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

What difficulty level is this interview question?

This is a medium difficulty Analytics & Experimentation question, commonly asked during Onsite rounds at DoorDash.

What role is this question designed for?

This question is commonly asked for Data Scientist candidates at DoorDash during technical interviews.

Boost App Installs: Analyze and Experiment with Conversion Funnel

Last updated: Mar 29, 2026

Quick Overview

This question evaluates skills in conversion funnel analysis, cohort definition, metric selection, instrumentation, and experimentation design for mobile web-to-app install flows within the Analytics & Experimentation domain.

DoorDash

Jul 12, 2025, 6:59 PM

Data Scientist

Onsite

Analytics & Experimentation

Mobile Web Order → App Install Funnel and Experiments

Context

You are a data scientist for a consumer marketplace with both mobile web and native apps. A meaningful share of customers place orders on the mobile web but never install the app. The company believes app users retain better and order more often, and wants to increase app installs among this segment without hurting core ordering metrics.

Task

Assess the current conversion funnel from mobile web order to app install for users with no prior app install.
Propose and design experiments to increase the install rate.

Guidance

Define clear cohorts and measurement windows.
Map and measure the baseline funnel; call out drop-offs.
Consider in-product prompts, incentives, and off-site retargeting.
Specify experimental groups, primary/secondary metrics, sample size/MDE, duration, randomization, and guardrails.
Note key assumptions or instrumentation needed to measure accurately.

Solution

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