Tablets – Why Marketers need to move out of the “Tablet – a Fad” Perspective!

For many of the marketers out there – there is not a great case for Tablets and Smartphones together. Most of them view tablets as a passing fad. This equation is perhaps complicated by the announcement of Phablets as a hybrid form and use factor! However, is Tablet really a fad?

A recent report published by the Adobe Digital Index is an eye opener. For February 2013, Tablets are attributed to be driving more traffic to websites than smartphones. The report is based on 100 billion visits to more than 1,000 websites worldwide over the last year – hence this isnt a fluke that you had blow over. Adobe attributes this shift in web browsing patterns primarily to the device’s form factor, which lends itself to leisurely (and more comfortable) browsing than smaller touch devices.

Listing down a key points on how and why Tablets are not a fad. They are here for good-
1. Frankly, with both WiFi Tablets and Entry-level Smartphones penetrating the $50 price point – the screen size is a big enabler for tablets.
2. As WiFi hotspot roll outs gather momentum – Tablets will push more and more of data.
3. So while Smartphone gathers numbers in the low end – it is the larger screen size devices (3.5″ – 4.0″ – 5″ – 7″- 9.7″) which will posssibly drive higher data consumption.
4. The customer at the economy end of connected devices ($50-$100) tends to use his device as a media machine – again for the $50-70 price – a tablet provides greater value than a 2.8″-3.5″ smartphone given the profusion of pirated content.
5. Tablets are also driving penetration across segments such as education, insurance for the large screen internet access advantage
6. For the Phablet space – this is a sub-category branching out into becoming a category by itself – but its numbers will take some building up – and the pricing still is $200 & above.
7. With tablet growth rates still well above smartphone growth rates, expect this gap to widen
8. Traditionally because of the higher screen size the engagement time on tablets has been higher than the smartphones as well.

Interestingly enough, in mature economies, Tablets have found yet another niche. Tablets are increasingly being used shopping activities.Adobe found that 13.5% of all online sales were transacted via tablets during the recent holiday season. Furthermore, as of January 2012, researchers found that consumers using tablets spent 54 percent more time per online order than their counterparts on smartphones, and 19 percent more than desktop/laptop users.

Thus the key take away from the Adobe report is this – tablets and smartphones are two different animals. Based on consumer use cases, one does not replace the other because mobile device owners are using tablets and smartphones to accomplish different tasks. This has implications on the way e-commerce companies as well as media companies and online content distributors would play up to serve the user. So this really gets into single device – multi use cases scenarios – all of is still building.

Thus i come back to my initial point – Marketers who are apprehensive of the scale and scope of tablets and are unable to fix “proper” answers to tablets, need to understand, there is no single answer… and the answers too are evolving at a fast clip! The risk that they run in trying to perfect the business cases and create understanding is that they could be left out of the markets. Proposition here is possibly not a case of inspiration but of evolution!

Laptops set to follow the way of the Dodo? (Counter arguements)

Worldwide PC shipments totaled 76.3 million units in the first quarter of 2013 (1Q13), down -13.9% compared to the same quarter in 2012 and worse than the forecast decline of -7.7%, according to the International Data Corporation. This is one of the steepest declines in this segment over the last 19 years.

IDC further states: ” Despite some mild improvement in the economic environment, and some new PC models offering Windows 8, PC shipments were down significantly across all regions compared to a year ago. Fading mini notebook shipments have taken a big chunk out of the low end market while tablets and smartphones continue to divert consumer spending. PC Industry efforts to offer touch capabilities and ultraslim systems have been hampered by traditional barriers of price and component supply, as well as a weal reception for Windows8. The PC industry is struggling to identify innovations that differentiate PCs from other products and inspire conssumers to buy, and instead is meeting significant resistance to changes perceieved as cumbersome or costly”.

Unlike the consumer PC market, the enterprise PC market has seen growth, driven by continuing PC refreshes. The professional market makes up about half of all shipments.

Gartner corroborates the sentiment measuring an 11.2 percent decline quarter over quarter and quarterly shipments of 79.2 million units, a bit higher than IDC’s numbers — and therefore the lowest levels since the second quarter of 2009, per its estimates.

And hence comes the much debated oft enquired questions – Is the PC/Laptop segment going the way of the Dodo??

And the way i see it – and the way i believe it – PCs are not dead. Sidelined – Yes! Dead – No! Steve Jobs would have been correct in a lot of other things – but as far as Post PC era is concerned, i am not the most convinced. To me it always is a PC+ Era – PC + Tablet + Smartphone + Tablet + Watch + Glass + what ever else.

Two principle reasons to support my arguement -

1. PC will be the enterprise hero – it will be the data generator – as opposed to a smartphone, Glass, tablet or watch which will essentially be data consumers and data. There is a point that most of the data will be in Video -but there will still need to be memos and accounts in office parlance. I hardly see any other device doing that as efficiently as the age old PC/Laptop

2. Supporting my numbers for Point 1 – the data generated and conducted through a laptop through 2017 will still be sizeable compared to a lot of other computing machines such as smartphones. The numbers from CISCO VNI on the data per unit machine forecasts through 2011 – 2017 has a point in favour of the Laptop PC.

Source: CISCO VNI

Even though Laptop contribution to the global data traffic will be around 14%, it would still be the second largest device in terms of data traffic share beyond the ubiquitous smartphone!

Source: CISCO VNI

Adding the facts and numbers so presented, Laptop category is far from dead – it will be an important member of the convergence and computing econ-system. One that is key to niche computing in enterprises.

Whats your point of view on the future of the laptop?

Ericsson Mobility Report: February 2013 (Summary)

Total number of net adds for Q4, 2012 accounted 140 million.

In terms of new subs/net adds, China leads the fray with 30 mln subs, followed by India (11 mln), Bangladesh (9mln), Indonesia (8 mln) and Nigeria (5mln).

Mobile subs have grown around 9% y-o-y and 2% q-o-q

In Q4, mobile broadband subscriptions1 grew ~125 million to 1.5 billion, reflecting a 50% year-on-year increase.

There is continued strong momentum for smartphone uptake in all regions. Approximately 40 percent of all mobile phones sold during 2012 were smartphones, compared to around 30 percent for the full year 2011. Only around 15-20 percent of the worldwide installed base of mobile phone subscriptions uses smartphones, which means that there is considerable room for
further uptake.

By the end of Q4, 2012, Global mobile penetration reached 89% totalling 6.3bln connections- However, actual number of subs is around 4.4 bln, since many users have multiple connections

GSM/GPRS/EDGE subscriptions grew ~44 million and WCDMA/HSPA grew ~70 million. Together these technologies represent ~80 percent of total net additions. LTE subscriptions grew from 14 million to 57 million. GSM/GPRS/EDGE + WCDMA/HSPA + LTE accounted for 90% of the global mobile net adds.

World wide data traffic continues a healthy uptrend and shows significant and stable growth. Data traffic has doubled Q-o-Q Q4, 2012 versus Q4, 2011 with a 28% quarterly growth between Q3, 2012 and Q4, 2012.There are variations in data consumption patterns across geographies and maturity of markets.

Source of data and Infographic: Ericsson Mobility

Q4, 2012 Smartphone Market shares- IDC

The new IDC report for smartphone shipments in Q4, 2012 hands it over to Android – which seems to have reached more dizzying heights than what Symbian/Nokia ever reached in their near monopolistic regime heydays. the two systems accounted for 91.1 percent of operating systems on all smartphone shipments during the fourth quarter of 2012. For the year 2012, Android and iOS accounted for 87.6 percent of operation systems on smartphones shipped.

Android smartphone vendors and Apple shipped a total of 207.6 million units worldwide during Q4 which is a 70.2 percent increase from the 122.0 million shipments of Q4 2011.

Android Saw triple-digit growth for the year. According to IDC, Samsung was the biggest contributor to Android’s success as 42.0 percent of all Android smartphone shipments during the year were by Samsung. The report notes that the intra-Android competition has not stifled companies from keeping Android as the cornerstone of their respective smartphone strategies.
At the end of 2012, Android had a 68.8 percent of market, with over 497.1 million shipments. In 2011, Android’s market share was 49.2 percent with 243.5 million shipments.

iOS also continued to register strong growth. But the report notes that iOS’s year-over-year growth has slowed compared to the overall market. Of course the report also mentions the growing buzz around a large-screen iPhone and a cheaper variant, which it says would help sustain growth. iOS shipments for 2012 stood at 135.9 million smartphones which represents an 18.8 percent market share. This is a 46 percent growth compared to 2011 when iOS smartphone shipments stood at 93.1 million at a market share of 18.8 percent.

BlackBerry OS: The report states that the decision to postpone the release of BB10 to 2013 left the platform vulnerable in 2012 and reliant primarily on older smartphones running on BB7. As a result, BlackBerry’s tight grip on enterprise users has loosened. BlackBerry had 32.5 million shipments for 2012, which gives it a market share of 4.5 percent. This is down 36.11 percent from 2011 where it had 51.1 million shipments and a market share of 10.3 percent.

Windows Phone/Windows Mobile: The report notes that this has made some progress in Q4 of 2012. Nokia’s Lumia phones were the key driver in Microsoft’s success, says IDC. Windows Phone/Windows Mobile had a 17.9 million shipments and represents a 2.5 percent market for mobile OS on smartphones. This is 98.9 percent increase from 2011 when it had only 9.0 million shipments which was a market share of 1.8 percent.

Integrating the elements of convergence: The case for APIs

Convergence has been the buzz word for a good part of the last decade and will continue to do so in this decade as well. However, for the discerning the definition or at least the meaning of convergence has now shifted from device convergence to technology convergence. The later being the superset of which devices are just another maifestation. So earlier its was the camera, the mobile phone, the GPS, the MP3 player and other such device charecterestics that really converged. However, in the present context it is the convergence of enabling technologies and the three big technologies that seem to be convergent at this time are: Mobility, Cloud Services and Big Data.

However, it is a relatively small lynchpin that drives the convergence of these three mega trends. Small in terms of what it is, but large in terms of the innovation spurts that it provides. The key here is APIs or Application programming Interfaces. APIs tie together the mega-trends in a fundamental and unalterable way. APIs are the lingua franca of the new wave in internet of all things combined with super mobility and seamless connectivity. In my mind, each of these three technology trends (on their own) will be on the fast track to commoditization and will risk facing the same fate as did most social business software plays. The magic and the premiums will come from contextual application of this innovation and smart integration.

To stake a few examples, Box.net as storage without document and device sync and collaboration is commodity. Apple’s iCloud as storage without ubiquitous local and iTunes media sync across devices is commodity. And Google Drive (as discussed here in Ben Kepes’ CloudU community) is also a commodity business not worth getting into had it not been for Google’s services such as Google Apps, Piccasa, and its media and unified communication capabilities under the Google Plus brand.

The premiums from big data, mobile access and cloud comes from
a) dynamically assembled media and content, and interpreted data in the cloud,
b) available wherever you need to consume and / or collaborate and
c) insanely focused and simple interfaces to complex backends.

Thats where money would be made in these commoditized services. APIs provide the integration through the value creation network. The only other differentiator in this case being experience!

Big Data: Controlling the beast by its horns

(This is the third of series of posts on Big data and the Internet of Things. Read the first, second and third posts here.)

I look for hot spots in the data, an outbreak of activity that I need to understand. It’s something you can only do with Big Data.” – Jon Kleinberg, a professor at Cornell

Researchers have found a spike in Google search requests for terms like “flu symptoms” and “flu treatments” a couple of weeks before there is an increase in flu patients coming to hospital emergency rooms in a region (and emergency room reports usually lag behind visits by two weeks or so).Global Pulse, a new initiative by the United Nations, wants to leverage Big Data for global development. The group will conduct so-called sentiment analysis of messages in social networks and text messages – using natural-language deciphering software – to help predict job losses, spending reductions or disease outbreaks in a given region. The goal is to use digital early-warning signals to guide assistance programs in advance to, for example, prevent a region from slipping back into poverty.

In economic forecasting, research has shown that trends in increasing or decreasing volumes of housing-related search queries in Google are a more accurate predictor of house sales in the next quarter than the forecasts of real estate economists.

Big Data has its perils, to be sure. With huge data sets and fine-grained measurement, statisticians and computer scientists note, there is increased risk of “false discoveries.” The trouble with seeking a meaningful needle in massive haystacks of data, is that “many bits of straw look like needles.”
Data is tamed and understood using computer and mathematical models. These models, like metaphors in literature, are explanatory simplifications. They are useful for understanding, but they have their limits. A model might spot a correlation and draw a statistical inference that is unfair or discriminatory, based on online searches, affecting the products, bank loans and health insurance a person is offered, privacy advocates warn.

Despite the caveats, there seems to be no turning back. Data is in the driver’s seat. It’s there, it’s useful and it’s valuable, even hip. It’s a revolution. We’re really just getting under way. But the march of quantification, made possible by enormous new sources of data, will sweep through academia, business and government. There is no area that is going to be untouched.

Channelizing and Structuring Big Data: Data First Thinking

(This is the third of series of posts on Big data and the Internet of Things. Read the first and second posts here.)

There is plenty of anecdotal evidence of the payoff from data-first thinking. The best-known is still “Moneyball,” the 2003 book by Michael Lewis, chronicling how the low-budget Oakland A’s massaged data and arcane baseball statistics to spot undervalued players. Heavy data analysis had become standard not only in baseball but also in other sports, including English soccer, well before last year’s movie version of “Moneyball,” starring Brad Pitt.

Artificial-intelligence technologies can be applied in many fields. For example, Google’s search and ad business and its experimental robot cars, have navigated thousands of miles of California roads, both use a bundle of artificial-intelligence tricks. Both are daunting Big Data challenges, parsing vast quantities of data and making decisions instantaneously.

The wealth of new data, in turn, accelerates advances in computing – a virtuous circle of Big Data. Machine-learning algorithms, for example, learn on data, and the more data, the more the machines learn. Take Siri, the talking, question-answering application in iPhones, which Apple introduced last fall. Its origins go back to a Pentagon research project that was then spun off as a Silicon Valley start-up. Apple bought Siri in 2010, and kept feeding it more data. Now, with people supplying millions of questions, Siri is becoming an increasingly adept personal assistant, offering reminders, weather reports, restaurant suggestions and answers to an expanding universe of questions.

Google searches, Facebook posts and Twitter messages, for example, make it possible to measure behavior and sentiment in fine detail and as it happens. In business, economics and other fields, decisions will increasingly be based on data and analysis rather than on experience and intuition.

Retailers, like Walmart and Kohl’s, analyze sales, pricing and economic, demographic and weather data to tailor product selections at particular stores and determine the timing of price markdowns. Shipping companies, like U.P.S., mine data on truck delivery times and traffic patterns to fine-tune routing. Police departments across the country, led by New York’s, use computerized mapping and analysis of variables like historical arrest patterns, paydays, sporting events, rainfall and holidays to try to predict likely crime “hot spots” and deploy officers there in advance. Data-driven decision making” achieved productivity gains that were 5 percent to 6 percent higher than other factors could explain.

Big Data and the Internet of Things.

(This is the second of series of posts on Big data and the Internet of Things. Read the first post here.)

With a 18 fold increase expected in the next 5 years timeframe Data is the new class of economic asset, like currency or gold.With growing multiplicity of data sources, Big Data has the potential to be “humanity’s dashboard,” an intelligent tool that can help combat poverty, crime and pollution. Privacy advocates take a dim view, warning that Big Data is Big Brother, in corporate clothing.

What is Big Data? A meme and a marketing term, for sure, but also shorthand for advancing trends in technology that open the door to a new approach to understanding the world and making decisions. There is a lot more data, all the time, growing at 50 percent a year, or more than doubling every two years, estimates IDC. It’s not just more streams of data, but entirely new ones. For example, there are now countless digital sensors worldwide in industrial equipment, automobiles, electrical meters and shipping crates. They can measure and communicate location, movement, vibration, temperature, humidity, even chemical changes in the air.

Linking these communicating sensors to computing intelligence and gives rise to what is called the Internet of Things or the Industrial Internet. Improved access to information is also fueling the Big Data trend. For example, government data – employment figures and other information – has been steadily migrating onto the Web. In 2009, Washington opened the data doors further by starting Data.gov, a Web site that makes all kinds of government data accessible to the public.

Data is not only becoming more available but also more understandable to computers. Most of the Big Data surge is data in the wild – unruly stuff like words, images and video on the Web and those streams of sensor data. It is called unstructured data and is not typically grist for traditional databases. But the computer tools for gleaning knowledge and insights from the Internet era’s vast trove of unstructured data are fast gaining ground. At the forefront are the rapidly advancing techniques of artificial intelligence like natural-language processing, pattern recognition and machine learning.

The age of Big data

Mobile data traffic to increase 18-fold by 2016 – CISCO

Between 2011 and 2016 the amount of mobile data traffic will grow at a compound annual rate of 78 percent as the number of mobile devices connected to the Internet exceeds the number of people on Earth in four years’ time, according to a study by Cisco.The United Nations projects that world population will reach 7.3 billion by 2016. By that time, according to Cisco’s annual visual networking index forecast, there will be more than 10 billion devices, generating global mobile data traffic of 10.8 exabytes per month.

That translates into around 130 exabytes of mobile data per year which is equivalent to 33 billion DVDs or 813 quadrillion text messages. While most of the devices driving mobile data traffic will be smartphones, ,laptops and other portable gadgets; M2M machine-to-machine connections are gaining momentum and by 2016 and are expected to reach 2 billion. Machine-to-machine connections (M2M) include GPS systems in cars, tracking systems in fleets and ships or meters to record energy consumption.

Mobile data, especially video, will put a strain on wireless networks and while service providers are increasingly offloading mobile traffic to their fixed-line networks, there is a need for additional spectrum to keep up with demand. Quality-of-service issues are seen to be arising in major metropolitan areas due to the increase in mobile data traffic.