Posts from the ‘Google’ Category

Apr 28

LinkedIn Best Companies To Work For In 2021 Dominated By Tech

Four of LinkedIn’s top ten companies to grow your career in 2021 are tech leaders.
Amazon is the highest rated company, followed by Alphabet (2^nd), IBM (6^th), and Apple (8^th).
15 of the 50 top companies in the U.S. are in the tech industry, including Oracle, Salesforce, and SAP.

These and many other insights are from the LinkedIn Top Companies 2021: The 50 best workplaces to grow your career in the U.S. published today. All 50 companies are currently hiring and have over 300,000 jobs available right now. LinkedIn’s analysis of the best companies to grow your career spans 20 countries, including Australia, Brazil, Canada, China, France, Germany, India, Italy, Japan, Malaysia, Mexico, the Netherlands, the Philippines, Saudi Arabia, Singapore, Spain, Qatar, the UAE, and the U.K.

LinkedIn is relying on a new methodology for the 2021 Top Companies Report. They’re basing the methodology has seven key pillars, each revealing an important element of career progression: the ability to advance, skills growth, company stability, external opportunity, company affinity, gender diversity, and educational background. LinkedIn provides an in-depth description of how they built their methodology here.

The 10 Best Companies To Grow Your Career In 2021

Amazon – According to LinkedIn, Amazon has built an innovative remote-onboarding system, and it has more than 30,000 openings now. The fastest-growing skills in demand at Amazon include User Experience Design (UED), Digital Illustration, and Interaction Design. LinkedIn’s analysis shows the most in-demand jobs are Health And Safety Specialist, Station Operations Manager, Learning Manager.

Alphabet, Inc – Planning to add at least 10,000 jobs in the U.S. alone and investing $7B in data centers and offices across 19 states, Alphabet grew revenue 47% last year, reaching $13B. According to LinkedIn, the most in-demand jobs are Digital Specialist, Field Sales Specialist, and Business Systems Analyst.

JPMorgan Chase & Co. – JPMorgan now offers 300 accredited skills and education programs to its workers, and the bank has been boosting wages for thousands of customer-facing roles to $16-$20 an hour. The most in-demand jobs include Market Specialist, Software Engineering Specialist, and Mortgage Underwriter.

AT&T – 2020 was a tough year for AT&T, increasing the urgency the company has to grow its wireless and WarnerMedia businesses. Due to the pandemic, the company had to close hundreds of stores. Fortunately, AT&T was able to help the employees affected by the closures to find new jobs. The most in-demand jobs are Service Analyst, Trading Analyst, and Investment Specialist.

Bank of America – Bank of America rose to the challenges of 2020, quickly redeploying almost 30,000 employees to assist in its role facilitating the government-backed Paycheck Protection Program. The most in-demand jobs are Trading Analyst, Investment Specialist, and Financial Management Analyst.

IBM – More than one-third of IBM’s revenue now comes from work related to cloud computing. The company’s Red Hat unit is a leading contributor to that growth, prizing skills such as Linux, Java, Python, and agile methodologies. IBM also is a leader in hiring autistic people through its Neurodiversity program. Most in-demand jobs include Back End Developer, Enterprise Account Executive, and Technical Writer.

Deloitte – Deloitte’s key activities span audit, assurance, tax, risk, and financial advisory work, as well as management consulting. It’s aiming to hire 19,000 people in the year ending May 29. Top recruiting priorities currently include cybersecurity, cloud computing, and analytics specialists.

Apple – LinkedIn finds that Apple is committed to building an inclusive culture. Over half of its new hires in the U.S. represent historically underrepresented groups in tech — and the company claims to have achieved pay equity in every country where it operates—looking for an in? Apple has nearly 3,000 open jobs in the U.S. right now, ranging from its “genius” role at its retail stores to executive assistants and software engineers.

Walmart – In February, the retail giant promised further raises to over 400,000 of its people and months later announced it would increase the share of its hourly store employees who work full-time to over 66% (up from 53% five years ago). Meanwhile, Walmart continues to think beyond the store as it ventures deeper into the e-commerce realm. Most in-demand jobs include Operational Specialist, Fulfillment Associate, and Replenishment Manager.

EY – The accounting firm spent $450 million on employee training in 2020. And it is planning to hire over 15,000 people in the next year. With that much talent coming in, EY is focused on bringing in workers with diverse backgrounds, focusing on gender identity, race, and ethnicity, disability, LGBT+, and veterans. The most in-demand jobs include Strategy Director, Business Transformation Consultant, and Information Technology Consulting Manager.

Sep 9

Google Needs To Make Machine Learning Their Growth Fuel

In 2017 Google outspent Microsoft, Apple, and Facebook on R&D spending with the majority being on AI and machine learning.
Google needs new AI- and machine learning-driven businesses that have lower Total Acquisition Costs (TAC) to offset the rising acquisition costs of their ad and search businesses.
One of the company’s initial forays into AI and machine learning was its $600M acquisition of AI startup DeepMind in January 2014.
Google has launched two funds dedicated solely to AI: Gradient Ventures and the Google Assistant Investment Program, both of which are accepting pitches from AI and machine learning startups today.
On its Q4’17 earnings call, the company announced that its cloud business is now bringing in $1B per quarter. The number of cloud deals worth $1M+ that Google has sold more than tripled between 2016 and 2017.
Google’s M&A strategy is concentrating on strengthening their cloud business to better compete against Amazon AWS and Microsoft Azure.

These and many other fascinating insights are from CB Insight’s report, Google Strategy Teardown (PDF, 49 pp., opt-in). The report explores how Alphabet, Google’s parent company is relying on Artificial Intelligence (AI) and machine learning to capture new streams of revenue in enterprise cloud computing and services. Also, the report looks at how Alphabet can combine search, AI, and machine learning to revolutionize logistics, healthcare, and transportation. It’s a thorough teardown of Google’s potential acquisitions, strategic investments, and partnerships needed to maintain search dominance while driving revenue from new markets.

Key takeaways from the report include the following:

Google needs new AI- and machine learning-driven businesses that have lower Total Acquisition Costs (TAC) to offset the rising acquisition costs of their ad and search businesses. CB Insights found Google is experiencing rising TAC in their core ad and search businesses. With the strategic shift to mobile, Google will see TAC escalate even further. Their greatest potential for growth is infusing greater contextual intelligence and knowledge across the entire series of companies that comprise Alphabet, shown in the graphic below.

Google has launched two funds dedicated solely to AI: Gradient Ventures and the Google Assistant Investment Program, both of which are accepting pitches from AI and machine learning startups today. Gradient Ventures is an ROI fund focused on supporting the most talented founders building AI-powered companies. Former tech founders are leading Gradient Ventures, assisting in turning ideas into companies. Gradient Venture’s portfolio is shown below:

In 2017 Google outspent Microsoft, Apple, and Facebook on R&D spending with the majority being on AI and machine learning. Amazon dominates R&D spending across the top five tech companies investments in R&D in 2017 with $22.6B. Facebook leads in percent of total sales invested in R&D with 19.1%.

Google AI led the development of Google’s highly popular open source machine software library and framework Tensor Flow and is home to the Google Brain team. Google’s approach to primary research in the fields of AI, machine learning, and deep learning is leading to a prolific amount of research being produced and published. Here’s the search engine for their publication database, which includes many fascinating studies for review. Part of Google Brain’s role is to work with other Alphabet subsidiaries to support and lead their AI and machine learning product initiatives. An example of this CB Insights mentions in the report is how Google Brain collaborated with autonomous driving division Waymo, where it has helped apply deep neural nets to vehicles’ pedestrian detection The team has also been successful in increasing the number of AI and machine learning patents, as CB Insight’s analysis below shows:

Mentions of AI and machine learning are soaring on Google quarterly earnings calls, signaling senior management’s prioritizing these areas as growth fuel. CB Insights has an Insights Trends tool that is designed to analyze unstructured text and find linguistics-based associations, models and statistical insights from them. Analyzing Google earnings calls transcripts found AI and machine learning mentions are soaring during the last call.

Google’s M&A strategy is concentrating on strengthening their cloud business to better compete against Amazon AWS and Microsoft Azure. Google acquired Xively in Q1 of this year followed by Cask Data and Velostrata in Q2. Google needs to continue acquiring cloud-based companies who can accelerate more customer wins in the enterprise and mid-tier, two areas Amazon AWS and Microsoft Azure have strong momentum today.

Jan 13

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By 2020 83% Of Enterprise Workloads Will Be In The Cloud

Digitally transforming enterprises (63%) is the leading factor driving greater public cloud engagement or adoption today.
66% of IT professionals say security is their most significant concern in adopting an enterprise cloud computing strategy.
50% of IT professionals believe artificial intelligence and machine learning are playing a role in cloud computing adoption today, growing to 67% by 2020.
Artificial Intelligence (AI) and Machine Learning will be the leading catalyst driving greater cloud computing adoption by 2020.

These insights and findings are from LogicMonitor’s Cloud Vision 2020: The Future of the Cloud Study (PDF, free, opt-in, 9 pp.). The survey is based on interviews with approximately 300 influencers LogicMonitor interviewed in November 2017. Respondents include Amazon Web Services AWS re:Invent 2017 attendees, industry analysts, media, consultants and vendor strategists. The study’s primary goal is to explore the landscape for cloud services in 2020. While the study’s findings are not statistically significant, they do provide a fascinating glimpse into current and future enterprise cloud computing strategies.

Key takeaways include the following:

83% Of Enterprise Workloads Will Be In The Cloud By 2020. LogicMonitor’s survey is predicting that 41% of enterprise workloads will be run on public cloud platforms (Amazon AWS, Google Cloud Platform, IBM Cloud, Microsoft Azure and others) by 2020. An additional 20% are predicted to be private-cloud-based followed by another 22% running on hybrid cloud platforms by 2020. On-premise workloads are predicted to shrink from 37% today to 27% of all workloads by 2020.

Digitally transforming enterprises (63%) is the leading factor driving greater public cloud engagement or adoption followed by the pursuit of IT agility (62%). LogicMonitor’s survey found that the many challenges enterprises face in digitally transforming their business models are the leading contributing factor to cloud computing adoption. Attaining IT agility (62%), excelling at DevOps (58%), mobility (55%), Artificial Intelligence (AI) and Machine Learning (50%) and the Internet of Things (IoT) adoption (45%) are the top six factors driving cloud adoption today. Artifical Intelligence (AI) and Machine Learning are predicted to be the leading factors driving greater cloud computing adoption by 2020.

66% of IT professionals say security is their greatest concern in adopting an enterprise cloud computing strategy. Cloud platform and service providers will go on a buying spree in 2018 to strengthen and harden their platforms in this area. Verizon (NYSE:VZ) acquiring Niddel this week is just the beginning. Niddel’s Magnet software is a machine learning-based threat-hunting system that will be integrated into Verizon’s enterprise-class cloud services and systems. Additional concerns include attaining governance and compliance goals on cloud-based platforms (60%), overcoming the challenges of having staff that lacks cloud experience (58%), Privacy (57%) and vendor lock-in (47%).

Just 27% of respondents predict that by 2022, 95% of all workloads will run in the cloud. One in five respondents believes it will take ten years to reach that level of workload migration. 13% of respondents don’t see this level of workload shift ever occurring. Based on conversations with CIOs and CEOs in manufacturing and financial services industries there will be a mix of workloads between on-premise and cloud for the foreseeable future. C-level executives evaluate shifting workloads based on each systems’ contribution to new business models, cost, and revenue goals in addition to accelerating time-to-market.

Microsoft Azure and Google Cloud Platform are predicted to gain market share versus Amazon AWS in the next three years, with AWS staying the clear market leader. The study found 42% of respondents are predicting Microsoft Azure will gain more market share by 2020. Google Cloud Platform is predicted to also gain ground according to 35% of the respondent base. AWS is predicted to extend its market dominance with 52% market share by 2020.

Nov 20

Google Getting More Aggressive In The Cloud

Deutsche Bank estimates Google Cloud Platform (GCP) has a $750M revenue run-rate estimate today.
The combined revenues of AWS, Microsoft Azure, and GCP are still less than $15B for a market penetration of just 1%-2% of the Total Available Market (TAM).
During the 2Q16 call, Google called out Cloud as the primary driver of the re-accelerating growth for Licensing and Other revenue, the first time the business has been called out in pole position.
Recent Orbitera and Apigee acquisitions underscore Google’s new focus and aggressiveness to grow GCP. Google has spent $1B+ on Cloud M&A over the past 12 months.
Deutsche Bank predicts GCP is preparing a series of new product announcements in September to strengthen their customer-facing roadmap further.

These and other insights are from Deutsche Bank Markets Research study, Google Getting More Aggressive In The Cloud, (client access) published 8 September 2016 by Ross Sandler Karl Keirstead, Deepak Mathivanan, Aki Aggarwal and Taylor McGinnis. Deutsche Bank found that Google is investing heavier in the cloud, making a financial commitment with over $1B in acquisitions in the past year including the recent Apigee deal. The study is based on interviews Deutsche Bank contacted with channel partners, prospects, partners, and customers. Despite the renewed focus on growth, Deutsche Bank predicts that GCP would continue to trail AWS and Microsoft Azure for the foreseeable future.

Key takeaways of the Deutsche Bank Markets Research survey include the following:

Deutsche Bank defines the Total Available Market (TAM) enterprise IT spend in nine categories that together account for over a $1T TAM. Deutsche Bank defines the Enterprise IT spending market by combining storage, network equipment, infrastructure software, IT outsourcing and support, data management software, BI/analytics, application software and consulting Deutsche Bank sees AWS make significant progress across a wide spectrum of their taxonomy categories.

GCP new product launches are concentrating on machine learning, data analytics and security, including data encryption and identity and access management. Google’s aggressiveness regarding the cloud is most visible from their new service announcements shown in the table below. Recent announcements include SQL Server Images, where customers can now natively spin up Microsoft database instances on GCP, akin to AWS RDS for SQL Server. GCP also announced a second generation version of Cloud SQL, its cloud-hosted alternative to MySQL and AWS Aurora. While all of these announcements provide GCP with greater potential to compete against AWS and Microsoft Azure, Google’s two larger competitors have formidable momentum in enterprises.

Aggressive build-out of global infrastructure locations continues. Google announced during their 4Q15 earnings call they would build 12 new regions in 2016 and 2017. Of the 12 new planned GCP regions, the US Western region in Oregon opened in July 2016, and Google has said that the new Tokyo region will be available later this year, leaving ten more regions to be added in 2017.

Google continues to believe in the importance of machine learning and artificial intelligence. Deutsche Bank interviews with GCP customers confirmed interest in using machine learning and artificial intelligence on the Cloud. Customers also perceive GCP is well ahead of AWS and Azure in this regard.

Google is quickly hiring enterprise sales reps in an attempt to close the sales gap between themselves and AWS & Microsoft Azure. Deutsche Bank found that Google has been “hiring very aggressively” to scale its enterprise sales rep capacity and also retrofitting existing sales reps from elsewhere in Google into GCP.

GCP is gaining share rapidly within the startup community. Deutsche Bank spoke with customers who estimated that 25% startups are using GCP today (with 75% on AWS), while another estimated the ratio to be 20%/80%. While both agreed that a couple of years ago only 10% of startups were using GCP (with 90% using AWS). During the GCP NEXT Asia-Pacific keynote earlier this month Google disclosed that Snapchat “is one of our largest customers,” making up to 2 million queries per second and consuming more Google bandwidth than any other organization except for YouTube.

Recent Orbitera and Apigee acquisitions underscore Google’s new focus and aggressiveness to grow GCP. Last month Google acquired Orbitera, a small cloud commerce platform. Orbitera simplifies the buying and selling of cloud-based software by providing vendors with packaging and provisioning, billing, and marketplace solutions on AWS and Azure. Earlier this month Google acquired Apigee for $625M, which is 5.2x Apigee’s FY17e revenues of $120M. Apigee is expected to grow by 30%-35% in The company focuses on larger enterprises (Walgreens, Nike, Target, AT&T) and despite an ongoing mix shift to the cloud or SaaS model, it still has a legacy on-premise license/maintenance business.

Google is very focused on building relationships with all systems integration (SI) firms but that building out a GCP channel is proving to be challenging. Deutsche Bank believes that Microsoft is also finding it tough to build out it’s Azure channel, in part because many traditional partners and resellers struggle with how they can monetize Azure, given its different price points and the lower services attach rate

Dec 27

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How Cloud Computing Is Accelerating Context-Aware Coupons, Offers and Promotions

Retailers and marketers often face the challenge of getting coupons, offers and promotions delivered at the perfect time and in the right context to their customers.

The rapid advances in cyber foraging, contextual computing and cloud computing platforms are succeeding at revolutionizing this aspect of the retail shopping experience. Context-aware advertising platforms and strategies can also provide precise audience and segment-based messaging directly to customers while they are in the store or retail outlet.

What makes context-aware advertising so unique and well adapted to the cloud is the real-time data integration and contextual intelligence they use for tailoring and transmitting offers to customers. When a customer opts in to retailer’s contextually-based advertising system, they are periodically sent alerts, coupons, and offers on products of interest once they are in or near the store. Real-time offer engines chose which alerts, coupons or offers to send, when, and in which context. Cloud-based analytics and predictive modeling applications will be used for further fine-tuning of alerts, coupons and offers as well. The ROI of each campaign, even to a very specific audience, will be measurable. Companies investing in cloud-based contextual advertising systems include Apple, Google, Greystripe, Jumptap, Microsoft, Millennial Media, Velti and Yahoo.

Exploring the Framework of Me Marketing and Context-Aware Offers

A few years ago, a student in one of my MBA courses in international marketing did their dissertation on cyber foraging and contextual mobile applications’ potential use for streamlining business travel throughout Europe. As a network engineer for Cisco at the time, he viewed the world very systemically; instead of getting frustrated with long waits he would dissect the problem and look at the challenges from a system-centric view. The result was a great dissertation on cyber foraging and the potential use of Near Field Communications (NFC) and Radio Frequency Identification (RFID) as sensors to define contextual location and make business travel easier. One of the greatest benefits of teaching, even part-time, is the opportunity to learn so much from students.

I’ve been following this area since, and when Gartner published Me Marketing: Get Ready for the Promise of Real-Time, Context-Aware Offers in Consumer Goods this month I immediately read it. Gartner is defining Me Marketing as real-time, context-aware offers in grocery stores. Given the abundance of data on transactions that occur in grocery stores, Gartner is predicting this will be the most popular and fastest-growing area of context-aware offers. The formula for Me Marketing is shown below:

The four steps of the Me Marketing formula are briefly described as follows:

Consumer Insight and Permission – The first step of the framework and the most difficult from a change management standpoint, this requires customers to opt in to receiving alerts, coupons, offers and promotions. The best retailers also have invested heavily in security and authentication technologies here too.

Delivery Mechanism and In-the-Moment Context – The real-time offer engine is used to determining which coupons, offers and promotions are best suited for a specific customer based on their shopping patterns, preferences and locations.

Select Best Offer – Next, the real-time offer engine next defines a very specific product or service offer based on location, previous purchase history, social media analysis, predictive and behavioral analysis, and previous learned patterns of purchasing.

Redemption – The purchase of the item offered. Initial pilots have shown that less frequent yet highly relevant, targeted offers have a higher redemption rate. It is encouraging to see that early tests of these systems show that spamming customers leads to immediate opt-outs and in some cases shopping competitors.

A Short Overview of Contextual Advertising and the Cloud

Cloud-based systems and applications are necessary for retailers to gain the full value that contextual advertising can provide. This includes the social context, with specific focus on aggregation and analysis of Social CRM, CRM, and social media content, in addition to behavioral analytics and sentiment analysis. It also includes the previous browsing, purchasing, returns and prices paid by product for each customer. Cloud-based integration architectures are necessary for making contextual advertising a reality in several hundred or even thousands of retail stores at the same time.

Geographical data and analysis is also essential. RFID has often been included in cyber foraging and contextual advertising pilots, in addition to NFC. As Global Positioning System (GPS) chip sets have dropped in price and become more accurate, companies including Google, Microsoft and Yahoo are basing their contextual advertising platforms on them. Finally the activity or task also needs to have a contextual definition.

Combining all three of these elements gives the context of the customer in the retail store. The figure below is from Three-Dimensional Context-Aware Tailoring of Information. This study also took into account how personas are used by companies building cloud-based contextual advertising systems. The taxonomies shown in the figure are used for building personas of customers.

There are many pilot projects and enterprise-wide system tests going on right now in the area of cloud-based contextual advertising. One of the more interesting is an application suite created entirely on Google App Engine, Android, and Cloud Services. The pilot is explained in the study Exploring Solutions for Mobile Companionship: A Design Research Approach to Context-Aware Management. The following figure shows a diagram of the suite. This pilot uses Cloud to Device Messaging (C2DM) which is part of the Android API to link the Google App Engine server and Android client. Google will most likely add more depth of support for C2DM as it plays a critical role in contextual system development.

Benefits of a Cloud-based Contextual Advertising Platform

For the customer, cloud-based advertising systems over time will learn their preferences and eventually impact the demand planning and forecasting systems of retailers. This translates into the customer-centric benefits of products being out of stock less. In addition, customers will receive more relevant offers. The entire shopping experience will be more pleasant with expectations being met more often.

For the retailer, better management of product categories and more effective gross margin growth will be possible. Having real-time analytics of each coupon, offer and promotion will also give them immediate insights into which of their selling strategies are working or not.

For the manufacturer, the opportunity to finally understand how customers respond at the store level to promotions, programs including the results of co-op funds investment and pricing strategies will be known. The manufacturers who partner with retailers using these systems will also have the chance at attaining greater product differentiation as their coupons, offers and promotions will only go to the most relevant customers.

References:

Me Marketing: Get Ready for the Promise of Real-Time, Context-Aware Offers in Consumer Goods Published: 24 December 2012 Analyst(s): Don Scheibenreif, Dale Hagemeyer

Tor-Morten Grønli, Ghinea, G., & Bygstad, B. (2013). Exploring Solutions for Mobile Companionship: A Design Research Approach to Context-Aware Management. International Journal of Information Management, 33(1), 227. http://www.sciencedirect.com/science/article/pii/S0268401212001259

Tor-Morten Grønli, & Ghinea, G. (2010). Three-Dimensional Context-Aware Tailoring of Information. Online Information Review, 34(6), 892-906. http://www.emeraldinsight.com/journals.htm?articleid=1896452

Aug 27

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How Google is Driving Mobile Video Market Growth

Google’s top advertising customers are pushing for convergence of mobile and video quickly, which is turning into a strong catalyst of growth of the global mobile video market. With their largest advertising customers wanting greater flexibility in bringing video to mobile devices, Google will make significant strides this year to make that happen.

During their latest earnings call, Google execs said that Android, Chrome and YouTube are the highest priority areas of their business. I’ve been following the last year of earnings calls closely, and it’s clear that Google’s largest advertising customers are pushing the company to bring video to mobile at a level of performance and usability not accomplished yet. The Q2, 2012 earnings call transcript makes this point clear which can be accessed here Google’s Management Discusses Q2 2012 Results – Earnings Call Transcript.

Mobile and Video: Transforming Convergence Into Cash

Over the last year, Google executives have mentioned the growth of YouTube and its quick evolution from a content management system to a profitable advertising platform. During the Q1, 2012 earnings call held on April 12, 2012 the following points were made:

Google reported they had over 800 million monthly users uploading over an hour of video per second

U.K. mobile operator O2 used YouTube as the foundation of a brand launch that year with support for 100 new original channels completed and launched

Global product launch plans from GM, Toyota and Unilever and several other large advertising accounts are also underway

During the Q2, 2012 earnings call, Nikesh Arora, Senior Vice President and Chief Business Officer started his comments regarding the YouTube business with the statement “I think in 2007 it was when newspapers frequently said YouTube is groping for an effective business model. I think we can declare we found our model.” Immediately after making this statement, Mr. Arora mentioned that yearly account signups have doubled year-over-year and users are uploading over 72 hours of video every minute. He also mentioned that “thousands of partners are making six figures and we’re proud to work with major record labels in Hollywood studios on this platform.”

The call continued with the points made of Danish advertisers shifting their television advertising dollars to YouTube and other Google branding solutions. Additional companies mentioned on the call using YouTube-based advertising include Denon, Shire, and Intel. Clearly these companies have major product introductions coming up and see mobile video as perfect for reaching more potential customers than ever before.

Google’s Challenge: Keep Content Quality and User Experience Constantly Improving

If Google is going to attain the full revenue potential of YouTube as an advertising platform, they’ll need to focus on the following factors:

Create Application Programmer Interfaces (APIs) and easy-to-use programming tools for quickly creating mobile-optimized sites. As Gartner studies have shown, video on telephones is most often used as a time-filler, with a median length of 2 minutes, 46 seconds.

YouTube will need to support more optimized mobile-based video browsers that can support contextual search. This will be a core requirement for the enterprise, specifically in the areas of mobile customer care, mobile commerce and mobile health.

More extensive analytics in YouTube than are available today, specifically tying into to major marketing strategies including product introductions. It is becoming common knowledge that videos improve viewer engagement and prospects attribute a more positive shopping experience when they are used. Luxury brands are investing heavily in this technology including BMW, Burberry, Channel, Louis Vuitton and many others.

A Google/Ipsos OTX MediaCT smartphone users study completed in April, 2011 shows that 77% of smartphone users said that their most visited site was a mobile search engine.

Mobile Video: The Market YouTube Built

The size of the worldwide mobile video market was comprised of 429 million mobile video users in 2011, projected to grow exponentially to 2.4 billion users by 2016. Smartphones and tablet sales will contribute 440 million new mobile video users during the forecast period. These market estimates are from the recently published Gartner report, Market Trends: Worldwide, the State of Mobile Video, 2012.

Additional take-aways from this report include the following:

Allot Communication’s reports that mobile streaming grew 93% in the first half of 2011; Allot also reports that the usage of YouTube’s mobile channel grew by 152% and YouTube generated 22% of all mobile video traffic in the first half of 2011. YouTube reports getting 400 million video views a month globally.

Gartner reports from a survey completed in the 4^th quarter of 2010 that 32% of mobile enterprise users watch short videos from YouTube and other sites optimized for video streaming.

The fastest growth for mobile video will be in Latin America as smartphone adoption continues to accelerate, replacing traditional cell phones in these markets. Asia/Pacific will have the highest number of mobile video users at 541 million by 2016. Both of these markets will benefit from low-cost smartphones being produced by contract manufacturers who are becoming the dominant production strategy of brand leaders globally. The following graphic shows the Mobile Video User Forecast by Region, Worldwide, 2008 – 2016.

By 2016, close to 60% of professionally developed mobile video content will be delivered via mobile-optimized websites that also have enhanced contextual search functionality included in the content management systems.

Mobile customer care, mobile commerce and mobile health will be the three primary industry drivers in the near-term of mobile video market, emerging as growth catalysts of this emerging market.

Cisco’s Visual Networking Index study reports that last year, mobile video accounted for 56% of all mobile data traffic.

3G/4G connections are emerging as a powerful catalyst of mobile video growth. Gartner is forecasting that the worldwide share of mobile video connections on 3G/4G will increase from 18% in 2011 to 43% in 2015. In more established markets incouding North America and Western Europe, the percentage of 3G/4G connections is expected to be as high as 80% and 96% respectively.

Gartner projects that 70% of mobile video users will use only Wi-Fi to view mobile video, with the remainder of the market relying on a mix of cellular and Wi-Fi networks to gain access and also upload content. The following figure shows the Mobile Video User Forecast by Network Type, Worldwide, 2008 – 2016.

Source: Market Trends: Worldwide, the State of Mobile Video, 2012. Gartner Group. Published: 10 February 2012 ID:G00223693 Author: Shalini Verma. Link: http://www.gartner.com/id=1920315