As consumers of digital (content, messaging, products, and services) every click, hover, swipe, and interaction on our devices constantly accumulates to shape our “digital identity.”
We acknowledge divergent perspectives and applications of this term and offer the following foundational definition for clarity and reference in analyzing its impacts:
A human’s digital identity encompasses all information generated by online and device signals and activities, including claims made by oneself or by another person, group, or entity. Specific facets or versions––personally identifiable, pseudo-identifiable, or anonymous––of a person’s s digital identity are used to represent individuals in specific contexts.
Today, both the concept and the reality of digital identity are highly fragmented. Different attributes, facets, and parts of the digital representation of our selves are scattered, inconsistent, and disjointed across countless organizations, channels, devices, databases, and data types (see figure below for partial list).
Analyzing the impacts of digital identity therefore covers virtually all technologies––any that collect individuals’ data and utilize it for any purpose. This includes advertising and marketing, personalization, customer service, authentication, security, and more.
In this Kaleido Insights impact analysis, we’ll examine the human impacts of digital identity as characterized by the organizations and devices that collect and act on our many data profiles.
About Kaleido Insights’ “Impact Analyses”
Kaleido Insights’ methodology for analyzing emerging technology assesses the impacts on humans, on businesses, and on ecosystems at large. As part of our ongoing coverage, we’ll be analyzing a series of topics using our methodology to help business leaders first understand, and then see beyond the “bright and shiny,” and cut right to what matters.
For each post, all Kaleido Insights analysts conduct a joint analysis session around a single topic (e.g. technology, event, announcement, etc.). In this post, we begin our analysis of the human impacts of digital identity. As this topic is quite robust, we’ll parse our analysis into multiple, more digestible posts, beginning here with assessing user attitudes and psychology, and user behavior and adoption.
- Topic: Digital Identity
- Sub-Topics: User Attitudes & Psychology, and User Behavior & Adoption
- Examples: Identity built within or at the behest of multiple and most often disparate: social logins and online accounts, loyalty programs, “360°” customer record, CRM, biometric authentication, facial recognition, NLP, and many other technologies and systems
- Impact Analysis: Humans (end users, consumers and employees)
Human Impact #1: User Attitudes & Psychology
According to the Privacy Rights Clearinghouse, there have been more than 2,800 data breaches since 2015, impacting more than 8 billion records. Most recently, Facebook’s association with Cambridge Analytica’s questionable data-sharing practices also ushered consumers at large to better examine and understand how their digital identity data is being collected, used, and sold when in the hands of the social giant. But do breaches and scandals like this actually make a difference? Facebook’s advertising revenues largely were not impacted, user utilization actually increased in the month following, and stock prices even went up. Uber, too, has been notoriously known for weathering customer impacts of data scandals via hiding in plain sight.
This begs the question: at what point are such data-driven services so ingrained in our lives that, regardless of a data breach or faulty privacy practices (or threat thereof) around our digital identity, we still choose to forge on with usage? And, do we really care to protect our identities? A new study from AARP reports two-thirds of those surveyed said that, given the number of data breaches that have occurred, it is inevitable that criminals will be able to exploit their credit at some point. We predict that, unless finances or reputation are gravely impacted, many consumers will not shift their attitudes or usage of habitual technologies in the wake of a data breach.
When examining consumer attitudes toward digital identity security, it’s clear that consumers still don’t believe they bear sole responsibility for protecting their data either. IDology’s Consumer Digital Identity Study reports that 67% of people agree it’s a company’s responsibility to protect consumer data, compared to 59% say it’s a consumer’s personal responsibility.
Human Impact #2: User Behavior & Adoption
Companies are sweeping up vast quantities of data about consumers’ activities and inferring profiles, preferences, and behaviors, both online and off. It’s quite impossible to not be attached to multiple digital identities today, based upon the number of companies and technologies we interact with. We all are forced to adopt digital versions of ourselves to exchange with modern-day services and conveniences.
But, a spectrum exists too: ranging from the low end––eg. those “off the grid” individuals who attempt not to be tracked by technology––to the pervasive end––eg. China’s mandated centralization of citizen data and Sesame Score’s impact.
Meanwhile new data collection technologies continue to emerge in the areas of genomics, computer vision, natural language processing/understanding (NLP), simultaneous localization, mixed reality (AR/VR), and blockchain, further adding to the data sources that comprise and authenticate digital versions of ourselves. Adoption of these technologies vary, and we will explore their proliferation more in a later post within this series.
Numerous studies from the likes of Harvard Business Review and Pew Internet have shown that consumers are indeed willing to give up their data if it is in exchange for tangible benefits like convenience, personalization, special offers, and more. This leads to the potential for unique behavioral and business models surrounding “data commerce” to emerge, as consumers recognize the true value of their data and become increasingly empowered by alternative forms of compensation (see figure below).
This framework from Jaimy Szymanski’s TEDx talk outlines four potential future states:
- Data Swindle: When consumers believe they’re receiving “value” by trading their data in return for seamless CX, interesting offers, and advertising-free services.
- Data Wasteland: When companies begin to take advantage of consumers so willingly bartering their data by charging for premium services, products, and tiered subscriptions.
- Data Revolution: Consumers finally say “enough is enough” and begin to take control of their personal identity and its data by closing accounts and decreasing usage of such platforms and services.
- Data Marketplace: Consumers are compensated monetarily for their data-rich identities by companies who wish to utilize such data for research, advertising, innovation, and more.
We’ll continue our analysis of the human impacts of digital identity in our next post where we explore user interface and use cases across myriad industries and behaviors. Please subscribe to our e-newsletter here, so you don’t miss it!