Top 22 Meta (Facebook) Business Analyst Interview Questions + Guide in 2024

Considering Facebook’s impressive earnings in 2023 and outlook for 2024, we can continue to expect exciting business developments and, therefore, more challenges for their business analysts to solve. Meta’s business analysts are sharp thinkers and pro communicators and solve complex problems using business intelligence, metric development, and tools such as SQL and Tableau.

Interview Query regularly analyzes interview experience data, which we’ve used to produce this guide. We’ve picked 20+ popular Meta (Facebook) business analyst interview questions and provided an overview of the interview stages, along with our top tips and resources to help you crack that job.

Business analysts at Meta analyze data to develop different insights that drive product business decisions, answering questions such as “How do we make the product better?” and “What do users like about the product?”

Facebook has a strong data culture, and business analysts use this data to inform and drive business decisions. Roles will differ by team, but the general expectation is that analysts should extract insights through data analysis, metric development, and business intelligence solutions.

The interview emphasizes skills with tools like Power BI, Tableau, and SQL, alongside effective communication and problem-solving, assessed through behavioral questions. You may also be asked questions on program and project management.

If you’re feeling stuck, read this article by Meta, where their employees provide some quick tips to get started.

Step 1: Recruiter Screening

A 15-minute phone interview with a recruiter will be scheduled to get a sense of your work experience and skillsets. Don’t underestimate this step, as prospective Meta business analysts are often asked a couple of high-level case study questions in this round. They may also ask you why you want to join Facebook or ask CV-based questions, so prepare some responses to help you sail through this important step.

Tip: Once you pass this stage, ask your recruiter for pointers on the next steps and if they have resources to guide you. They’ll likely be more than happy to help you prepare for the next stages.

Step 2: Technical Phone Screen

Next, you’ll have one or two 45-minute technical rounds where you’ll be given SQL, business intelligence, Excel, and analysis case questions to solve. Some typical analysis case questions are: “How would you improve [X] product or feature?” or “Would you recommend that we double our ads on Instagram?” For the coding questions, you’ll be asked to write your code in a Google or Word document.

Even though this round is more high-level than the following ones, be detailed in your answers and avoid missing any edge cases.

Step 3: Panel Interview

In this final step, you’ll be invited on-site to meet a panel of interviewers who will likely be managers from different teams. The panel will ask you a mix of case study and behavioral questions. This round is more team-specific and will assess your cultural fit. This will be a fun and engaging round, with lots of opportunities to brainstorm with your interviewers and demonstrate how well you think on the go.

Let’s examine the top questions asked by Meta in their analyst interviews. Try to solve the questions on your own before looking at the solutions. Remember that the interviewer will gauge how well you handle open-ended questions and how creative and articulate you are at thinking through these problems while solving them. It’s not about arriving at the perfect answer but how you engage with the problem.

It’s helpful to spend time using Meta products from the mindset of someone tasked with improving them. Follow the STAR framework for behavioral questions and research Facebook’s core values and mission.

1. Walk me through your resume.

Your response will help your interviewer gauge how well you can present yourself and whether you can tell a compelling story about yourself. It’ll also give them an overview of your key achievements.

How to Answer

Talk about your previous roles and projects in a way that relates to the position at hand, particularly those involving data analysis, project management, and cross-functional collaboration. Be concise, and don’t forget to highlight outcomes.

Resource: Here is a detailed guide to the behavioral questions analysts are often asked, with a tried-and-tested framework for solving them.

Example

“I hold a bachelor’s in information systems, which laid the foundation for my data analysis and business process modeling skills. My first role was as a junior analyst at Company [A], where I helped maintain performance dashboards to support data-driven decision-making. After two years there, I moved to Company [B], where I worked as a business analyst, leading projects that involved data integration for business intelligence solutions. One project I’m particularly proud of is when our team optimized our data collection process and reduced errors by 30%. As a result, we saved around thirty work hours per week.”

2. Why do you want to join Facebook?

Understanding why you want to join will help your interviewer determine if your values and aspirations align with Meta’s mission.

How to Answer

Your answer should reflect your understanding of Facebook’s work, culture, and the opportunities that attract you to the company. Be honest and specific about how their offerings align with your career goals.

Example

“I want to join Facebook because I am passionate about using data to solve meaningful problems that can impact millions of people worldwide. Facebook’s mission to give people the power to build community aligns with my values. I see a unique opportunity to leverage my analytical skills to help enhance product features, to make a tangible difference in how people access and use information.”

3. How have you used data to inform a decision?

This question tests whether you have practical experience leveraging analytics to influence business outcomes, as this is the crux of the analyst role.

How to Answer

Describe a relevant scenario following the STAR framework. Make your answer as business-focused as possible, where data is simply a tool you use to drive a business decision. If it was a team effort, specify your role in the process.

Example

“In my previous company, our product manager asked us if expanding a particular product line was profitable. I conducted an ad hoc analysis to explore customer purchase data and market trends to identify high-demand products. I used SQL for data querying and Tableau for visualization to present my findings. My analysis suggested a significant market opportunity for eco-friendly products, which were trending positively among our core demographic. Based on my recommendation, the company launched a new line of eco-friendly products, which resulted in a 20% boost in sales within the first six months.”

4. Tell me about a conflict you’ve had with a co-worker.

This question checks your emotional intelligence and conflict resolution skills—critical to being a good team player.

How to Answer

Describe a conflict in which you played a role in finding a mutually beneficial outcome. Highlight what you learned from the experience, showing you are flexible and have a growth mindset.

Example

“I once had a conflict with a co-worker over prioritizing project features. To resolve it, I set up a one-on-one to discuss our viewpoints and come to an agreement. We decided to consult other team members and gather more user data to make an informed decision. This experience helped me appreciate the importance of empathy and flexibility in teamwork.”

5. Could you give us an instance where you had to explain complex data findings to a non-technical audience?

At Meta, business analysts are expected to collaborate with diverse teams and stakeholders. Being able to communicate effectively is non-negotiable.

How to Answer

It’s important to highlight your emotional intelligence here as well. Show that you held a dialogue that invited questions and respected diverse perspectives.

Example

“In my previous role, I was once tasked with analyzing seasonal sales data to optimize our inventory for the upcoming season. The data included variables like purchasing trends, customer demographics, and regional sales performance. To communicate these findings to our marketing and sales teams, I distilled the information into key insights and actionable recommendations. I avoided technical jargon and created interesting visuals in Tableau to illustrate the most important trends. I held a Q&A session at the end of the presentation and even included feedback from the team in our findings. As a result, our targeted marketing strategy led to a 10% increase in sales in the following season.”

6. Given a table of account statuses, write a query to get the percentage of accounts active on December 31, 2019, and closed on January 1, 2020, over the total number of active accounts on December 31. Assume that each account has only one daily record indicating its status at the end of the day.

This tests your ability to understand complex data queries while testing your SQL coding skills.

How to Answer

Explain your approach to structuring an optimized SQL query, and mention which functions you would use.

Example

“I’d first create a subset of data by identifying all active accounts on December 31, 2019. Then, I’d filter out accounts from this subset that were closed on January 1, 2020, before calculating the percentage. I’d use the COUNT() function on both subsets to count the relevant accounts and then divide the count of accounts closed on January 1 by the count of active accounts on December 31. The key is to ensure that data is accurately filtered by date and status in each step.”

7. Tell me about a project you’ve managed. What metrics did you use to determine its success?

You have to make sure that the projects you are responsible for are completed in a way that supports Meta’s business goals. This involves first principles thinking and designing frameworks and metrics to benchmark success.

How to Answer

While defining success metrics, consider the project and the organization’s goals. Discuss how you used these benchmarks to make necessary adjustments in the project.

Example

“I led a project to improve the user interface of our e-commerce platform. As our primary goal was to boost sales, we defined several key metrics, including customer satisfaction scores gathered through post-interaction surveys, the conversion rate measured by completed purchases relative to site visits, and average session duration as an indicator of user engagement. We used a combination of Google Analytics for real-time data monitoring and weekly customer feedback sessions to gather insights. We were able to quantify an increase in session duration and conversion rates after implementing simplified navigation, which confirmed the project’s success.”

8. Let’s say you are managing products for an e-commerce store. You think products from a particular category have a lower average price than those in all other categories. Calculate the t-value and degrees of freedom for such a test.

Skills like hypothesis testing and basic statistical analysis are required as you will need to statistically validate assumptions about data to make informed decisions.

How to Answer

Explain the method for calculating the t-value. Discuss the steps to determine sample means, variance, and sample sizes for both groups. Mention the assumptions you’d make, like normality and equal variance.

Example

“I’d first calculate the mean prices for both the category in question and all other categories. Then, I would use the formula for the t-test statistic, which compares the difference between the two means relative to the variability of the prices, scaled by the sample size. The degrees of freedom for this test would be the sum of the two sample sizes minus two. This allows us to understand if the observed difference in means is statistically significant or due to random chance.”

9. What are some key considerations when designing dashboards for different stakeholders (e.g., executives vs operational managers)?

Meta is all about quick decision-making and pivoting based on data-driven decisions and experimentation. Dashboards need to be tailored to this need, so you’ll have to design them by keeping the end user in mind at all times.

How to Answer

Talk about the importance of understanding different stakeholders’ specific information needs and decision-making processes. Highlight how you would customize the complexity of data and the level of detail accordingly.

Example

“If I were to present to an executive, I’d focus on high-level, strategic insights that directly align with the organization’s goals. This means using concise visualizations like KPI metrics, trend graphs, and summary tables that provide a quick snapshot of performance. For operational managers, who need more granular data to manage daily operations, I’d include detailed data views, such as drill-down capabilities and time-series analyses.”

10. Given a table with event logs, find the top five users with the longest continuous streak of visiting the platform.

Analyzing user activity is crucial for understanding user retention and engagement, thereby maintaining platform health.

How to Answer

Discuss the solution step-by-step, mentioning which SQL functions you would use, and any edge cases that might be relevant in the business context.

Example

“We’d first want to extract each user’s daily logins, which would mean filtering and sorting the data by user and date. I’d use the LAG() function to compare each login date to the previous one for the same user. If the dates are consecutive, the streak continues; if not, it resets. I would then use a window function to assign a unique streak identifier each time a streak resets and another to calculate the streak length for each identifier. Finally, I would identify the top five users by aggregating these lengths and sorting them in descending order.”

11. How would you set up a forecast model for Facebook’s revenue for the coming year?

This question assesses your knowledge of predictive analytics and forecasting, which is essential for strategic planning at Meta.

How to Answer

Approach these types of questions with the following steps:

1. Ask clarifying questions to define the scope of the problem.
2. Assess requirements to understand the needs and expectations of the stakeholder in question.
3. Provide your solution.
4. Define a framework for monitoring and validating your solution.

Resource: Read our data analytics case study guide to prepare a strategy for tackling these questions.

Example

“I would gather historical revenue data and secondary variables such as ad spending trends, user growth metrics, and economic indicators. Using this data, I would deploy an ARIMA model, which is suitable for capturing trends. I would also consider seasonal patterns observed in past data, and adjust the model to account for expected cyclical variations in advertising spend during major events or holidays. I would validate the model by back-testing it against prior years’ data to measure its accuracy. This should be an iterative process to ensure it remains robust against fluctuations.”

12. We’re given two tables, a table of notification_deliveries and a table of users with created and purchase conversion dates. If the user hasn’t purchased then the conversion date column is NULL. Write a query to get the distribution of total push notifications before a user converts.

This kind of data analysis in SQL will be common in your day-to-day at Facebook. Understanding how user engagement correlates with conversion actions is important for optimizing communication strategies.

How to Answer

Discuss how you’d handle NULL values and potential edge cases, such as users who receive notifications but never convert. Also, mention the importance of ensuring data consistency and completeness when joining and filtering records.

Example

“I’d perform a LEFT JOIN between the users table and the notification_deliveries table on the user ID. This would include all users, capturing those who have not converted. Next, I’d filter the notifications to include only those sent before the conversion date for each user. I’d filter out the NULL values in the conversion date column since they indicate the user hasn’t converted.

The next step would be to count the notifications for each user, grouping them by user ID, and then aggregate this data to get the distribution of notifications across all users. An important consideration would be checking for data quality issues such as duplicate notifications or users with incorrect timestamps, which could skew the analysis.”

13. Explain how you would implement row-level security in Power BI.

Row-level security (RLS) ensures that data access can be limited to specific users or roles, which is essential for maintaining confidentiality.

How to Answer

Describe the process of implementing RLS in Power BI by defining roles and setting up rules that filter data based on user attributes. Also, address the need to test the security rules rigorously to avoid data breaches.

Example

“We’d first need to define which user roles need what level of access. I would set up specific DAX filter expressions for every role to determine which data each role can view based on attributes like department, geographic location, or management level.

Once the roles and rules are defined, I would publish the Power BI report to the Power BI Service, where I’d assign users to their respective roles under the security settings of the dataset.”

14. Let’s say you’re in charge of an e-commerce D2C business that sells socks. What business health metrics would you care about tracking on a company dashboard?

Meta values product sense in its analysts, believing that a business-oriented way of thinking is the first step in helping them achieve their goals.

How to Answer

Emphasize metrics that provide insights into sales performance, customer engagement, and operational efficiency. Explain how you envisage how each metric will impact insights.

We’ve also published a resource on tackling business intelligence interviews, which you can check out here.

Example

“First, I would track sales revenue to measure the business’s financial performance. Customer acquisition cost and return on investment (ROI) are important to gauge the cost-effectiveness of marketing strategies. Customer retention rate would help us assess how well we are maintaining customer relationships, which is vital for long-term revenue.

Additionally, I would monitor the average order value (AOV) to understand purchasing behavior and conversion rate to gauge how user-friendly the website or app is. Lastly, tracking inventory turnover would tell us about the health of our inventory management.”

15. Explain the concept of dual-axis charts in Tableau.

This question checks if you are acquainted with advanced visualization techniques in Tableau, as you might use this tool for BI solutions.

How to Answer

Mention the practical applications of these charts and how they enhance data interpretation.

Example

“Dual-axis charts in Tableau are a visualization tool used to display two scales of two measures in the same graph. This is useful when comparing data with different units or illustrating the relationships between them on a single graph. For example, you might use a dual-axis chart to display both the revenue and the number of items sold on the same timeline, where one axis shows revenue in dollars and the other shows quantity in units.

To create a dual-axis chart in Tableau, you would add one measure to the rows shelf and then add another measure to the rows shelf. From there, you can right-click on the second measure on the rows shelf and select ‘Dual Axis.’ This overlays the two measures on the same graph but with separate y-axes on the left and right.”

16. Determine whether adding a feature identical to Instagram Stories to Facebook is a good idea.

This is a common analysis case question to gauge your understanding of user behavior, market trends, and cross-platform synergies, which are key to Facebook’s strategy of integrating its apps.

How to Answer

The expectations for product sense questions are deliberately kept ambiguous, and this type of problem can be large in scope. Make sure you clarify expectations at the outset. Read our article here if you’re looking for a comprehensive framework for tackling open-ended case study questions.

Example

“I’d look at user engagement data from Instagram to understand why and how users interact with Stories. This includes demographic data to see which user segments are most engaged. I’d then assess Facebook’s current user engagement and compare demographic and behavior overlaps. A/B testing would be critical here: deploying the feature to a small, diverse group of Facebook users could provide initial data on engagement and acceptance. I would monitor metrics such as the increase in daily active users, time spent on the app, and interaction rates with the Stories feature. If the test shows positive results that align with our goals—like increased user engagement and content sharing—this would suggest that implementing Stories on Facebook could complement the success seen on Instagram.”

17. You are provided two tables. One is an attendance log for every student in a school district, and the other is a summary table with demographics for each student in the district. Which grade level had the largest drop in attendance between yesterday and today?

This question tests how well you integrate data, a common requirement for analysts at Meta.

How to Answer

Highlight the importance of joining tables efficiently. Mention using window functions and simple aggregation functions to calculate differences in attendance. Briefly state any assumptions you’re making or any likely data quality issues; this shows you pay attention to detail.

Example

“I would first join the attendance log table with the demographics summary table using a common key, like student ID. I would then filter the attendance records for only the two relevant days. Using the GROUP BY clause, I’d aggregate attendance by grade level for each day and calculate the total attendance. To find the change in attendance, I would subtract yesterday’s attendance from today’s for each grade. The LEAD or LAG functions could be useful here to compare day-to-day changes directly in a single query. Finally, I’d use an ORDER BY clause on the difference to identify the grade with the largest drop.”

18. Our team helps small businesses increase sales through the Marketplace app. How would you determine their customer service quality? Assume you have access to all interactions in the customer chat box.

You can expect many such open-ended problems at your analyst interview, as the interviewers want to test your critical thinking and engagement with ambiguous business cases.

How to Answer

Before solving the problem, ask clarifying questions and set expectations. Detail the methods you’d use to examine customer interactions, such as sentiment analysis and response time metrics.

Example

“I’d look at response times, as shorter ones generally correlate with higher customer satisfaction. I’d also conduct a sentiment analysis on the chats to gauge the tone of customer inquiries and business responses. This analysis would help us identify any recurring pattern, too.

I would also analyze the resolution rate, as this is the main goal of every customer service interaction. By correlating these metrics with customer feedback and satisfaction surveys, we can better understand the perceived quality of customer service.”

19. You want to de-duplicate products from multiple sellers in a large e-commerce database. How would you approach this?

Managing product listings from multiple sellers to avoid duplicates ensures customers have a clear, streamlined browsing and purchasing process, essential for platforms like Meta’s Marketplace.

How to Answer

Discuss methods for comparing product attributes, using algorithms or tools for matching similar items, and establishing a process for confirming duplicates before removal.

Example

“I would start by defining the criteria for what constitutes a duplicate. Typically, this includes matching key product attributes such as name, description, SKU number, and price. I would use SQL queries to filter and sort data based on these attributes to identify duplicates.

If this method isn’t enough, I’d employ fuzzy matching to identify products that are not exactly identical but very similar. This step would help us catch duplicates that might not be caught by exact matching due to minor variations in spelling and other factors.

Once potential duplicates are identified, I would review these matches manually or set up a semi-automated process to validate these findings.”

20. Looking at our weekly metrics, you see a gradual decrease in the average number of comments per user from January to March. Why might the average number of comments per user be decreasing, and what metrics would you look into?

For Meta, gaining a deeper understanding of engagement metrics is crucial for preemptive action to reverse negative trends and improve product health.

How to Answer

Ask clarifying questions, state your assumptions clearly, and cite ways to validate your hypotheses. Watch this video to learn more about how to approach such problems.

Example

“A decrease in the average number of comments could indicate several issues. First, it might suggest changes in the user base, such as an influx of new users who are less active or existing users becoming less engaged over time. To understand this, I would look into metrics like the new user acquisition rate versus user churn and engagement metrics for different user cohorts over time.

Another reason could be changes to the product or its environment, such as a recent update that made commenting less intuitive or necessary. Investigating the adoption and usage rates of recent features, along with user feedback from surveys or support tickets during the same period, could offer insights into product-related causes.

External factors, such as seasonal changes or shifts in work patterns due to holidays or global events, could also impact user engagement. Comparing the trend with the same period in previous years and examining broader industry or global trends might help identify these external influences.

Lastly, it’s crucial to consider the overall user experience and satisfaction, which could be affected by issues like increased bugs or performance problems. Metrics like load time, error rates, and support ticket volumes related to commenting features would be valuable to examine in this context.”

21. Let’s say you work on the growth team at Facebook and are tasked with promoting Instagram from within the Facebook app. Where and how could you promote Instagram through Facebook?

This question assesses your ability to leverage user data and cross-platform synergies to drive growth, a core aspect of Facebook’s strategy for integrating its apps.

How to Answer

Product growth questions often involve hypothesizing and testing various strategies to boost user engagement or acquisition. Begin by clarifying the scope and objectives of the growth initiatives. For a structured approach, consider formulating hypotheses and designing experiments that test these ideas with real user data.

Example

“To promote Instagram from within Facebook, I would first analyze network effects by assessing how friends’ activities influence user behavior. My hypothesis is that notifying users on Facebook when their friends join Instagram will increase Instagram sign-ups. To test this, I would conduct an A/B test with a control group and a test group where the latter receives notifications. I’d measure the sign-up rates for Instagram across both groups to evaluate the effectiveness of this approach. Additionally, integrating Instagram posts into Facebook and tracking engagement metrics could provide further insights. By analyzing user interactions and sign-up rates, we can determine if the exposure on Facebook drives meaningful growth for Instagram.”

22. How would you test whether having more friends now increases the probability that a Facebook member is still an active user after 6 months?

Determining whether having more friends increases the probability that a Facebook member remains active after 6 months involves analyzing user engagement data and employing machine learning techniques to understand the impact of friend count on user retention.

How to Answer

Start by segmenting users based on their friend count from six months ago and track their activity over the following six months to analyze trends. Compare the engagement metrics across these segments to determine if a higher number of friends correlates with increased activity. To refine your analysis, normalize for other variables that could affect engagement, such as initial activity levels and demographics.

Example

“I would begin by categorizing users into groups based on their number of friends six months ago and measure their engagement over the next six months. For each group, I’d calculate the percentage of active users and observe if higher friend counts correlate with increased activity rates. For more precise results, I’d use a supervised machine learning model, such as logistic regression, to analyze the relationship between friend count and the likelihood of being an active user. The model would help us control for other influencing factors by including variables like account age and initial activity levels. By examining the model’s coefficients and probability outputs, we can determine if having more friends significantly impacts the probability of remaining active after six months.”

Here are some tips to help you excel in your Facebook interview.

Tailor Your Resume

Understand the job description clearly and prepare your resume accordingly. The resume screening determines whether you’ll make it to the interview process, so be sure to highlight your work experience and skills in line with what the recruiter wants to see.

Study the Company and Role

Research recent news, updates, Meta values, and business challenges the company is facing. Understanding the company’s culture and strategic goals will allow you to better present yourself and learn if they are a good fit for you.

Facebook has an excellent resource for preparing for product sense case rounds. Take a look at it to understand the frameworks they use.

Further, if you know business analysts, data scientists, or product managers who work at Meta, it’s a good idea to talk to them to understand what will be expected of you. Leverage your LinkedIn network to chat with current or former Meta employees.

Understand the Fundamentals

Brush up on topics like SQL, Power BI/Tableau, program management, and any other tools and technologies specified for the role. Be comfortable with Python libraries commonly used for statistical modeling, although this may not be required for your role. Consider practicing more SQL and general business analyst interview questions. Also, check out and work through our list of SQL interview questions that have been asked in Meta interviews.

If you need additional guidance, we also offer tailored product metrics, SQL, and data analysis learning paths covering core topics and practical applications.

Highlight Your Soft Skills

Meta values communication and critical thinking, so structuring your responses articulately and demonstrating your past professional experiences in an actionable way is paramount to acing your interviews.

To test your current preparedness for the interview process and improve your communication skills, try a mock interview. It is helpful to go through multiple mock interviews for case study rounds.

What is the average salary for a business analyst role at Facebook?

The average base salary for a business analyst at Facebook is $131,795, making the remuneration over 1.5x higher than the average base salary for general BA jobs in the US: $80,835.

What other companies can I apply for besides Meta’s business analyst role?

You can apply to similar roles in other MAANG companies. We have interview guides for Google, Apple, Amazon, and Netflix.

You can read about other firms’ interview processes on our Company Interview Guides page.

Are there job postings for Facebook business analyst roles on Interview Query?

We have one opening listed on our job portal right now, although you can expect more positions to open up later. The portal also allows you to look at similar roles, filtering by location, firm, and seniority level.

Succeeding in Meta business analyst interview questions requires a strong understanding of their products and business, fundamental statistical knowledge, and the ability to creatively apply your technical skills to solve their business challenges.

Understanding Facebook’s experimentation-driven culture and thoroughly preparing with both technical and behavioral questions will be key to success. For other data-related roles at Meta, consider exploring our guides for data analysts, data engineers, ML engineers, data scientists, and other positions in our main Meta interview guide.

Wishing you the best in your journey to landing a fulfilling role at Facebook!