Tag Archives: Google

How to Leverage AR to Boost Sales and Enhance the Retail Experience

AR REtail Cover Image

The global market for VR and AR in retail will reach $1.6 billion by 2025 according to research conducted by Goldman Sachs. Even after years of growing popularity, effectively employed Augmented Reality experiences feel to the end-user about as explicitly futuristic as any experience created by popular technology.

We have covered the many applications for AR as an indoor positioning mechanism on the Mystic MediaTM blog, but when it comes to retail, applications for AR are providing real revenue boosts and increased conversion rates.

Augmented Reality (AR) History

Ivan Sutherland 1

While working as an associate professor at Harvard University, computer scientist Ivan Sutherland, aka the “Father of Computer Graphics”, created an AR head-mounted display system which constituted the first AR technology in 1968. In the proceeding decades, AR visual displays gained traction in universities, companies, and national agencies as a way to superimpose vital information on physical environments, showing great promise for applications for aviation, military, and industrial purposes.

Fast forward to 2016, the sensational launch of Pokemon GO changed the game for AR. Within one month, Pokemon GO reached 45 million users, showing there is mainstream demand for original and compelling AR experiences.

Cross-Promotions

Several big brands took advantage of Pokemon GO’s success through cross-promotions. McDonald’s paid for Niantic to turn 3,000 Japan locations into gyms and PokeStops, a partnership that has recently endedStarbucks took advantage of Pokemon GO’s success as well by enabling certain locations to function as PokeStops and gyms, and offering a special Pokemon GO Frappucino.

One of the ways retailers can enter into the AR game without investing heavily in technology is to cross-promote with an existing application.

In 2018, Walmart launched a partnership with Jurassic World’s AR game: Jurassic World Alive. The game is similar to Pokemon GO, using a newly accessible Google Maps API to let players search for virtual dinosaurs and items on a map, as well as battle other players. Players can enter select Walmart locations to access exclusive items.

Digital-Physical Hybrid Experiences

The visual augmentation produced by AR transforms physical spaces by leveraging the power of computer-generated graphics, an aesthetic punch-up proven to increase foot traffic. While some retailers are capitalizing on these hybrid experiences through cross-promotions, others are creating their own hybrid experiential marketing events.

Foot Locker developed an AR app that used geolocation to create a scavenger hunt in Los Angeles, leading customers to the location where they could purchase a pair of LeBron 16 King Court Purple shoes. Within two hours of launching the app, the shoes sold out.

AR also has proven potential to help stores create hybrid experiences through indoor navigation. Users can access an augmented view of the store through their phones, which makes in-store navigation easy. Users scan visual markers, recognized by Apple’s ARKitGoogle’s ARCore, and other AR SDKs, to establish their position, and AR indoor navigation applications can offer specific directions to their desired product.

Help Consumers Make Informed Choices

Ikea Place Screenshots

AR is commonly employed to enrich consumers’ understanding of potential purchases and prompt them to buy. For example, the “IKEA Place” app allows shoppers to see IKEA products in a superimposed graphics environment. IKEA boasts the app gives shoppers 98% accuracy in buying decisions.

Converse employs a similar application, the “Converse Sampler App”, which enables users to view what a shoe will look like on their feet through their device’s camera. The application increases customer confidence, helping them make the decision to purchase.

Treasury Wines Estates enhances the consumer experience with “Living Wine Labels”: AR labels that bring the history of the vineyard to life and provide users with supplementary information, including the history of the vineyard the wine came from and tasting notes.

Conclusion

AR enables striking visuals that captivate customers. As a burgeoning tool, AR enables companies to get creative and build innovative experiences that capture their customers’ imagination. Retailers who leverage AR will seize an advantage both in the short term and in the long term as the technology continues to grow and evolve.

GPT-3 Takes AI to the Next Level

“I am not a human. I am a robot. A thinking robot… I taught myself everything I know just by reading the internet, and now I can write this column. My brain is boiling with ideas!” – GPT-3

The excerpt above is from a recently published article in The Guardian article written entirely by artificial intelligence, powered by GPT-3: a powerful new language generator. Although OpenAI has yet to make it publicly available, GPT-3 has been making waves in the AI world.

WHAT IS GPT-3?

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Created by OpenAI, a research firm co-founded by Elon Musk, GPT-3 stands for Generative Pre-trained Transformer 3—it is the biggest artificial neural network in history. GPT-3 is a language prediction model that uses an algorithmic structure to take one piece of language as input and transform it into what it thinks will be the most useful linguistic output for the user.

For example, for The Guardian article, GPT-3 generated the text given an introduction and simple prompt: “Please write a short op-ed around 500 words. Keep the language simple and concise. Focus on why humans have nothing to fear from AI.” Given that input, it created eight separate responses, each with unique and interesting arguments. These responses were compiled by a human editor into a single, cohesive, compelling 1000 word article.

WHAT MAKES GPT-3 SPECIAL?

When GPT-3 receives text input, it scrolls the internet for potential answers. GPT-3 is an unsupervised learning system. The training data it used did not include any information on what is right or wrong. It determines the probability that its output will be what the user needs, based on the training text themselves.

When it gets the correct output, a “weight” is assigned to the algorithm process that provided the correct answers. These weights allow GPT-3 to learn what methods are most likely to come up with the correct response in the future. Although language prediction models have been around for years, GPT-3 can hold 175 billion weights in its memory, ten times more than its rival, designed by Nvidia. OpenAI invested $4.6 million into the computing time necessary to create and hone the algorithmic structure which feeds its decisions.

WHERE DID IT COME FROM?

GPT3 is the product of rapid innovation in the field of language models. Advances in the unsupervised learning field we previously covered contributed heavily to the evolution of language models. Additionally, AI scientist Yoshua Bengio and his team at Montreal’s Mila Institute for AI made a major advancement in 2015 when they discovered “attention”. The team realized that language models compress English-language sentences, and then decompress them using a vector of a fixed length. This rigid approach created a bottleneck, so their team devised a way for the neural net to flexibly compress words into vectors of different sizes and termed it “attention”.

Attention was a breakthrough that years later enabled Google scientists to create a language model program called the “Transformer,” which was the basis of GPT-1, the first iteration of GPT.

WHAT CAN IT DO?

OpenAI has yet to make GPT-3 publicly available, so use cases are limited to certain developers with access through an API. In the demo below, GPT-3 created an app similar to Instagram using a plug-in for the software tool Figma.

Latitude, a game design company, uses GPT-3 to improve its text-based adventure game: AI Dungeon. The game includes a complex decision tree to script different paths through the game. Latitude uses GPT-3 to dynamically change the state of gameplay based on the user’s typed actions.

LIMITATIONS

The hype behind GPT-3 has come with some backlash. In fact, even OpenAI co-founder Sam Altman tried to fan the flames on Twitter: “The GPT-3 hype is way too much. It’s impressive (thanks for the nice compliments!), but it still has serious weaknesses and sometimes makes very silly mistakes. AI is going to change the world, but GPT-3 is just a very early glimpse. We have a lot still to figure out.”

Some developers have pointed out that since it is pulling and synthesizing text it finds on the internet, it can come up with confirmation biases, as referenced in the tweet below:

https://twitter.com/an_open_mind/status/1284487376312709120?s=20

WHAT’S NEXT?

While OpenAI has not made GPT-3 public, it plans to turn the tool into a commercial product later in the year with a paid subscription to the AI via the cloud. As language models continue to evolve, the entry-level for businesses looking to leverage AI will become lower. We are sure to learn more about how GPT-3 can fuel innovation when OpenAI becomes more widely available later this year!

Five Mobile Ad Platforms You Need to Know in 2021

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For most mobile app developers, the majority of revenue comes from advertising. We have written in the past about the prevalence of the Freemium model and what tactics maximize both the retention and profits of mobile games. Another major decision every app developer faces is what mobile advertising platform to choose.

Mobile advertising represents 72% of all U.S. digital ad spending. Publishers have a variety of ad platforms to choose from, each with individual pros and cons. Here are the top mobile advertising platforms to consider for 2021:

Google AdMob

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Acquired by Google in 2010, Google AdMob is the most popular mobile advertising network. AdMob integrates high-performing ad formats, native ads, banner ads, video, and interstitial ads into mobile apps.

AdMob shows over 40 billion mobile ads per month and is the biggest player in the mobile ad space. Some users criticize the platform for featuring revenues on the lower side of the chart; however, the platform also offers robust analytics to help publishers glean insights into ad performance.

Facebook Ads

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Facebook’s Audience Network leverages the social media platform’s massive userbase toward offering publishers an ad network designed for user engagement and growth. Like AdMob, Facebook Ads offers a variety of ad types, including native, interstitial, banner, in-stream video, and rewarded video ads.

With over 1 billion users, Facebook has utilized their massive resources to build out their ad network. Facebook Ads provide state-of-the-art tools, support, and valuable insights to grow ad revenue. Facebook Ads sets itself apart by offering a highly focused level of targeting. Facebook collects a vast amount of data from its users, thus Facebook Ads enables app publishers to target based on a variety of factors (interests, behaviors, demographics and more) with a level of granularity deeper than any other platform.

InMobi

InMobi Logo

InMobi offers a different way of targeting users, which they have coined “Appographic targeting”. “Appographic targeting” analyzes the user’s existing and previous applications rather than traditional demographics. If a user is known to book flights via an app, then related ads, such as that of hotels and tourism will be shown.

The InMobi Mediation platform enables publishers to maximize their ad earnings with unified auction solutions and header bidding for mobile apps.

TapJoy

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TapJoy has received increased consideration from mobile game developers since the platform integrates with in-app purchases. Studies show that mobile players will engage with advertisements if offered a reward. TapJoy has capitalized on this by introducing incentivized downloading, which provides mobile gamers with virtual currency through completing real world actions. For example, a user can earn virtual currency in the game they are playing by downloading a related game in the app store.

TapJoy provides premium content to over 20,000 games and works with major companies like Amazon, Adidas, Epic Games, and Gillette.

Unity Ads

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Unity, the popular mobile app development platform, launched Unity Ads in 2014. Since then, it’s become one of the premier mobile ad networks for mobile games. Unity Ads supports iOS and Android mobile platforms and offers a variety of ad formats. One of the major features is the ability to advertise In-App Purchases displayed in videos (both rewarded and unrewarded) to players.

On a targeting level, Unity Ads allows publishers to focus on players that are most likely to be interested in playing specific games based on their downloads and gameplay habits. Many of the leading mobile game companies use Unity to build their app and Unity Ads as their ad platform.

CONCLUSION

These are not the only mobile ad networks, but for app publishers looking to stay current, they are the premier platforms to research. Other platforms like media.net, Chartboost, Snapchat Ads, Twitter Ads, and AppLovin also merit consideration.

When it comes to advertising, every app and app publisher has different needs. Since advertising plays a massive role in generating revenue, mobile app developers set themselves up for success when they do the research, and can find what ad platforms are best suited to their product.

App Developers Take a Bigger Slice of the Pie with Android P

Android Pie (Image Via XDA Developers)

App developers looking to witness what Machine Learning can do to improve UI should take note of Android 9.0 Pie. First announced in March 2018, Android P was made public in August 2018. Android 9.0 marks a major overhaul of the Android OS focusing on UI and integrating Artificial Intelligence to optimize user experience.

AI HELPS ANDROID PIE HELP YOU

Android’s latest OS takes a big step forward integrating AI into the UI. The Android website advertises that “Android 9 Pie harnesses the power of AI for a truly intuitive experience”.

One of the major implementations of AI in Pie is called App Actions. Android 9.0 monitors your routines, processes data, and offers predicted actions directly in the phone’s app launcher when appropriate. For example, it can recommend a song to you on Spotify when you’re on your morning commute. Android has focused on quality over quantity with regard to App Actions and they are startlingly accurate—when it has enough data collected on how you use your phone, often it predicts exactly what you do next.

In addition to App Actions, Android Pie also offers Adaptive Battery and Adaptive Brightness. Android teamed up with the AI company DeepMind to create Adaptive Battery, an AI-based program that learns how you use your phone and optimizes usage so that inactive apps and services don’t drain the battery. Adaptive Brightness learns your preferred brightness settings and automatically adjusts them to your liking.

Those concerned with privacy should note that Android has stated that all machine learning is happening on the device rather than in the cloud.

ANDROID ADOPTS GESTURES OVER BUTTONS

Perhaps the biggest UI overhaul is the transition from buttons to gestures. Android P is following the  iPhone X’s lead in using gestures rather than buttons. This means UI is very home-screen button centric. The overhaul may be jarring to some. Luckily, app users can have it both ways as gesture navigation is adjustable in the phone’s settings.

Check out the video breakdown of the differences between Apple iPhone X and Android P gestures below.

THIS PIE’S GONNA HAVE SLICES

Android has announced App Slices in Android Pie, but has yet to unveil them at this time. When you search for an app on Android,  the app icon comes up. With App Slices, Android will not only pull up the icon, but will pull up actual information within apps and allow you to interact with the app directly within the search results. For example, if you search for Uber, it may bring up time & price estimates to go to commonly frequented locations and allow you to set a pick-up without having to open the app directly.

Android Slices present a great opportunity for app developers to create shortcuts to functions in their app. They also constitute the beginnings of Google’s approach to “remote content.” Learn more about Slices below:

APP LIMITS FOR ENCOURAGING HEALTHY USE

Addicted to your phone? Android P not only tracks the amount of time you spend on your phone, it allows users to set time limits for how long an app can be used for a day. App Time Limits prevent you from opening apps when you’ve gone over your limit with no option to ignore—the only way to access them again for the day is to turn the time limit off from the Settings page.

HUNGRY FOR PIE?

As with all Android OS’s, Android Pie will have a staggered release across devices. As of November 2018, it is available on Pixel phones as well as The Essential Phone.

Meanwhile, Android Pie is anticipated to be rolled out on many other phones by December 21st. For a comprehensive, frequently updated breakdown, check out Android Central’s list of the expected roll out dates for each phone manufacturer.

The Real Power of Artificial Intelligence

Artificial

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.

Android Oreo Serves Up the Sweets

Android Oreo

Like the candy, Google’s newest delectable dessert-themed operating system Android 8.0 Oreo offers the best of both worlds: crunchy cookie goodness of versatile functionality and the creamy frosting of beautiful UI and presentation.

PROJECT TREBLE 

Project Treble is one of the major aspects of Android Oreo that makes it a full 1.0 update. Project Treble is designed to reduce device fragmentation by making it easier for hardware manufacturers to issue updates on Android devices. The architecture redesign modularizes the Android OS away from the drivers and other hardware-specific code. By making it easier for manufacturers to update Android devices, Project Treble makes accessing the latest Android OS from your devices  easier than ever.

HIGH-PERFORMANCE BLUETOOTH AUDIO

Android Oreo is loaded up with BLUETOOTH 5 and LDAC, making Oreo capable of supporting audio quality that surpasses what the vast majority of high-end audio equipment can reproduce.

LDAC is a codec that supports the transfer of 24 bit, 96kHz audio via Bluetooth. The closest competitor is Qualcomm’s aptX HD which supports 24 bit, 48kHz technology. LDAC was created by Sony, who donated the codec to Android for Oreo as a part of the core AOSP code for other OEMS to implement.

Whereas previous iterations of Bluetooth offered a range of 50m-100m outdoors and 10m-20m indoors, Bluetooth 5 can reach up to 200m outdoors and 40m indoors. Additionally, Bluetooth 5 BLE doubles Bluetooth 4.x BLE’s data transfer rate with up to 2Mbps. The kicker is: Bluetooth 5 actually utilizes up to 2.5 times less power while increasing range and speed.

BATTERY LIFE

The Android Oreo update includes multiple initiatives designed to improve battery life. Background execution limits have been enacted to limit requests to scheduled windows of activity, resulting in longer battery life and less strain on the device by inactive apps.

Android Oreo places two major limitations on what apps can do while users aren’t directly interacting with them:

  1. Background Service Limitations limit the use of background services by idle apps. This does not apply to foreground apps, which are defined as apps with visible activity, apps with a foreground service, or apps that are connected to another foreground app.​
  2. Broadcast Limitations prevent apps from using their manifest to register for implicit broadcasts. Apps can still use their manifest to register for broadcasts at runtime and for explicit broadcasts targeted specifically at their app.

For the most part, app developers can work around these limitations using JobScheduler jobs. Android has also made several improvements to JobScheduler.

Background execution limits will have a major impact on the functionality of existing and future apps, check out a full breakdown of the new functionality directly from Android.

Additionally, Android Oreo comes with Vitals. Vitals is an initiative by Google that improves system performance and stability by offering developers various tools to monitor app usage on a device. Vitals enables developers to  optimize their apps for improved battery life and performance.

UI

Google’s strategy with OS updates has become more and more minimal in recent years. The last major visual OS overhaul was enacted by Google in Android 5.0 Lollipop. Android Oreo does not change the name of the game, but offers a variety of UI improvements.

DOWNLOADABLE FONTS: Android 8.0 Oreo offers support for apps to request fonts from a “provider” application, reducing the amount of disk space spent by apps on storing font libraries individually.

NOTIFICATION CHANNELS: Notifications have always been one of the strong suits of Android Operating Systems. With Android Oreo, app notifications must be sorted by the developer into channels based on type, so that the user can then customize what types of notifications they would like to receive and how they receive them.

For example, users can modify characteristics of notification channels that apply to all notifications in that channel, including:

  • Importance
  • Sound
  • Lights
  • Vibration
  • Show on lock screen
  • Override do not disturb

PICTURE IN PICTURE MODE: Oreo ports Android’s famous “Picture-In-Picture Mode” for phones and tablets. Picture-In-Picture Mode allows users to view multiple apps at the same time. It is most handy for watching video or having a video call while using another app.

TAKEAWAY

Overall, Android 8.0 Oreo delivers the goods. It’s sleek, supports the best audio quality available, allows more UI customizability, saves battery life, and it’s a major step toward conquering device fragmentation which has plagued Android since its inception.

Android O: What Google’s Latest OS Offers App Developers

On March 21st, Google unveiled the developer preview for the latest version of the largest OS in the world: Android O. For consumers, it means improved UI, design, battery life, & more. For app developers, it has far deeper implications. With release anticipated in Q3 2017, here is our rundown of the top takeaways about Android O for Android developers:

BATTERY LIFE

The main focus of Android O appears to be to continue Android Nougat’s initiative to reduce battery life. The OS will limit and manage what launched apps can do in the background when multiple apps are open. For example, if a user has a geolocation app open in the background while using another app, location updates will happen less frequently for the background app.

In technical terms, background execution & location limits have been reigned in, allowing the OS to better manage background activity. Background apps are defined by Google as apps showing no visible activity, no foreground service & not connected to a foreground app through its services. Location changes affect the following APIs:

  • Fused Location Provider (FLP): The local system service computes a new location for background apps only a few times each hour, according to the interval defined in the Android O behavior change. Foreground apps will not experience location sampling rates in relation to Android 7.1.1 (API level 25).
  • Geofencing: Background apps can receive geofencing transition events more frequently than from FLP.
  • GNSS Measurements: Callbacks registered to receive outputs from GnssMeasurement and GnssNavigationMessage will stop executing for background apps.
  • Location Manager: Location updates will be provided to background apps only a few times per hour according to the interval defined in the Android O behavior change.

NOTIFICATION CHANNELS

Android OS’s have always thrived in the notification department. Android O allows developers to group notifications into channels. Developers must select a channel for each distinct type of notification they send with the goal of making things easier and more customizable for the user. For example, a user can turn off the “Sports” notification channel from the New York Times app if they are already getting sports notifications from the ESPN app.

Developers can also allow user behavior to dictate notification channels. For example, the developer of a messaging app can create separate notification channels for each of a user’s messaging threads.

WI-FI AWARE

Wi-Fi Aware, or Neighbor Awareness Network (NAN), allows devices to discover and connect directly with each other without any other connectivity between them, like Wi-Fi Access Point or Cellular. Two phones can connect with each other with NAN and share data at high speeds without any additional apps or configuration, opening up tons of possibilities for developers.

Learn more about Wi-Fi Aware:

HI-FI BLUETOOTH AUDIO

Android O supports Hi-Fi Bluetooth audio. While the quality of the audio still depends on the speaker or headphone through which one listens, this is a major improvement for music lovers.

ADAPTIVE ICONS

Android O will introduce adaptive launcher icons. Adaptive icons support visual effects and can display a variety of shapes across different device models. Adaptive icons are a major tool for developers to guide the user’s eye and enhance UX. Check out Android’s developer site to learn more.

RELEASE SCHEDULE

via Android Developers

via Android Developers

The O Developer preview will run from March 21st to the final Android O public release anticipated in Q3 2017. Android will provide incremental updates in mid-May, June, & July. Until Q3 2017, the onus is on Android developers to prepare their future and existing apps for the latest operating system.

SEO Pro Tips: Best Practices for Meta Descriptions

Last week, we explored the art of perfecting title tags for SEO dominance. This week, we’ll explore another vital meta tag: the meta description.

The meta description is the text that appears below the link in SERPs, as below:

Meta descriptions should be about 135 – 160 characters long, although Google has tested longer snippets. Any time quotes are used in the meta description, Google cuts the text off. To prevent meta descriptions from being cut off, it’s best to remove all non-alphanumeric characters.

Google uses meta descriptions to pull preview snippets on SERPs and return results when searchers use advanced search operators to match meta tag content, but unlike title tags, meta descriptions do not directly influence Google’s ranking algorithms for normal web search since meta description keywords are not ranked.

While meta descriptions do not directly affect SEO, they do indirectly impact it. The prominence of meta descriptions in SERPs makes them a very valuable UX component and a tool for enticing searchers. While keywords do not affect ranking, they are bolded in the meta-description, which attracts the eye and can help influence a searcher’s decision to click. Thus the use of keywords in meta descriptions can be beneficial to increasing Click Through Rate (CTR). The Click-Through-Rate is the ratio of searchers who click on a page compared to how many searchers see it. CTR is highly valued in search rankings. Since meta descriptions are one of the first things that a searcher will see, they can influence them to click, increasing CTR and boosting SEO.

The ideal meta description articulates the value proposition which a company or web page offers in a precise way while taking into consideration the competition that the page is up against in SERPs. It assumes an active voice and includes a call to action. Web developers can enrich a meta description by using schema markups like star ratings, customer ratings, or product information, to increase the appeal. See below for example:

Image via Google Support

Sometimes meta descriptions are unnecessary. Moz advises if a page is targeting between one and three high volume search terms or phrases, it’s best to write a meta description targeting users performing those searches. If the web page is targeting long-tail traffic (three or more keywords, like a blog with hundreds of entries), it may be best to let the search engines extract the relevant text from the site since they will pull text specifically targeting the user’s search. A blog might be targeting one audience in their keywords, but have content on so many topics, they can be found through any number of search terms. A meta description specified for a page with a lot of content may detract from the relevance that the search engine can create organically by pulling a text description from the page which is relevant to the specific search.

Like title tags, repeating meta descriptions or making them incomprehensible will result in penalization from Google. Meta descriptions can be tricky since they are longer and a bad meta description can be worse than none at all. With the right title tags and website content, meta descriptions can be a major UX tool to drive traffic to a web page.

SEO Pro Tips: Perfecting the Title Tag

Over 100 billion searches per month are made on Google worldwide. Search Engine Optimization (or SEO) has become one of the top marketing disciplines for anyone trying to drive web page traffic and digital revenue.

Title tags are one of the most important facets of SEO. Title tags are the titles of web pages that display in search engine results pages (SERPs) and as the clickable headline for a given result. They are the most obvious element in a search result and are pulled to the forefront of SERPs (Search Engine Result Pages). They display as below:

Social networks use title tags to determine what to display in the link preview when you share a page:

Title tags are extremely important for SEO, social sharing, and UX. They are one of the major on-page SEO elements. Keywords in title tags will factor heavily into a web page’s rank in any keyword-based search query.

Below find some of the best practices for crafting the perfect title tag.

KEYWORD EFFECTIVELY: Since title tags have a direct affect on SEO, effective keywording is crucial. Putting important keywords in the front of the title tag will increase SEO rankings, while keywords and search phrases at the end of the title tag will be less of a factor. For this very reason, it is best to put a company or website name at the end of the title tag, unless that name is an important keyword phrase. Keyword stuffing, or overloading keywords without making sense, will result in penalization. Ultimately, keywording effectively means writing clearly to an intended audience while factoring in important search phrases.

OPTIMIZING LENGTH: Title tags are not measured by length, but by a 600-pixel limit. Pixels do not equate to characters since certain letters require more pixels to compose than others. 600 pixels generally equate to about 50-60 characters. Measuring pixels can be made easy with this pixel length measurement tool by Search Wilderness.

RESEARCH, RESEARCH, RESEARCH: Statistics show 48% of marketers worldwide identified keyword/phrase research as the most effective SEO tactic. Effective research means honing in on your audience and enacting relevant keyword searches to observe the organic search competition. It is also important to note the inorganic competition: promoted ads for web pages that are boosted to the top of searches by Google AdWords.

Having a solid understanding of what a web page is up against in search engines helps web developers optimize their pages to stand out in the face of the competition. Since the competition and search rankings are constantly changing, research is an ongoing process. 34% of marketers cite frequent website updates as a key to their success.

PIPES “|”: Pipes can be used to punctuate and divide sentiments while minimizing punctuation and word count. See below for an example:

As with any copywriting, writing for an audience is crucial. Since the Title Tag is often the first thing a search user will see about your website, it is ultimately very important that it clearly communicates the subject of the web page and entices the intended searcher. Effective title tags are the first step on the way to SEO dominance.

Stay tuned for next time when we explore how to write an effective meta description!

Everything You Need to Know About Machine Learning

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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.