’s search algorithm. Google Play also does its part to give independent developers an opening through regional-specific results and Google+ recommendations. Apple’s App Store, on the other hand, relies on curation. The Mystic Media Blog previously discussed  how Android is considered more developer-friendly since they feature open-source coding and skip the process of approval Apple uses to filter bad apps from making it onto their App Store (review our post on Why Android Rules the Mobile Application Market). Apps receiving approval before making the the app store filters out sub-par entries, allowing Apple to curate more effectively. Every app on the Apple App Store, big or small, starts with an evaluation.

Apple’s App Store is much more volatile and reactive to trends than Google Play. Within the same seven day study at MobileDevHQ, the top ranking apps in Apple’s App Store fluctuated—no single app stayed in the same rank through all seven days—while of the top ten ranking apps on Google Play, five failed to change position once. In addition, no new apps broke into the top ten for Google Play.

DESCRIPTION

While it’s recommended developers include keywords in their app description, the Apple App Store barely weighs the description, unlike Google Play which weighs the keywords in app descriptions heavily. For more on keywording and app descriptions, review App Store Optimization Part 2: Master the Art of Writing a Catchy Title and Effective Keywords.

VIDEO

Google Play also allows developers to post a video preview of their app. The purpose of the video is to show the app in use, to preview the graphics, the sound, the UX, the function, etc. Google Play preview videos are hosted through Youtube, which creates a new avenue for app developers to market their product through Youtube SEO. For more on the topic, check out this cool article on How Youtube Videos are Ranked.

DISPLAY

Google’s recent talk about getting discovered on Google Play yielded a lot of great information concerning Google Play’s display strategy. Ankit Jain, Google Play’s Head of Search, Discovery & Store Infrastructure, explained how Google Play attempts to create a UX which is simultaneously personalized and personal.

Personalized, as it relates to Google Play, means the results are catered to the user based on their history of searches, purchases, what device the user is on (remember, unlike iOS, Android allows third-party companies to develop  devices on its OS), and what’s popular in their geographic region. The amalgamation of user history and geographic popularity factor heavily into Google Play’s search algorithms.

Personal means results are annotated by Google Play analytics with reasons why the user should download the app. This involves linking to the user’s Google+ account to allow the Google Play store to show if anyone in a person’s Google+ circles has given an app a +1.  Apps relevant to a search which are recommended by people in a user’s Google+ circles will surface high in the search results, thus targeting Google+ for social media campaigns pays off for developers releasing through Google Play.

CONCLUDING THOUGHTS

The goal of any app store is to effectively promote the top apps for the platform. Both Google and Apple look to share the apps which will best please the user and make the most of the technology of their respective platforms. When it comes to ASO, no keyword, app title, icon, or description will change anyone’s mind about a bad app. No curator will elevate the status of a bad app because it is well-marketed. Thus, it’s fitting remind you: the first step to optimizing any app for an app store is to create a great app. By observing the rules of each app store and excelling in each of the processes of ASO with intelligent strategy and an efficient external marketing campaign, a great app can catch the attention of app curators and rise to the top of any app store search. The rest, as they say, is search history.

Mystic Media is considered among the most versatile and capable web agencies in the US. Our workforce includes experts across a variety of fields including app development, strategic marketing, social media, web design, Search Engine Optimization, radio streaming, and more. We have the resources necessary to effectively develop and market applications for any platform. Contact us today by clicking here or calling 801.994.6815

App Store Optimization Part 2: Master the Art of Writing a Catchy Title and Effective Keywords

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In an effort to emphasize the importance of App Store Optimization, the Mystic Media Blog is applying its expertise into a six-part blog series on the topic. In our previous post, we gave an introduction to ASO, giving a general overview on the basics and defining the factors which impact your app’s placement in the app store. This week’s entry, part-two, will focus on the two primary factors in ASO: Title and Keywords.

The window for users to decide whether or not to download your app is increasingly short. In a generation defined by content overload, if you don’t catch the user’s eye within a matter of seconds, chances are your app will be overlooked. Even if you have an app icon that stands-out, unless you are within the first batch of search results for the keywords associated with your app, the user will likely settle before they see your app listing. ASO is about increasing the ranking of your app in search strings, and the two most important factors in ASO are title and keywords.

The title of your app, along with the app icon, is the most visible aspect to the casual user in the App Store. The App Store favors more descriptive titles. The use of keywords within your title will raise your place in the search results. Granted, your title should first and foremost be catchy, it’s also vital users get a sense of what the app does when they read the title. While the rules are different for big brands such as Grubhub and Uber, these companies worked to establish a preexisting relationship with consumers before launching their apps. If you can balance brand catchiness with keyword functionality in your title, you’ll have a winner.

Keywords are the most important factor in ASO. The keywords attached to an app make or break its SEO. Keywords are select terms or phrases attached to an app which apply to its functionality. The app stores have developers attach keywords to their apps so that when a given term is searched, apps with the keywords attached appear. It’s vital for developers to maximize and diversify their keyword offerings. Keywords like “food” or “taxi” yield a highly competitive search string, but synonyms like “grub” or “trolly” are less frequently searched, thus providing an avenue for your app to excel. The most relevant and logically searchable terms related to your app should also be keyworded. Yelp uses not only “food” and “restaurant, but also “bars”, “reviews”, “comida”, and “local”. By keywording a diverse group of terms, an app has a much greater chance of rising to the top when any of the terms are used in combination. Apptamin got it right when they said: “[It’s] better to be in the top 5 results for an average-searched keyword than in the top 100 for a highly-searched keyword.” The best avenue for an app to stand out is in a more focused group.

Determining keywords can be tricky. It requires time spent creatively analyzing the app in question as well as research. Many sites such as Searchman and AppTweak offer ASO analytics and third party consulting. There are also a number of ways to measure keyword analytics through independent research. Developers can search for a specific keyword in the app store in order to learn how many apps are targeting the term. Sensortower allows users to search for apps and find the keywords associated with each in the app store for free.

Keyword volatility is a crucial metric which measures how keyword rankings fluctuate over time. Some keyword searches yield consistent results while other results fluctuate over time. Although it takes mass amounts of data to get a truly accurate read on volatility, a simple way for developers to measure the volatility of a given keyword search is to search the term everyday for a couple of weeks and record the top ten, watching to see if the results and rankings change. While this simple method yields somewhat accurate results, a developer’s best bet is to outsource volatility tracking to a third-party SEO specialist.

Be on the look out next week for the third part of our ASO series focusing on the secondary factors in ASO, including app description, icon design, garnering better reviews and boosting your number of downloads

Finding the right title and keywords is likely the most difficult part of ASO, but also the most rewarding. If you want to save yourself some time and maximize your investment, Mystic Media’s experts are happy to assist you in your ASO, Strategic Marketing, and App Development needs. Contact us today by clicking here or by phone at 801.994.6815