Mobile Growth Glossary

A focused web destination designed to continue an acquisition message and move a visitor toward a specific next action, such as app install, lead, trial, or purchase.

Why it matters: Performance depends on message match, speed, clarity, proof, accessibility, tracking, and a low-friction path into the app or store.

The period during which an ad platform gathers conversion and delivery feedback to stabilize audience, placement, bid, and creative decisions.

Why it matters: Frequent structural changes can reset or contaminate learning; decisions should reflect event volume and reporting delay rather than a universal day count.

Coordinated communication and product experiences tailored to stages such as onboarding, activation, engagement, monetization, renewal, lapse, and win-back.

Why it matters: It increases the value of acquisition by helping users reach value, form habits, and return for relevant reasons.

Adapting store metadata, creative, product language, proof, pricing context, and cultural cues to a specific market rather than translating text literally.

Why it matters: True localization improves both discoverability and conversion because users search, evaluate trust, and interpret benefits differently across storefronts.

A modeled prospecting audience built from patterns found in a first-party seed group, such as high-value purchasers or retained users.

Why it matters: Seed quality and consent matter more than seed size alone, and performance should be validated against broad targeting and downstream value.

The expected cumulative revenue or contribution margin generated by a user or customer over the modeled relationship with the product.

Why it matters: LTV must specify cohort, horizon, discounting, margin basis, and prediction method before it can justify acquisition spend.

The number of distinct users who satisfy the product's active-user definition during a monthly period.

Why it matters: MAU is useful for scale and stickiness analysis only when meaningful activity and identity deduplication are defined consistently.

The continuity between an ad's promise and the language, visuals, proof, and action presented on the landing page, store page, onboarding, or paywall.

Why it matters: Strong message match reduces cognitive friction and usually improves qualified conversion more reliably than an isolated creative change.

Store-managed text and classification fields such as app name, subtitle, short and long description, keywords, category, and promotional text where supported.

Why it matters: Metadata shapes relevance and comprehension, but its indexing behavior and limits differ between Apple App Store and Google Play.

A statistical approach that estimates the contribution of marketing and external factors using aggregated time-series data rather than user-level attribution.

Why it matters: MMM can support budget planning under privacy constraints, but results depend on data quality, variation, model assumptions, and calibration with experiments.

An independent platform that attributes installs and in-app events, manages partner integrations and links, and supports cross-channel reporting and raw-data export.

Why it matters: An MMP is a measurement layer, not a perfect truth source; its results must be reconciled with platform, store, product analytics, and backend data.

A model that distributes conversion credit across multiple observed interactions instead of awarding all credit to one touchpoint.

Why it matters: It can describe journey participation, but model-based credit remains different from causal incrementality and is constrained by privacy and observable identity.

A term used to prevent ads from serving for specified searches or matching paths that are irrelevant, duplicative, or already controlled elsewhere.

Why it matters: Negatives improve relevance, protect discovery budgets, and reduce internal competition when maintained through regular search-term review.

An install for which the active attribution system finds no eligible paid or owned marketing interaction within its rules and windows.

Why it matters: Organic is a residual attribution classification, not proof that marketing had no influence; paid activity can create branded demand and organic uplift.

Additional unpaid store visibility or installs associated with stronger paid demand, rankings, brand interest, product quality, or improved conversion performance.

Why it matters: Because deterministic attribution may classify these installs as organic, blended analysis and incrementality tests are needed to estimate the relationship.

The time required for cumulative contribution margin from an acquired cohort to recover its acquisition cost.

Why it matters: It translates LTV and CAC into a cash-efficiency timeline and prevents long-horizon revenue forecasts from hiding unsustainable growth.

An in-app surface that presents subscription, purchase, trial, pricing, plan, benefit, and eligibility options before access to premium value.

Why it matters: Paywall performance depends on audience intent, onboarding context, offer clarity, localization, pricing, trust, and renewal quality, not conversion rate alone.

A delayed data payload sent by a platform or attribution framework to report an eligible conversion outcome without exposing unrestricted user-level behavior.

Why it matters: Postback timing, privacy thresholds, sequence, and data granularity must mature before teams use the result for campaign decisions.

An estimate of future lifetime value produced from early behavior, revenue, retention, and cohort patterns before the full customer lifetime is observed.

Why it matters: It enables faster bidding and budget decisions, but the model must be calibrated against realized value and monitored for drift.

The single outcome chosen before an experiment or initiative as the main criterion for judging whether the hypothesis succeeded.

Why it matters: Pre-committing a primary metric reduces selective interpretation and keeps sample-size and statistical decisions coherent.

Attribution inferred from statistical combinations of eligible device and engagement signals when deterministic identifiers or referrer matches are unavailable.

Why it matters: It can improve coverage but is less certain than deterministic matching and should remain labeled separately in reconciliation work.

Apple's native product-page experimentation capability for testing selected default App Store creative assets against a control.

Why it matters: PPO supports store-native conversion learning, but traffic mix, test duration, confidence, and downstream user quality still determine whether a result should ship.

An eligible in-app purchase or subscription promoted on App Store surfaces with its own display name, description, and promotional image.

Why it matters: It can create additional discovery and direct users to a specific monetization proposition when metadata and product fulfillment are aligned.

A permission-based message delivered outside the active app to bring a user back to timely, relevant content or action.

Why it matters: Push should be triggered by user value and lifecycle context; excessive or generic messaging increases opt-outs, fatigue, and uninstall risk.