Facebook Meta Certified Marketing Science Professional 200-101 Exam Dumps Are Available

Facebook Meta Certified Marketing Science Professional 200-101 Exam Dumps Are Available

You may be familiar with the Meta Certified Marketing Science Professional exam, which can define business goals, set KPIs for meeting them, run test campaigns and build on consumer insights to develop marketing recommendations. Now you are going to pass Facebook 200-101 exam to earn the Meta Certified Marketing Science Professional certification. The valid 200-101 exam dumps are available at ITPrepare, which could be your best study materials for passing. Just come to download the Facebook 200-101 exam dumps pdf file to start learning all the questions and answers for good preparation.

You can test Facebook 200-101 free demo dumps before downloading:

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1. An analyst for a primarily brick-and-mortar retailer is reviewing measurement results from the last half for all marketing. The media plan was 50% TV spend, with some Facebook (10%), search (10%), print (10%), and radio (20%).

No solution provides the same numbers for a single point in time. The analyst needs to recommend how to allocate budget across channels to maximize sales for the next business quarter.

Which measurement solution should be the primary source of the analyst's recommendation?

2. 1.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.





Which Attribution model should the retailer choose?

3. 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)

4. A snack company ran a preliminary simple linear regression analysis to determine channel contributions to sales. The model, coefficients, and data set are as shown. All numerical values are rounded.

Sales(week) = BO (Intercept) + B1 f(FB Video) + B2 f(FB Display) + B3 f(TV) + B4 f(Digital Video)





What are the attributed sales from Facebook for Week 2?

5. An advertiser is running an A/B test on Facebook with the goal of finding whether creative strategy A or B achieves the most conversions.

What is the null hypothesis of this test design?

6. An advertiser recently ran a month-long campaign on a new media platform. This campaign targeted customers who had purchased from the advertiser in the past year. Of the 10 million customers targeted, 3 million were reached. The average frequency for the campaign was three impressions over the month. The advertiser spent $100,000 on this media buy.

After the campaign, an analyst from the media platform noticed that customers who received six or more impressions were twice as likely to purchase than those who received three or fewer impressions. To increase the number of users who receive six or more impressions, the analyst recommends that the advertiser double their spend. The goal is to increase the frequency from three to six in order to drive a significant increase in incremental return on ad spend.

What primary concern should the advertiser's in-house measurement team have about this conclusion?

7. An advertiser wants to know whether campaign strategy A had significantly different performance than campaign strategy B in terms of additional sales. The campaigns both ran at the same time against mutually exclusive portions of the advertiser's customer base.

What is the null hypothesis of the test design?

8. An ecommerce brand runs a multi-cell Conversion Lift test. The brand needs to determine if bidding in the Facebook auction based on user value calculated from its LTV model versus demographic targeting improves performance by 10%. The p-value for the test is calculated as p = 0.95.

How should the analyst interpret bidding based on user value?

9. A brand needs to measure how frequency affects conversions and ROI. Currently the brand runs a campaign on 2x frequency for seven days.

How should the brand set up a test to understand how frequency affects incremental conversions?

10. A start-up ecommerce brand that sells pet products wants to test campaign structure. It would like to determine if it should have separate ad sets targeting different pet interest groups or consolidate all interest groups into one ad set.

The brand sets up a multi-cell Conversion Lift test for one month. At the end of the test, no results are available to review, due to insufficient statistical power.

Which two approaches should the analyst recommend? (Choose 2)


 

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