LiveRamp’s Data Collaboration Glossary: A simple list of must-know industry terms

Audience segmentation

Audience segmentation refers to the process of splitting an audience into different segments, each of which have something in common (like interests, age etc.). There are various benefits to audience segmentation, mainly being able to tailor your marketing efforts to audience profiles.

Consumer insights

Consumer insights refer to the assessment and interpretation of consumer data, consumer feedback, and consumer behaviors. Consumer insights can be used to enhance customer support and product development.

See our FAQs page for more information on the different types of consumer insights.

Contextual advertising

Contextual advertising refers to the process of serving ads on webpages deemed to include relevant content, therefore maximising the contextual impact of the ads. Learn more about contextual advertising via our The Renaissance of Digital Advertising ebook.

See our FAQs page for more information on how contextual advertising works and what value it brings to marketers.

Cookieless

Cookieless refers to a type of marketing in which marketers don’t need to use third-party targeting and advertising cookies (text files that include data to identify a user’s device when browsing the internet). Learn how to manage the end of the third-party cookie.

See our FAQs page for more information on a cookieless future.

Cookieless advertising

Cookieless advertising refers to any advertising performed without the use of cookies.

CPG data

CPG data is any data associated with a consumer product goods (CPGs) company. This can be bucketed into three main examples: observational data, activity data, and sales data. Learn how Pinterest increased sales through the utilisation of CPG data.

Cross-channel attribution

In cross-channel attribution, marketers assign credit to each of the media channels and touchpoints involved in influencing a customer’s conversion. Learn how cross-channel attribution works.

Customer data platform

A customer data platform (CDP) is a solution that gathers and unifies first-party customer data from multiple sources. It does this in order to build a single, organised and complete view of each customer.

See our FAQs page for more information on what a customer data platform does.

Data-driven marketing

Data-driven marketing is a data-driven approach to marketing, where data analysis underscores all aspects of a marketing campaign’s efforts.

Data activation

Data activation is what happens when you develop insights from data and then make those insights actionable, thereby unlocking value.

Data clean room

A data clean room is a safe, neutral digital space used for data collaboration. Data clean rooms allow parties to access and share personally identifiable information, allowing them to unlock more customer insights.

See our FAQs page for more information on how a data clean room works.

Data collaboration

Data collaboration refers to the process of two or more parties collating and sharing data from different sources. It generally includes a combination of data sets from multiple teams, including sales, marketing or product management. Read more in our explainer.

Data management platform

A data management platform (DMP) is designed to collect, organise and assess data from different sources. They are designed to collect first-party, second-party and third-party data.

Data marketing

Data marketing refers to any form of marketing that is focused on data. Examples of this data can include customer data, market research, commerical transactions and more.

Data monetisation

Data monetisation happens when marketers or advertisers use data for economic interests. The data itself can be sold with or without additional analysis. It is one of the benefits of data collaboration.

Data sharing

Data sharing refers to the process of making data resources available to one or multiple parties (whether users, individuals or organisations) to enable data collaboration.

Demand-side platform

A demand-side platform (‘DSP’) is software that automates the buying of display, video, mobile and search ads for you. It automates the trickier elements like targeting the right audiences, buying preferred impressions in real time, delivering creative, and identifying appropriate publishers.

See our FAQs page for more information on how a demand-side platform works.

Deterministic matching

Deterministic identity matching creates device relationships by joining devices using directly identifiable personal data, such as email, name, and phone number. Devices are only linked when they are directly observed using the directly identifiable personal data tied to a consumer, prioritizing accuracy and limiting false positives.

See our FAQs page to find out about the difference between deterministic and probabilistic matching.

Differential privacy

Companies use differential privacy to collect and distribute aggregate data about users, while also maintaining individual user privacy. Achieving that requires the addition of random ‘noise’ to the aggregate data — in other words, deliberately perturbed elements which obscures precise details while still allowing for extraction of useful insights. Learn more about differential privacy via our Clean Room Primer guide. Learn more about differential privacy via our Clean Room Primer guide.

Digital fingerprinting

Digital fingerprinting is a process that’s followed in order to recognise and track both users and devices, provided they are online. Learn more about saying ‘no’ to digital fingerprinting.

See our FAQs page for more information on how digital fingerprinting works.

DSP marketing

DSP marketing is marketing that’s focused around demand side platforms. They give marketers the opportunity to buy ad inventory through a single interface, as well as set up their ad campaigns quickly and easily.

First-party data

First-party data comes directly from a company’s customers and is collected with their explicit consent. By collecting first-party data, you can use it to develop strategies, experiences, and campaigns catering to your ideal customer.

See our FAQs page for more information on why first-party data is important, how to collect it and what the difference is between first and third-party data.

Google PAIR

Google’s ‘Publisher Advertiser Identity Reconciliation’ (aka Google PAIR) is an identity solution that brands and publishers can access via Google DV360. Both parties can use PAIR to match their respective customer email lists against the others’ audiences.

Identity resolution

Identity resolution is a process designed to identify users across different devices or channels, and then equating them with specific information for marketing and advertising purposes. This approach aims to create 360-degree customer profiles, which encompass a holistic view of an individual’s interactions and preferences across touchpoints. The profiles themselves act as the cornerstone for achieving specific marketing and advertising goals. In short: they allow brands to deliver more personalized and effective campaigns.

Last click attribution

Last-click attribution is an attribution model used by marketers to evaluate which marketing touchpoint a customer last clicked on (or engaged with) prior to buying. In last-click attribution, that ‘last’ touchpoint is given 100% of the credit for the purchcase. Learn how to avoid the common pitfalls of attribution modelling.

Online to offline attribution

Online to offline attribution happens when integrations with destination platforms enable advertisers to attribute offline transactions/events to online advertising on those platforms. After you upload transaction data (the allowed types depend on the specific integration), you either receive an attribution report from the platform or view the report in their UI. These programs are a great opportunity for advertisers to access measurement/reporting on the efficacy of their campaigns without having to perform the analysis themselves.

Personally identifiable information

Personally identifiable information (‘PII’) is any information that can be used to identify an individual. Examples include direct identifiers like name or address, or quasi-identifiers like date of birth or ethnicity. Identifiers and quasi-identifiers can be sometimes be combined to reveal an individual. Learn more about PII via our guide.

Probabilistic matching

Probabilistic identity matching creates device relationships by using a knowledge base of linkage data and predictive algorithms as the foundation for an identity graph. Devices are also grouped together implicitly—via device fingerprinting, IP matching, screen resolution, operating system, location, Wi-Fi network, and behavioral and browsing data—using statistical modeling at a given confidence level. These groups can be linked to identities based on predictive algorithms.

Pseudonymisation

Pseudonymisation refers to the processing of personal data while avoiding that data being attributed to a specific person. It works by swapping individual identifiers with artificial equivalents.

Retail media networks

Retail media networks (RMNs) are platforms owned by retailers, and used by marketers to reach those retailers’ customers with specific marketing messages. Learn about the 4 things you need to know about RMNs for 2023.

See our FAQs page for more information on the benefits of retail media networks.

Second-party data

Second-party data is essentially another brand’s first-party data. It is a means of unlocking access to high value in-market data outside a brand’s own walls. Brands can use second-party data to engaging in data-sharing partnerships or collaborations, enabling them to match their data with that of other companies.
This helps them build a better picture of their customer base, uncover valuable insights about their own customers, and collectively create a more comprehensive view of their results and market dynamics.

Third-party data

Third-party data refers to information obtained by organizations from external sources not directly involved in their primary interactions with customers. It includes demographics, online behavior and more, collected by data brokers or other entities. Businesses use third-party data for marketing, customer profiling, and data analysis.

Third-party cookie deprecation

Third-party cookie deprecation refers to the transition away from cookie-based advertising. Google’s plan to phase out cookies, making them obsolete by the end of 2024, is a prominent catalyst for this transition. However, other factors — like growing privacy concerns and evolving browser practices — have also played a significant role. The likes of Firefox and Safari have been proactive in limiting third-party cookie tracking.

TV advertising

TV advertising is the process of generating and airing ads or commercials on television.

Walled garden

In data terms, a walled garden is a private programmatic advertising ecosystem operated by the likes of Meta and Google. Everything within walled gardens, including inventory and its buying, serving, tracking and measuring, is owned and operated by the walled garden owner. Learn more about walled gardens via our addressability whitepaper.

Zero-party data

Zero-party data is data a customer has proactively or voluntarily shared with a brand via things the likes of social media and interactive quizzes. Learn about targeted advertising in a post-cookie world.