vmartinez

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.

 

A customer wants to try a new privacy-centric media strategy and is looking for a way to test effectiveness. Which test could you recommend?

 

• Use Go-dark with the budget of the new media strategy treatment group while the control group remains the same.
• Use 5% Treatment to test gradual budget increments in the new media strategy while the control group remains the same.
• Use heavy-up treatment group to increase the budget of the new media strategy while the control group remains the same.
• Use Holdback treatment group to test the new media strategy while the control group remains the same.

or

• Use the heavy-up treatment group to increase the budget of the new media strategy whilst the control group remains the same.
• Use the 5% treatment to test gradual budget increments in the new media strategy whilst the control group remains the same.
• Use the holdback treatment group to test the new media strategy whilst the control group remains the same.
• Use go-dark with the budget of the new media strategy treatment group whilst the control group remains the same.

 

What’s an example of a key benefit of conversion modelling?

 

• Conversion modelling won’t need to adapt to address user behaviours since there’s a one-size-fits-all measurement approach.
• Conversion modelling allows advertisers to quantify the impact of marketing efforts when a subset of conversions can easily be tied to ad interactions.
• By using conversion modelling, campaigns and bidding strategies will be better optimised, leading to better campaign results.
• Using conversion modelling ensures that your clients’ measurement will no longer be required to remain privacy-safe.

 

What’s an example of applying user privacy solutions as a positive business opportunity?

 

• By offering a transparent and fair value exchange, users are more likely to share their information.
• By removing user controls, users have a more seamless experience navigating an advertiser’s website.
• By offering the ability to reject user data deletion requests, users are more likely to submit their information.
• By limiting the ability to view website offerings, users are more likely to provide their personal information.

 

What’s a main benefit of linking Google Analytics and Google Ads?

 

• You can increase the profit margin of the customer by looking at Analytics’ recommended target ROAS for each campaign.
• You can download unified reports of Analytics and Ads data that can be integrated in the customer’s CRM.
• You can capture user information built on third-party cookies that would otherwise be inaccessible.
• You can use the event data you capture for app install and conversion tracking.

or

• You can capture user information built on third-party cookies that would otherwise be inaccessible.
• You can use the event data that you capture for app install and conversion tracking.
• You can increase the profit margin of the customer by looking at Analytics’ recommended target ROAS for each campaign.
• You can download unified reports of Analytics and Ads data that can be integrated in the customer’s CRM.

 

Why is optimised targeting a good fit for a cookieless world?

 

• Because it allows the use of third-party cookies without informing the users, whilst using machine learning algorithms that ensure user privacy.
• Because it was designed to be implemented with Google Analytics 4, which is also well equipped for privacy-safe marketing strategies.
• Because it optimises display and video campaigns to reach users who frequently accept to be tracked through cookies across sites.
• Because it relies on using first-party data, Google audiences and machine learning instead of third-party data.