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Thursday, July 21, 2016

How A/B Testing at LinkedIn, Wealthfront and eBay Made Me a Better Manager

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How A/B Testing at LinkedIn, Wealthfront and eBay Made Me a Better Manager

Over his career, Instacart VP of Product Elliot Shmukler has seen the interplay of people and products unfold across many industries. For instance, the former Wealthfront and Linkedin product leader knows that much of what takes people sideways with money and career involves emotions. He’s also seen the same dynamic at play as product managers make decisions to pursue ideas, essentially their currency at a startup. Bake into the equation different product management styles with shrinking launch windows and the pressure compounds. That’s why Shmukler champions A/B testing not only as a sound product development practice, but also as an effective management tool.
While at eBay, Shmukler pioneered the use of A/B testing to improve eBay’s Search experience and helped launch eBay Express, its largest product bet at the time. At LinkedIn, he led a 15-person product team that was responsible for nearly half of LinkedIn’s page views. While he was the VP of Product at Wealthfront, Shmukler not only helped the startup grow from $150 million to over $3 billion in client assets, but also launched Direct Indexing, Single-Stock Diversification Service and its first mobile app. Over his career, he’s learned to extract the full benefits of A/B testing for his products and team.
In this interview, Shmukler shows why he uses A/B testing as a management framework, illustrating how it works to not only accelerate decisions, but also empower the teams making them. He outlines the framework’s benefits and challenges, as well as how to implement and scale it a startup. Any product or growth leader will learn from his data-driven approach to product and team management.

A Tale of Two Decisions

At the heart of any management framework is the goal of making better decisions. As people naturally gravitate to the different permutations ofbetter — quicker, higher quality, cheaper, etc. — they neglect to take a nuanced look at the distinct types of decisions that a company makes. In anannual letter to shareholders, Amazon CEO Jeff Bezos speaks of two varieties of decisions: the irreversible (Type 1) and the changeable (Type 2). Here’s how he describes them:
  • Type 1 decisions: “Some decisions are consequential and irreversible or nearly irreversible – one-way doors – and these decisions must be made methodically, carefully, slowly, with great deliberation and consultation. If you walk through and don’t like what you see on the other side, you can’t get back to where you were before.”
  • Type 2 decisions: “But most decisions aren’t like that – they are changeable, reversible – they’re two-way doors. If you’ve made a suboptimal Type 2 decision, you don’t have to live with the consequences for that long. You can reopen the door and go back through. Type 2 decisions can and should be made quickly by high judgment individuals or small groups.”
As a company grows, there’s a tendency to broadly apply the Type 1 decision-making process to every choice, including Type 2 decisions. To paraphrase Bezos, what results is a slowness and an unthoughtful risk aversion that leads to a failure to experiment and diminished invention. If Type 2 decision-making is applied indiscriminately, he argues that most companies will go extinct before they get large, having used a lightweight process for irreversible choices.
Shmukler believes universal A/B testing is an ideal way to focus an organization on using Type 2 decision making for most choices. He says, “In the traditional sense, A/B testing is about having at least two versions of the product live: an A version, typically the original implementation or control, and a B version, which you think might be better,” says Shmukler. “Thus when A/B testing is applied to Type 2 management decisions, it’s very easy to walk back through the door as Bezos suggests by simply turning off B and returning to A. Universal A/B testing may even highlight when a Type 1 decision is needed. If you’re having significant trouble coming up with a way to test a direction or sense you won’t be able to roll back the test without consequence, you might be dealing with a Type 1 decision.”
While Bezos warns of “one-size-fits all” decision-making from the helm of Amazon, Shmukler has seen similar pitfalls at early-stage startups, especially in the product management function. The notion of PM as CEO of her product is well-known, but when it comes to decision-making, there’s a real truth to it. The path to shipping a product takes an acute ability to expertly triage different types of decisions along the way. To complicate matters, product managers naturally bring their own management style to how they make the decisions.
Elliot Shmukler

A Case For A/B Testing as a Management Framework

Early in his career, Shmukler co-founded Sombasa Media, which he eventually sold to About.com. It was at his startup that he first noted two different product management styles of making decisions: the way of the visionary and the data-driven PM. “The visionary product manager reads the tea leaves and decides more on gut feel, while the data-driven PM uses experimentation and analysis to make calls,” he says, “There are manyeffective decision-making frameworks out there, but I wanted to use one that would simultaneously surface the best choice for the product while still encouraging the inherently different approaches to ideation among my product managers.”
For visionary PMs, a lot of power is generated when they know something works and they want to bring it to the rest of the world. Shmukler admits that many of the visionary PMs that he’s known have been or become founders or CEOs, because of their deep belief in taking something personally relevant to scale. “Reid Hoffman built LinkedIn to reflect how he approached professional networking and his vision for how it should work online. Obviously, the product has evolved over the years but the site is still largely true to his original vision, which was right on the money.”
Data-driven PMs develop their insights methodically and are less headstrong before making decisions. “I’d characterize these product managers with the phrase: ‘strong opinions, held weakly.’ Data-driven PMs come to their stance not so much from how they're living their life, but by looking at and collecting new data. As more information comes in, they’re much more likely to refine those insights,” says Shmukler. “It’s more of a challenge to give recognizable names for these types of PMs because the data is at the forefront. But you’ll find them working on growth teams and gravitating toward roles where data already has a very strong role.”
Given these vastly different styles, it can be a challenge as a leader to reconcile these different approaches to product management. For heads of product, this scenario may sound familiar: a visionary PM says, “We need to do X.” Then, a data-driven PM responds. “No, X is wrong. It won’t work. We need to do Y.” Shmukler faced this countless times — and on a daily basis as his team grew. “It’s draining and very hard to resolve without seeming to favor a side,” says Shmukler. “Instead of giving a verdict, test both theories and let data be the judge. At first pass, this method may seem to favor the data-driven people, but it empowers each PM to push ideas forward. They learn independently rather than feeling that a decision was made for them.”
Your team's undoubtedly better with diversity of thought, but trigger the relief valve when tension mounts.
To illustrate its simple effectiveness, here’s how Shmukler has applied A/B Testing as a management practice. “A group of visionary PMs wanted to change how we talked about the company, specifically in the language on our homepage. The more metrics-driven PMs said they had run those experiments before and that it hadn’t had an impact on sign-ups,” he says, “To resolve that situation, someone has to make the decision to deploy time and headcount to do the test or not. Either way, someone will think you’re making a bad decision. Visionary PMs will say you’re too data-driven and not being grounded in the bigger goal and data-driven PMs will say it’s a waste of time. Universal A/B testing solves this, as no such decision has to be made. Instead, there’s an understanding that any idea from a trusted team will be tested in a lightweight way. The results — rather than a single arbiter — decide if ideas should be pursued further.”
In this case, Shmukler asked the team to work together to put the theory to the test to gauge impact. “The visionary PMs wrote the new content for the homepage and the data-driven PMs took point on structuring the experiment. It took a day or two to implement and we collected data over a month,” he says, “All the tests’ results are public on a dashboard that the entire company can access. Both camps are happy: the data-driven PMs got to use data to experiment and determine results, and the visionary PMs got their idea out there. In this specific case, the new homepage language did not have a significant impact. There were no hard feelings. The visionary PMs recalibrated and redirected their energy to new, different ideas.”
Universal A/B testing also allows Shmukler to say “yes” to multiple product ideas — with the only restriction being that they need to tested. “It’s a great way to implement a Type 2 decision making process and prevent the team from getting bogged down with a Type 1 approach unnecessarily,” says Shmukler. “It not only helps the team steer clear of the ‘one-size-fits-all’ trap that Bezos cites, but it increases experimentation, autonomy and learning throughout the organization. Most critically, it fosters goodwill among smart — but very different — PMs who want to try out their ideas.”
Regardless of which idea wins, there isn't a lot of conflict among PMs because the results come from an authoritative test, not an authority. The key is that it’s done quickly and transparently to everyone. Here’s a summary of this method’s benefits and challenges:

Benefits

  • Autonomy. “One thing I found pretty valuable in running things this way is everyone basically gets their ideas to come to life, regardless of rank or tenure. As a manager, I am less a dictator and more an arbiter, stepping in only to help refine future ideas.”
  • Lower risk. “Once there’s a tool to quickly run tests, the company bears very little cost to experimentation but the act of doing experiments reduces overall risk. If an idea is a bad — or potentially damaging — one, we’ll know quickly and not move ahead with the idea. If it’s a good idea, there may be benefits that would not have been discovered without testing.”
  • Employee engagement. “This approach keeps product managers on my team a lot happier because they know there’s a channel to get their ideas out there and to prove that their ideas work. They’ve told me they learn and develop at a faster clip because they can try a bunch of ideas and learn from the results.”
  • Changes actions, not styles. “This system allows data-driven PMs to evaluate ideas rationally and lets visionary PMs more quickly hone their instinct by literally ‘experiencing’ more of their ideas faster. It embraces — not alters — their styles.”

Challenges

  • User sample size. “At the very beginning, startups need to operate more in visionary mode. To run this system effectively, you’ll need a bit of traction and some user base. There's no airtight rule of thumb, but if you're trying to test around a particular action that your users take — signing up, clicking a button or sharing a post — you probably want hundreds of people taking that action a week at a minimum. Ideally, you’re testing in the thousands for faster results and to run multiple tests concurrently. Of course, companies that throw millions of users into an experiment have significant advantage in leveraging these approaches.”
  • Legacy decision-making methods. “In one of my jobs, my company didn’t know about A/B testing. Instead they required each person to prepare a detailed financial and impact analysis on how each idea would move the needle. To me, that’s a surefire way to kill ideas and manufacture models with gobs of assumptions. But some companies still take this approach.”
  • A culture of metrics, but not around experimentation. “I was at one company that was very good at monitoring its business metrics every day, but didn’t do A/B testing or small experimentation. It put its faith in those high-level metrics, but when things went south, it couldn’t isolate the problem quickly. One time, it had launched seven releases — all without an A/B test — when a major issue surfaced. The team had to roll-back most of the changes in order to A/B test and find the issue.”
Get ahead of complaints from crestfallen colleagues about squashed ideas. It’s so easy to test. Soon you’ll have a dozen A/B tests running.

How to Implement and Scale A/B Testing

Through the years, Shmukler has heard all the objections around implementing A/B tests not just for product development, but as a management tool. “For growth and later stage companies, it nearly always takes a crisis. At scale, people get stuck in their ways and it’s hard to convince them otherwise merely on theoretical merit,” he says, “But for startups, the protest is always around time and cost. I’ve used this system at a startup when it was 20 employees and barely retrofitted it as it grew past 100 people.”
Shmukler has worked at both large companies and startups, and has found that, regardless of size, this testing framework produces very little friction to launching an experiment, because its not a drag on time or cost. Here’s how:
Invest in a lightweight experimentation tool. In Shmukler experience, it takes just a handful of engineers to do the initial build of a tool and dashboard to run, monitor and evaluate A/B tests. “Most folks who’ve never done this think the resources required are more than they actually are. With less than a month of work, startups can get A/B tests practically automated. PMs can get the results quickly and without a lot of work. If they want to dig into data, they can, but they don't have to since most of the core evaluation is being done for them,” says Shmukler.
If you don’t have the engineering bandwidth or chops, there are many tools available. “If you're using a tool like Optimizely, you probably don't even have to write any code to enable A/B testing,” says Shmukler. “It takes care of it all for you: the testing, the data gathering and the evaluation. Of course, you have to build the different features, but that must be done in any model. If you're using an A/B testing tool, it's almost no additional work for you. There may be some cost, but usually there are freemium options for early-stage startups. It’s a worthy investment when you consider that it’ll help you make sound product decisions and align your team. In the long run, rolling out releases blindly will always take longer.”
If you’re still not convinced, Shmukler intently breaks it down further, “Really, what you’re doing is choosing a user, flipping a coin and putting them in either the A or B group. Depending on that association, you’ll show users a different page or send them to a different flow," he says, “At the start, you can quickly develop something simple. Just get the experimentation going. Continue to collect and test data — for all that’s happening with your product.”
Reduce the barrier to test to one decision. Making A/B tests a universal practice means making each experiment an easy, instant choice. “The friction to launch a test should be as low as possible. Essentially, you want the only hurdle to be just the decision to test at all. After that, the system will essentially run and evaluate it all,” says Shmukler. “It comes down to building great frameworks. For engineers, you need a framework where launching a test is incredibly easy — maybe it's a couple of lines of code to create a new experiment. For everyone else, this is where you need, essentially, an internal dashboard that automatically evaluates the test.”
Shmukler recommends that product teams use dashboards that automatically recognize when new experiments are launched. He describes one that he’s built in the past: “It lets you pick a goal for that experiment. Then, based on that goal, it shows all the metrics that you should be looking at for that experiment,” says Shmukler. “Then it immediately evaluates the data and gives a simple red or green signal to indicate if the change should roll out or roll back. If it doesn’t have enough data, it gives a neutral indication to recommend that the test should keep running. That's the level of simplicity and automation you want. You shouldn’t feel like you’re paying a price at each step to experiment.”
Untangle interactions among tests. As with any system, it’s prone to break at scale. “At LinkedIn, we eventually noted interactions between experiments. For example, tests on a sign-up flow and a profile page could color the other’s results. This becomes hard to untangle,” says Shmukler. “Use statistical methods to alert your dashboard if there’s a problematic interaction. It should allow you to choose to shut down one of the experiments and evaluate your remaining test. If you anticipate an issue before testing, consider using different selection criteria to route specific users into experiments to avoid those kinds of interactions altogether.”
At LinkedIn, Shmukler and his team used sophisticated selection criteria to avoid interaction between experiments. “We’d select from users that weren't in other experiments or sub-segment them to made sure that a segment was only in a single experiment at a time. You end up having to build more complex processes for selecting someone into an experiment then evaluating the experiment over time,” he says.
As the complexity increases with concurrent experimentation, dashboards must become easier to interpret. “The best dashboards are the simple ones — where it gives an indicative green or a red signal — but you still must read the results. You may want to run a red experiment for longer to gather and interpret more data,” says Shmukler. “But as you scale, you want less and less of that interpretation happening because you're going to distribute this information across a much larger team. The likelihood that everyone will extract the same interpretation decreases. So, fool-proof your dashboard so that it gives anyone the full — and same — picture.”
Understand the broad impact of your experiment. Both visionary and data-driven PMs will put increasing faith in A/B testing as the tool itself sharpens. “Most A/B tests tell you whether the experiment is a good idea or a bad idea. The next step is to develop a dashboard that shows the impact of the experiments on the key metrics for the entire product or the entire company,” says Shmukler. “Tests don’t always make that obvious. For example, you may optimize some small part of the sign-up flow and see a 10% lift in completion of that step, but that doesn’t necessarily translate to 10% more sign-ups because not every user may encounter that step.”
Deepening the capability of your testing software to translate an experimental result into top level impact should be on every product team’s A/B testing roadmap. “It’ll helps you understand what to expect in top level numbers as a unit and organization. Also, it helps people select experiments a little better by rooting them in the context of the company. It’s important to know if it’s a 10% win for the entire product or just for a small corner of the product. By reflecting the impact of an experiment on business metrics, the hope is to build each team’s awareness of these experiments, making them more meaningful to run.”

Tying it All Together

Many startups understand the value of A/B testing as a tool to grow a product, but it’s also a built-in mechanism to better develop a product team. Universal A/B testing not only resolves the tension between different product manager types, but it also does so while giving them autonomy and acknowledgement of their personal style. Even if startups face challenges with small sample sizes and alternative systems, investing in a lightweight experimentation tool is always worth it. As the company and number of experiments grow, so must the testing software — and it must employ simpler signals so any employee can understand the big picture.
“A/B testing does more than elevate products faster — it does the same for teams. Using universal A/B testing as a management tool sends a message to PMs of all stripes: intelligently tested ideas will rise to the top, regardless of who thinks of them,” says Shmukler. “They say that to go fast, go alone. And to go far, go together. This system allows you to be both ambitious and autonomous. Most people want to be both in their work — and everyone wants to see their ideas come to life.”

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My STARTUP :

Let me introduce myself. My name is Richard Nata. I am an author, novelist, blogger and ghost writer. My articles, including short stories have been published in magazines and newspapers since 1994. I have written a lot of books, both fiction and non-fiction. So I was a professional in the field of writing, both fiction and non-fiction.

I was born in Jakarta, August 17, 1968.  

In 1988, at the age of 20 years, I started working as an accounting staff. Age 24 years has occupied the position of Finance Manager. Age 26 years as a General Manager.

In 1994, my articles published in magazines and tabloids.

In 1997, I wrote a book entitled "Buku Pintar Mencari Kerja". This book is reprinted as much as 8 times. Through the book, the authors successfully helped tens of thousands of people get jobs at once successful in their careers. They were also successful when moving to work in other places.

In 1998, I started investing in shares on Bursa Efek Indonesia (Indonesia stock exchange). As a result of investing in the stock market then I can provide consulting services for companies that want to go public in Indonesia stock exchange.

more information :
1. IPO KAN PERUSAHAAN ANDA DI BEI, TRIK TERCEPAT MENJADIKAN ANDA SEORANG KONGLOMERAT. brand, ideas, story, style, my life: IPO KAN PERUSAHAAN ANDA DI BEI, TRIK TERCEPAT MENJADIKAN ANDA SEORANG KONGLOMERAT.
2. JASA KONSULTAN GO PUBLIC ( IPO ) DI BURSA EFEK INDONESIA. 


BUKU PINTAR DAPAT KERJA GAJI TINGGI PINDAH KERJA GAJI SEMAKIN TINGGI made by retyping the book BEST SELLER of the author, entitled “Buku Pintar Mencari Kerja”. This ebook available on google play.

In 2015, I had the idea of a startup company where the readers can decide for themselves the next story. WASN'T THIS A GREAT IDEA? IF can be realized WILL BE WORTH billions USD. Because CAN PRODUCE FOR MILLIONS OF DOLLARS even tens of millions USD annually. 

In theory, in 10-20 years into the future, my startup income, amounting to hundreds of million USD annually can be obtained easily. AND IF FOLLOWED BY MANY COMPANIES IN THE WHOLE WORLD WILL THEN BE A NEW INDUSTRIAL worth trillions USD. 

To be honest. Currently I'm not having a lot of money. So I start marketing my startup with blogspot.

My STARTUP :


A story with millions of choices in it - looking investor like you.



Try to imagine this. When you're reading a story on the web or blog, you are given two choices. You can choose the next story based on your own choice. After selecting then you can continue reading the story. Shortly afterwards you will be presented back to the 2 other options. The next choice is up to you. Then you continue the story you are reading. After that you will be faced again with 2 choices. So onwards. The more stories you read so the more options you have taken.


If you feel curious then you can re-read the story by changing your selection. Then you will see a different story with the story that you have read previously. The question now is why is this so? Because the storyline will be varying according to your choice. 


I, as the author is planning to make tens of thousands of articles with millions of choices in it. With tens of thousands of articles then you like to see a show of your favorite series on TV for several years. The difference is while watching your favorite TV series, then you can not change the story. Meanwhile, if you read this story then you can alter the way the story according to your own choice.

You might say like this. Sounds like a book "choose your own adventure". Books I read when I was young.

Correctly. The idea is taken from there. But if you read through a book, the story is not so exciting. Due to the limited number of pages. When a child first you may already feel interesting. But if you re-read the book now then becomes no fun anymore because you don't get anything with the amount of 100-200 pages. 

Have you ever heard of game books?  When you were boy or girl, did you like reading game books? I think you've heard even happy to read it.

Gamebooks are sometimes informally called choose your own adventure books or CYOA which is also the name of the Choose Your Own Adventure series published byBantam BooksGamebook - Wikipedia, the free encyclopedia
Gamebook - Wikipedia, the free encyclopedia

A gamebook is a work of fiction that allows the reader to participate in the story by making effective choices. The narrative branches along various paths through the use of numbered paragraphs or pages.
Lihat preview menurut Yahoo

Bantam Books with the Choose Your Own Adventure 

series has produced more than 250 million US 

dollars. While I offer you more powerful than the Choose 

Your Own Adventure. Because of what? Because the 

story that I made much more interesting than the stories 

created by the authors of Bantam Books. You will not get anything just to 100-200 pages. While the story that I created is made up of tens of thousands of articles with millions of choices in it.

For comparison are the books published with the theme "choose your own adventure" produces more than 250 million copies worldwide. If the average price of a book for 5 USD, the industry has produced more than 1.5 billion USD. But unfortunately this industry has been abandoned because the reader begins to feel bored. The last book was published entitled "The Gorillas of Uganda (prev." Search for the Mountain Gorillas ")". And this book was published in 2013.

Based on the above, then you are faced with two choices. Are you interested in reading my story is? Or you are not interested at all. The choice is in your hands.
If you are interested then spread widely disseminated this article to your family, friends, neighbors, and relatives. You can also distribute it on facebook, twitter, goggle +, or other social media that this article be viral in the world. By doing so it is a new entertainment industry has been created.

Its creator named Richard Nata.

The full articles that talks about this: 
  



WHY DO I NEED STARTUP FUNDS FROM INVESTORS? I NEED A LOT OF FUNDS FROM INVESTORS BECAUSE I HAVE TO LOOKING FOR EXPERT PROGRAMMERS(IT).BECAUSE THE DATA IS HANDLED IS VERY LARGE, IT MAY HAVE TO WEAR SOME PROGRAMMERS(IT).

I CAN NOT WEAR SOME FREELANCE PROGRAMMER BECAUSE THE DATA MUST BE MONITORED CONTINUOUSLY FROM VIRUSES, MALWARE, SPAM, AND OTHERS.

IN ADDITION FUNDS FROM INVESTORS IS ALSO USED TO BUY SERVERS WITH VERY LARGE CAPACITY. FUNDS ARE ALSO USED TO PAY EMPLOYEE SALARIES AND OPERATIONAL COSTS OF THE COMPANY.

FUNDS CAN ALSO BE USED FOR ADVERTISING AND OTHER MARKETING STRATEGIES.FUNDS CAN ALSO BE USED TO ADVERTISE MY STARTUP AND OTHER MARKETING STRATEGIES.

IF I GET A VERY LARGE FUND, THE PART OF THE FUNDS USED TO TRANSLATE THE STORY INTO VARIOUS LANGUAGES.With more and more languages, the more readers we get.
WITH MORE AND MORE READERS, THE MORE REVENUE WE GET. 

AS AN INVESTOR THEN YOU DO NOT HAVE TO FEEL ANXIOUS ABOUT YOUR FUNDS. BECAUSE YOUR FUNDS WILL NEVER BE LOST BECAUSE IN 3-5 YEARS YOU HAVE RETURNED THE FUNDS COUPLED WITH PROFIT.
THIS BUSINESS IS ONE AND THE ONLY ONE IN THE WORLD.

If we can make a good story, so that the readers will 

come again and again for further reading the story then 

our earnings will continue to grow and will never 

diminish. This is due to new readers who continued  to 

arrive, while long remained loyal readers become our 

customers.

So that the number of our readers will continue to 

multiply over time. With the increasing number of loyal 

readership then automatically the amount of income we 

will also grow larger every year. The same thing 

happened in yahoo, google, facebook, twitter, linkedin, 

and others when they still startup.

Deuteronomy {28:13} And the LORD shall make thee the 

head, and not the tail; and thou shalt be above only, and 

thou shalt not be beneath; if that thou hearken unto the commandments of the LORD thy God, which I command thee this day, to observe and to do [them: ]

Try to imagine this. If I give a very unique story. It was the first time in the world. But the world already know this story even liked it. Because the world love the game books. While the story that I made is the development of game books.
Do you Believe if I dare say if I will succeed because my story will be famous all over the world as Harry Potter?
I believe it. Not because I was the author of the story, but because of the story that I made is unique and the only one in the world. 
Income from my startup :
1. Ads. With millions of unique visitors, the price of the ads will be expensive.
2. Affiliate marketing. In addition to advertising, we are also able to put up some banner from affiliate marketing.
3. Contribution of the readers. If you have a million readers and every reader to pay one US dollar per year then you will get the income of one million US dollars per year. 
If you have a million readers and every reader to pay one US dollar per month then you will get as much revenue twelve million US dollars per year.
4. Books and Comics. After getting hundreds of thousands to the millions of readers of the story will be made in books and the form of a picture story (comics).
5. Movies. If we have a good story with millions of readers then quickly we will be offered to make a film based on the story.
6. Merchandise related to characters. After the movies there will be made an offer for the sale of goods related to the characters.
7. Sales. With millions of email that we have collected from our readers so we can sell anything to them.
    Each income (1-7) worth millions to tens of millions of US dollars. 
    Because each income (1-7) worth millions to tens of millions of US dollars. Then in 10-20 years into the future, AI will be earning hundreds of million USD annually.
So how long do you think my story that I made could gather a thousand readers? Ten thousand readers? One hundred thousand readers? A million readers? Five million readers? Ten million readers? More than ten million readers?
But to get all of it of course takes time, can not be instant. In addition, it takes hard work, big funds and placement of the right people in the right positions.
By advertising, viral marketing, strong marketing strategies and SEO then a million readers can be done in less than a year. Ten million readers can be done in two to three years.
This is the marketing strategy of my startup.
When hundreds of thousands or millions of readers already liked my story then they have to pay to enjoy the story that I made.
If you are a visionary then you will think like this.
With the help of my great name in the world of business, my expertise in marketing, advertising, marketing by mouth, viral marketing, then collecting a million readers to ten million readers will be easy to obtain. Is not that right?
The question now is what if people like my story as they like Harry Potter? You will get tens of millions or even hundreds of millions of email addresses from readers. With that much email, we can sell anything to the readers.
Since April 2013, Wikipedia has around 26 million articles in 285 languages are written by 39 million registered users and a variety of anonymous people who are not known from other parts of the world.  Web ranked by Alexa, Wikipedia is a famous website number 6 which has been visited by 12% of all Internet users with 80 million visitors every month and it is only from the calculation of America.

resource : http://www.tahupedia.com/content/show/136/Sejarah-dan-Asal-Mula-Wikipedia

If no Wikipedia then need hundreds of thousands to millions of books required to make 26 million articles in 285 languages into books.

With the Wikipedia then people started to leave to read a book or books to seek knowledge about a subject or many subjects.

The same thing will happen. Read a story in a book or books to be abandoned. Read a story with millions of choices on the web or blog is far more interesting than reading a book or books. 

So what happens next? In 10-20 years ahead then read a story in a book to be abandoned. Otherwise my startup will grow and continue to develop into a new entertainment industry.

New entertainment industry, where I was a forerunner startup will continue to evolve. 
Therefore, in 10-20 years into the future, my startup will be earning hundreds of million USD annually.

So do not delay. Invest your money immediately to my startup. Take A Look. There are so many advantages if you want to invest in my startup.
WHY YOU SHOULD INVEST YOUR MONEY RIGHT NOW? .
IF YOU INVEST YOUR FUNDS IN ONE, TWO OR THREE YEARS INTO THE FUTURE, YOU MAY BE TOO LATE.
BECAUSE IN 1-3 YEARS INTO THE FUTURE THEN I'VE GOT THE FUNDS. THE FUNDS CAN COME FROM SOME INVESTORS, LOANS FROM BANKS OR FROM ADVERTISEMENTS POSTED ON MY BLOG.

IF I'VE GOT A LARGE AMOUNT OF FUNDS THEN I'VE NO NEED OF YOUR FUNDS. SO INVEST NOW OR NOT AT ALL.

My BLOG started to be written January 11, 2015. TODAY, MAY 30, 2015, THE NUMBER OF CLICKS HAS REACHED 56,750. SO FAR SO GOOD.

If I get big funds from investors then with a quick story that I wrote will spread throughout the world.

So I got acceleration because I can put ads in a large variety of media such as Google AdWords, Facebook, and others. I also can perform a variety of other marketing strategies.
If I do not get funding from investors then my story would still spread throughout the world. But with a longer time, Slow but sure.

So either I get funding from investors or not, the story that I wrote will remain spread throughout the world. Ha ... 7x

So don't worry, be happy.

My advice to you is you should think whether the data that I have provided to you makes sense or not .
If my data reasonable then immediately invest your funds as soon as possible.

Then we discuss how we plan further cooperation.

Thank you.
Lord Jesus bless you.
Amen
P.S. The offer letter I gave also to the hedge funds and 

venture capital and other major companies 

in the entire 

world. So who is fast then he will get it.


P.P.S. In addition, there is one more thing I 

want to tell you. If a story can generate tens 

of millions of US dollars, then what if made 


many stories? Then why do not you make 2, 3 or many stories? You will get hundreds of million USD annually. 

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