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A marketing analyst wants to understand the relationship between campaign frequency and additional return on ad spend (ROAS) across 150 CPG Facebook campaigns. The analyst has the following information on these campaigns: reach, frequency, duration, budget, product category, buying strategies, and outcomes like additional sales and ROAS. The analyst suspects that campaign frequency is related to other campaign characteristics and is planning to run the following statistical model:
ROAS Lift = bO + b1.reach + b2.frequency + b3.duration + b4.budget + b5.product category + b6.buying strategy
What two additional statistical analysis are required to test the analyst's hypothesis? (Choose 2)
An analyst analyzes 1,000 Facebook video campaigns and calculates there is a correlation of r = 0.6 between view duration of a campaign and additional ad recall lift. What should the analyst tell the company about the relationship between view duration and ad recall lift?
An analyst calculates data averages (norms) of more than 2,500 brand lift tests in the industry, then compares it to recent campaign results:
• Campaign delivered Ad recall lift +8.3pt (the norm Ad Recall is 9.Opt with a standard deviation of 0.6pt)
• Campaign delivered Message Association +7.1pt (the norm for Message Association is 7.8pt with a standard deviation of 0.8pt)
• Campaign delivered Favorability +6.3pt (the norm for Favorability is 4.Opt with a standard deviation of 1.1pt)
• Campaign delivered Purchase Intent +5.9pt (the norm for Purchase Intent is 5.3pt with a standard deviation of 0.5pt)
Which conclusion should the analyst make based on this data?
A brand plans to run a one-month multi-cell Conversion Lift test on Facebook. The cells are designed to help the brand understand experimentally whether its current creative strategy works for different business goals. The different targets are as follows:
• Prospective audience
• Retargeting audience
What should the analyst recommend pursuing after the test?
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?