The data-driven advertising industry moves fast. So does its lexicon. If you’ve ever felt confused by a certain term, you’re not the only one! This glossary helps clarify the landscape’s most important terminology. Find the definitions you need here — and get a deeper dive on some of the most important of them with our frequently asked questions.
- Audience segmentation
- Consumer insights
- Contextual advertising
- Cookieless advertising
- CPG data
- Cross-channel attribution
- Customer data platform
- Data-driven marketing
- Data activation
- Data clean room
- Data collaboration
- Data management platform
- Data marketing
- Data monetisation
- Data sharing
- Demand-side platform
- Deterministic matching
- Differential privacy
- Digital fingerprinting
- DSP marketing
- First-party data
- Google PAIR
- Identity resolution
- Last click attribution
- Online to offline attribution
- Personally identifiable information
- Probabilistic matching
- Retail media networks
- Second-party data
- Third-party data
- Third-party cookie deprecation
- TV advertising
- Walled garden
- Zero-party data
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 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 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.
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.
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 is a data-driven approach to marketing, where data analysis underscores all aspects of a marketing campaign’s efforts.
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 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 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 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 refers to the process of making data resources available to one or multiple parties (whether users, individuals or organisations) to enable data collaboration.
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 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.
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 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 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 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.
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 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 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 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 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 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.
TV advertising is the process of generating and airing ads or commercials on television.
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 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.