Click Fraud: Market Share of Digital Advertising Estimation Model

First Published Summer 2010. Updated Summer 2019

Click Fraud is best understood as a business model that profits from network contagion.

This model allows you to apply network effects to discover the potential impact of click fraud on the USD$225 Billion global digital advertising market

Note: The model assumes a global average of 3 "legitimate" ads being served per web page or app

Move the sliders to explore how an infectious contagion of machine traffic has the potential to distort the costs of doing business in the global digital advertising market.



Est. Global Click Fraud Market Value

The scale of the problem compared to traditional advertising funded "mass media" models

The scale of the problem compared to other types of cyber crime


The use of these calculators, charts, visualisations, data or any information shall be at the user’s sole risk. Such use shall constitute a release and agreement to hold harmless, defend and indemnify Digital Partners from and against any liability (including but not limited to liability for special, indirect or consequential damages) in connection with such use. Such release from and indemnification against liability shall apply in contract, tort (including negligence of such party, whether active, passive, joint or concurrent), strict liability, or other theory of legal liability; provided, however, such release, limitation and indemnity provisions shall be effective to, and only to, the maximum extent, scope or amount allowable by law.

Questions of accuracy

Tymbals is an experiment in machine learning and statistical modelling of small data pools. Tymbals is still under development. It is still learning. Tymbals is Beta - i.e. Pre-release.

The probabilities and outputs (e.g. calculators, charts, visualisations) will evolve and change as the system ingests more data.

Tymbals is a probability model. The results generated by Tymbals are market estimates based on the cummulative value of the data within the distributed data pools.


All data inputs are automatically added to the learning pool from which Tymbals models are generated.

If you do not want your data added the data pool do not use Tymbals

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