Identify Potential Users for Instagram Shopping Tab Adoption

Q: Identify Potential Users for Instagram Shopping Tab Adoption

This question evaluates a data scientist's competencies in user segmentation, product analytics, and experimentation design for an in-app shopping tab rollout, placing it squarely in the Analytics & Experimentation domain and emphasizing practical application of historical event data and metric definition.

Q: How do I approach Analytics & Experimentation interview questions?

Analytics & Experimentation questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master analytics & experimentation interviews.

Question

Instagram Shopping Tab: Targeting, Metrics, and Trade-offs

Context

Instagram is launching a new in-app Shopping tab. As a data scientist, you need to:

Identify users most likely to adopt the Shopping tab at launch.
Define success metrics to evaluate the feature.
Specify trade-offs and guardrails to monitor, especially impacts on the core feed experience.

Assumptions:

You have historical logs for commerce-related actions (e.g., product-tag clicks, Shops visits, checkout usage).
Feature placement (tab) is visible to eligible users; adoption is not forced.

Questions

How would you identify potential users most likely to adopt the Shopping tab?
Which success metrics would you track for the feature?
What trade-offs and guardrails would you monitor (e.g., impact on core feed engagement)?

Identify Potential Users for Instagram Shopping Tab Adoption

Instagram Shopping Tab: Targeting, Metrics, and Trade-offs

Context

Questions

Solution

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