5.4. On the Eve of Revolution

At present, telecom providers, banks, and so on build their own local and closed database about clients. A given client is registered individually in each of the systems, and these data are closely guarded (see example in Figure 5.1). Companies do not usually exchange these data with one another¹² due to legal restrictions (e.g., data protection), obligations to a client in the scope of confidentiality, the fear of losing clients, or legal claims due to data leakage.

Figure 5.2 shows hypothetical warehouse data about clients, where Ω is identified as a client:

• α in a cellular telecommunications provider A
• β in a retail bank B
• γ in an Internet social media portal C

Thanks to this integration, the data of a client’s banking operations, telephone contacts, and social media activity are connected. What is most significant here is the synergy effect: the fact that we learn more from the two pieces of information combined than we would have learned from them individually.¹³ Is the situation shown in Figure 5.2 possible at all?¹⁴ Refraining from considering this issue from the formal and legal angle or in the context of works conducted by governmental institutions,¹⁵ let us ponder it on a purely technically basis and consider the possible business consequences of such a solution. The idea of the registration of data connected from all aspects of an individual’s life took shape in the MyLifeBits project.¹⁶ Its author, Gordon Bell, formulated the concept of tracing events from the life of a specific person. These events can be stored on a computer and searched. The following events from a person’s life could be registered:

• Written documents (e-mails, articles, notes, letters, blogs, bills, etc.)
• Viewed e-mails, newspapers, websites, studies, books, etc.
• Viewed photos, images, and posters
• Music (radio, CDs, MP3s, etc.)
• Movies
• All owned files
• All telephone calls and sent or received texts and MMS
• Shopping done
• Places visited
• Results of both periodic medical tests and day-to-day monitoring of one’s pulse, body temperature, etc.

In the final phase of the project, it was even tested to see whether it would be possible to register all the events in a person’s life by means of a head-mounted camera. Data warehouses with a large memory capacity, which are able to store the data provided for a person’s whole life, are cheap and easily available. For a better understanding, let us consider two possible applications:

1. Recommendation of an optimal diet and warnings of dangerous dietary practices on the basis of
   • analysis of day-to-day monitoring and history of consumed products;
   • health;
   • availability of recommended products;
   • analysis of the diet and its results for people with similar health problems.
2. Support for a high school graduate in selecting a university and major on the basis of
   • evolution of interests;
   • ranking and kind of high school he or she graduated from;
   • availability of universities and analysis of their graduates’ careers;
   • data about employment, demography, and forecasts about the developments of different sectors;
   • career paths of people with similar career profiles.

All in all, the vision of a total-surveillance society in a totalitarian state ruled by Big Brother, as described in Nineteen Eighty-Four by George Orwell, is at present technically viable. However, the so-called paradox of privacy and confidentiality emerges.¹⁷ There is a natural contradiction between clients’ concerns about their privacy and their desire to receive messages that are adjusted to their needs. It is impossible to satisfy these two mutually opposite needs at the same time. Clients can consent to their personal data being processed and even support the process of building their profile if, for instance, they are given

• a possibility to sell their profile, for example, to companies that manage marketing databases for direct marketing purposes;
• special offers, bonuses, discounts, promotions, and so on;
• a high-quality personalized message in the area they are particularly interested in, provided that they have a guarantee that the information about them will remain confidential.

Google products may become an interesting platform for the application of customer intelligence techniques. Let us consider its business model and current solutions as an example of potential analytical possibilities. The basic business model provided by Google consists of offering Internet advertisement related to specific keywords. Therefore, these advertisements reach users by means of sponsored links, among other things, and Google matches their interests expressed by entries in the search engine.

As mentioned before, it is important for advertisers to adjust their marketing message to match the targeted user’s profile. Therefore, the collection of information about clients enables Google to profile clients potentially very precisely. This should result in Google being able to offer advertisers numerous target groups that are interested in advertised products and services. One of the ways to achieve this could be to ensure Internet users free access to a number of Internet applications. If registered users take advantage of such an offer and use the search engine, a notepad, blogs, and documents, it is possible to determine their interests, views, opinions, career profile, and so on, and then their contact groups and the nature of those personal contacts, business contacts, interests, and so on might be determined when they make use of discussion groups, e-mail, or calendars. Subsequently, it is highly probable to be able to determine age, sex, education, occupation, place of residence, income, and so on. Requiring an ID¹⁸ to allow the client access to all the applications solves the problem of identifying a specific person. Giving one’s ID plays a key role in, inter alia, linkage of a client’s various activities.

As a result, personalized marketing activities as shown in Figure 5.3 become possible. The clients’ activities can be monitored and their data stored in the data warehouse. Consequently, the history of clients’ behavior is retained and their profile discovered. Such a profile is dynamic by nature and is updated after each activity at fixed intervals. The creation of the profile might be supported by BI methods. It’s worth remembering that the cross- and upsell proposals for a given target group can make use of data-mining methods. Single profiles can be grouped accordingly, and that might be the basis for determining the regularity and rules for client segments. A lot of items in a profile are derived data, which means that this knowledge is unreliable. This is due to the fact that there is a great quantity of text data (i.e., blogs, e-mails, documents). It is essential to use text data-mining methods. The profile of a given client is the basis for the selection of an advertised product.¹⁹

In this context, virtual reality simulators such as Second Life²⁰ seem to be an interesting research laboratory. In such artificial worlds, total surveillance is possible, which translates into extremely precise profiling. Consequences for marketing are remarkable, but consequences for mankind are alarming.