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Google Product Manager Interview Questions

48 practice questions for Google Product Manager interviews

Google product manager interviews test product strategy, prioritisation frameworks, metrics design, A/B testing, and cross-functional collaboration.

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coding Medium Verified Question #1

1. Dictionary of Sorted Letters


Category: Array coding problem
# Question Given a string where letters are sorted in alphabetical order, identify all letters that appear more than twice and record their first and...
Input: Array
Output: Computed result
coding Medium Verified Question #2

2. GPS Error Tracking


Category: Algorithm coding problem
# Question You are tracking GPS location errors by comparing measured GPS locations against a set of "golden" (reference) locations. Each location...
Input: List
Output: Computed result
coding Hard Verified Question #3

3. Minimum Boxing Area


Category: Binary search coding problem
# Question Design a data structure to maintain a dynamic set of points on a 2D coordinate plane. Support operations to insert points, remove points,...
Input: List
Output: Integer
coding Medium Verified Question #4

4. Reverse Segment of Linked List


Category: Linked list coding problem
# Question Given a singly linked list, reverse the second half of the list and then interleave the nodes from the first half and the reversed second...
Input: Linked list
Output: Computed result
coding Medium Verified Question #5

5. Unpainted Segments


Category: Binary search coding problem
# Question You are given a range [A, B] and a sequence of painting operations. For each operation [L, R], calculate the total length of unpainted...
Input: Array of intervals
Output: Computed result
coding Medium Verified Question #6

6. Running Tests With Failing Pairs


Category: Algorithm coding problem
# Question You are given a set of test cases and a black-box function runTests() that accepts a subset of these test cases and returns whether...
Input: List
Output: Integer
coding Medium Verified Question #7

7. Connected Crop Allocation


Category: Grid/matrix coding problem
# Question You are given an M x N garden grid and a list of crops, each requiring a specific number of plots. The total number of plots required by...
Input: 2D grid
Output: Computed result
coding Medium Verified Question #8

8. [CodeSignal] Maximum Zero-Sum Triplets


Category: Array coding problem
# Question You are given an array A of integers. A triplet is a sequence of three consecutive elements. A triplet is called zero-sum if the...
Input: Array
Output: Computed result
coding Easy Verified Question #9

9. [CodeSignal] Coin Table Game


Category: String coding problem
# Question A player is playing a game in which coins are placed on and removed from a table. The game consists of multiple rounds. At the beginning...
Input: String
Output: Computed result
coding Medium Verified Question #10

10. Longest Match Tokenizer


Category: Array coding problem
You are given a text string text and a dictionary array where each element is in the format "<key>:<id>". Here key is a token string and id...
Input: Array
Output: Computed result
coding Hard Verified Question #11

11. Dual Extremes Queue


Category: Queue-based coding problem
Design a StreamBuffer class that buffers a stream of integer latency samples in FIFO order and supports O(1) access to both the minimum and maximum...
Input: Integer(s)
Output: Integer
coding Medium Verified Question #12

12. Daily Branch Pruning


Category: Tree coding problem
A file system manages a directory tree. Each day, all leaf directories (those with no child directories) are simultaneously removed. Directories that...
Input: Array
Output: Array
coding Medium Verified Question #13

13. Path Router


Category: Algorithm coding problem
# Question Design a PathRouter class that maps URL-like path patterns to handler names. Patterns may contain wildcard segments (*) that match any...
Input: Number(s)
Output: Computed result
coding Medium Verified Question #14

14. Frequency Merge Tree


Category: Tree coding problem
# Question Given a string, build a Frequency Merge Tree as follows: 1. Count the frequency of each character in the string. 2. Create a leaf node...
Input: String
Output: Computed result
coding Hard Verified Question #15

15. Expression Simplifier


Category: String coding problem
Given an algebraic expression string containing single lowercase-letter variables, the operators + and -, and parentheses ( and ), simplify...
Input: String
Output: Computed result
coding Medium Verified Question #16

16. Largest Island Perimeter


Category: Grid/matrix coding problem
You are given an m x n binary grid where each cell is either '1' (land) or '0' (water). A group of connected land cells (connected horizontally...
Input: 2D grid
Output: Computed result
coding Hard Verified Question #17

17. Interval Coverage Counter


Category: Interval-based coding problem
Given a list of closed intervals on the integer number line, build a data structure that efficiently answers point-coverage queries. A closed...
Input: List
Output: Computed result
product strategy Hard product strategy #1

1. [OA] Roadmap Prioritization — YouTube Monetization Features

YouTube is exploring new monetization features to enhance creator revenue options. As a Product Manager, you must prioritize which features to implement in the next product cycle. How would you structure your prioritization criteria, and what trade-offs would you consider given the diverse needs of creators?
Success Criteria:
- Clear framework to prioritize features based on impact and feasibility.
- Identify trade-offs between user experience and complexity of implementation.
- Establish metrics to evaluate the success of the prioritized features.
- Comprehensive consideration of creator feedback in the prioritization process.
Key Stakeholders:
- Content creators: want features that directly impact their revenue.
- Advertising partners: need ad integration that benefits their campaigns as well.
- Data analytics: responsible for tracking the performance of new features.
- User experience team: ensuring features are easy to use and access.
Common Pitfalls:
- Focusing only on high-revenue potential features at the expense of creator satisfaction.
- Neglecting the value of user testing before making final prioritizations.
- Overcomplicating feature sets, leading to user confusion.
- Ignoring feedback loops to improve feature offerings continually.
Examples:
- Discuss how to balance feature requests from large creators versus smaller ones to maintain equity across the platform.
product strategy Senior product strategy #2

2. [OA] Go-to-Market Strategy — Launching Google Workspace for Small Businesses

In the current market landscape, Google is considering a tailored launch of Google Workspace specifically for small businesses. This initiative aims to increase accessibility and affordability for startups and small enterprises.
Given this context, how would you propose a go-to-market strategy that addresses the unique needs of these businesses while ensuring scalability of operations?
Success Criteria:
- Clear identification of target user segments and their pain points.
- Specific marketing channels that will be most effective for small businesses.
- Detailed upfront budget considerations and ROI expectations.
- Metrics to evaluate the success of the launch within the first year.
Key Stakeholders:
- Small business owners: affordability, usability, and seamless integration with existing tools.
- Marketing team: campaign effectiveness and engagement metrics.
- Product development: feature prioritization based on feedback.
- Customer support: training and resources needed for small businesses.
Common Pitfalls:
- Failing to accurately define the target user segments.
- Overlooking competition in a saturated market.
- Neglecting follow-up on customer feedback post-launch.
- Underestimating necessary support resources required for onboarding.
Examples:
- If asked about a specific feature needed for small businesses, outline why it is essential and how it aligns with overall strategy.
product design Medium product design #3

3. [OA] Feature Design — Enhancing Google Photos Sharing Capabilities

Google Photos aims to improve how users can share albums with friends and families. As a Product Manager, you're responsible for scoping the new feature. How will you address user needs while aligning with technical feasibility and Google’s privacy policies?
Success Criteria:
- Comprehensive analysis of user needs around sharing features.
- Explicit details on how privacy will be maintained in the design.
- Creative solutions for enhancing functionality within existing frameworks.
- Clear prioritization of features based on user benefits versus technical complexity.
Key Stakeholders:
- End-users: require an easy and secure way to share photos.
- Engineering team: needs clarity on technical constraints.
- Design team: focused on user experience and interface design.
- Legal: ensures all sharing capabilities comply with privacy laws.
Common Pitfalls:
- Overlooking essential user feedback on sharing functionalities.
- Not accounting for the balance between feature richness and simplicity.
- Ignoring legal constraints during the design process.
- Assuming technical feasibility without close collaboration with engineering.
Examples:
- If proposing a tagging feature for shared photos, articulate user benefits while ensuring privacy standards.
metrics Medium metrics #4

4. [OA] Metrics Framework — Success Measurement for Google Maps

Google Maps has seen accelerated growth in user engagement and feature expansion. As a Product Manager, you are tasked with developing a metrics framework to assess the success of new features introduced in Google Maps, such as the 'Live View' and 'Explore' functionalities.
What metrics would you define, and how would you structure your analysis to ensure user engagement and satisfaction are maximized?
Success Criteria:
- Clear definition of user engagement metrics relevant to new features.
- Structured analysis to derive insights from user feedback.
- Identification of key performance indicators that correlate with user satisfaction.
- Plan for A/B testing new features to validate their effectiveness.
Key Stakeholders:
- End-users: seeking navigational ease and feature utility.
- Engineering team: needs data to iterate on existing features.
- Marketing: requires insights on user response for promotional strategies.
- Data analytics team: responsible for implementing the metrics system.
Common Pitfalls:
- Focusing solely on quantitative data without qualitative insights.
- Neglecting to tie metrics back to user experience.
- Failing to iterate metrics based on evolving feature sets and user needs.
- Overcomplicating the metrics framework, making it difficult to communicate findings.
Examples:
- When asked how to handle negative A/B test results, identify roots in user feedback to pivot the feature or messaging strategy.

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