We wrote this glossary to help you feel comfortable with the complex language in the ever-accelerating marketing and advertising industry
To maximize marketing effectiveness, marketers must be able to understand consumer attributes and how different audiences interact with their brand across channels and devices, so they can optimize budgets and create relevant experiences that drive meaningful business results.
Nielsen Visual IQ’s glossary provides definitions of common terms associated with marketing effectiveness. Some of them may be new to you, and we want to demystify words you’ve heard but haven’t had a chance to clarify.
You’ll find definitions for some of the most important terms, including current vocabulary associated with data collection and activation, multi-touch attribution, people-based marketing, predictive analytics, and other related concepts.
Addressable Channels: Marketing and media channels where individual, user-level data (such as cookie data) is available to track touchpoints in the consumer journey.
Algorithmic Attribution: A multi-touch attribution methodology that uses machine-learning to calculate and fractionally assign credit for a given success metric to the influential marketing touchpoints and dimensions (campaign, placement, publisher, creative, offer, etc.) along the consumer journey, as well as to predict the outcome of future marketing spend allocations.
Audience Attributes: Demographic, behavioral, interest and intent qualities that characterize an individual. Examples include: gender, age, occupation, income, lifestyle interests, purchase intent and more.
Audience Segment (aka Segment): An identifiable group of individuals who share similar characteristics, needs or behaviors and who generally respond in a predictable matter to a given marketing or media stimulation.
Baseline (aka Brand Equity): The intrinsic value and level of performance against a set of key performance indicators (KPIs) derived solely from a brand’s recognition in the marketplace. It provides an initial value from which to evaluate the impact of incremental marketing investments.
Brand Engagement: The measurement of the extent to which a consumer has a meaningful interaction with a brand (visits a landing page, views a video, downloads content, etc.) when exposed to a brand marketer’s middle- and upper-funnel marketing or media.
Channel: A digital and/or offline marketing category. Channels can be classified by paid, owned and earned, as well as addressable versus non-addressable.
Constraints: Factors associated with specific channels or tactics that limit the extent to which the media spend invested in them can be changed during the optimization process, and then the specific range of values in which media spend can vary to ensure the recommendations produced by an attribution solution can realistically be put in market given those factors. For example, the available inventory of branded search terms in a paid search marketplace is a constraint that limits the ability for increase spend on those terms more than 60% and decrease spend on those terms more than 100%.
Consumer Journey: A chronological sequence of all the marketing and media touchpoints experienced by an individual user.
Container Tag: A delivery mechanism for pixels that eliminates the need to place multiple data tracking codes on a website.
Cookie: A unique piece of code that is placed on a user’s browser by a tracking technology the first time that user accesses a given digital asset. Each piece of information a cookie tracks is called an “event,” and events are transmitted to ad servers or data collectors via codes called tags. For example, each time a user searches for an item online, it is recorded in their browser and later retrieved by ad servers to remember their behavior and better customize their search queries.
Cost: The price that is paid for media.
Cost Per Thousand (CPM): The standard pricing model for many media channels (e.g. online display, video, etc.). Alternative pricing models are flat rate, pay per click (PPC) or cost per acquisition (CPA).
Cost Reconciliation: The process of associating actualized cost data with paid media channels and their publishers to accurately calculate efficiency metrics like cost per acquisition.
Cross-Device Mapping: The process of matching a single user to two or more connected device ID’s associated with that user. This process may also be referred to as “cross-device matching,” “cross-device pairing,” or “cross-device bridging.” There are three different approaches to this process that can be used individually or together to maximize accuracy and scale: first-party deterministic, third-party deterministic, or third-party probabilistic.
Data Management Platform (DMP): A data warehouse technology that centralizes and deduplicates first, second and third-party data sources to generate audience segments that can be used for marketing and media audience targeting and creative optimization.
Device ID: A unique identifier that can be used to identify a mobile device.
Dimension: A characteristic or feature associated with a marketing or media touchpoint. Each touchpoint may include over a dozen dimensions. For example, an online display ad may include the campaign, placement, publisher, ad size, creative, line of business, etc.
Earned Marketing: The free, publicity generated marketing produced by a brand’s fans. Examples include: Facebook likes, retweets, online reviews, word of mouth, etc.
Engagement Score: A KPI metric used to measure and optimize brand marketing campaigns. The score is typically a compilation of a set of events known as brand engagement activities, such as: first time website visits, rich-media ad interactions, video completions, etc.
Even Weighted (aka Linear): A rules-based attribution model that distributes equal credit for a given success metric to each touchpoint experienced by a user.
Exogenous Factors: Factors external to the dimensions associated with marketing, including: seasonal factors (weather, holidays, etc.), economic factors (interest rates, gas prices, etc.) and competitive activities (changes to media tactics, new product launches, etc.) that lie outside of marketers’ immediate control and may impact marketing effectiveness.
First Click/First Touch: A rules-based attribution model that gives 100% of the credit for a given success metric to the first touchpoint experienced by a user.
First-Party Data: Consumer data that a brand produces at no cost. This data is typically collected from direct contact with the company’s customers, and includes site analytics data, CRM data, etc.
First-Party Deterministic: : One of three cross-device mapping approaches. It may also be referred to as “brand authentication” since this approach uses the brand’s own first-party, authenticated user data. User authentication may include a website login, app interaction, email interaction, etc.
Halo (aka Halo Effect): A value that quantifies the degree to which different channels lift, or in some cases, cannibalize each other. For example, as the result of a halo effect, a marketer may see an increase in branded search queries or conversions while running an online display campaign.
Impressions: In digital media, impressions are a measure of the number of times a media advertisement or marketing message is served. In offline media, impressions are a measure of the number of times an ad or message may have been seen.
Incrementality: A desired outcome (revenue, sales, leads, brand engagement, etc.) gained from a marketing activity that would not have been generated without that marketing activity.
Inter-Channel: The affinity between tactics used within one channel and those used within another, such as which online display ads drive searches on which keywords.
Intra-Channel: The affinity between different tactics used within the same channel, such as which non-branded keywords drive searches on which branded keywords.
Key Performance Indicator (KPI): The metric that a marketer uses to judge the success of a marketing initiative.
Last Click/Last Touch: A rules-based attribution model that gives 100% of the credit for a given success metric to the last marketing touchpoint experienced by a user.
Lookback Window: The defined period of time for which an ad can be expected to influence a user to convert or engage with a brand after exposure.
Marketing Mix Modeling: A statistical modeling attribution approach that uses summary-level data from both non-addressable channels and addressable channels to infer the relationships between different channels and tactics and deliver recommendations for optimization. The summary-level data that feeds a marketing mix model may include counts of individuals who were exposed to and/or took action upon various marketing initiatives; the particular date, time or location from which a marketing message was viewed; as well as exogenous factors, such as economic, seasonal and competitive data that have an impact on performance, such as interest rates, the weather, new product launches, etc.
Match Rate: The number of user ID’s associated with a marketer’s touchpoint data that also match a set of user ID’s associated with another data provider (such as a cross-device data provider), divided by the total number of user ID’s associated with the marketer’s touchpoint data. Match rate is expressed as a percentage.
Model Validation: The process of verifying the accuracy of attribution measurement and the optimization recommendations it delivers by comparing the predicted results with the actual results.
Movement Data: Location-based data that represents the anonymous offline movement and visitation patterns of consumers.
Multi-Touch Attribution: A rules-based or algorithmic attribution methodology that leverages individual, user-level data from addressable channels like online display and paid search to calculate and assign fractional credit of a success metric to the influential marketing touchpoints and dimensions (campaign, placement, publisher, creative, offer, etc.) along the consumer journey to measure past marketing performance.
Non-Addressable Channels: Includes channels like broadcast TV, radio, print, out-of-home, in-store displays, etc., where marketing messages are delivered to individuals who cannot be identified at a user-level.
Owned Marketing: All the communication assets that a marketer creates and has control over without having to make per-unit investments in order to expose them to consumers. Examples include a brand’s website, blog, mobile website, etc.
Paid Media: All of the advertising assets for which a marketer pays in order to expose them to consumers. Examples include TV commercials, print ads, online display ads, paid search, retargeting, etc.
People-based Marketing: The process of combining various, disparate IDs associated with a single consumer (e.g. cookie ID, device ID and offline ID) into a single, anonymous unique identifier for the purpose of understanding consumer attributes and behaviors within the context of marketing performance measurement.
Personally Identifiable Information (PII): Any data that can be used to identify a specific individual. Most marketers prefer to use non-PII data in order to protect consumer privacy.
Pixel: A transparent gif file or clear image placed within websites, ads and emails to track digital activity (e.g. impressions, website visits, etc.) at a user level. A pixel may also be referred to as a tag.
Point of Diminishing Returns: The point at which increased investment in a particular piece of marketing or media results in a decrease in the overall return (assuming all variables remain fixed). For example, the point of diminishing returns for a PPC campaign occurs when increasing the budget results in a decline in conversion rates and an increase in cost per acquisition.
Publisher: A media vendor that owns or manages media inventory, such as ad space, made available for purchase by marketers.
Response Channels: Any channel that enables a customer or prospect to initiate a desired action in response to exposure to a marketing or media stimulation. Some marketers call these “sales channels” or “revenue channels.” Examples include an eCommerce website, mobile website, traditional retail store, call center and more.
Rules-Based Attribution: A subjective multi-touch attribution methodology that distributes credit for a success metrics across one or more marketing touchpoints using a prior defined or arbitrarily assigned weight. Examples of rules-based attribution models include first click, last click, u-shaped and even weighted methods.
Scenario Planning (aka “What-If?” Scenarios Planning): The use of predictive analytics to forecast future performance and produce customized marketing and media plans containing the optimal mix of channels and tactics needed to maximize marketing return while also accounting for constraints.
Second-Party Data: Consumer data that is shared between trusted marketing partners. Examples include “intent to purchase” data that is shared between an airline and a hotel chain or “online shopping” data that is shared between a retailer and a manufacturer.
Stimulation Channels: Any channel whose assets produce a marketing or media impression with a customer or prospect. Some marketers call these “impression channels,” “communication channels,” or “marketing channels.” Examples include paid search, online display, TV, radio, out of home, email, direct mail and more.
Tag: A piece of code placed on a website or an ad by which user-level data is collected. A tag may also be referred to as a pixel.
Taxonomy: Predefined, hierarchical classifications and naming conventions of touchpoint dimensions, KPIs and other brand-specific categorizations. Taxonomies differ across marketing organizations and ensure that the analyses, insights and recommendations map directly to a brand’s unique jargon and business goals.
Third-Party Data: Consumer data that is collected by an external source from the marketer that intends to use it.
Third-Party Deterministic: One of three cross-device mapping approaches. It may also be referred to as “third-party authentication” because this approach uses a third-party common login across devices (e.g. Google, Facebook, Twitter, etc.).
Third-Party Probabilistic: One of three cross-device mapping approaches. It may also be referred to as “third-party inferred match” because this approach requires partnering with a cross-device technology vendor to make an inferred match across multiple devices to a single user. The connection is made using consumer behavior, relationship-based patterns, Wi-Fi linking, geo-clustering, as well as other variables.
Time Decay: A rules-based attribution model in which the percentage of success metric credit gradually builds while leading up to the last touchpoint in the consumer journey.
Touchpoint: Any media or marketing interaction to which a consumer is exposed. Touchpoints can include a wide range of interactions, from seeing a television commercial to conducting online price comparisons on a comparison shopping engine site, to clicking on a display ad or search result.
Trafficking: The process that places advertisements within media inventory.
Tribal Knowledge Factors: Any internal knowledge that lies within a company and may impact marketing effectiveness. Examples may include mergers and acquisitions, pricing changes, product launches, etc.
U-Shaped (aka Position based): A rules-based attribution model in which the majority of success metric credit is assigned to the first and last touchpoint experienced by a user, and the remaining credit is distributed evenly to the touchpoints in between.
Unique Identifier/Unique ID: The mapping of multiple, disparate, anonymous user IDs associated with a unique user to a single, anonymous user ID that identifies the unique user across platforms, channels and devices.
Yield Curve: A line that plots the maximum number of theoretical “what-if?” marketing and media spend scenarios available to a marketer based on historical marketing performance data for purposes of forecasting marketing performance.