Online Access Free 200-101 Exam Questions

An analyst has calculated an average lift from a random sample of 300 similarly sized campaigns. The analysis showed the following:
* Minimum lift is 98
* Maximum lift is 177
* 95% confidence interval for the average lift per campaign is (133, 145)
* Average p-value for each individual campaign's lift is p = 0.03
What should the analyst conclude about the distribution of lifts?

• A.There is 99% certainty that next campaign will have lift covered by the interval of (98, 177)
• B.There is 95% certainty that the true average lift of all campaigns is covered by the interval of (133, 145)
• C.95% of the 300 campaigns had observed lift covered by the interval of (133, 145)
• D.There is 95% certainty that next campaign will have lift covered by the interval of (133, 145)

An online retailer knows their incremental effect from Facebook ads from their previous Conversion Lift test. They want an always-on attribution solution that allows them to allocate its budget across publishers on an ongoing basis. The challenge is identifying a model that is as close to their true business value as possible.
Refer to the following results:

Which Attribution model should the retailer choose?

• A.Time decay
• B.Positional 30%
• C.Positional 40%
• D.Even credit

A medium-sized travel business executes a digital strategy with a focus on building brand awareness for its new travel package. The advertiser runs a 4-cell Brand Lift test comparing the Engagement objective against other objectives. Assume the following results:

What strategy is most efficient to achieve the KPI?

• A.Traffic objective
• B.Brand Awareness objective
• C.Reach objective
• D.Engagement objective

A local retailer wants to measure the effectiveness of Facebook campaigns based on the number of in-store purchases after customers have been exposed to an ad within the platform.
Where should outcome data be sourced?

• A.Third-party data sources as an estimation of real customers
• B.Data from the Facebook pixel in its site
• C.First-party data such as email or phone number captured in-store
• D.Coordinates from each of its regional shops

An advertiser is reviewing campaign results in Facebook Attribution and determines that optimizing its campaigns for website content views appears to be more successful than optimizing for clicks.
Details reviewed were as follows:
* A last touch attribution model was used
* Look back window was 90 days
* Campaigns optimized for clicks delivered a cost per view for SO.55
* Campaigns optimized for website content views yielded a cost per view of S0.49
The advertiser wants to assess whether or not this difference is meaningful or due to random chance before adjusting its strategy accordingly. What action could the analyst take to determine if the difference is meaningful?

• A.Run a single linear regression analysis
• B.Run data-driven attribution
• C.Run a single-cell Conversion Lift test
• D.Run a multi-cell Conversion Lift test