Risk Assessment & Mitigation Flashcards

A marketing team discovers that 30% of its conversion tracking pixels fire duplicate events. What is the PRIMARY risk this poses to analytics-based decisions?

Answer: Inflated conversion counts leading to over-investment in well-performing channels

Duplicate pixel fires inflate conversion counts, making channels appear more effective than they are and causing misallocation of budget.

Which statistical technique is most appropriate for identifying outliers that could distort marketing attribution models?

Answer: Interquartile range (IQR) method

The IQR method flags values beyond 1.5×IQR from quartiles, making it a robust standard technique for outlier detection in attribution datasets.

A company's email click-through rate drops 40% after an ISP updates its spam filters. This scenario best illustrates which type of marketing analytics risk?

Answer: External environment risk

Changes by third parties such as ISPs are external environment risks that alter channel performance independently of internal marketing decisions.

When building a customer lifetime value (CLV) model, which mitigation strategy best addresses the risk of training on a non-representative historical cohort?

Answer: Stratified sampling across acquisition years and channels

Stratified sampling ensures each historical cohort is proportionally represented, preventing the model from over-fitting to one acquisition period or channel.

A marketing analyst notices that A/B test results consistently favor Variant B on weekdays but Variant A on weekends. What risk does this reveal?

Answer: Temporal confounding

Day-of-week differences in user behavior create temporal confounding, making the test period itself a variable that distorts true treatment effects.

A retailer's attribution model credits 80% of revenue to paid search because most purchases happen shortly after a search ad click. Which risk does this most likely reflect?

Answer: Last-touch attribution bias

Last-touch models over-credit the final touchpoint before conversion, obscuring the contribution of earlier channels like display or social.

To mitigate the risk of PII exposure in a marketing analytics data warehouse, which control is most directly effective?

Answer: Encrypting data at rest and applying column-level masking for sensitive fields

Encryption at rest combined with column-level masking limits PII exposure even if unauthorized access to the warehouse occurs.