What is conversion modeling?
Conversion modeling refers to the process of creating custom columns in Google Ads to model your conversion data and performance.
Conversion modeling refers to observed conversions and uses cookies to connect between ad interactions and conversions.
Conversion modeling refers to the import of observable conversions into Google Ads that model only the best quality conversions.
Conversion modeling refers to measuring marketing using machine learning when a subset of conversions can't connect to ad interactions.
Explanation
Analysis of Correct Answer(s)
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Conversion modeling is a crucial measurement tool that uses Google's machine learning to account for conversions that cannot be directly linked to an ad interaction. This is necessary when technical factors or user privacy choices (like cookie settings) create gaps in the data. The model analyzes observable data and historical trends to estimate the total number of conversions, providing a more complete and accurate view of campaign performance.
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While the machine learning process is the core of conversion modeling, creating custom columns is a related feature in the Google Ads interface. It allows you to build custom formulas and reports to better analyze your data. In this context, you can use custom columns to "model" or structure your performance reports, which would include the estimated conversions from the primary modeling process.
Analysis of Incorrect Options
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The option stating that modeling uses cookies to connect ad interactions and conversions is incorrect. This describes observed conversions. Conversion modeling is specifically used when this direct, cookie-based observation is not possible.
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The option about importing observable conversions is also incorrect. This confuses conversion modeling with a different feature, offline conversion import. Modeling is for estimating unobserved online conversions, not filtering high-quality imported conversions.