You are working on a campaign with the objective to drive app downloads. You have created an audience on Facebook for your campaign. But, you also have a list of emails from people who have downloaded an app from you before, and you plan to create a custom audience using that list. Now, you would like to know which audience will be most likely to download your app. The new audience you created, or the custom audience of people who downloaded one of your apps before. Which study could help you?

Practice More Questions From: Graded Quiz: Optimizing Your Marketing Mix

Q:

Jesse is preparing an A/B test of an ad. They are planning on only changing a single thing between the two ad variants. Why is that?

Q:

True or false: In an advertising A/B test, it’s best practice to only change one variable at a time between versions A and B.

Q:

Which of the following is a primary benefit of A/B testing different ads?

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True or false: When you are only testing two variations of one variable, you use an A/B test to determine which version will produce the best results.

Q:

Imagine you are planning a campaign for scented candles on Instagram. You have several images of the candles you want to promote, but you are not sure which image will work best. After a meeting with your team, you narrowed the choices down to two different images. One is an image of three candles on a dresser, the other one is an image of one candle only. You have already decided which copy will accompany the image. What should you do to help you decide on the right image to use?

Q:

Imagine you are planning a campaign for a shoe brand on Instagram. You have several images of the shoes you want to promote, but you are not sure which image will work best. After a meeting with your team, you decide to run an A/B test. Version A includes an image of three shoes and a model with the caption “Put your best foot forward. Check out our summer collection.” There is a call to action button that says ‘order now’. Which of the following approaches follows best practice when developing your version B?

Q:

You are working on a campaign with the objective to drive app downloads. You have created an audience on Facebook for your campaign. But, you also have a list of emails from people who have downloaded an app from you before, and you plan to create a custom audience using that list. You also want to run ads on television and radio. Now, you would like to know which platform would be most effective for delivering your message. You have data from previous marketing campaigns and you work with a market research agency to help you with this. Which study could help you?

Q:

You are working on a campaign with the objective to drive app downloads. You have created an audience on Facebook for your campaign. But, you also have a list of emails from people who have downloaded an app from you before, and you plan to create a custom audience using that list. Now, you would like to know which audience will be most likely to download your app. The new audience you created, or the custom audience of people who downloaded one of your apps before. Which study could help you?

Q:

You are working on a campaign with the objective to drive newsletter sign-ups. You have created an ad with copy that has previously tested well with a small focus group. But, you also have an ad with new copy written by the marketing team. Now, you would like to know which ad copy would be most effective for getting people signed up for your newsletter. Which study could help you?

Q:

When setting up an A/B test in Facebook, what is the power of the test meant to tell you?

Q:

True or false: the power of a test tells you the likelihood that this test can find a difference in your ads if there is a difference to find.

Q:

Jesse is running an A/B test on Facebook. They find that the estimated power of their test is 80%. Is this high enough to feel confident in the results?

Q:

True or false: the confidence level you receive after running an A/B test on Facebook tells you the likelihood that the results will be the same if the test is run more than once.

Q:

True or false: a good confidence level after an A/B test is at least 75%.

Q:

After running an A/B test on Facebook, what is the confidence level of the test meant to tell you?

Q:

After running an A/B test on Facebook, you find that you have a confidence level below 90%. What are some things you can do to raise the confidence level? (Choose all that apply)

Q:

Jesse is not pleased with the confidence level they received on a report after running an A/B test. What should they do?

Q:

True or false: you can increase the confidence level received after a test by running the test for more time.

Q:

True or false: it’s a good idea to avoid running ad campaigns before and after an A/B test.

Q:

When referring to an A/B Test, what is the dark period?

Q:

Jesse has a number of ads that are ready to launch leading up to and directly after an A/B test they’re planning on running. What should they do?

Q:

Jesse is attempting to analyze a campaign that ran on Facebook, YouTube, and TV. What type of analysis should they run?

Q:

True or false: marketing mix modeling is not useful for making predictions about future ad campaigns.

Q:

What are some of the things that marketing mix modeling can help with? (Choose all that apply)

Q:

When including data from Facebook in a marketing mix model, what are some considerations? (Choose all that apply)

Q:

What are some of the developments in marketing mix modeling that may make this type of study cheaper to run in the future?

Q:

True or false: all data is worth including in a marketing mix model even if there isn’t something to compare it to.

Q:

APIs and machine learning have many benefits in marketing mix modeling, including: (Choose all that apply)

Q:

What are some innovations that are helping to improve marketing mix modeling? (Choose all that apply)

Q:

True or false: machine learning should be used sparingly with marketing mix modeling because it can drastically slow down analysis

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