Question: Since 2017, the ads ecosystem has seen an increased need for machine learning due to which of the following reasons?
- In recent years, data scientists began driving machine learning projects and efforts forward.
- Chrome announced its intent to phase out first- and third-party cookies as soon as an alternative is available.
- Marketers began using machine learning to find patterns to predict behavior and to quickly optimize.
- Increasing user expectations, privacy regulation, and technology changes have impacted campaign measurability.
or
- Increasing user expectations, privacy regulations and technology changes have impacted campaign measurability.
- Chrome announced its intent to phase out first- and third-party cookies as soon as an alternative is available.
- Marketers began using machine learning to find patterns to predict behaviour and to quickly optimise.
- In recent years, data scientists began driving machine learning projects and efforts forwards.
Explanation
Changes in consent, identifiers, and browser behavior reduce the amount of directly observable conversion data. Google AI helps address gaps when deterministic signals are incomplete. Conversion modeling estimates conversions that cannot be directly observed without identifying individual users. Machine learning becomes more important because campaign performance must be optimized from partial signals instead of complete user-level paths.
Why the other options are incorrect
Chrome cookie phaseout is incorrect because Chrome did not frame the issue as removing both first-party and third-party cookies.
Machine learning adoption is incorrect because it describes a response to signal loss, not the reason signal loss increased.
Data scientist projects is incorrect because internal project ownership does not explain ecosystem-level measurement changes.
Source for verification
https://support.google.com/google-ads/answer/12443859
https://business.google.com/us/privacy/products/
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