Fraud Type Guide

CTIT (Click-to-Install Time): How It Reveals Mobile Ad Fraud

Q: What does a normal CTIT distribution look like?

Legitimate traffic shows a natural decay curve: most installs happen within minutes to a few hours after the click, with a sharp peak in the first hour and a rapid decline. The majority of genuine installs occur within the first 24 hours, with very few beyond 72 hours.

Q: How does CTIT analysis detect click injection?

Click injection produces an abnormally high concentration of installs within seconds of the click (typically under 10-15 seconds). This is because the fraudulent click is fired after the download has already begun, so the time between the click and the install completion is unnaturally short.

Q: How does Opticks use CTIT analysis?

Opticks analyses CTIT distributions at the source, sub-publisher, and campaign level in real time. It automatically flags traffic with anomalous patterns -- such as suspiciously short CTITs indicating click injection or flat distributions indicating click spam -- and provides actionable fraud intelligence.

CTIT analysis is one of the most powerful tools for detecting mobile attribution fraud. Learn how click-to-install time patterns expose click injection, click spam, and other manipulation.

What Is CTIT (Click-to-Install Time)?

Quick answer: CTIT measures the time between an ad click and an app install. Abnormally short or long CTIT values are strong indicators of click injection, click spam, or other mobile attribution fraud.

CTIT (click-to-install time) is the elapsed time between when a user clicks on a mobile ad and when the corresponding app install is registered by the attribution platform. This seemingly simple metric is one of the most powerful fraud detection signals available to mobile marketers because different types of ad fraud produce distinctly abnormal CTIT patterns.

Legitimate mobile ad traffic produces a characteristic CTIT distribution: a sharp peak in the first few minutes (users who click and immediately install), followed by a natural exponential decay over the next several hours. Most genuine installs occur within the first hour, with a long tail extending to 24-48 hours. This pattern reflects real human decision-making and the time required to download and install an app.

Fraudulent traffic, by contrast, produces CTIT distributions that deviate dramatically from this natural pattern. Click injection creates an unnaturally tight cluster of installs within seconds of the click. Click spam produces a flat, random distribution with no decay curve. Understanding these patterns enables marketers to identify and exclude fraudulent sources with high confidence.

CTIT Patterns and What They Reveal

Different fraud techniques produce characteristic CTIT signatures that can be identified through distribution analysis.

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Normal CTIT (Legitimate Traffic)

Sharp peak within the first 10-60 minutes, followed by natural exponential decay. Most installs within 24 hours. Represents genuine user interest and real download behaviour.

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Ultra-Short CTIT (Click Injection)

Massive spike of installs within 0-15 seconds of the click. The click was fired after the download started, so completion happens almost immediately. A clear fraud signal.

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Flat CTIT (Click Spam)

Installs are distributed evenly across the entire attribution window with no decay pattern. The clicks were random and unrelated to install decisions, producing uniform timing.

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Bimodal CTIT (Mixed Fraud)

Two distinct peaks — one normal and one anomalous — indicate a source mixing legitimate traffic with fraudulent activity to dilute detection signals.

Why CTIT Analysis Matters

CTIT analysis provides objective, data-driven evidence of fraud that goes beyond simple rule-based detection.

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Objective Detection

CTIT distributions are based on measurable timing data, not subjective assessments. Statistical analysis of these patterns provides high-confidence fraud identification.

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Fraud Type Identification

Different fraud types produce different CTIT signatures, enabling you to identify not just that fraud is occurring but exactly what type — informing the right response.

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Source-Level Granularity

CTIT analysis can be applied at the network, sub-publisher, campaign, and creative level, pinpointing exactly which sources are delivering fraudulent traffic.

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Budget Protection

By identifying and excluding sources with anomalous CTIT patterns, you redirect budget to legitimate sources that deliver genuine app users.

How Opticks Uses CTIT Analysis

Real-Time Distribution

Opticks builds CTIT distributions for every traffic source in real time, comparing patterns against legitimate baselines and flagging anomalies as they emerge.

Multi-Signal Correlation

CTIT data is combined with 30+ additional fraud signals — device fingerprinting, behavioural analysis, IP reputation — for comprehensive fraud detection that minimises false positives.

Actionable Reporting

Visual CTIT distribution charts and automated alerts make it easy to identify problematic sources and take action before significant budget is wasted.

Frequently Asked Questions

What is CTIT (click-to-install time)?

What does a normal CTIT distribution look like?

How does CTIT analysis detect click injection?

How does Opticks use CTIT analysis?

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Related Resources

Glossary of Ad Fraud Terms Click Spam Guide Ad Fraud Guide Click Scam Guide Install Fraud Guide Start Your Free Trial

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