Four: Big Data and Reputation
"Big Data" is a popular concept, which considers that a person provides a great deal of information about themselves to the digital world. Every click online leaves a footprint, every transaction involves an exchange of data. Even if they purchase in a brick-and-mortar store and pay their bills by mail, their information goes into various data systems. The theory of Big Data is that if all this information were aggregated, it would provide a very detailed and permanent record of a person's behavior, from which even more information could be derived about their habits, lifestyle, and personality.
Aggregating this data would be a huge task - much of it is stored in proprietary databases of firms that do not wish to share their customer data, and of course there is the desire of customers for that information never to be shared in order to protect their personal privacy. So Big Data remains a theory and not a reality.
(EN: what's not mentioned is that even firms that aggregate a great deal of information about a person, such as their bank or credit card provider, tend not to do much with it. They dispose of the data after seven years, and pay little attention while they have it because they haven't figured out how to monetize it.)
For organizations, Big Data has big potential: if you can predict what a customer is likely to do, you can plan accordingly, significantly increasing your chances of winning their business. A 2014 study on the subject considered 400 companies with advanced data analytics capabilities, and compared to firms that lack those abilities, they were ...
- Twice as likely to refer to data when making decisions
- Five times as likely to make decisions must faster than their competitors
- Three times as likely to execute decisions as intended
- Twice as likely to be in the top quartile of their industries for financial performance
So while "Big Data" remains a myth and an aspiration, the indications are that the use of data in decision-making leads to greater operational efficiency and success. It is certainly better than the instinctual gut-feel approach to management.
In terms of marketing, Big Data has great potential to be a predictor of customer behavior and enable companies to make more accurate and informed decisions. Moreover, the data is growing: with the constant use of smart phones and other portable/wearable devices, more and more data is being collected and aggregated - and there remains faith that it will eventually be utilized.
Big Talk About Big Data
In studying business uses of big data, researchers found a lot more talk than action. More than 90% of C-level executives express a high level of interest in big data and believe it can do wonders for their business, and 56% of them indicated they were basing their business strategies on data.
But most could not articulate quite how, nor give any indication of how they analyze the data they presently have. Only about 39% could provide more than a vague and general description of how data is used, and even of those that did their accounts seemed highly improbable.
In a separate study, 64% of executives complained that they companies were dysfunctional - data is not collected, or ignored, or intentionally disregarded in decision-making processes. So decision making remains very much gut-feel and ignorant, in that it doesn't consider data or, worse, simply dismisses data that does not support their gut-feel decisions.
Customer Personas and Expectations
The author cites a few research studies into consumers' online behavior and privacy expectations.
Online Behavior: Six Personas
The first study suggested that customers adopt personas online (and likely in the physical realm) and can behave very differently in different situations. Specifically, there are six different categories of online behavior:
- Social - Interacting with other people via email, text, social media, and other instances, in which a person projects a positive image of themselves. It is not who they are, but how they want to be perceived, that governs what information they share.
- Professional - When a person is job-seeking or posting information (resume or experience) that might lead to a job offer, they are very circumspect about what they post and prone to exaggeration.
- Financial - Interacting with banks and financial institutions, customers tend to be more transparent. It is understood that a bank or credit card company keeps a lot of transactional information.
- Citizen - When expressing political and religious beliefs, people are very vocal about their opinions but very clandestine about their personal identities.
- Medical - Interaction with doctors, medical institutions, and health insurers is often quite candid, but can also be deceptive because an individual is doubtful about what their insurer will cover or what treatment a provider will prescribe.
- Consumer - When purchasing online, customers understand that a given retailer has a history of past purchases but wish to keep this information compartmentalized - retailers should not share data, and in some instances (unusual purchases or those that impact parts of their lives they want kept secret) they do not wish the retailer to retain the information after the transaction.
It is clear that in each of these six capacities, the consumer has a different level of willingness to share personal information and different expectations about how that information will be handled, such that there cannot be a single set of practices that applies to them in all situations.
Privacy Expectations: Three Paradoxes
In terms of privacy, the author identifies three attitudes he calls "paradoxes" but seem more in the nature of hypocrisies:
- The customer wants to be recognized as an individual and served according to their personal preferences, but does not want to share the data that is necessary to customize service to them.
- The customer wants those who receive their information to go to extreme measures to safeguard it against unauthorized access, but their personal practices (choosing strong passwords, changing them often, logging off a site, etc.) are very much neglected.
- In their social interactions, people want to actively share information that creates a positive impression and recognize that different things make a positive impression on different people, but they do not use groups/filtering and are horrified when information they posted to the public is "discovered" by groups they did not want to know it.
The ultimate problem is that consumers demand a level of privacy but are unwilling to do what they must in order to support it. They expect that the system will know what is appropriate or inappropriate to share, forgetting that computers have neither intelligence, discretion, nor moral sensibility and are ultimately faithful to the manner in which they are used.
Hackers and Brand Trust
Hackers represent an external threat to brand reputation, as consumers are reluctant to trust brands whose information systems are infiltrated. The author lists a few instances in which customer databases were stolen, where customer accounts were hijacked, etc.
It's too often implied in media reporting that these "hackers" represent clandestine organizations with a broader agenda for control, or that they are highly skilled individuals with the ability to bypass sophisticated security systems. Some might be, but most are simply independent vandals with no greater agenda than to cause a little mayhem, and who are not at all technically sophisticated but are simple "script kiddies" who run software that exploit known weaknesses.
As mentioned earlier, the greatest weakness is insecure passwords. One security firm notes that the most common user password is "123456" followed by "123456789" and "password" and "letmein." It's not just individual users, but often systems analysts, who use extremely weak passwords on otherwise secure systems, making them vulnerable to the most simple and primitive "canned hacks."
The convergence of big data and poor security create a situation in which there is a vast amount of data available in corporate systems that is poorly guarded.
To make matters worse, the blame for poor security falls on the brand with which the consumer is most familiar. The media reports that Google or Apple was hacked, not the name of the firm whose security software or services failed to prevent the hack - so the brand most to blame is seldom ever mentioned in the media coverage, and the negative impact is focused on consumer brands while the reputations of the firms that provide security is protected by their anonymity.
Case Study: Music Piracy
There's a brief diversion about the "deep Web" where a great deal of illegal activity takes place - a volume of content that is speculated to be thousands of times larger than the surface of the web, contained in file formats that search engines don't index and often blocked from access by the general public.
As an example, the author mentions music piracy: once a song is digitized, it can be shared an infinite number of times. Bands and record companies have been horrified by this, believing that they were losing billions of dollars in sales on the assumption that fans who download pirated files would have purchased them.
(EN: For a time, there was a counter-argument that downloaders would sample music this way and then purchase if they liked what they heard, but when music went entirely digital, there would be no point in purchasing a CD because the digital copies are just as good and more convenient to use.)
A contrast is drawn between Metallica, who reacted very sternly against the downloaders, and Iron Maiden, who tolerated them. Instead of being horrified that people were stealing their music, the marketers for Iron Maiden did research to find out the locations of the downloaders in planning a tour, recognizing that downloaders were fans who liked their music and would likely attend a live concert. It's implied that the tour was extremely successful in locations that were assumed to be dead markets for live concerts.
Virtualized Experiences
Virtual Reality (VR) is nothing new. It's as old as the written word, as anyone who is able to read and visualize has experienced. Older still, as even illiterate cultures have verbal storytelling, and even before language existed man conveyed the ideas about places and events through pictographs. The emergence of photography and video simply enabled this depiction to be more detailed and accurate, and enabled those without storytelling or artistic skills to share their experiences.
So in the modern day, a person who has never seen something with their own eyes can still give a reasonably accurate description because they have seen pictures and films, read the Facebook and Twitter posts of visitors, and has a fairly detailed idea of what the place looks like. The amount of information we have by proxy is exponentially greater than that which we have by experience, now more than ever before.
It's also mentioned that people are naturally communicative: they want to share their experience with others. The vast amount of data that has been posted to social media in just a few years is testimony that people are not only interested in living vicariously through the experiences of others, but also in sharing their own experiences with others.
(EN: Accuracy is often an issue. The early media were very selective and depended on the skill and choices made by writers and artists. Even modern media is selective, in that people choose the details they share. The popularity of "photoshopping" images shows that people don't want to share reality such as it is, but such as they wish it to be - to alter an image, or even just to crop it, is to exclude detail from the account.)
There's a brief mention of the Internet of Things - recording devices that are simply placed and left to collect information that is automatically digitized and posted. A person may occasionally take a photograph of the view from their window, but a web-connected camera constantly watches the same area. A person may choose where a sensor is placed, but once it is situated and turned on it begins recording and reporting all on its own, without exercising any editorial restraints.
Loose Bits
The author speaks a bit about the risk and rewards for being distinctive. He mentions a popular B2B advertising slogan, "No one every got fired for buying IBM," as indicative of the fear that many executives of being different - and this is often reflected in the way they tend to follow convention. Unfortunately, following convention prevents doing anything distinctive, or even particularly intelligent, that will give their firm any unique quality that gives them a competitive advantage. Products, services, and entire industries are commoditized, stuck in the quagmire of anonymity, by being afraid of doing anything different than anyone else.
He then turns to the familiar example of Apple computer, whose slogan was "think different." The firm became distinctive by focusing on the user rather than the machine - recognizing that people didn't buy machines for their technical capacities, but as tools to accomplish tasks. This user-centric thinking distinguished Apple from every other computer company, which produced "clones" of one another's machines. As a result, Apple was very unpopular with the conservative and fearful business customers, but remains highly popular to this day with the users of their machines.
Switch to another survey, which indicated that about two-thirds of office workers use devices and services other than those provided by their employers. It's an indication that the tools they are given are not up to the job - but more significantly, that business depends heavily on unofficial/unapproved software. To insist that employees restrict their tools is to insist that they restrict their innovation and productivity. It's an attitude that seems to be changing.
Another bit speaks about the widespread rebellion against a UK plan to create a central database to store medical information about all citizens (remember that healthcare is nationalized there, all administered by the government). There remains a great deal of mistrust of institutions when it comes to personal data.