What is Click to Install Time? Why Advertisers Need to Map this to Detect Mobile Ad Fraud?

Bots are becoming sophisticated and more human-like every passing day. And with the emergence of AI, it is becoming a dominant force for shaping online traffic.

According to Imperva BadBot Report 2025, 51% of the internet traffic is driven by bots, which is further amplifying with the introduction of AI and LLM. Unlike the basic bot traffic showing abnormal signs like high number of clicks/installs etc., the sophisticated bots can mimic human behaviour, therefore bypassing the validation checks.

As a precautionary measure and to check if your campaigns are impacted by bots/invalid traffic, there are signs that you can look for in your campaign data.

One of them being Click to Install Time to identify invalid installs in your mobile app campaigns.

In this blog we will breakdown how CTIT can be seen as a signal to identify invalid traffic and how marketers can use it to take proactive action against mobile ad fraud.

What is Click to Install Time? How to Identify Invalid Traffic Evaluating CTIT?

Let’s simply breakdown what CTIT means before moving forward to understand the kind of patterns that reveal exploitation of mobile ad fraud and click to install time.

Click Time: The moment a user clicks on your ad.

Install Time: When the app actually finishes installing.

Click-to-Install Time (CTIT): The time gap between these two.

It is basically a metric used in mobile advertising to map the time it takes for a normal user to download an app after clicking on an ad.

This gap varies naturally. Real users don’t install apps instantly every time; there can be delays, pauses, network differences, and human behaviour involved.

What a genuine user’s install journey looks like

This process takes time, usually a few seconds to a few minutes, depending on network speed and app size.

However, fake installs show different timing patterns.

Here’s are the two types of abnormal CTIT patterns we observed recently that clearly indicate towards install fraud:

Examples of Abnormal CTIT Patterns

Case 1: Extremely short click-to-install time (click injection)

This snapshot compares the click time and install time for multiple installs coming from the same publisher. The gap between click and install is consistently just 1–3 seconds, and in several cases, the values are identical or nearly identical.

Why it is a problem?

A real user cannot click an ad, get redirected to the Play Store, download the app, complete the installation, all within a few seconds, repeatedly.

This pattern strongly indicates click injection, where fraudsters:

• Detect that an app install is already in progress
• Inject a click at the last possible moment
• Steal attribution credit for a genuine install

mFilterIt insight: Why this matters?

Although these installs appear valid in attribution reports, the timing exposes manipulation. Extremely short and repeated click-to-install times are a strong indicator of high-risk fake attribution, not real user engagement.

Case 2: Google Play install begins before the user clicked on an ad

In this snapshot, the timestamps reveal something even more concerning. The Google Play install begin time occurs before the recorded ad click time. This results in a negative click-to-install time, meaning the install process started before the user supposedly clicked on the ad.

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