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 |