Affise MMP Glossary

A method of testing two or more variations of an ad, landing page, or app feature to determine which performs best.

An open-source framework developed by Google to optimize web pages for near-instant loading on mobile devices.

A user who interacts with an app within a specified time period (e.g., daily active user (DAU), monthly active user (MAU)).

The process of determining which marketing effort led to a user’s action, such as an install or purchase.

A user tapping on an ad, which is recorded as an engagement.

The total expenditure incurred by advertisers to run marketing campaigns, measured across various pricing models. Ad costs are a core metric for calculating ROI and optimizing budgets.

A real-time marketplace where advertisers and publishers buy and sell ad inventory.

Fraudulent activities such as fake installs, click spamming, and bot traffic intended to steal advertising budgets.

A single instance of an ad being displayed to a user.

Total available advertising space (impressions) within digital properties (apps, websites, streaming platforms) that publishers can sell to advertisers.

A technology that allows publishers to manage multiple ad networks for optimal monetization.

A platform that connects advertisers with publishers to distribute ads.

An advanced ad delivery technique where multiple video ads (typically 3-5) are served back-to-back within a single ad break, creating a "pod" of commercials.

A system that stores, delivers, and tracks ad placements.

A fraudulent practice where multiple ads are invisibly layered in a single ad placement, allowing fraudsters to collect payment for ads that users never actually see. This sophisticated ad fraud technique artificially inflates impression counts and steals advertising budgets.

Monitoring clicks, impressions, and interactions related to an ad campaign.

Apple's privacy-centric attribution framework for iOS, introduced at WWDC 2024 as the successor to SKAdNetwork (SKAN). It enhances mobile app attribution while maintaining strict user privacy controls under Apple's App Tracking Transparency (ATT) policy.

Unique device identifiers used for tracking ads on iOS (IDFA) and Android (GAID).

A server-to-server (S2S) method of tracking and attributing mobile app installs or in-app events by exchanging data between platforms (e.g., ad networks, MMPs, or advertisers) via Application Programming Interfaces (APIs). Unlike client-side tracking (SDK-based), API attribution relies on direct server communication for greater accuracy and privacy compliance.

Monitoring user acquisition and engagement for Android apps distributed via APK files (outside Google Play).

A unique string that identifies your app across Apple's and Google's ecosystems. It's essentially your app's digital fingerprint in the stores.

Assigning credit to a source for an app install using tracking models.

Techniques to improve an app’s ranking and visibility in app stores.

The process of tracking and attributing app installs or conversions that originate from ads displayed in Apple's App Store Search results. ASA uses a combination of SKAdNetwork (SKAN) and AdAttributionKit (AAK) for privacy-compliant measurement, along with optional device-level attribution (when users grant ATT permission).

A metric that measures the average revenue generated from each active user within a 24-hour period.

A metric that measures the average revenue generated from each paying user during a specific period. Unlike ARPU (which includes all users), ARPPU focuses exclusively on monetized users, revealing true spending patterns of your customer base.

A metric that measures the average revenue generated per user (both paying and non-paying) during a specific period. It's a fundamental metric for assessing overall monetization health across industries like mobile apps, SaaS, and telecom.

Occurs when a user interacts with multiple marketing touchpoints (e.g., ads, emails, social posts) before finally installing an app. Unlike Last-Click Attribution (which credits only the final touchpoint), assisted installs recognize the contribution of earlier engagements in the user journey.

The method of identifying the source of a user acquisition, engagement, or purchase.

Occurs when bad actors manipulate the mobile attribution process to falsely claim credit for organic installs or legitimate paid installs.

A tracking URL that records the origin of a conversion.

The predefined period during which a conversion is credited to an ad interaction.

Grouping users based on behavior (e.g., "payers," "churned users") for targeted campaigns.

A metric that measures the average amount spent each time a customer places an order. It's a critical e-commerce and mobile app metric that reveals purchasing behavior and revenue potential.

Delivering ads based on users' previous actions and preferences.

The maximum amount an advertiser is willing to pay for an ad placement.

A real-time call for ad impressions initiated by publishers, containing details about the available ad slot and user context. It's the foundational mechanism of programmatic advertising, triggering auctions where advertisers compete to display ads.

A list of fraudulent publishers or sources that advertisers block from campaigns.

Automated traffic generated by scripts, often causing fraudulent ad interactions.

The percentage of users who leave an app or webpage without engaging further.The percentage of users who leave an app or webpage without engaging further.

Strategies to ensure ads appear in appropriate, non-harmful environments.

Аn automated HTTP request sent by the MMP to your server or an ad network's server to share attribution data. It enables real-time synchronization of installs, in-app events, and fraud alerts.

The systematic process of improving ad performance through continuous testing, data analysis, and tactical adjustments across targeting, creatives, and bidding strategies.

Measures the percentage of users who stop using your app within a specific period.

The deliberate falsification of ad clicks to drain advertiser budgets or artificially inflate performance metrics. In mobile marketing, it primarily affects CPI (cost-per-install) and CPC (cost-per-click) campaigns.

A fraudulent technique where fake clicks are generated just before an app install.

Fraudulent clicks generated in large volumes in hopes of claiming organic installs.

The time elapsed between a user clicking an ad and the app installation completing. It's a critical metric for detecting fraudulent installs in mobile user acquisition campaigns.

The process of verifying the legitimacy of ad clicks to prevent fraud before attributing installs or conversions. It's the first line of defense against invalid traffic (IVT) in mobile user acquisition.

An attribution model crediting conversions to the last clicked ad.

The ratio of users who click on an ad to the total impressions.

In MMPs involves grouping users by shared characteristics (install date, source, etc.) and tracking their behavior over time to measure retention, monetization, and campaign effectiveness.

Any television that connects to the internet to stream content beyond traditional broadcast/cable.

An advertising method that displays ads based on the content environment (app category, page content, or in-app activity) rather than personal user data. It's gaining traction as a privacy-friendly alternative to behavioral targeting.

A desired action taken by a user, such as an app install or purchase.

The journey users take from awareness to conversion.

The cost incurred for a user completing a specific action.

The amount paid for each ad click.

A pricing model where advertisers pay only when a user watches 100% of a video ad (or a predefined duration like 30 seconds for longer videos). It's the gold standard for video campaign performance measurement.

An advertising pricing model where advertisers pay only when users complete specific interactive actions beyond clicks/views. It's ideal for campaigns prioritizing quality user interactions over vanity metrics.

The amount paid per app install driven by an ad.

The cost per 1,000 ad impressions.

The cost incurred per completed purchase.

Occurs when fraudsters artificially generate fake conversions (installs, sign-ups, purchases) to steal advertising budgets. Unlike click fraud, it targets performance-based campaigns where advertisers pay only for completed actions.

Tracking a user's interactions across multiple devices.

The predicted revenue a user will generate over their lifetime.

A key performance metric that measures the number of unique users who engage with a product, app, website, or service within a 24-hour period.

A secure, privacy-compliant environment where multiple parties (e.g., advertisers, publishers, or platforms) can share and analyze data without exposing raw, sensitive information to each other. It enables collaboration while enforcing strict access controls, encryption, and governance rules to protect user privacy and comply with regulations (e.g., GDPR, CCPA).

Enhancing tracking data with additional insights.

The technology that directs users to a specific location within a mobile app (rather than just launching the app homepage) based on a link click.

Directing users to a specific app page even if the app was not previously installed.

A system that automates the buying of digital ad inventory.

A method of attributing user actions (e.g., app installs, purchases, or ad clicks) to a specific marketing campaign or touchpoint using exact, directly identifiable user data. It relies on unique, user-level identifiers to match interactions with conversions with 100% certainty.

Tracking users based on device characteristics.

A unique identifier assigned to a user’s smartphone or tablet, used to track and attribute app installs, engagements, and conversions to specific marketing campaigns.

Personalized, automated advertisements that display real-time, user-specific content (e.g., products, prices, or recommendations) based on behavioral data, preferences, or contextual triggers. They dynamically adjust creative elements (images, text, CTAs) to maximize relevance and performance.

An AI-driven ad technology that automatically generates and tests thousands of personalized ad variations in real time, optimizing creative elements (images, headlines, CTAs) for each user to maximize engagement and conversions.

Organic brand exposure gained through unpaid channels, such as word-of-mouth, press coverage, social shares, reviews, or influencer mentions. Unlike paid media (ads) or owned media (brand-owned channels), earned media is third-party validation of your brand’s credibility.

A key advertising metric that calculates the estimated revenue earned per 1,000 impressions (displays of an ad), helping publishers and advertisers compare the profitability of different ad campaigns, formats, or platforms.

Simulated or virtual mobile devices (often created via software like Android Emulator, Xcode Simulator, or cloud-based testing tools) that mimic real smartphones/tablets for testing app installs, attribution, and fraud detection.

The level of user interaction with an app or ad.

Recording user actions within an app for analysis.

Аraudulent or artificially generated engagements (installs, clicks, or in-app actions) designed to deceive advertisers, MMPs (Mobile Measurement Partners), or ad networks into paying for non-genuine traffic. These are commonly used in mobile ad fraud schemes to steal marketing budgets or inflate performance metrics.

Linear streaming channels that deliver scheduled, live-like TV content (movies, shows, news) for free, supported by ads—similar to traditional broadcast TV but delivered over the internet.

A key performance metric in mobile advertising that measures the percentage of ad requests that are successfully filled with an ad impression. In the context of MMPs, fill rate helps publishers and advertisers evaluate the efficiency of their ad inventory and demand sources.

Tracking users based on non-unique device signals.

Attribution model crediting the first touchpoint in the user journey.

A multi-touch attribution (MTA) model that distributes credit for a conversion (e.g., app install, purchase) across multiple marketing touchpoints (ads, clicks, impressions) instead of giving 100% credit to a single source. Fractional attribution helps advertisers understand the true contribution of each campaign in a user’s journey.

Displaying ads based on a user’s geographic location.

A location-based marketing technology that uses GPS, Wi-Fi, or Bluetooth to create a virtual boundary (a "geo-fence") around a real-world area. When a user enters or exits this zone, it triggers automated actions, such as push notifications, ads, or app messages.

A unique, resettable identifier assigned to every Android device for advertising and analytics purposes. It allows advertisers and MMPs to track user activity, attribute app installs, and deliver personalized ads while respecting user privacy controls.

A legacy Android attribution mechanism that passes campaign data (e.g., source, medium, campaign name) from the Google Play Store to an app after installation. It was commonly used by MMPs and advertisers to track organic and paid installs before more advanced methods like Google Play Referrer API and Google Play Install Attribution API were introduced.

Total revenue before expenses.

A cryptographically hashed (obfuscated) version of a device identifier (GAID, IDFA) used for privacy-safe attribution.

An advanced programmatic advertising technique that allows publishers (app developers) to offer their ad inventory to multiple demand sources (ad exchanges, DSPs, networks) simultaneously before making calls to their primary ad server. Header bidding helps maximize ad revenue while providing transparency into which demand partners drive the highest eCPMs.

A privacy-compliant attribution model that tracks ad-driven conversions at the household level (instead of individual users), often used for CTV (Connected TV) and multi-device campaigns.

Combines deterministic (exact matches) and probabilistic (statistical modeling) attribution methods to balance accuracy and scale. Used for cross-device tracking.

Delivering ads/content to users in very specific locations (e.g., a street, store, or event), often using geofencing + MMP data.

A unique, user-resettable identifier assigned to iOS devices for advertising and attribution tracking. Requires user consent via Apple’s App Tracking Transparency (ATT) framework.

A persistent ID shared across apps from the same developer on iOS. Unlike IDFA, it doesn’t require ATT consent but cannot be used for cross-app tracking.

Fraudulent inflation of ad impressions through bots, hidden ads, or fake traffic, wasting advertiser budgets.

The measurement of how many times an ad is displayed (viewed by users). MMPs log impressions to calculate metrics like CPM (cost per mille) and fill rate.

Actions or events occurring within a mobile app (e.g., purchases, level completions).

A real-time auction system where advertisers bid directly for in-app ad inventory, bypassing traditional mediation waterfalls.

User actions tracked within an app (e.g., "Add to Cart," "Level Achieved").

Push or in-app messages sent to users to drive engagement (e.g., promotions, reminders).

Transactions made inside an app (e.g., subscriptions, virtual goods).

Ads integrated into content streams (e.g., video ads in TikTok, rewarded ads in games).

Measuring the actual effect of marketing efforts.

A fraudulent practice where malicious actors intercept and claim credit for organic app installs that should not be attributed to paid campaigns.

Legacy Android attribution mechanism that passed campaign data from Google Play Store to installed apps.

The percentage of users who complete an event after installation.

Full-screen ad format that appears at natural transition points in mobile apps.

The process of identifying jailbroken iOS devices (modified to bypass Apple's restrictions) to prevent fraud.

A method where attribution is processed immediately upon install (vs. batch processing).

Analyzing the sequence of touchpoints (ads, clicks, organic search) that led to an app install or conversion.

A measure of an app’s viral growth.

A metric used to evaluate campaign success.

The process of improving app store visibility by targeting relevant keywords in the title and description.

An attribution model crediting the last interaction before conversion.

The projected revenue a user generates.

A privacy feature on iOS (under "Allow Apps to Request to Track") and Android (via "Opt out of Ads Personalization") that prevents advertisers from using a device's advertising identifier (IDFA or GAID) for targeted ads and attribution. When enabled, MMPs receive a blank or zeroed-out identifier, limiting user-level tracking.

An attribution model that distributes credit for a conversion equally across all touchpoints in the user journey (e.g., clicks, impressions, or ad views). Unlike last-click attribution, it gives weight to every interaction, providing a more balanced view of marketing effectiveness.

A targeting strategy where platforms (e.g., Facebook, Google Ads) use algorithms to find new users who resemble an app’s existing high-value customers. These audiences are created based on shared behaviors, demographics, or interests, helping expand reach to likely converters.

The time period during which an ad interaction (click or impression) can be credited for a conversion.

A user who consistently engages with an app over time.

Analyzing marketing efforts to determine their impact.

Deceptive practices that artificially inflate ad metrics (installs, clicks, impressions) to steal marketing budgets.

The process of tracking which marketing source (e.g., Facebook ad, Google UAC) led to an app install or in-app event.

Google’s practice of prioritizing mobile app content over desktop for SEO rankings.

Strategies to generate revenue from an app, including:

- In-app ads (banners, interstitials, rewarded videos)
- In-app purchases (IAPs)
- Subscriptions (e.g., freemium models)

The number of unique users who engage with an app at least once in a 30-day period. A core metric for measuring app growth and retention.

A metric for subscription-based apps, showing predictable monthly income from active subscribers.

Attribution that assigns credit to multiple touchpoints.

Ads designed to blend with platform content.

Delays in tracking data processing.

An app install that results from paid marketing efforts (e.g., ads, influencer campaigns, or incentivized promotions) rather than natural discovery (e.g., App Store search, word-of-mouth).

A monetization and user acquisition tool where users complete offers (e.g., surveys, app installs, purchases) in exchange for in-app rewards (e.g., currency, premium content).

Explicit user consent to receive communications (e.g., push notifications, email, tracking) or share data (e.g., location, IDFA/GAID for ads).

An app install not driven by paid advertising.

Advertising on streaming platforms that deliver content directly via the internet (bypassing cable/satellite), e.g., Hulu, Netflix, Roku.

Marketing assets fully controlled by a company.

A digital advertising model where advertisers bid to display ads on search engine results pages (SERPs) based on user queries. Ads appear above or below organic results and are marked as "Sponsored."

An online ad pricing model where advertisers pay only when a user clicks their ad. Common in paid search, social media ads, and display networks.

A gating system that restricts access to digital content (e.g., articles, apps) until users pay or subscribe.

A pixel (or tracking pixel) is a tiny, invisible piece of code (usually a 1x1 transparent image) embedded in an app, website, or ad that fires when a user takes a specific action (e.g., installs an app, makes a purchase). In MMPs, pixels help track conversions, retarget users, and measure campaign performance.

Interactive mini-game ads that let users "test" an app before installing.

A server-to-server notification confirming a conversion.

Google’s initiative to replace third-party cookies and device IDs (e.g., GAID) with privacy-preserving ad targeting and measurement APIs.

A statistical method to attribute user actions (e.g., installs) when deterministic data (e.g., device IDs) is unavailable (common post-IDFA).

Automated ad buying using real-time bidding.

Web apps that mimic native app experiences (offline access, push notifications).

A unique identifier assigned to a publisher.

Real-time messages sent by apps to users’ devices (lock screen or notification center) to drive engagement, even when the app is closed.

Used in tracking links (e.g., ?utm_source=facebook&utm_medium=cpc) to analyze traffic sources and campaign performance. MMPs parse these parameters for attribution.

A financial metric sometimes used in mobile app businesses to measure liquidity, but can also refer to performance benchmarks in app analytics.

Unprocessed, unfiltered data collected from user interactions, such as app installs, clicks, in-app events, or ad impressions. MMPs provide raw data exports for deep analysis.

Marketing strategies aimed at bringing inactive users back to an app after they’ve stopped using it. The goal is to reactivate dormant users, improve retention, and maximize lifetime value (LTV).

Automated, auction-based ad buying.

The time period during which an MMP can reassign credit for an install or event to a different marketing source if the original attribution is invalid (e.g., if fraud is detected).

When a user who previously installed an app reinstalls it after uninstalling. MMPs track reinstalls to measure retention and campaign effectiveness.

Targeting users who have previously interacted with an app (e.g., installed but didn’t purchase) with tailored ads to re-engage them.

Similar to remarketing, but often refers specifically to serving ads to past users based on their behavior (e.g., viewed a product but didn’t buy).

The percentage of users who remain active over time.

Revenue generated per dollar spent on ads.

Full-screen video ads where users voluntarily watch in exchange for in-app rewards (e.g., game currency, extra lives). A popular monetization format in mobile apps.

A method of data transmission where servers communicate directly without relying on client-side (user device) tracking and when there’s no option to set up MMP’s SDK.

A set of tools used to track app interactions.

The practice of optimizing websites or app store listings (App Store Optimization - ASO) to rank higher in search engine results (Google) or app stores (Apple App Store, Google Play). The goal is to drive organic (non-paid) traffic.

The time a user spends in an app.

Apple’s privacy-friendly attribution system.

A monetization strategy where users pay a recurring fee (weekly, monthly, annually) to access an app’s content or services. Common in news, fitness, and streaming apps.

A subscription-based streaming service where users pay for unlimited access to video content (movies, TV shows). A subset of the subscription revenue model.

A technology platform used by publishers (app developers, websites) to automate the sale of ad inventory to demand-side platforms (DSPs) and ad exchanges. Maximizes ad revenue by connecting to multiple buyers.

The process of using data collected and analyzed by an MMP to segment and deliver personalized marketing campaigns to specific user groups. MMPs enable advertisers to refine audience targeting based on attribution data, user behavior, and engagement metrics.

External services that assign conversion credit.

The duration during which a user has not engaged with an app (e.g., no opens, sessions, or in-app actions) after installation or their last recorded activity. MMPs track inactivity to measure churn, optimize re-engagement campaigns, and assess user retention.

The origin of user traffic.

The process of detecting when users remove an app from their device, measured through MMPs or platform-specific methods (iOS/Android SDKs).

Apple's deep linking technology that seamlessly redirects users from web content to corresponding app pages without going through Safari.

Gaining new users through marketing.

Any content created by app users rather than the company - reviews, posts, videos, etc.

A metric measuring how frequently and consistently users engage with an app over time.

Attribution model crediting conversions to ad impressions.

A metric that measures whether an ad was actually seen by a user.

A pricing model where advertisers pay per 1,000 viewable ad impressions—meaning the ad was actually seen by users (not just loaded).

The process of identifying which marketing sources (e.g., paid ads, organic search, social media) drive traffic and conversions on a website.

Measuring how web-based campaigns (e.g., browser ads, QR codes) drive app installs or in-app actions.

Advertising models in decentralized web3 ecosystems (blockchain, dApps, NFTs), often leveraging tokenized incentives or on-chain data for targeting.

Tracking user interactions within in-app webviews (embedded browsers) and attributing them to marketing sources.

A metric counting unique users who engage with an app at least once in a 7-day period.

Comparison of key metrics (installs, revenue) with the same period in the previous year.

Cumulative metrics from January 1st to current date.

Consumer data that a customer proactively provides.