Introduction to Cindicator (CND) Part 8

Corporations and businesses. Network effect example.

 

As a platform that combines human and artificial intelligence, Cindicator could be of a lot of help for businesses. Many corporations today, including Apple, Johnson & Johnson, Google and others, use collective intelligence in their managerial decision. However, Cindicator could help with more than that because the platform also allows for collection and management of all kinds of data about all kinds of decisions, technologies and practices.

A lot of people do not understand where the real value is in a search engine such as Google. They think that the value is in technology, but other big companies can also create technology. Some think that it’s about people, but other corporations can also hire experienced workers. The real value is in the combination of technologies, people, the network effect and the data. It is the network effect that is responsible for making Google the most popular search engine that by now others simply can’t catch up with.

 

While network effects have existed long before the Internet, the Internet has allowed companies that have network effects built into what they do move ahead faster and more efficiently. For example, today Facebook by far the biggest social network and no other network can catch up with it because of the visible network effect. The visible network effect is very simple: the more people use Facebook, the more people will be joining Facebook and it is easy to see for a person right away whether his or her friends are on Facebook or not. According to the data from Statista, in the United States over 210 million people are on Facebook, which means virtually every adult and teenager.

Google tried to do so with its Google Plus social network, but the network never became as successful as Facebook.

Google by far is the biggest search engine and nobody has been able to catch up with it so far. Yahoo is far behind. Microsoft tried by introducing Bing, but to this day Google has about 70% of the market, Bing around 20% and Yahoo about 10%.

With Google, the most important part of the network effect is about the data. When a person types in a search string into a search engine, the engine gives back a list of results almost instantly. This is what all search engine creators know and this is what all search engines do. But which results are more relevant to the user and which ones would the user prefer? To answer this question, search engines need data. For example, if a user clicks on a search result, takes a look at the page, immediately clicks on the back button and then starts looking at other search results, then it is obvious that the user did not consider the result relevant. If the user clicks on a result, spends a significant amount of time on the page, and then closes the page with the search engine results, then it is also obvious that the user found this latter page very relevant.

Google realized very early that it needed data from the websites that its users visited, which was one of the reasons it created a set of tools for webmasters called Google Analytics. The company has launched this service in 2005.

With Google Analytics, web designers get an extensive set of tools for free. They can see who is visiting their website, where the users are coming from, how much time they are spending on the website, and much more. However, Google also has access to this data. Practically speaking, this means that with every new search that occurs on the Google platform, the platform is collecting more data about it users, the habits of the users, and the websites that the users are visiting. The company can then use this data to create even better algorithms and deliver even better search results to its users. Better search results means that users are likely to use Google again in the future, and Google will again get data to improve its algorithms, and the loop continues.

The competition may be able to hire great scientists and create algorithms, but it does not have access to Google’s data, which is why it simply can’t build the product that would be as good. This is how network effects work in real life.