How does the selection of systems that implement conversation media occur?

In Biology, the mechanism of natural selection, proposed by Darwin, was fundamental to explain the evolution of living beings and the diversity of species. Conversation system selection differs from natural selection because it’s based on social selection, as will be discussed in this chapter.

Natural selection All species produce a much greater number of individuals than the environment is capable of sustaining. Each individual is different from the others from a genetic point of view and is exposed to interaction with the environment; most die before they are capable of reproducing and only a few survive and do so, leaving descendants that will be a part of the subsequent generation. These better adapted individuals possess a few attributes that make their survival more likely and help perpetuate their species.

Popularity is the indicator that we use in order to measure and compare the success of conversation systems. It shows how well a system is adapted to the contemporary sociocultural environment. We adopted popularity as a success indicator because the value of a conversation system increases with the number of users, as established by Metcalfe’s Law.

Metcalfe’s Law A conversation system presupposes at least two users in order for a conversation to be established. If only one person uses the system, its value will be nil, because it will be useless for conversation. With two people using the system, it acquires usefulness. The more users, the more useful it is. Metcalfe’s Law states that “the value of a communication system is proportional to the square of the number of connected users”. This law explains how to calculate the value of a conversation system based on the number of users of this system.

In order to understand the process of system evolution, we need to establish that the greater the popularity of a system, the greater the chances that its features will be propagated to the next generation of systems. If a system is popular or successful, that’s an important indicator of the acceptance of that set of features by users and, besides, there’s a greater probability that system developers will know these features. Being accepted by users and being known by system developers increases the likeability that features will propagate to subsequent systems, in a process of Lamarckist evolution of use and disuse. If the system doesn’t become popular, its features tend to remain unknown and unable to influence the following generations of systems.

There’s no formula for the success of a conversation system, because, if there were, a renowned company like Google would not have discontinued systems such as Google Buzz and Google Wave, which implemented conversation media. Even though there isn’t a precise formula, the factors that influence the process of social selection are well known, as we will discuss in the sections of this chapter.

Understanding how the mechanism of conversation system selection works and knowing which factors influence this selection allow us to recognize what directs evolution, what leads to success or failure and how things came to be as they currently are.

Social selection

Unlike the natural selection that occurs in Biology, the mechanism that promotes system selection is social selection. People choose which systems they will use, and this constitutes the social selection that determines which systems are better adapted to the cultural environment of a given time.

Social selection in cultural evolution (Nesse, 2009) The development of a culture is the result of choices and behaviors of people throughout history. Social selection helps us understand cultural evolution and the cooperation among people. It’s related to the very survival of the species.

The users are the ones responsible for system selection. Without users, systems are doomed to be forgotten, to become extinct. The systems that survive are the ones that are mostly used, those that manage to attract and keep users. Systems can be compared to living beings that feed off users; users are the resources for which systems fight.

Even if a system has innovative features, in order for these features to influence subsequent systems, they have to become known. If a system is adopted by many people, it becomes popular and successful, and its features influence the development of posterior systems. Otherwise, the system fails and is discontinued; the company abandons its development, removes access to it and no longer offers it support, and its features are forgotten. With discontinuation, web systems are no longer available; smartphone systems are removed from application stores; and desktop systems are only used by those who already had a copy installed – new users don’t have the option of choosing that system.

Factors that lead to the success or failure of systems

Some factors contribute to the success or failure of a system: the people who designed it, its marketing, those who influence the adoption of a system by users, and the competition between systems.

Factors during the design phase

Many systems are interrupted even before they are released: the failure rate of projects is between 60% and 70% (Gordon, 2013). Failure happens due to problems such as: lack of support from the board of the company, lack of clear business purposes, scope, lawsuits, failures in management and execution, technological inadequacies and infrastructure inadequacies. However, the most frequent problems are related to the complexity of the project: systems that are more complex need more time to be developed and have higher costs.

One of the solutions found to decrease the odds that a system will fail still in the project phase is the release of Beta versions, considered unfinished. The acceleration of development and the characteristics of web and smartphone platforms contribute to make changes in features occur at increasingly shorter intervals; users already expect changes to be presented in updates.

Marketing

Marketing influences the success or failure of a system. Marketing is meant to generate value and consumer satisfaction in order to identify consumers’ needs and attract them to buy or use a product or service. Marketing encompasses a strategy that includes product, price, promotion and distribution. The system is generally seen as the product. However, if the system is free, as is the case of the majority of systems that implement conversation media, the product is the user.

When the user is the product Developers offer free access to a system; however, they’re compensated for this offer by selling the browser data of system users to ad buyers: “if you are not paying for it, you’re not the customer; you’re the product being sold.” (Lewis, 2010).

After a system is released, the company that developed it has to publicize it, in order to make it reach its target audience. It’s through the system’s publicity that its features come to influence other projects. This influence occurs even after a system is discontinued, because records of it or the memory of it remain.

For a system release to be successful, new ways to publicize it were developed. One of them is viral marketing, where a system becomes successful because each new user attracts more users by showing them that they use the product.

Viral marketing in Hotmail’s release This concept inspired the developers of Hotmail to publicize the system by using, at the end of each message sent by a user, the slogan “P.S. I Love You. Get your free email at HoTMaiL” with a link for the registration of a new user. In less than six months the system, released in 1996, reached one million users. This marketing strategy was adopted to publicize several systems, such as Twitter and Gmail, which encouraged users to send invitations for their contacts to create accounts.

Another marketing strategy is releasing the system in a controlled manner, limiting its access to a specific group of users. That was Facebook’s strategy.

Facebook’s gradual release Facebook was first released in Harvard University, where Mark Zuckerberg and the other founders studied. The website, in a gradual and controlled manner, added students of other universities before allowing the access of high school students and, later, of anyone who was over 13 years of age.

Marketing is not enough to ensure the success of a system. Even with all publicity advantages, a system released by a big company like Google is not a guaranteed success, as exemplified by the systems Google Wave and Google Buzz, which were considered failures and were discontinued shortly after being launched. Both systems became known by many users because they were amply publicized in the media or because they were integrated to other systems, such as Gmail. However, being known by users doesn’t guarantee use after the first experiences; other factors influence the adoption of systems.

Factors that influence the adoption of systems

The process of adoption of a system by a user goes through different stages: knowledge, persuasion, decision, implementation, confirmation (Rogers, 1962 and 2003). When an individual comes to know a new system and becomes curious, they pass to the persuasion stage, in which they look for information and details. After analyzing the advantages and disadvantages, they make a decision about adopting the system or not. After implementing and using it for some time, the individual either confirms or goes back on their decision.

The factors that influence the decision of adopting a system are related to the acceptance of the technology, to the benefit-cost ration of the adoption and to the number of users of that system.
According to the Acceptance of collaboration technology model (which includes systems that implement conversation media), the determinant factors in implementation decision are: the system, task and user characteristics, and the opinion of other users.

System characteristics: purpose definition and social presence are system characteristics that influence its adoption. If the purpose of the system isn’t well presented, the user will find it difficult to understand the utility of the system. If the user doesn’t have a clear perception of interlocutors, it will be hard to establish conversations. Task characteristics: the need for the user to access the system when they’re outside the work or home environment, the number of people involved in the conversation and the possibility of mistakes occurring when a task is being performed through the system are factors that influence the choice of the user. Tasks performed on the move or outside the work or the home require the adoption of systems designed for smartphones. Tasks that require a conversation among many people imply the adoption of systems that implement conversation media meant to be used by several interlocutors, such as forum, chat and group messages. Complex tasks – which can generate multiple interpretations, doubts or mistakes – lead less experienced users to choose systems that minimize those problems. User characteristics: the ability to use a technology influences the acceptance of a system. A user that has experience with systems of a given conversation medium requires less learning time and is among the first ones to adopt a system and influence the adoption by other users. The opinion of other users: the individual choice of which system will be adopted to establish a conversation is greatly influenced by other users. The adoption by other people directly influences the use of systems; even if the conversation system is useful and easy to use, if the people with whom the user has relationships don’t adopt it, the user tends to stop using it.

The adoption of a system also depends on the benefit-cost ratio: the more people who are well-known use a system, the greater the incentive for the other members of a social group to use them also, increasing the cost of its non-adoption.

 

Benefits of adoption and costs of non-adoption of a conversation system (Markus and Connolly, 1990) The decision to adopt a system is influenced by an evaluation of the costs and benefits of that adoption. In part, this cost-benefit evaluation is related to a system’s number of users. After the system gains a critical number of users, the benefits of adopting it surpass the costs (such as the cost involved in learning to use the new system or leaving aside a competing system). As more people adopt a conversation system, the benefits of using it increase (As explained by Metcalfe’s Law). There comes a point when the number of users is so big that even the ones that are most resistant to new technologies are led to adopt the system. This characteristic is favorable to the concentration of users in one or few system, constituting a winner-takes-all market. One example of this is Facebook: with over one billion users, it became the most used social network in nearly all countries.

The number of users greatly influences the decision of adopting a system. An individual adopts a technology due to the influence of other individuals that adopted it previously. In relation to the moment in which they adopt a new system, users are classified in the curve of adoption as: innovators, early adopters, early majority, late majority and laggards (Rogers, 1962). A system is initially adopted by few innovators that like to search for new technologies and to try new systems and features. If those innovators like a new system, they attract early adopters, who in their turn influence the opinion of the early majority, with the system than obtaining a share of the market. This mass of users pressures even the most resistant, who compose the late majority and the laggards, to adopt a system.

 

Innovators: they are the first individuals to adopt a new technology. They’re technology enthusiasts, they’re younger, they have a high social and educational level and they know how to handle finances and, therefore, are more likely to deal with the risks of using a new technology. They have the advantage of interacting with other innovators. One example are the young people who began abandoning Facebook to talk to their friends through apps like WhatsApp; Early adopters: they are the second group to adopt a new technology. They have characteristics that are similar to those of innovators, but they’re more discreet in the acceptance of new technologies and are more sensible and discerning in their selection process. They play the roles of leaders in the diffusion of the technology. One example are the first friends that young innovators invited to use WhatsApp; Early majority: they’re pragmatic and decide to adopt a technology when the benefits have been proven and the risks are acceptable. They also have a high social and educational level, but their opinion is less influential in leading other people to adopt the technology. They need the system to be known and used by many people in their social group; Late majority: they’re conservatives and they adopt the new technology after most users, and generally only due to social pressure. They’re skeptic in the adoption of a new technology, they take few financial risks, they are, on average, of a lower social level than innovators, early adopters and the early majority, and they have little influence in the adoption of technologies by other people. This group is partly composed by older users who adopted Facebook after they noticed that conversations among their friends and relatives were taking place through this social network; Laggards: they’re the last to adopt a technology because they’re very resistant to change. They’re connected to traditions, are averse to change, have few social relationships and hardly no influence in the adoption of new technologies. They adopt these technologies only when they don’t have any other choice. Examples of this group are those people who took a while to abandon postal mail and begin using email.

 

Competition

The adoption of a conversation system by a user is subject to influences such as the migration of their contacts to a competitor. Throughout time, a user will stop using a given system and adopt another because they consider it more popular. An example of this phenomenon was the mass migration of MySpace users to Facebook that took place in the US around the year 2008.

<https://www.google.com.br/trends/explore#q=myspace%2C%20facebook&cmpt=q&tz=Etc%2FGMT%2B3>.

As Facebook gained adopters, more people were led to use it as a social network; as MySpace lost users, the less benefits there were in using it. Facebook became so successful, with over 1 billion users all over the world, that not using it meant giving up many interaction opportunities that take place among users.

A popular system has its popularity threatened by competitors all the time. Moreover, changes in culture and the release of new technologies for a given support are also constant threats to market leaders. New competitors can one day occupy the first positions, while former leaders decline in popularity. The release of new technologies for a support influences cultural change, particularly when these technologies provide a new platform for development, such as the web and smartphones. For example, with the popularization of social networks, Facebook’s messenger became popular and decreased the uses of system based on the desktop platform, such as MSN Messenger, which was once a market leader, but was later incorporated to Skype and discontinued. WhatsApp, in its turn, became the leader in the market of smartphone messengers, and was later bought by Facebook.

Many innovations are released by new companies, the so-called startups. Instagram, Skype, Twitter, Hotmail and Blogger are a few examples of systems that were developed by startups and presented innovations in comparison with systems that implemented the same conversation medium. Bigger companies, which already have their share of the market, are more resistant to change. However, when a startup’s system is successful, it tends to be acquired by a bigger company; for example, Skype and Hotmail were bought by Microsoft, Blogger was bought by Google and Instagram was bought by Facebook.

Blogger, Google, Twitter, Instagram: a trajectory A curiosity about the acquisition of Blogger by Google is that Evan Williams, one of the founders of Pyra Labs, responsible for Blogger’s release, after one year working in the system’s development team at Google, left to found another company, Odeo, which years later was responsible for the release of Twitter. One of the interns at Odeo was Kevin Systrom, who also worked for Google and years later released Instagram.

 

 

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