abdullah video m2(25) Alibaba stock secrets and the Future of Business

 Alibaba stock secrets and the Future of Business

Seven of the 10 most valuable companies in the world right now are internet companies with business models . Five of them have been around for less than 20 years: Amazon, Google, and Facebook in the United States, and Alibaba and Tencent in China. Why did so much value and market power come about so fast? Because of new ways to coordinate networks and get information from data that all of these companies use. They take care of ecosystems that are much more customer-focused and economically efficient than traditional industries. We call the way these companies do business "smart business," and we think it will be the most important way to do business in the future. In today’s video, we will discuss the secrets of Alibaba and the Future of business but before that, subscribe to our channel and hit the bell icon. 

What makes a business smart?

Step 1: "Datafy" every exchange with a customer.

Ant was lucky to have access to a lot of information about possible borrowers, which helped it answer the questions that its lending business raised. The process of getting data will be harder for a lot of businesses. But feedback loops, which are the foundation of machine learning, can't be made without live data.

Think about the business that rents bikes. Start-ups in China have made the whole rental process more data-driven by using mobile phones, the internet of things (in the form of smart bike locks), and existing mobile payment and credit systems.

In the past, renting a bike meant going to a rental place, leaving a deposit, getting a bike, using it, bringing it back, and then paying for the rental with cash or a credit card. Several Chinese companies that competed with each other put all of this online by combining new and old technologies. The clever use of QR codes and electronic locks to automate the checkout process was a key innovation. When a rider opens the bike-sharing app, they can see which bikes are nearby and reserve one. When the rider gets to the bike, he or she scans a QR code on the bike with the app. The QR code will open the electronic bike lock if the person has money in their account and meets the other rental requirements. The app can even check the person's credit history through Ant Financial's new online consumer credit rating service, Sesame Credit. This lets the rider skip paying a deposit and speeds up the process even more. When the bike is returned, the transaction is complete when the lock is shut. The process is simple and easy to understand, and it usually only takes a few seconds.

In a smart business, software is used to set up all activities, not just knowledge management and customer relations, so that decisions that affect them can be made automatically. This doesn't mean that a company needs to buy or make ERP software or something similar to run its business. In fact, the opposite is true. Traditional software makes processes and decision-making more rigid and often turns into a straightjacket. Smart business, on the other hand, is based on acting in real time. The first step is to make a model of how humans make decisions now and find ways to use software to copy the simpler parts of that process. This isn't always easy, since many human decisions are based on common sense or even unconscious brain activity.

Alibaba Group's website for shopping in China, Taobao, is growing because the way people shop is getting easier and easier. One of the first big software tools made for Taobao was a tool called Wangwang that lets buyers and sellers easily talk to each other through instant messaging. With this tool, sellers can do things like greet buyers, tell them about products, negotiate prices, and so on, just like they would in a regular store. Alibaba also made a set of software tools that help sellers create and open a wide range of high-tech online storefronts. Once online shops are up and running, sellers can use other software to issue coupons, offer discounts, run loyalty programmes, and do other things related to customer relationships. All of these things work together.

Step 3: Let the information flow.

Business decisions are hard to make in ecosystems with a lot of interconnected players. For example, Taobao's recommendation engines need to work with the systems that sellers use to manage their inventory and with the systems that social media sites use to profile their users. Its transaction systems need to work with discount offers and loyalty programmes and connect to our logistics network.

Communication standards like TCP/IP and application programming interfaces (APIs) are important for getting data to flow between multiple players while keeping tight control over who can access and change data in the ecosystem as a whole. APIs, which are a set of tools that let different software systems "talk" to each other and work together online, have been very important to the growth of Taobao. As the platform grew from a place where buyers and sellers could meet and sell goods to China's most popular e-commerce site, merchants on the site needed more and more help from third-party developers. For the new software to be useful, it had to work with most of the other software on the platform. So, in 2009, Taobao started making APIs so that other companies could use them. Today, merchants on Taobao subscribe to an average of more than 100 software modules. The live data services that these modules make possible greatly reduce the cost of doing business for merchants.

Step 4: Use the formulas.

When a business moves all of its operations online, it will get a lot of information. To take in, understand, and use the data to its advantage, the company must create models and algorithms that make clear the underlying product logic or market dynamics that the company is trying to optimise. This is a huge creative project that needs a lot of new skills, which is why there is a huge need for data scientists and economists. Their challenge is to say what job they want the machine to do, and they have to be very clear about what a good job is in a certain business setting.

From the beginning, our goal for Taobao was to make it fit the needs of each person. Without progress in machine learning, this would not have been possible. When a customer logs on today, they see a personalised page with a selection of products chosen from the billions that our millions of sellers offer. The list is made by Taobao's powerful recommendation engine, which chooses the items automatically. Its algorithms churn data from all over Taobao's platform, from operations to customer service to security. This is done so that the conversion rate of each visit is maximised.

Creating a smart business starts with these four steps: Engage in creative datafication to add to the pool of data the business uses to get smarter; software the business to put workflows and key actors online; implement standards and APIs to allow real-time data flow and coordination; and use machine-learning algorithms to make "smart" business decisions. All of the four steps' tasks are important new skills that require a different kind of leadership.

CONCLUSION

Digital-native companies like Alibaba have the advantage of being born online and ready to use data. This makes it easy for them to switch to smart business. Now that they have shown that the model works and are changing the old industrial economy, it is time for all companies to understand and use this new business logic. That may seem hard to do with technology, but it's becoming more and more possible. Since cloud computing and artificial intelligence have become commercialized, anyone can now use a lot of computing power and do a lot of analysis. In fact, the cost of storing and processing large amounts of data has gone down a lot in the last ten years. This means that machine learning can now be used in real time and can be done for less money in more and more places. As the internet of things grows quickly, more and more of our physical world will be turned into digital data. As all of these new ideas come out over the next few decades, companies that learn faster than their rivals will win.

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