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TikTok Data Analyst Interview Question: User Journey Analysis | Data Analyst Interview Guide

Introduction

Hi everyone, I'm Alma. I'm currently a data analyst at Lyft and also one of the coaches at Interview Query. Today, we're going to be discussing a case study interview question called user journey analysis.

Introduction

One of my first impressions of this problem is that it is quite vague and can go in many different directions. An interviewer might ask this question to assess your product knowledge and your ability to apply your analytical thinking skills. In a vague question like this, it’s essential to engage the interviewer in conversation, ask a lot of clarifying questions, and keep the interviewer engaged in your conversation.

Pre-interview Preparation

Before diving into the question, you should have already done your pre-interview homework, which involves researching the company you are interviewing for, the product, and any team-specific information. Here are some guiding questions for studying for product-type interviews:

  • What is the main product of the company?
  • What specific features of the product should I focus on?

For the sake of this article, let’s pretend we’re analyzing data for a hypothetical company that operates a smaller community forum app, similar to Reddit.

Clarifying Questions

The first step is to ask clarifying questions. It's important to ask the interviewer for a moment to brainstorm quietly. Here are some crucial clarifying questions you might consider:

  1. What are the user journeys we are analyzing?

    • Possibilities include a user browsing the forum or a user writing a post.

  2. What kinds of user events are present in the table?

    • Examples: user ID, session ID, timestamps of various interactions.

  3. What is the goal behind improving the UI?

    • Possible goals: increase engagement, increase the number of posts, increase time spent on the app, increase DAU, increase revenue from ads and sponsored posts.

  4. What time period and geographic region does the data cover?

    • Assumption: last 4 months, US-based.

  5. Is it known whether the user experience is bad due to a bug or UI issues?

    • Assumption: No technical issues are present.

Assuming we focus on the journey of a user browsing the forum and our goal is to increase engagement (i.e., likes, comments, shares), let’s move forward.

Detailed User Journeys

Browsing the Forum

  1. Open the app.

  2. View the post on the home screen.

  3. Possible actions: like, comment, share.

    Commenting Steps:

    • Click comment section.
    • Type in the comment.
    • Post the comment.

    Sharing Steps:

    • Press the share button.
    • Copy the link.
    • Send the link to a friend.

Writing a Post

  1. Open the app.
  2. Press the write post button.
  3. Type in the subject and body text.
  4. Publish the post.

Analyzing the User Journeys

Let's brainstorm ways to conduct our analysis:

  1. Conversion Rate Analysis:

    • Examine where users typically drop off in the journey.

  2. Time Spent Analysis:

    • Look at how many minutes users spend on each step.

  3. Action Attempt Analysis:

    • Check how many times a user attempts an action across multiple sessions.

  4. Cohort Analysis:

    • Breakdown user behaviors by geographic or demographic segments.

  5. User Surveys and Focus Groups:

    • Directly gather feedback from users on what they are struggling with.

Validating the Analysis

Scenario 1: Specific Step Issues

If a particular step proves problematic:

  1. A/B Testing:

    • Compare multiple versions of the UI.

    Caveats:

    • Avoid if too costly or lacking infrastructure.

  2. Targeted User Surveys:

    • Gather detailed feedback on the specific problematic step.

Scenario 2: Overall UI Issues

If the user flow is generally poor:

  1. User Surveys and Focus Groups:
    • Focus on overall feedback for holistic UI improvements.

Conclusion

To sum up, improving the user interface to boost engagement (likes, comments, shares) involves looking at conversion rates, time spent on steps, action attempts, cohort analysis, and conducting user surveys or focus groups. If a specific step is problematic, consider A/B testing or targeted surveys. For broader issues, user feedback helps drive overall UI improvements.

Keyword

  • User journey analysis
  • Community forum app
  • Data analyst
  • Clarifying questions
  • Conversion rate analysis
  • Time spent analysis
  • Action attempt analysis
  • Cohort analysis
  • User surveys
  • Focus groups
  • A/B testing

FAQ

Q1: What is the purpose of conducting a user journey analysis?

A1: The purpose is to understand how users interact with the app, identify steps where they face difficulties, and make data-driven improvements to enhance user experience and engagement.

Q2: What types of data are crucial for this analysis?

A2: Key data include user IDs, session IDs, timestamps of various interactions (viewing, liking, commenting, sharing), and potentially demographic information for cohort analysis.

Q3: How can conversion rate analysis assist in improving UI?

A3: Conversion rate analysis can pinpoint steps where users drop off, indicating potential UI issues that need refinement to create a smoother user journey.

Q4: When is A/B testing not advisable?

A4: A/B testing is not advisable when it is too costly, the timeline is tight, there's insufficient engineering infrastructure, or the user base is too small for meaningful results.

Q5: What alternative methods can be used if A/B testing isn't feasible?

A5: User surveys and focus groups are effective alternatives, enabling direct feedback from users to identify and resolve UI problems.

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