Analytics & Experimentation Brainstorm (Scenario Provided)

Context

You are evaluating a feature proposal for a large consumer e-commerce site: add a "sticky Add to Cart" (ATC) button on mobile product detail pages (PDPs) that stays visible as users scroll. The goal is to increase add-to-cart conversion without harming performance, accessibility, or overall customer experience.

Assume for planning purposes:

• Baseline PDP add-to-cart rate (per eligible session) = 8%.
• Daily eligible mobile PDP sessions = 80,000.
• Significance level α = 0.05 (two-tailed), power = 0.8.
• Desired minimum detectable effect (MDE) = 5% relative uplift on ATC rate.

Task

Brainstorm and outline an approach that covers:

1. Success metrics and constraints

• Define primary/secondary metrics and guardrails. State key non-functional constraints (e.g., latency, accessibility).

2. Hypotheses

• List plausible hypotheses for why the feature may help or harm, and where effects might differ (segments, categories, device characteristics).

3. Required data and instrumentation

• Identify what data needs to be logged (events, identifiers, attributes), experiment keys, and quality checks.

4. MVP experiment or analysis plan

• Define randomization unit and eligibility.
• Specify control/variant and exposure.
• Estimate sample size and recommend test duration.
• Outline analysis steps and decision criteria.

5. ML versus heuristic baselines

• If you were to gate or personalize the feature, compare a simple heuristic baseline with a potential ML approach and how you would evaluate them.

6. Risks and mitigations

• Enumerate major product, data, and statistical risks and how you would detect and mitigate them.