How to Pass the Facebook Certified Marketing Science Professional Certification Practice Test?
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Before you get to the answers below here are some things you should know about the exam.
Exam Name – Facebook Certified Marketing Science Professional Exam
Total Questions and Time Limit – 10 minutes to complete entire exam.
Exam URL – https://www.facebook.com/business/learn/certification/exams/200-101-exam
200-101: Facebook Certified Marketing Science Professional Exam Answers 2021 – Updated!!
✅ An advertiser is running monthly individual conversion lift tests across multiple digital channels.
The latest lift tests showed the channels A, B, and C had statistically significant positive lift results whereas channel D did not have statistically significant results. The tests were all run targeting the advertiser’s previous customers (CRM). They also hope to run future campaigns similarly using multiple channels with new customers. One of the blind spots the digital marketers want to clear up is how much overlap there is between the digital channels and whether efficiencies can be gained as a result of that finding.
What should the analyst pursue to most effectively answer the digital marketing team’s question?
- Use multi-touch attribution to identify where multiple platforms are overlapping reach
- Use last-touch attribution to avoid double-counting conversions that were captured on multiple platforms
- Run future tests where audiences are not overlapping so that there is no ability to see ads on multiple platforms
- Identify correlations in daily sales data between channels using a marketing mix model
Explanation: Multi-touch attribution (MTA) measures incremental sales generated by each touchpoint in the path to conversion, rather than assign full credit to a single touchpoint.
✅ An agency for a film studio has historically focused on driving awareness and consideration for upcoming movie releases. They currently run a mixture of brand and direct response campaigns. Sixty percent of sales are from in-app and online ticket purchases, and 40% are offline.
To evaluate the success of their current strategy, the agency runs a Brand Lift test to poll the client’s audience on consideration, purchase intent, and ad recall. The test revealed strong results with a 6% lift in consideration and a 5% lift in purchase intent. They want to use this evidence to request increased investment from their client.
The client’s analyst argues that this does not provide adequate evidence that the strategy drives sales.
Which test should be run to make the strongest case that the direct response campaigns are driving incremental sales?
- Account-level Conversion Lift including all brand and direct response campaigns
- Campaign-level Conversion Lift including only direct response campaigns
- Campaign-level Brand Lift including only direct response campaigns
- Campaign-level Conversion Lift including brand and direct response campaigns
Explanation: Since the goal is to understand the effectiveness of direct response campaigns only, a Conversion Lift test of direct response campaigns would be the most appropriate test to run since it measures incremental sales and conversions caused by the campaign.
✅ A shoe brand recently ran a multi-cell Conversion Lift test to compare evergreen digital marketing campaigns against a new promotional campaign using dynamic ads. The hypothesis was that the dynamic ads campaign would outperform the evergreen campaign on conversion and sales lift. This test ran for six weeks during the holiday periods between November and December.
The dynamic ads campaign created a 4% lift in overall conversions and $250,000 in sales
The evergreen campaign created a 1.5% lift in overall conversions and $100,000 in sales
The dynamic ads campaign resulted in a $120.43 cost per incremental conversion and a 1.5x ROAS
The evergreen campaign resulted in a $35.45 cost per incremental conversion and 2x ROAS
What should an analyst recommend as the next steps to use these insights?
- Shift total budget to the evergreen digital campaign
- Continue running both the dynamic ads and evergreen campaigns, but reduce spend on dynamic ads
- Reduce spend from both campaigns because they did not result in an efficient lift
- Shift total budget to the dynamic ads campaign
Explanation: Dynamic ads are driving the highest additional sales and incremental conversions but also cost the most for additional conversion. Evergreen campaigns have a significantly lower cost for an additional conversion as well as a higher ROAS. The correct recommendation would be to continue running both and reduce spend on dynamics ads.
✅ A financial services company is launching a month-long Facebook campaign to promote its new credit card. The audience strategy is to reach people who have previously applied for one of the company’s current credit cards but did not get approved.
The campaign has been set up with a single-cell Conversion Lift test to determine how effective the campaign is in getting people to apply. The company would like a post-campaign report that highlights the total budget spent and the number of approved applications.
What should the analyst recommend for the campaign?
- The schedule of the campaign should be longer than one month
- A multi-cell Conversion Lift test should be used instead
- The KPI should be the number of applications submitted
- The KPI should be the number of people reached
Explanation: Since the goal of the campaign is for people to apply for the new credit card, the metric the company should focus on is the number of applications submitted.
✅ A car manufacturer releases a new model. The manufacturer creates a campaign with the business goal of increasing purchases of the new model. It also wants to conduct a test to determine the sales impact of targeting shoppers who showed interest in buying a car similar to last season’s new model.
Which data source does this manufacturer need to run this test?
- Facebook pixel
- Facebook SDK
- Offline Conversions API
- Online Conversions
Explanation: To measure the impact of transactions that typically take place in-store, the manufacturer should ensure it is using Offline Conversions, which allows the manufacturer to upload offline events and associate those purchases to the campaign included in the test. Without that in-store sales activity, the test will not produce accurate results.
✅ A famous sneaker brand plans to launch a national TV campaign with an online campaign across a few digital platforms, including Facebook, to promote its new product. The TV campaign spans across April. The Facebook campaign starts the second week of April and ends the first week of May.
The brand wants to know if the national TV exposure will contaminate a Brand Lift test run on Facebook because both campaigns target people, ages 18-34.
How will the national TV exposure interact with the Brand Lift test run on Facebook?
- All the people in the Brand Lift control group will see the ads for the new product on TV, which leads to underestimating the effectiveness of the Facebook campaign
- All the people in the Brand Lift control group will see the ads for the new product on TV, which leads to overestimating the effectiveness of the Facebook campaign
- TV exposure will not contaminate the test because the audience reached on TV and digital platforms are different
- TV exposure will not contaminate the test because Brand Lift uses Randomized Control Trial methodology
Explanation: There is equal opportunity for the test and control groups to have seen the TV ads since the test and control groups are assigned randomly.
✅ An eCommerce advertiser sells activewear. The advertiser needs to assess which proportion of the advertising budget should be spent on re-targeting previous buyers versus targeting consumers who visited its website but did NOT make a purchase. To make this decision, the advertiser needs to measure the proportion of sales generated by each targeting strategy to learn which strategy generates the largest proportion of additional sales.
The advertiser pauses its usual campaigns and sets up an A/B test using two ad sets. Both ad sets are optimized for purchases. The only difference is the targeting strategy used. The advertiser runs the ad sets for seven days. The A/B test results are based on attributed conversions using a last-touch attribution model to identify the winning strategy.
This measurement approach does NOT accurately measure causality.
What is causing this measurement issue?
- The test should be set up to prevent contamination to the control group
- The test should be set up to prevent contamination to the test group
- The test should run for a minimum of three weeks to collect adequate data
- The test needs to run randomized test and control groups
Explanation: Conducting an A/B test will not measure causality; instead, an RCT (lift test) should be used to more accurately measure the causal impact of each strategy.
✅ An advertiser is running a Conversion Lift test on a new media platform. In discussing how the campaign will be measured, the media platform’s team says that it will compare the conversion rates for the test group exposed to ads vs. a pre-selected control group. The platform does have the ability to run a public service announcement instead but feels that its methodology is valid.
What concern should the analyst have with the test design?
- Randomization is required for valid experimental design
- Pre and post measurements will provide a more accurate assessment
- There may be contamination between the test and control groups
- An A/B test will provide a more accurate assessment
Explanation: There is no randomization for the pre-selected control group. In this case, it makes the experimental design invalid.
✅ A large quick-serve restaurant brand launches a new holiday-themed dessert. The brand runs an always-on campaign on Facebook to maintain its brand awareness. They launch a two-week campaign to drive traffic to a landing page with a discount offer for the dessert during the holiday period. The discount campaign is running two weeks prior to the holiday period.
The brand runs Brand Lift tests every quarter to measure the impact of their always-on campaign and is planning to run a Conversion Lift test to see the incremental coupon downloads generated by the discount-offer campaign. The Conversion Lift test will be set up as a nested test within the Brand Lift test setup.
Which rationale should the brand use to document that the Conversion Lift test results will be unbiased?
- The nested setup accounts for possible contamination across studies
- The discount-offer campaign is unlikely to reach the same audience as the always-on campaign
- The Conversion Lift test is measuring a different KPI than the Brand Lift test
- The Brand Lift test only polls 1000 respondents and is unlikely to be impacted by the discount-offer campaign
Explanation: Having tests nested ensures there is no contamination between the studies.
✅ An automotive manufacturer launches a campaign to sell its newest model. The manufacturer uses a last-click attribution model with a 90-day conversion window to evaluate its media investment.
The attribution results show lower-than-expected online conversions on Facebook. The manufacturer needs to validate these results.
In order to validate the results, what should they be compared to?
- The results from the last-click attribution model with a conversion window of 30 days
- The number of offline conversions
- The results from Facebook data-driven attribution
- The results from Facebook Brand Lift tests that were run during the campaign
Explanation: Facebook data-driven attribution (DDA) gives a more accurate measure of Facebook-driven conversions when compared to last-click attribution.
✅ A luxury car company wants to measure the effectiveness of its investment on Facebook during the holidays. It intends to deliver its campaigns across both Facebook and Instagram. It has multiple audiences across 5 major markets that it wants to reach. These markets are defined by zip code or geolocation. The car company wants to measure the incremental sales driven within each major market.
What variable should the company test?
- Buying type
Explanation: The only variable that can be tested which relates back to the major market is the location.
✅ A cruise brand advertises on Facebook, Instagram, and YouTube. The brand is evaluating the performance of these channels in Ads Manager and Google Analytics to determine how to allocate its increased budget for the upcoming season. The brand suspects the impact of Facebook platforms is over-represented in Ads Manager and under-represented in Google Analytics.
How should the company measure the causal contribution of the Facebook platforms accurately?
- Adopt multi-touch attribution models for all platforms
- Use Ads Manager results to evaluate Facebook platforms
- Use Google Analytics to evaluate Facebook platforms
- Run an ad-account level randomized control trial on Facebook
Explanation: A Brand Lift test is the only way to poll for purchase intent, and it also ensures no contamination between the two cells.
✅ An online fashion retailer wants to test the Video Views objective against the Brand Awareness objective. The goal is to see which objective generates better purchase intent among the target audience.
Which method should the retailer use to achieve this?
- Multi-cell Conversion Lift test to test Video Views versus Brand Awareness
- Split test to measure Video Views versus Brand Awareness
- Multi-cell Brand Lift test to test Purchase Intent with Brand Awareness versus Video Views
- Split test to measure estimated ad recall for each objective
Explanation: A Brand Lift test is the only way to poll for purchase intent, and it also ensures no contamination between the two cells.
✅ A TV advertiser needs to attract more sports fans to tune into their upcoming live events. According to a global index survey, 90% of sports fans online report that they use another device while watching TV. More than 50% of sports fans reported that their top activities were using social media and chatting with friends.
To maximize ad reach, which hypothesis should the advertiser test?
- Placing ads on popular social media platforms is the most cost-efficient way to generate conversions
- Placing ads on top sports channels is the most cost-efficient way to generate reach
- Messaging apps provide incremental conversions
- Social media platforms provide incremental reach to TV
Explanation: With the goal of maximizing reach, diversifying its media investment may help the advertiser reach additional users it wasn’t reaching before.
✅ An advertiser is planning on running a campaign that includes TV, Facebook, and search, with the goal of increasing sales. The attribution results from that campaign will determine how they run their future campaigns.
What should the advertiser do based on the attribution results?
- Reallocate budget to the channel driving the highest number of conversions
- Stop spend entirely on the channel with the lowest number of conversions
- Allocate budget evenly across all three channels
- Conduct a multi-cell Brand Lift test to validate the attribution results
Explanation: Attribution results will illustrate performance across channels and show where the budget should be allocated based on the ROI.
✅ An automotive brand runs a $1,000,000 branding campaign on Facebook for its newest model. The goal is to encourage men and women, ages 18+ to believe that it is “the car for everyone.” A single-cell Brand Lift test runs and obtains 150 responses for each test and control group. The results are as follows:
45% of the test group respondents agree with the statement that the car is “the car for everyone”
40% of the control group respondents agree with the statement that the car is “the car for everyone”
The results are statistically significant at the 80% confidence level
What is a potential action that the brand could take to increase the power of the Brand Lift test?
- Increase the target sample size
- Run a multi-cell Brand Lift test
- Poll men and women separately
- Decrease the target sample size
Explanation: Increasing the sample size increases the ability of the test to detect lift, which results in a more powerful test.
✅ A large gaming company wants to know if its Facebook campaign is increasing purchase consideration due to ad exposure on Facebook.
What measurement solution should be used?
- Facebook Conversion Lift
- Facebook Brand Lift
- Facebook A/B test
- Facebook Analytics
Explanation: The only way to measure consideration is by polling via a Brand Lift test.
✅ A restaurant with a low volume of online orders wants to understand how a Facebook advertising campaign is impacting overall sales via a multi-cell Conversion Lift test. The test is planned to run for two weeks and the chosen strategy will then be implemented. The company has the following:
Facebook pixel properly implemented on its website
Facebook SDK connected to its app
A loyalty program among customers that aggregates data on all orders
What should the company do to ensure the feasibility of the measurement plan?
- Upload in-store orders via the Offline Conversions API
- Use clickthrough and view through traffic as a proxy for conversions
- Decrease the advertising dollar amount spent on the campaign
- Run a single-cell Conversion Lift test instead
Explanation: The majority of the restaurant’s transactions have been completed offline. In order to account for those sales, the restaurant should upload information about those transactions (offline events) to Facebook. This can be done via Events Manager, the Offline Conversions API, or through a partner.
✅ A brand runs a multi-cell experiment to confirm whether its campaign is generating sales lift. The results were as follows.
sales lift = 4.0%
90% confidence interval = (0.010,0.070)
sales lift = 4.5%
90% confidence interval = (-0.010, 0.084)
Cell A – Cell B
sales lift = -1.2%
90% confidence interval = (-0.023, 0.001)
What is the correct interpretation of the results?
- Cell A performed positively, Cell B did not perform positively, Cell A performed better than Cell B
- Cell A performed positively, Cell B performed positively, Cell B performed better than Cell A
- Cell A performed positively, Cell B performed positively, and it is not possible to tell which was better
- Cell A performed positively, Cell B did not perform positively, and it is not possible to tell which was better
Explanation: A confidence interval containing zero means we’re uncertain whether there is an effect. Having zero in the confidence interval implies that the effect could have a positive or negative effect on the outcome of interest. This means we can’t conclude that cell B resulted in a positive outcome, nor can we conclude there was any difference between cells A and B.
✅ A media agency analyst ran a regression model to understand the relationship between advertiser media and the competitive media on a sales KPI.
The following results were obtained from the regression software:
Dependent Variable: LOG(SALES)
Method: Least Squares
Sample: 01-2016 52-2018
Included Observations: 150
Adjusted R-squared: 0.998515
S.E of regression: 0.01685
Akaike info criterion: -5.263574
Schwartz criterion: -5.143130
What two interpretations should the analyst make from this statistical output? (Choose 2)
Select All Correct Responses
- The constant variable is not statistically significant in the model
- The competitive media variable is statistically significant in the model
- The competitive media variable is not statistically significant in the model
- The media variable is not statistically significant in the model
Explanation: By using standard levels of statistical significance (p = 0.05, p = 0.1 etc), we can see that the probability (Prob) of the constant variable is more than the threshold (0.9734 > p = 0.05 ; or 0.9734 > p = 0.1) which is means this variable is not statistically significant in the model. The probability (Prob) for the competitive media variable, on the other hand, is less than the aforementioned threshold, which indicates the variable is statistically significant in this model.
✅ An advertiser’s primary product offering is a series of subscription boxes. The advertiser wants to increase user retention. Approximately 25% of customers who buy a three-month subscription do NOT buy another subscription the following year.
A key objective is to reduce the churn rate by 5%. A data scientist develops a model to identify users who have a high probability of churning and to create exclusive offers designed to entice these users to buy another subscription.
Which type of model should the data scientist use?
- Logistic regression
- Linear regression
- Multinomial regression
- Support vector regression
Explanation: Logistic regression is the preferred method when the dependent variable (shown here as churn yes=1 or churn no=0) is a categorical or discrete variable.
✅ A research team presents the following insights about their brand’s sales quarterly results:
The previous year (with digital campaigns during Q1-Q2)
What is the only thing that can be concluded about the brand’s year-over-year sales observable behavior?
- Sales increased 10% during Q4 due to digital campaigns
- Sales decreased during Q1 and Q2 due to the absence of digital campaigns
- Sales during Q3 would have increased more if digital campaigns were active earlier
- Sales increased 6.7% during Q2, which could be due to digital campaigns
Explanation: The correct answer was Sales increased 6.7% during Q2, which could be due to digital campaigns.
✅ Refer to the chart.
An analyst in a technology company aggregates 42 Brand Lift studies that contained favorability questions. The analyst plots these studies against the engagement rate that the ads received. The engagement rate is a summation of likes, comments, and shares over the total reach in each campaign.
Each dot in the chart is a separate campaign.
What is the correct interpretation from this chart regarding the correlation between the engagement rates and favorability lift?
- No correlation
- Weak positive correlation
- Weak negative correlation
- Strong positive correlation
Explanation: If there is no apparent relationship or trendline between the two variables in the scatter plot, it means there is no correlation between the two variables.
✅ Refer to the tables.
Which query will retrieve all results for movies released only after the year 2000?
- SELECT release_year FROM movies WHERE movies > 2000;
- SELECT movies FROM movies WHERE release_year > 2000;
- SELECT * FROM movies WHERE release_year > 2000;
- SELECT release_year > 2000 FROM movies;
Explanation: The star (*) in the SELECT statement stands for all the columns in all the tables in the table list.
✅ An insurance company needs to use data to identify the appropriate communication strategy for its brands. Recently, the company commissioned a creative agency to produce longer and more sophisticated video ads. The company is currently focusing on the amount of additional leads it is able to generate. Each evaluated strategy consists of a set of different combinations of reach levels, ad formats and campaign costs. The company has already run a large number of lift tests to measure additional conversions so it also has the average lift scores for each strategy.
The average outcomes of three strategies standout from the rest:
Short video formats: 1 lift point, 5 million people reached and an average cost of 25,000 USD
Mix of short videos and static formats: 0.5 lift points, 14 million people reached and an average cost of 30,000 USD
Long video formats: 2 lift points, 3 million people reached and an average cost of 50,000 USD
Which action should be taken to improve the communication strategy based on the available data?
- Use long videos and increase the investment
- Use short videos instead of longer ones
- Use a mix of short videos with static formats
- Use long videos and maintain the current level of investment
Explanation: The mix of the short videos and static images provides the most cost-efficient ROI.
✅ A cruise ship brand conducts tests to optimize its digital strategy to improve incremental brand awareness and conversions.
The brand decides to hire a creative agency to improve performance.
Which piece of evidence supports this decision?
- Brand Lift results are flat or below vertical averages
- The conversions campaign did not reach enough people to drive adequate lift
- Lift in brand consideration should be over 3% to be considered successful
- No website purchases were observed in the conversions campaign
Explanation: Since the Brand Lift results are flat or below vertical averages, this may indicate that the cruise ship brand may have sub-par creative.
✅ Sales of a dine-in restaurant brand continue to decline. This trend occurs across the dine-in category as new competitors enter the market.
To help bring more customers to the restaurant locations, the brand runs a series of promotional campaigns that feature existing products at a discounted price. The campaign has successfully brought customers into the locations. However, customers tend to order the promoted items only. As a result, the average spend size remains very low, which reduces profit.
Which insight should an analyst provide to the brand?
- The brand may have an issue with value perception
- The customers do not want a dine-in experience
- The competitors have better promotions in the market
- The customers are not having a good customer experience
Explanation: The brand’s choice to run discounted prices for specific products in their advertising associates those products with the brand.
✅ An online shoe brand ran two Conversion Lift studies. Test 1 resulted in the control group showing a 20% conversion rate while the test group showed a 25% conversion rate. The results were significant at 60%. Test 2 resulted in a 20% conversion rate in the control group while the test group showed a 30% conversion rate. These results were 95% significant.
What can the analyst conclude?
- Test 2 results are more reliable than Test 1
- Test 1 results are more reliable than Test 2
- Both tests are equally robust
- A comparison cannot be made between Test 1 and Test 2
Explanation: Test 2 showed both a 10% difference in lift between the test and control groups, and was at a higher confidence percentage than Test 1; therefore, Test 2 results were more reliable than Test 1.
✅ An online food brand that ships high-quality meat has a loyal audience of people, ages 35+. The brand conducts market research and learns that younger consumers are starting to shop for food online more frequently, but are extremely health conscious. The brand is worried they will struggle to be top-of-mind among this new prospective young audience.
The brand runs a multi-cell Brand Lift test for eight weeks to compare how its current creative performs against people, ages 35+ versus people, ages 18-34. Both cells had the same budget and used the same optimization.
- Develop new creative
- Keep serving the existing creative
- Rerun the test
- Increase the spend
Explanation: The test shows flat results for the 18-34 audience indicating that the current creative is not effective at improving brand perception amongst Adults 18-34 in comparison to Adults 35+ audiences.