Unlock the Power of First-Party Data
Identity has always been the cornerstone of customer intelligence, enabling brands to gain a complete view of their customers so they can see them as real people, across channels and devices, and understand what they want. But a number of factors —including the deprecation of third-party cookies, increased privacy regulation, and the growing complexity of the martech landscape—have made identity a pressing priority for marketers in recent years.
It’s not just these industry changes that highlight the need for a robust yet flexible identity backbone. Your enterprise is constantly changing as it adopts new technologies, and explores new systems and channels for customer engagement. Can you maintain a unified view of your customers through all that? Finally, your customers themselves are always changing. They’re moving houses, switching numbers, changing jobs, even changing names. Keeping up with these changes across 260 million US adults is a never-ending challenge for any brand.
Data is Static. Your Customers Are Not.
Because identity is fueled by data about people, which is constantly shifting, you have to reconcile new signals and ever-changing information about individuals. In other words, identity is as much about data management as it is about understanding.
“Data is like electricity for businesses: essential to almost every aspect of its operations, but deadly if mishandled.”
— Dave Frankland, Co-author of Marketing to the Entitled Consumer
Getting Identity Right
So identity is critical to customer intelligence, and it’s only growing in importance as the digital landscape shifts around every brand today. But identity is still, somehow, a widely overlooked and undervalued capability.
To build an enterprise-level identity management capability, you need strong data expertise, the right processes, and the best technology in place. This ensures you can connect with people as individuals now and in the future—all with a compliant, privacy-by-design approach.
Maybe you’ve worked with a referential graph, also known as a third-party or public graph. This kind of graph is made up of data that you and your competitors all have access to, so it can give you a good idea of individual and household identity—but that’s often not enough on its own.
To build a complete view of identity that reflects the needs of the individual and your business, you need what’s called a first-party graph as your foundation. This represents your brand’s unique view of the people you’re trying to engage, encompassing personally identifiable information (PII) and digital signals, across the offline and online worlds. We’ll dig into more definitions later.
For now, ask yourself a few important questions about your identity capabilities:
- Are you collecting data at every engagement?
- Are you informing platforms and channels of engagement with a single view of identity?
- Are you in control of your enterprise identity or are you dependent on third parties?
- Are you able to deliver a consistent and individualized customer experience across all touchpoints?
Read on to learn what the key terms in this space mean,
and how to unlock the power of first-party data.
Defining Our Terms
What is Identity?
IDENTITY - The ability to recognize an entity, be it a person, household, place, or other customer type, along with associated relationships, consistently and accurately based on both physical and digital attributes, regardless of channel, location or device with contextually appropriate levels of precision.
IDENTITY RESOLUTION - A data management process or framework that pulls information from disparate datasets to identify customer and prospect relationships creating group identifiers such as individual, household, business, etc.
IDENTITY MANAGEMENT - The ability to manage identity over time using all possible identifiers across all possible touchpoints, behaviors and devices over the individual’s history with a brand to improve precision and reach, specifically focusing on brand-specific rules for resolving identity and ultimately driving human-like interactions and closed loop attribution at scale. Identity management solutions must be agnostic and flexible enough to adapt to new sources/types of data without having to ‘rip and replace’ your existing solution to accommodate these changes.
Different Types of Graphs
IDENTITY GRAPH - A repository of all the identifiers and signals associated with a person that is organized to provide a single view across disparate sources. Graphs connect and maintain consumer identity across touchpoints, devices, channels, and dynamic identity relationships such as households.
REFERENTIAL GRAPH - Third-party, multi-sourced identity graph that supports point-in-time match services to brands. Brands have no control over the manner in which entity IDs are assigned/managed. Intelligent entity IDs can only be assigned where source data is able to be correlated to the graph.
PRIVATE IDENTITY GRAPH - A brand-specific first-party identity graph that utilizes the brand’s own data assets to curate brand-specific enterprise entity views over time. It may also utilize third-party identity assets with first-party data for optimal resolution and persistence.
CROSS-DOMAIN GRAPH - Third party identity graph that maps to a network of match partners for onboarding (e.g. LiveRamp, Neustar) essentially, a combination of the leading online websites and publishers.
Collecting Data: Terms to Know
ZERO-PARTY DATA - A subset of first-party data, this is data that a customer intentionally and proactively shares with a brand. It can include preference center data, purchase intentions, personal contexts, and how an individual wants to be recognized by the brand
FIRST-PARTY DATA - First-party data is information a company collects directly from its customers and owns. It is the best form of data from a privacy and compliance perspective.
SECOND-PARTY DATA - Second-party data is essentially someone else’s first-party data. Most often, this is in the form of “partner data” provided to build a better understanding of individuals and households that could represent customers or prospects in the brands’ and partners’ worlds.
THIRD-PARTY DATA - Information that is ethically collected from a wide variety of sources by third-party aggregators, and is sold or shared with brands that do not directly interact with the customer or user.
PERSONAL IDENTIFIABLE INFORMATION (PII) - The definition of PII can vary based on legal jurisdiction but for the most part, PII is data that could potentially be used to identify a particular individual, including contact information (full name, address, email, phone) and more sensitive identity attributes such as Social Security Number, driver’s license number, bank account number, passport number, postal address and email address.
TAGS AND PIXELS - The use of a short segment of code, placed in a website’s source code in order to recognize user actions and collect data. A first-party tag is specific to a brand and has a privileged position in terms of browser behavior, meaning that it is able to more accurately persist an identity across owned media (first-party domains). This data is used to support higher match rates and downstream use cases involving identity resolution and management. A third-party ad placement tag, owned by publishers, is code generated for placement into an ad server, and is able to capture activity (impressions and clicks) from paid media campaigns and other third-party contexts.
IDENTIFIERS - There are many types of IDs that exist to uniquely identify a user. Some commonly known third-party identifiers include cookies which are being deprecated by Google, mobile ad IDs or MAIDs, and Apple’s Identifier for Advertisers (IDFA). Many alternative identifiers such as UID 2.0, are being evaluated in the ecosystem in the wake of cookie deprecation. First-party identifiers are unique to a brand and serve to consistently recognize consumers as they interact with the brand and are not subject to privacy regulations because they result from the brand’s direct relationship with the consumer.
Creating Intelligence: Terms to Know
KNOWN - Offline, terrestrial, or known data that can include PII tied to a specific individual.
PSEUDONYMOUS - The processing of personal data in such a manner that the personal data can no longer be attributed to a specific person without the use of additional information.
MATCHING - Matching refers to the process of comparing two different sets of data and matching them against each other. This can be deterministic (for exact matches) or probabilistic (for a desired degree of similarity between datasets).
STITCHING - As in the type of matching typically done in CDPs, stitching is most often a type of simplistic matching designed to produce faster results. Most often, it is a hard key match based on an account ID, email address, and/or phone. In some cases stitching mimics string matching by using “normalized” PII-based data mapped to an algorithm. At best, stitching is a compromise in match precision for fast response and is not used in true identity resolution/identity graph applications.
CUSTOMER VIEW - A customer view is a compilation of information, including demographic, geographic, psychographic, and behavioral data, to create a detailed and holistic understanding of people for marketing and research purposes.
Connecting Everything: Terms to Know
DATA ONBOARDING - The technical process of uploading offline customer data to the online environment to match with digital identifiers.
ACTIVATION - API-driven capability to push data to the digital ecosystem.
WALLED GARDENS - Closed platform or ecosystem wherein the provider of the platform has total control over the content, applications, and/or media and restricts access as it sees fit with the end goal of creating a monopoly (e.g. Facebook, Google, Amazon).
PERSONALIZATION -Collecting data to tie to one individual to drive relevant and consistent communications.
MEASUREMENT - Ability to tie data together to determine value/results of activity like the success of a marketing campaign.
Staying Compliant: Terms to Know
PRIVACY PREFERENCES - Your understanding of if, when, and how people want to be communicated with and how they want their data to be used, and your management of those preferences.
COMPLIANCE - Privacy compliance is the line between the legal and the illegal. Such regulations help protect consumers in different countries by ensuring data is handled appropriately.
PRIVACY BY DESIGN - Acxiom’s core technology and data governance practice to ensure data protection and compliance with global government privacy regulations and consumer preference practices.
DATA GOVERNANCE - The process of managing the availability, usability, integrity and security of the data in enterprise systems, based on internal data standards and policies that also control data usage.
Technology: Terms to Know
CUSTOMER DATA PLATFORM (CDP) - Software that aggregates and organizes prospect and customer data across a variety of touchpoints and is used by other software, systems, and marketing efforts. CDPs collect and structure real-time data into individual, centralized profiles that are primarily used for audience activations and campaign planning. The primary focus of a CDP is marketing, not wider enterprise identity.
DATA MANAGEMENT PLATFORM (DMP) - A technology platform that gathers, sorts and stores digital audience data (primarily cookie-based information) to build audience segments for media targeting. Includes anonymous user data so no PII is stored/managed. DMPs are being phased out due to changes in the industry. Both Adobe and Salesforce have announced they’re stopping sales of their DMPs.
MASTER DATA MANAGEMENT (MDM) - A technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise’s official shared master data assets. Multi-domain including customer, product, and location. MDMs historically take a ‘golden record’ approach, and they can require a longer time and higher investment to implement, so they may not be the best bet if you’re only looking to manage a single domain.
Identity and Addressability on a Spectrum
What Success Looks Like
With the help of Acxiom Real ID™, a national retail brand was able to improve communications with customers across more touchpoints, achieving:
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more individuals recognized
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of records with blank addresses enhanced
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of outdated addressed updated
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of missing email addresses appended
Another retailer reduced advertising waste, unlocking 10% savings in ad budget via optimized campaign targeting.
A major financial services company increased activation match rates, leading to 30–90% higher rates compared toother vendors and current distribution partners.
A top-10 financial services company used Acxiom Real ID™ to elevate media measurement, achieving
150% higher attribution of conversions to paid media.