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Data Analytics Methods for Marketing Final Quiz :Data Analytics Methods for Marketing (Meta Marketing Analytics Professional Certificate) Answers 2025

Question 1

How many segments should James define for his marketing campaign?
3 Clusters
❌ 1 Cluster
❌ 2 Clusters
❌ 4 Clusters


Question 2

How would you define Cluster 3?
Small businesses that spend a lot.
❌ Medium businesses that spend a medium amount.
❌ Large businesses that spend little.
❌ None of these are true.

.


Question 3

What was the ROAS for Snackwall last year?
400%
❌ $200K
❌ 150%
❌ $800K


Question 4

Which formula should James use to calculate ROI?
ROI = (net profit / net spend) × 100
❌ (revenue made from ads / advertising spend) × 100
❌ (net spend / net profit) × 100
❌ (net profit × net spend) / 100


Question 5

It’s difficult to show CLTV because of the value of the Customer Retention Period. True or False?
True
❌ False


Question 6

Given:

  • Average Order Value = $1,800

  • Orders per Year = 9

  • Retention = 3.5 years

  • Profit Margin = 63%

$35,721
❌ $10,629
❌ $258.125
❌ $3,717,000


Question 7

What does the regression chart help James prove?
There is a positive correlation between advertising spending and sales, and R² suggests we can be confident that our data fit this result.
❌ Sales and ad spending are 93.5% correlated.
❌ Negative correlation.
❌ 93.5% of cases positive correlation.


Question 8

Should James plan to run an attribution study?
True
❌ False


Question 9

Should James run a Marketing Mix Model to analyze past performance?
True
❌ False


Question 10

Based on the funnel visualization, which approach should James take?
This funnel is a blocker, he should consider why customers are getting stuck at this stage.
❌ Reverse funnel
❌ Classic funnel
❌ Tornado funnel

🧾 Summary Table

Q# ✅ Correct Answer Key Concept
1 3 Clusters Optimal segmentation (K-means elbow)
2 Small businesses that spend a lot Segment definition
3 400% ROAS = Revenue ÷ Ad Spend
4 (Net Profit ÷ Net Spend) × 100 ROI formula
5 True Retention period missing for CLTV
6 $35,721 CLTV formula
7 Positive correlation (R² = strong fit) Regression insight
8 True Attribution study for channel performance
9 True MMM for cross-channel impact
10 Blocker – fix drop-off point Funnel optimization