Mobile Growth at 91Springboard

Workshop by branch.io on Mobile Applications and how you can use certain techniques to increase the usage of your Mobile App.

  • Getting Downloads and Install is the first step.
  • Retaining is more important.
  • Growth Hacking is a misnomer. Overemphasis on acquiring and not retaining.
  • Good Product is key to growth.
  • Story of color app which raised US$ 41 million funding and closed down in 2012.
  • You can start with a low advertising of Rs 2000 if you advertise on facebook and google.
  • Mobile Web – Best Experience to get App installs.
  • Try to get users and influencers on board.
  • Paid Marketing – How much money should be used ? Budget it with Rs 100 you can get 5- 6 Downloads.
  • Facebook and Google are the World’s best Ad Networks for selling app installs.
  • Book – Traction by founder of DuckDuckGo – A must read to know more about channels – http://tractionbook.com/
  • The Average Indian User looks at his mobile phone for 178 minutes in a day.
  • What is the best Time to send push notifications.
  • For Dating Apps , the most popular time is in the morning 9-12 am when most people expected it to be at night.
  • Build a demo button on your website where you can download app. Then take them to the demo page coming soon. Track how many clicks you get to know if there is user interest for your App.
  • Andrew Chen – http://andrewchen.co/
  • Mobile App Marketing – https://appspire.me/

Carl Sagan Quote and other Random Jottings

“It is far better to grasp the Universe as it really is than to persist in delusion, however satisfying and reassuring.”- Carl Sagan

  1. Ask Successful for Tips. Learn and apply.
  2. Get out of the Mental Trap that successful people are better than you. They were just doing things differently.
  3. The ability to concentrate single mindedly on your most important task, to do it well and to finish it completely , is the key to great success, achievement, respect, status and happiness in life.
  4. Elevate your vision it will attract big people.
  5. Go where people have not gone before.
  6. Don’t get hung up on results. Focus on process.

Other Random Self Improvement Observations.

A email forward that is interesting.

Imagine there is a bank account that credits your account each morning with $86,400. It carries over no balance from day to day.

Every evening the bank deletes whatever part of the balance you failed to use during the day. What would you do? Draw out every cent, of course?

Each of us has such a bank. It’s name is TIME.

Every morning, it credits you with 86,400 seconds.

Every night it writes off as lost, whatever of this you have failed to invest to a good purpose.

It carries over no balance. It allows no over draft. Each day it opens a new account for you. Each night it burns the remains of the day.

If you fail to use the day’s deposits, the loss is yours. There is no drawing against “tomorrow.”
You must live in the present on today’s deposits. Invest it so as to get from it the utmost in health, happiness and success!

The clock is running!! Make the most of today.

  • To realise the value of ONE YEAR, ask a student who failed a grade.
  • To realise the value of ONE MONTH, ask a mother who has given birth to a premature baby.
  • To realise the value of ONE WEEK, ask the editor of a weekly newspaper.
  • To realise the value of ONE HOUR, ask the lovers who are waiting to meet.
  • To realise the value of ONE MINUTE, ask a person who just missed a train.
  • To realise the value of ONE SECOND, ask someone who just avoided an accident.
  • To realise the value of ONE MILLISECOND, ask the person who won a silver medal at the Olympics.

Treasure every moment that you have! And treasure it more because you shared it with someone special, special enough to spend your time with. And remember time waits for no one.

Yesterday is history. Tomorrow is a mystery. Today is a gift. That’s why its called the present.

Random Resolves made

  1. Live in the present.
  2. Observe your state of mind at all times.
  3. When solving problems, dig at the roots.
  4. Have long range goals to prevent frustration from short range failures.
  5. The best helping hand you will ever receive is the one at the end of your own hand.
  6. A successful person is one who lays the foundation with bricks thrown at him.
  7. Never waste a minute of your life thinking of people you don’t like.
  8. The shell must break before the bird can fly. – Alfred Tennyson

  9. Be brave take risks, nothing can substitute experience.
  10. You are today where your thoughts have brought you; you will be tomorrow where your thoughts take you. –  James Allen Read

  11. Sri Sri RV believes obsessions and addictions are a result of overeating and being oversexed.

Data Analytics Workshop at IIM-B

Enterprise Marketing and Analytics – Trends and Case Study held by NSRCEL at IIM Bangalore in June 2014.

By Kingshuk Banejee, IBM Global Consulting Services.

Summary :

  1. Predict and Prescribe, not just describe. Three Guidelines of Analytics. Refer to the book by Thomas Davenport on Analytics.
  2. Data is an Asset : The “Information Age” Gold.
  3. Personalization, Micro-Segmentation and Next Best Action, hottest area in customer analytics.
  4. Big Data Leverage.
  5. Mining the Unstructured.
  6. Real Time Decision Making – People, Processes and Technology.
  7. Data Scientists are in great demand all over the world.
  8. Leads to transformation of Business Model – Getting into others business

Followed by talk by Joy Mustafi of IBM called Customer Analytics Best Practices

 

Quotes on Dreams

Destiny is no matter of chance. It is a matter of choice.
It is not a thing to be waited for, it is a thing to be achieved.”
William Jennings Bryan

A Dream doesn’t become reality through magic ;
it takes sweat, determination and hard work”
Colin Powell

Every ceiling, when reached, becomes a floor, upon which one
walks as a matter of course and prescriptive right.”
Aldous Huxley

The Age of Big Data Analytics

A Report of the World Economic Forum in Davos in 2012, termed data as a new class of economic asset, which touches all aspects of society. Almost 90 per cent of the data in the world, as of 2013, has been created in the last two years.

wef big dataThe Internal and Social networks have enormously increased the data available on the Net on such a huge scale that observers have described that we are in the Age of Big Data. It is estimated that there will be 44 times as much data in computer devices over the next decade, reaching 35 zetta bytes in 2020. A zetta byte is one trillion gigabytes (1 followed by 21 zeros).

Indicating this, IBM’s former Chairman Samuel Palmisano said advanced computation and analytics would enable us to make sense of the enormous data in real time. Online data indexed by Google alone is estimated to have increased from 5 exabytes (1 exabyte equals 1 million bytes) in 2002 to 280 exabytes in 2009, which works out to 56-fold increase in seven years. In contrast, the growth in computing in terms of Moore’s Law in the same period was only a 16-fold increase.

Moreover, 20 per cent of the Internet search queries typically yield new data. Samuel Arbesman, a Harvard mathematician, has explored the length of time it takes for half of the facts to become obsolete. The study called scientometrics, provides a quantitative analysis of science, which examines why everything we know has an expiration date. Arbesman has cited the analogy of predicting the decay of half the atoms in a chunk of uranium over a period. In a somewhat similar manner, data stored online would become obsolete, given the unprecedented inflow of new data.

The huge increase in data is attributed to three main reasons. One, rise of mobile phones and tablets including services based on location-oriented mobile devices; two, enormous increase in video uploading on the Internet; and three, rise of the so-called Internet of Things, which would make devices in daily use (e.g. refrigerators) generate data on their own.

Internet Of Things
Image-credit:www.perforce.com

Let us first look at the rise of mobile devices. Their increase has been phenomenal in recent times. The number of mobile devices is expected to exceed the human population by 2013. Cisco, an Internet company, predicts that by 2016 there will be 10 billion mobiles around the world and that the networks will be carrying 130 exabytes of data each year, equivalent of 33 billion DVDs.

The forecast is justified going by the recent trends: mobile data traffic in 2011 was eight times the size of the global Internet traffic in 2000. Moreover, smartphones have added to the flood of data. By 2015, the number of smartphones in the world will be up to one billion. An average smartphone uses 150 megabytes of data per month and it is expected to rise to 2.6 megabytes by 2016. By then, 60 per cent of the mobile users will be using more than one gigabyte of data per month. In a related traffic to smartphones, has tripled to 34 million since 2011. Finally, the introduction of 4G phones is expected to pick up more data than the earlier generations of mobile phones. Google’s Android phones are increasing by 850,000 per day or 10 devices per minute and will account for 15 per cent of Google’s search volume from mobile devices.

youtube bandwidthThe second major reason for data increase is the huge input of video from camera phones and other user-friendly devices. Cisco predicts that 70 per cent of mobile data traffic will be video by 2016. You Tube is the second largest search engine today. One report points out that the video uploaded to YouTube in 60days is more than what three major US networks created in 60 years! With Google pushing for open standard for television on the Net, the video surge will continue unabated.

Third, data will start flowing form everyday objects like refrigerator and microwave ovens in the Internet of Things.

Data: A Gold Mine of the Internet Age

What is Data Mining ?

Sorting out data according to predetermined categories is easy with say 10 data-sets but becomes a challenge if the number involved is say five billion. Only powerful computers can handle this sort of processing.

Data on the scale of billions has become common place. This needs automation and that is what data mining is all about. Data mining is the process by which new information is gleaned by examining large databases.

Processing becomes a program in machine learning according to given instructions. The techniques of data mining can be broadly characterized according to the targets given. Let us see some examples.

First, the target could be detecting anomalies in a huge pile of identical returns pertaining to property details or tax levied or claimed. Even one in thousand, which is different from the rest of the files, will be significant. Second, learning by association could be a target. It is best understood by sales strategies. For instance, if you bought a music player, then advertisements offering CDs and the latest hits will be suggested. Or if you have been mostly buying tickets to crime thriller movies, the newly released crime movies would pop up on your screen. A well-known online bookseller invariably adds that those who bought this book which you have ordered have also bought the other titles listed on your screen. It is an inducement for you to consider and buy.

Third, the data on the goods ordered would be used to group the buyers and their location, if possible, for further marketing strategies. For instance, the data on dental equipment sold online would be used to build up a profile of demand for such equipment. A lot of other conditions should qualify such projections. Those who buy nets need not be fishermen: they could be anglers who have fishing as a hobby.

Fourth, computers can be programmed to locate spam on the basis of objectionable or unwanted mails. Lastly, building predictive models based on the data gathered has become a professional exercise. Such projections of consumer demand, weather patterns and production and sales trends have been found quite useful.

Though primarily used for advertising on the Internet, data mining is fast becoming a discipline on its own predicting the probable trends in many areas of the uncertain world of today.

data analysis servers

How Data Mining affects us all ?

Data mining has its impact on individuals. It allows companies and governments to use the information one provides to reveal more than one thinks. Even as we gather more data than we can handle, powerful computers especially those working with social networks, will gobble up the huge mountains of data and try to make some sense of it, often in response to corporate demands.

The International Data Corporation foresees a high technology industry in the convergence of mobile devices, social networks and cloud-based computing and data storage. Spending on new technologies is growing at six times that of traditional computer servers and PCs. It will pose new demands, especially for storage of data. Cloud computing has come in time. Companies that provide cloud servers to business are expected to get more than half of the spending. On privacy, the Corporation says in a report that while there is increased awareness of privacy issues, there is still no sense of immediate urgency. Users trust the system and the convenience it provides as long as no harm is inflicted on a personal level.

A survey by Ericsson Consumer Lab finds that users feel safe sharing music playlists or their beliefs on religion etc., but are least inclined to share data about their medical records or finances.

Big Data Analytics in India

Computer facilities to handle data are coming up in India in a big way. The Indian grid (network of computers that shares resources) called GARUDA (Global Access to Resources Using Distributed Architecture) has a computing capability of close to 70 teraflop (a teraflop is a trillion floating point operations per second).

It may reach exascale (a billion billion flops) by 2016. GARUDA will facilitate data exchange and analysis over a wide range: health care, bioinformatics and climate modeling etc.). India has also a National Knowledge Network which connects over 700 institutional networks. In addition there is ERNET which is a national network of academic institutions in the country.

An overview of Big Data and Data Mining is provided in the video below :

Kaalari capital launches Kstart

Kalaari Capital, a Venture Capital firm which has more than US$ 650 million (Rs 4000 Cr) in assets under management, last week announced the launch of it’s incubator called Kstart. Kstart seeks to nurture start-ups and help accelerate their growth. The hub is based at the International Technology Park in Whitefield, Bangalore.

Kaalari which derives it’s name from the ancient marital art of Kaalaripayattu has notched up several high profile investments in Indian startups in the past few years. Some of their high profile investee’s include Myntra.com, Via.com, Snapdeal.com, Yourstory.com and Zivame.com. Kalaari Capital is headed by Vani Kola who is counted among India’s most successful entrepreneur and serves as it’s managing director.

Startup India – Join the Party !

The Starup India mission announced by Narendra Modi last month, is expected to give a fillip to the entire sector in the coming years with a host of incentives like annual tax rebates and a US$ 1.5 billion government fund to invest in new startup’s . Indian VC’s are looking to capitalize on this opportunity and eager to invest in startups with unique ideas which can address unmet needs in global markets. The business environment in India is very tough with stringent regulatory norms and various hurdles.  Startups today require a lot of hand holding before they can mature into a sustainable business.This is where Kstart steps in.

kstart logo

The Kstart Program Launch

The program was launched on 5th February 2016 at the International Technology Park in Whitefield, (ITPL) with a one-on-one chat between Mr Ratan Tata and Mr Vani Kola, the MD of Kaalari Capital. The chat which started at 11:00 am and lasted till noon had Mr Ratan Tata speaking about his investments in Startups and how he see’s the startup sector shaping up in India.

vani kola ratan tataAfter the session concluded , it was followed by a short speech by the Art Curators who have furnished the Kstart office with an eclectic mix of modern art and installations.

art-vc

The Kstart incubator is decked up with Murals and Electronic Art installations that lend it a hip and haute couture finish. It should in time emerge as an art connoisseurs delight for it’s varied use of dynamic art elements. For those who missed out on the event , you can take a look at some of the high end art decorating the incubator below. More than 12 Artists from around the world collaborated for months to produce these art works.

art on walls
A mural on one side of the conference hall.

 

black white office
A corner in the office decked up in Black and White interiors and furniture.

 

led
An interactive LED Display.

The opening session was followed by a session which had Bangalore based founders Bhavish Aggarwal (Ola Cabs), Mukesh Bansal (Myntra), Naveen Tewari (Inmobi), Kunal Shah (Freecharge) in a free wheeling chat with David Rowan, Editor of Wired Magazine UK. Yourstory has a detailed write-up about what they discussed here.

david rowan wired startup

The session was followed by a round of sumptuous snacks that included cakes, rolls and tuna sandwiches (a rarity in India!).

tuna sandwhich

The afternoon session had presentations by Google India and IBM Watson and concluded with a talk by David Rowan , where he spoke about 10 trends that are shaping the digital economy around the globe. That wraps up a brief overview of the launch event of Kstart by Kalaari capital. Stay tuned for more updates about Startups in India!

The Challenge of Big Data

Data storage is increasing by leaps and bounds thanks to the vast spread of various sensors, transactions and clicks online. The emerging challenge is data analysis to make sense of it in quick time in response to changing demands. The challenge is indicated in the definition of big data that it is too big, too fast and too hard for the existing tools to process. We have today data systems which handle data on a petaflop scale (a thousand million million flops), though fast processing is demanded by situations such as fraud detection or sale of goods.) What is wanted is machine-learning algorithms that are easier for common users.

The US Government has announced a ‘Big Data’ initiative to advance the state-of-the-art core technologies needed to collect, store, preserve, manage, analyse and share high quantities of data. For example, the data from the 1000 Genomics Project will be put into the cloud. The world’s largest set of data on human genetic variation is a 200 terabytes. Another type of data stored will be related to our planet which will be of great interest to geo-scientists. All of this data will be free hosted by the Amazon Web services cloud.

Global pulse, a United Nations initiative, wants to leverage Big Data for global development. It plans to get digital warning signals to guide assistance programmes in advance. The warning is timely as algorithms increasingly determine an expanding space in our lives.

There can be a downside as well to the emergence of data deluge. Computer virus will have greater scope to attack. Identity impersonation may increase. And intrusions into privacy may go up. These are inevitable consequences of a historic change in the way computers will handle data in the near future.

In 2011, a total of 1.8 trillion gigabytes of data per day was created. Significantly, three-fourths of it was produced by ordinary consumers. The trend will continue as people expect almost every service from the Internet. The meteoric rise of data on the Internet has a profound impact on the world’s energy resources and pollution levels.

the challenge of big data

Big Data and Energy Demand

One of the features about the search engine is the enormous power it consumes for its work. A video on YouTube, for example, showed one of its data centres, where 45,000 servers were placed. It was disclosed that Google has placed on uninterrupted power supply at each server instead of a centralized supply source. It has been stated that a typical search needs 0.3 watt hours of electricity, which is equivalent of a 100-watt light bulb to be lit for ten seconds.

For handling a billion searchers a day, it needs 12.5 million watts Hence it is imperative to save on power. Google recently disclosed that it needs 260 million watts (equivalent at one fourth the output of a typical nuclear power plant) for its data centres around the world. This is considered enough to power 200,000 households. As the Internet traffic is expected to increase four-fold in the next five years, Google has set up a power plant on the Baltic coast of Finland. Globally, 1.5 per cent of the total electricity generated is used by Google.

Social media and search engines make a huge demand on the world’s energy resources, if only to keep themselves free from potential breakdown. Most of the world’s three million data centres, where mega servers handle data from the Internet, consume vast amount of energy in a wasteful manner. Worldwide, the digital data centres use about 30 billion watts of electricity, equal to the output of about 30 nuclear power plants. Though a data centre runs at maximum capacity, it typically uses an average only 6-12 per cent for the computational tasks of its servers. The over-provisioning is made simply to keep the servers running for fear of a crash even for a few seconds. Many servers are labelled idle or comatose by engineers but no attempt is made to stop them from idling. Contrary to popular nation, cloud computing does not save energy. The cloud just changes the location, where applications are carried out.

Moreover, together with back-up generators and batteries, the deployment of power sources pollutes the atmosphere. Several centres have been found violating air quality regulations.

There are several challenges posed by Big Data. First, identifying which data are relevant is a problem. Second, perfect information is invariably not available to base corporate decisions, which are often driven by leadership and windows of opportunity as perceived by the managements. Third, formulating the right questions will be more important than going by the data collected in general.

It is tempting to recall the prescient words of T.S. Eliot who asked, “Where is the wisdom we have lost in knowledge? Where is the knowledge we have lost in information?” To this one may add the question posed by a critic, viz. “Where is the information we have lost in data?” Certainly, we have created more than what we can comprehend, much less utilize. Perhaps it is a tribute to human ingenuity. As Danny Hillis, inventor of supercomputers says, the greatest achievement of human technology is tools that allow us to create more than we understand.