Marketing Measurement Glossary
Clear, factual definitions of the terms used across marketing measurement, media mix modeling and media planning - from attribution and incrementality to saturation curves and offline media measurement.
Adstock / Carryover Effect
The lingering impact of advertising on consumer behavior after a campaign has ended. Adstock models decay this effect over time, since media exposure doesn't stop driving results the moment a campaign stops running.
Attribution
The practice of assigning credit for a conversion or sale to specific marketing touchpoints a customer interacted with before converting. Digital attribution typically relies on clicks and cookies, which limits it to channels that can be tracked at the user level. Read more →
Baseline / Base Sales
The level of sales or conversions a business would achieve with no marketing activity at all, driven by factors like brand equity, seasonality, distribution and organic demand. Marketing Mix Modeling separates baseline sales from the incremental sales driven by media.
Causal Inference
A statistical approach that estimates the true cause-and-effect impact of a marketing channel on business outcomes, rather than just measuring correlation. Causal inference is the foundation of Marketing Mix Modeling, since correlation alone can't tell you whether a channel actually drove results. Read more →
GRP (Gross Rating Point)
A standard unit for measuring the size of an advertising campaign's audience delivery, calculated as reach multiplied by average frequency. GRPs are commonly used to plan and report on TV, radio and OOH campaigns.
Halo Effect
The indirect, positive impact one marketing channel or campaign has on the performance of another channel or on brand metrics overall. For example, a TV campaign can lift branded search volume and direct traffic even though those channels get the attribution credit.
Incrementality
The additional business outcome - sales, leads, app installs - that would not have happened without a specific marketing activity. Incrementality is the core question Marketing Mix Modeling and causal inference are designed to answer. Read more →
Last-Click Attribution
An attribution model that gives 100% of the credit for a conversion to the last touchpoint a customer clicked before converting. It's simple to implement but systematically overvalues bottom-of-funnel channels like branded search and undervalues upper-funnel and offline channels. Read more →
Marginal ROI
The additional return generated by the next unit of spend in a channel, as opposed to the average ROI across all spend to date. Marginal ROI typically declines as spend increases, which is why it's the key metric for deciding where to move the next dollar of budget.
Marketing Mix Modeling (MMM)
A statistical, causal method for measuring how each marketing channel - offline and online - contributes to business results, using aggregate data rather than individual user tracking. MMM isolates the incremental impact of each channel from seasonality, pricing, distribution and other external factors. Read more →
Media Mix
The combination of marketing channels - TV, OOH, radio, print, digital and more - that a brand uses to reach its audience and drive results. Optimizing the media mix means finding the allocation of budget across channels that maximizes overall return. Read more →
Media Planning
The process of deciding which channels, formats and schedules to use for a campaign before it launches, typically based on audience data, historical performance and budget constraints. Predictive media planning tools can simulate expected performance before any budget is committed. Read more →
Multi-Touch Attribution (MTA)
An attribution model that distributes credit for a conversion across multiple touchpoints in the customer journey, rather than giving all the credit to one interaction. MTA improves on last-click attribution for digital channels but still can't measure channels without trackable clicks, like TV or OOH. Read more →
Offline Media Measurement
The practice of quantifying the business impact of media channels that can't be tracked via clicks or cookies - TV, out-of-home, radio and print. Modern offline measurement uses causal statistical models fed by campaign delivery data rather than user-level tracking. Read more →
Out-of-Home (OOH)
Advertising that reaches consumers outside the home, including billboards, transit ads, street furniture and digital screens in public spaces. OOH is measured using reach, frequency and GRPs rather than clicks. Read more →
ROAS (Return on Ad Spend)
The revenue generated for every dollar spent on advertising, calculated as revenue divided by ad spend. ROAS measures overall channel efficiency but, unlike marginal ROI, doesn't show whether an additional dollar of spend would still be profitable.
Reach & Frequency
Reach is the number or percentage of a target audience exposed to a campaign at least once; frequency is the average number of times that audience was exposed. Together they describe how broadly and how often a campaign delivered.
Saturation Curve
A curve showing how a channel's returns diminish as spend increases, eventually flattening out once the audience is fully reached or frequency exceeds what's effective. Saturation curves, derived from Marketing Mix Modeling, help identify the optimal spend level for each channel before returns start to decline. Read more →