Mobile Growth Glossary

A controlled experiment that randomly assigns comparable users or traffic to a control and one or more variants, then measures whether a defined outcome changes.

Why it matters: It replaces opinion-led decisions with causal evidence, provided assignment, exposure, sample size, primary metrics, and guardrails are designed correctly.

The meaningful product action that indicates a new user has experienced the app's core value, such as completing a first transfer, workout, booking, or saved item.

Why it matters: Optimizing acquisition to an activation event usually produces better users than optimizing only to installs, registrations, or other shallow milestones.

The percentage of eligible new users who complete the defined activation event within a specified time after install, registration, or first session.

Why it matters: It reveals whether onboarding and early product experience convert acquired users into people who have actually reached value.

The decline in response that occurs when the same audience sees the same advertising concept too often, commonly reflected in rising frequency, weaker CTR, and higher CPA.

Why it matters: Fatigue signals that creative needs a new hook, angle, proof mechanism, or format rather than another cosmetic variation.

A campaign subdivision that groups related targeting, keywords, bids, placements, audiences, or creatives under a shared optimization setup.

Why it matters: A clean ad-group structure preserves interpretable learning without fragmenting conversion volume across too many small cells.

The practice of earning revenue by showing in-app advertising through formats such as banners, interstitials, rewarded video, native ads, or offerwalls.

Why it matters: It should be optimized against retention and user experience as well as eCPM because aggressive ad load can reduce lifetime value.

A resettable device-level identifier provided by an operating system for eligible advertising and measurement use, such as IDFA on iOS or GAID on Android.

Why it matters: Availability depends on platform rules, consent, and device settings, so it cannot be assumed to exist for every user.

An automated mobile acquisition campaign that distributes creative assets across a platform's inventory and optimizes delivery toward installs or selected in-app events.

Why it matters: Its performance depends heavily on event quality, sufficient conversion volume, creative diversity, and trustworthy downstream measurement.

A lightweight portion of an iOS app that lets a user complete a focused task without downloading the full application first.

Why it matters: It can reduce first-use friction and create a path into the full app when the experience and upgrade prompt are well aligned.

Store-observed signals associated with product quality, such as stability, uninstall behavior, engagement, ratings, reviews, update health, and policy compliance.

Why it matters: Modern store discovery is not driven by metadata alone; weak quality can suppress visibility and conversion even when keyword targeting is strong.

The continuous practice of improving an app's discoverability and conversion across search, browse, explore, custom pages, promoted content, metadata, and creative surfaces.

Why it matters: Effective ASO connects qualified visibility with product-page conversion and retained user quality instead of chasing rankings in isolation.

The default store destination that presents an app's name, icon, subtitle or short description, screenshots, preview video, ratings, reviews, and supporting information.

Why it matters: It is the final conversion surface for most organic and paid store traffic, so message clarity and proof directly affect install efficiency.

Apple's paid App Store advertising platform, including Search Results and discovery-oriented placements such as Search Tab, Today Tab, and Product Pages where available.

Why it matters: Each placement represents different intent and should have separate expectations for bids, conversion, incrementality, creative, and measurement.

Revenue generated during a period divided only by users who made at least one payment during that same analytical scope.

Why it matters: ARPPU isolates payer intensity, but it must be read alongside payer conversion because a high value can coexist with very few paying users.

Total revenue generated during a period divided by all users included in the chosen active-user or cohort definition.

Why it matters: It combines payer conversion and payer value into a broad monetization metric that can support LTV and acquisition planning.

A measurement view that records eligible marketing touchpoints which influenced a conversion journey but did not win the primary attribution credit.

Why it matters: Assists can reveal upper-funnel or supporting channel value, but they should not be added to last-touch conversions as independent outcomes.

Apple's permission framework requiring apps to request user authorization before accessing IDFA or engaging in defined cross-app and cross-company tracking practices.

Why it matters: ATT consent-eligible device-level attribution and SKAdNetwork reporting are separate measurement paths and must not be merged at user level.

The rule-based process of assigning credit for an install, re-engagement, or conversion to an eligible marketing interaction or classifying it as organic.

Why it matters: Attribution describes credited contribution, not guaranteed causality; incrementality testing is needed to estimate what would not have happened otherwise.

The allowed time between an ad click or impression and a later install or conversion for that engagement to remain eligible for credit.

Why it matters: Platform and MMP reports can diverge materially when click, view, event, timezone, or reattribution windows are not aligned.

Grouping users according to observed product actions, recency, frequency, value, lifecycle stage, or feature adoption rather than only demographics.

Why it matters: Behavioral segments make onboarding, messaging, offers, and win-back programs more relevant to the user's actual state.

A bidding control that limits the maximum amount an advertiser is willing to bid or pay within a platform's auction rules.

Why it matters: A cap protects unit economics but can suppress delivery when set below competitive clearing prices or before the campaign has enough learning data.

Total acquisition-related sales and marketing cost divided by all newly acquired customers, including those not deterministically attributed to a paid channel.

Why it matters: It connects channel activity to overall business economics and captures organic lift, unattributed demand, and cross-channel effects more honestly than platform CPA alone.

A campaign targeting an app or company name, branded variants, and closely associated navigational demand.

Why it matters: Brand traffic usually converts efficiently but may include users who would have arrived organically, so defensive value and incrementality should be evaluated separately.

A keyword matching mode that allows an ad platform to serve beyond the exact entered term using related meanings, variations, or inferred intent.

Why it matters: It is useful for discovery but requires search-term review, negative keywords, controlled bids, and separation from exact-match performance reporting.