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200-101: Meta Certified Marketing Science Professional
200-101: Meta Certified Marketing Science Professional is a Professional-level exam about using data, insights and measurement to make informed marketing recommendations. The Meta Certified Marketing Science Professional credential is awarded to professionals who have proven advanced competency in using data, insights, and measurement to make marketing recommendations. The ideal candidates for this certification have approximately 3 years of career experience with consulting on measurement strategies and executing research, as well as statistics knowledge and data manipulation skills.
Exam Objectives
Assess (24%)
- Reconcile business goals with KPIs and analysis plans
- Apply concepts required to inventory and monitor existing data sources
- Evaluate differences in measurement methodology across channels
- Communicate assumptions based on situation assessment
- Validate data quality
Hypothesize (18%)
- Determine a variable for testing
- Determine a measurement approach
- Apply concepts required to formulate a hypothesis to be proven or disproven
- Determine actions based on hypothesis validation/invalidation
Recommend Measurement Solutions (15%)
- Make decisions required to design a test addressing the hypothesis
- Recommend an appropriate Meta or partner measurement solution
- Determine feasibility to move forward with a measurement solution
Perform an Analysis (16%)
- Interpret statistical outputs
- Analyze data using statistical methods
- Analyze data using exploratory methods
- Make decisions and judgments required to create data visualization methods
- Make decisions and judgments required to write a simple script or query to extract and manipulate data
Generate Insights (14%)
- Make decisions and judgments required to synthesize the results from statistical and data analyses
- Apply concepts required to prove or disprove the hypothesis
- Evaluate the success of the measurement approach
Make Data-Driven Recommendations (13%)
- Make recommendations for future campaigns based on insights
- Determine iterative measurement opportunities based on insights
- Determine opportunities beyond the scope of the measurement approach
View Online Facebook Certified Marketing Science Professional 200-101 Free Questions
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?
A. It cannot be concluded that 95% of the performance increase is due to bidding based on user value.
B. It cannot be concluded that 10% of the performance increase is due to bidding based on user value.
C. Ten percent of the performance increase is due to bidding based on user value.
D. Bidding based on user value is responsible for 95% of the performance increase.
Answer: B
A startup ecommerce company is beginning to run media campaigns to increase sales. It is having trouble taking action from its media campaigns because of the high number of KPIs it is considering when analyzing results.
The startup company has been in the growth phase, so the focus has been on increasing the number of people who see ads for their products on Facebook. As the company grows, the focus is shifting towards generating sales. For its Facebook campaigns, the business is considering incremental purchases, incremental reach, CPMs, website visits, clicks and impressions.
Which metric should be prioritized to support the company’s new Facebook marketing strategy?
A. Website visits
B. Incremental purchases
C. Incremental reach
D. Click-through rate
Answer: D
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)
A. Run a campaign-level A/B test instead
B. Run a multi-cell Conversion Lift with fewer interest groups
C. Run a multi-cell Conversion Lift test with an increased holdout percentage
D. Review campaign results in Ads Manager instead
Answer: AC
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?
A. Marketing mix model
B. Multi-cell Conversion Lift
C. Multi-touch attribution
D. Nielsen Total Ads Ratings
Answer: A
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. First-party data such as email or phone number captured in-store
C. Coordinates from each of its regional shops
D. Data from the Facebook pixel in its site
Answer: D
A large ecommerce company wants to know which of its two creative strategies is generating the highest number of conversions. It already knows that both strategies generate significant lift compared to a holdout group.
What measurement solution should be used?
A. Facebook Brand Lift
B. Facebook Analytics
C. Facebook Conversion Lift
D. Facebook A/B test
Answer: C
An analyst working for a financial services company is reviewing Facebook campaign results to assess how many new credit card signups can be attributed to its Facebook campaign. The analyst is comparing attributed results in Facebook Ads Manager with those in Google Analytics and needs to explain why these are different.
What are two key differences between the platforms that can provide a reasonable explanation for this outcome? (Choose 2)
A. Google data includes impressions, conversions and clicks
B. Facebook data includes visits, conversions and clicks
C. Different platforms tend to attribute more conversions to its own platforms
D. Different platforms may be using different attribution models
E. Different platforms have access to different data
Answer: CD
An analyst wants to measure a campaign that is delivering across Facebook and Paid Search. The client wants to understand the causal sales impact of each channel.
Which methodology should the analyst use?
A. A/B test
B. Randomized control trial
C. Attribution
D. Marketing mix model
Answer: B