As the American organizational consultant, Warren Bennis, stated: “Trust is the lubrication that makes it possible for organizations to work”, growing customers’ faith has once been the most important thing for the survival of a business. But as time goes by, it seems that a new kind of business strategy that violates the trust-first dogma has been formed, and it should be known as the “data-first” strategy since the top priority of it is to gather customers’ data.
Such strategy first caught public attention in early 2018 due to the Cambridge Analytica data scandal of Facebook. Ever since then the news of data abuses have become frequent to us. Social media sells our personal information has become an open secret, Amazon, Apple and Google have all been reported to secretly listen to our private conversation, and many smartphone apps were accused of collecting users’ data without any permission. It’s obvious that the era of no data privacy has already arrived, and today companies are in an awkward position where they need to ask themselves a crucial question: which one is more important to you – customers’ trust or their data?
In this article, we give a thorough discussion about the data-first strategy, and then making some predictions about the possible futures we may have to face. Finally, some directions of thinking regarding how to choose between trust and privacy are provided, and hopefully this can help you to get a deeper view on the topic.
The factors that fuel the data-first strategy
There’s no way to tell who started it, but it’s certain that the trend is fueled by many things. The followings are factors that in some way contribute to the rise of the data-first business model.
The rise of social media:
Social media has become a necessary part in many people’s lives. Through it we share our moods, thoughts, personal information and private episodes with whom we’d like to connect to, but at the same time exposing ourselves to strangers as well, including those who have malign intention. In other words, social media has made us get used to sharing our own data on the Internet, correspondingly making data gathering easier than ever before.
Besides hackers that steal online data illegally through data breaching, the social media companies, whom we give our info to willingly, may be a bigger threat since many are not aware of the danger behind, and therefore failing to take any action to protect themselves from malicious data use.
Sponsorship-based business model:
Who should pay for an online service is an intriguing question, where there are at least two possibilities: users pay or sponsors pay. While the former is straightforward (who use, who pay), the later is getting more and more popular for app sellers and online service providers since the products can be utterly free for the general public, and it usually results in a larger user number.
From this sponsorship-based model, however, a critical question emerges, that is, what is the advantage for the sponsors who pay the bill? One of the answers to this is to gain commercial value. With more people using the service, the more people will see the ads implanted in the service’ website. Another answer is to directly gain access to users’ data for special purposes, such as doing market research or certain statistical studies. But no matter which one it is, users’ data will be analyzed in some way. For those who aim at commercial value, such analysis can help one to better target the potential customers. As for those who are conducting research, performing statistical investigation is the only way to derive conclusions from the data collected.
Consumers like a company to understand what they want and provide them just that. Or better, the company personalizes its services for every individual according to his or her unique desires. However, in order to do that, the company must study you as a customer in some fashion, and one of the easiest ways is through examining the data about you (e.g., your age, gender, etc.) and your online behaviors (e.g., which pages you spend the most time with, which products you’re currently looking for, etc.). In comparison with asking you to complete a survey, such method can proffer more reliable insights about an individual since the analysis is based on objective data instead of subjective responses. And the business that masters the trick can potentially proffer a better user experiences, making their customers more unlikely to switch to another service provider. In other words, our preference for customized services provides companies a good reason to monitor your actions on the net, and accordingly urging data misemploying.
The thriving of data science and AI-powered products / services:
Today machine learning models still require a large amount of data to train. Yet once properly trained, it can add significant value to a product or service by making it easier to use. According to one survey, the number of smart speakers in U.S. households grows by circa 78% from December 2017 to December 2018, indicating that more and more people are using AI assistant in their life, and it may just provide another excuse for a company to collect your data in the name of providing a better service or product.
Lack of knowledge about how the Internet and computers works:
The Internet and computers are as a black box for many users, and such ignorance makes one extremely susceptible to data abuses because we don’t know when and how to protect ourselves on the net, increasing the chance for us to reveal sensitive info to strangers (especially consider how easy to share data online). The lack of understanding about computers and the Internet also prevents law makers from making pragmatic laws to regulate companies that collect users’ data, making us have no choice but to rely on the conscience of these companies for treating our information properly.
The situation, fortunately, can be improved by a simple means – education, but it does require the current educational system to change with respect to what to teach to our children in school.
How can a company lives without customers’ trust?
Since the companies which adopt the data-first strategy can no longer lure people with their reliability, they will need something else to retain their customers. Lucky for them (and unlucky for us as consumers), there are actually many substitutions they can choose from, and the following are two of them.
Taking advantage of people’s laziness.
Human beings are extremely lazy! Thus, when a product or service that can conspicuously reduce human effort or increase convenience comes out, people will quickly develop dependency on it. Once that happens, even if the service or product provider is proven untrustworthy later on, people will continue to use the service or product as long as nothing deadly serious occurs.
Personal computers, the Internet and smartphones are three of the most representative things that matches the depiction above. Other examples include search engines, social media, e-mail, cloud storage and so on.
Building an ecosystem to prevent users from leaving.
I first discovered the importance of building an “ecosystem” to a business when I was a freshman in the University. At that point, Facebook has become a necessary part for many Taiwanese students. Not only were all my classmates using it for maintaining personal relationships, but they also exchanged important messages about school with it. And because of that, it was almost impossible for one to quit using Facebook; otherwise, you would be literally isolated from all the critical information within the social group.
Today, not just social media, many companies have realized the benefits of having their own ecosystem. As a result, many services or products are built to support only the devices made by a certain manufacturer. Take Apple’s AirDrop as an example, this technique allows one to easily transfer files between devices. But in order to enjoy such convenience, your sending and receiving machines are all have to be Apple’s products.
Other strategies that help building an ecosystem includes using special specs or document format, developing one’s own operating system, growing membership or running online community, and so on.
Some predictions of the future
Since we’ve done discussing the status quo, it’s time for us to make some conjectures about the future. But before getting into the details, one should note that the following predictions do not necessarily contradict with each other. Also, we include a likelihood rating for each possibility based on our own evaluation, with 5 stars mean the highest in chance of happening and 1 star the lowest.
People will get used to it – Likelihood: ***** (almost certain):
It has been an indubitable trend that our data online becomes more and more transparent to the public. These data not only includes the static info we provide (e.g., our name, phone number, e-mail address, etc.) but also the dynamic data that we generate with the use of the Internet everyday (e.g., our posts on social media, browsing history, shopping hobbies, etc.).
Although we may feel uncomfortable about it at first, note that the results of such data transparency are not all bad. By reasonably sharing our data, we can help companies building better services or products, authority guarding our safety more efficiently and so forth. Thus, it’s possible that our next generation will be more open to the idea of their data being collected and scrutinized by companies or government as long as no serious damage is caused.
Our data will be handled 100% automatically – Likelihood: **** (very likely):
Today, many companies, such as Amazon, Facebook and Google, have started to handle users’ data with artificial intelligence. Such approach, if mature, can not only be more efficient than human handling, but it also may proffer an additional value: lowering the chance of data leaks and misuse. The logic behind this is that unlike human being who may have bad or selfish intention, AI is just a program designed to carry out its functions, and it’s therefore less possible for them to steal or leak users’ data.
However, such strategy has at least two major problems. First, the automatic algorithm for data handling nowadays is far from perfect, and therefore all the companies must still recruit human workers to double check the judgment of AI. As a matter of fact, for an AI to have the ability equals to human in respect of content reviewing, we’ll need a system that has an extremely wide range of knowledge and possesses comprehension as good as human’s, and it has been proven to be very difficult to realize.
Second, of course, even if we have employed a super-smart AI system capable of performing all tasks without human supervision, it can still be hacked or programmed to carry out malicious missions, and therefore it’s definitely not an ultimate answer to data abuses.
Big tech companies will fall from grace – Likelihood: ** (perhaps):
With the appearance of Arduino, Python and other open-source hardware / software resources, creating one’s own programs or building personal electronic devices has never been easier before. From here a new possibility rises, that is, at certain point in the future, the knowledge about computer, Internet, programming and electronics become such a common sense that we no longer rely on tech companies to provide us the services or products that we need. And therefore, it’s no longer necessary for us to hand over our private information to a company that we don’t know whether we can trust or not.
However, even thought the bar of becoming a developer has become lower and lower, it certainly hasn’t reached to the point that everyone can effortlessly enjoy. Thus, at least in the short run, one can expect that people will continue to hand over their data to some companies in exchange of a more convenient and efficient life.
Data-collecting companies are perfectly regulated – Likelihood: * (very unlikely):
As long as our economic system remains to be a free market, such thing is truly unlikely to happen. Accordingly, although it has a slight chance to become reality due to the pressure from the general public or Congress, we should not count on it to occur.
Customers’ trust vs. data, which one do you choose?
Like it or not, customers’ data has become the new gold for today business, and consequently it’s time for all of us, both consumers and enterprises, to rethink about where’s the thin line between normal data use and data abuse. In the rest of this article, we’ll point out a few directions where people can be looking at this problem, and hopefully it can help you to obtain your own answer.
Safety vs. Privacy:
Imagine if there’s a chance to stop a mass shooting beforehand, but all messages online will have to be monitored, will you agree to cooperate? Safety and privacy are always on the two sides of a balance: the more information we allow the authority or a company to access, the easier they can spot suspicious activities or individuals and thus keep us secure, but at the same time we’ll lose our anonymity and concealment online. Thus, we’ll have to ask ourselves: which one do we treasure more, our safety or our privacy?
Also, it’s important to consider that whether the one who has access to our data is trustworthy or not. And on a relevant subject: do we trust AI and automation over human being on handling our personal info?
Convenience vs. Privacy:
As many companies and app developers turn to sponsorship-based business model (users use, sponsors pay), more and more free but powerful tools are open to us online. Nonetheless, to enjoy these convenient resources, one may still have to pay some price, and in this case it means your personal data. Are you willing to give up some private data in exchange of a more pleasurable life? If yes, how much of your private data you are willing to give up (or you prefer to pay cash over your data)? These are the questions that we will have to ask ourselves inevitably in the modern life.
Good Products / Services vs. Privacy:
In order to provide finer products or services, it’s natural that a company does some research on the market to better understand their customers. However, how much do you want a company to know you (i.e., what are the necessary data for a business to improve its products and services)? And how do you want a company to know you (e.g., a questionnaire with an informed consent, data automatically collected from the websites and apps, etc.)? These are the crucial questions that will have to be discussed beforehand.
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