Marketing Glossary

Terms that come up constantly in performance marketing and app analytics, but rarely get defined anywhere concisely.

Adstock
The lingering effect of an ad that carries over after it stops running
CAC (Customer Acquisition Cost)
Cost of acquiring one customer — total acquisition spend divided by customers acquired
Cannibalization
When paid ads steal conversions that would have happened organically anyway
Click Injection
Fraud that fires a fake click right before install to steal attribution credit
Cohort
A group of users who all started (installed/signed up) at the same time
CPA (Cost Per Action)
Cost per desired action (signup, purchase) — spend divided by conversions
CPC (Cost Per Click)
Cost per click — equal to CPM divided by CTR
CPI (Cost Per Install)
Cost per app install — total spend divided by number of installs
CPM (Cost Per Mille)
Cost per 1,000 impressions — the closest metric to raw media cost
CTR (Click-Through Rate)
Share of impressions that got clicked — clicks divided by impressions
CVR (Conversion Rate)
Share of clicks (or visits) that converted — conversions divided by clicks
Deep Link
A link that opens an app straight to a specific screen instead of the home screen
eCPI (Estimated CPI)
A modeled CPI estimate used when individual installs can't be observed, e.g. under SKAdNetwork
Funnel
The step-by-step conversion path (impression → click → install → signup → purchase) that narrows at each stage
Holdout Test
Randomly withholding ads from part of an audience to measure true incrementality
Incrementality
The pure additional performance an ad actually caused
LTV (Lifetime Value)
The total revenue a customer generates before they churn
Marginal CPA
The cost of the conversion your next dollar of spend would buy — different from your average CPA so far
MMP (Mobile Measurement Partner)
A third-party service that aggregates conversion data from multiple ad networks into one attribution view
Multicollinearity
When independent variables move together so tightly a regression can't tell their effects apart
Probabilistic Attribution
Matching a click to an install by pattern (device, OS, timing) instead of a unique ID
Response Curve
The curve showing how conversions respond as spend increases — typically S-shaped
Retention
The share of installed/signed-up users still active after a given number of days
ROAS (Return On Ad Spend)
Revenue generated per dollar of ad spend — revenue divided by spend
Uplift
The pure increase in outcomes an ad actually caused, isolated from what would've happened anyway