Evercommerce, a leading international provider of software solutions for the service economy, has made waves in the tech industry with cutting-edge technology and tailor-made solutions. As a Growth Marketing Analyst at Evercommerce, you'll delve into data to optimize marketing campaigns, drive user acquisition, and fuel company growth. This role demands strong analytical abilities, hands-on experience with marketing tools, and a deep understanding of data-driven strategies.

If you're aiming to join Evercommerce, our guide will prepare you for the interview journey. We’ll outline the interview process, typical questions, and essential tips to boost your preparation and confidence. Dive in with Interview Query to optimize your chances!

Submitting Your Application

The first step in your journey to become a Growth Marketing Analyst at Evercommerce is to submit a compelling application that showcases your technical skills and enthusiasm for the role. Whether you were contacted by an Evercommerce recruiter or applied on your own, you should carefully review the job description and tailor your CV and cover letter to meet the specific requirements.

Tailoring your CV includes using specific keywords that resonate with the hiring manager, highlighting key competencies, and emphasizing relevant work experiences.

Recruiter/Hiring Manager Call Screening

If your application gets shortlisted, you will receive a call from a recruiter from the Evercommerce Talent Acquisition Team. During this call, they will validate your experiences and skillset. You may also encounter some behavioral questions.

In some cases, the hiring manager might join the screening call to answer questions about the role and discuss your experience in more detail. This call generally takes about 30 minutes.

Technical Virtual Interview

Once you pass the recruiter screening, you will be invited for a technical virtual interview. This interview is usually conducted via video conferencing tools and may last for about an hour. The focus will be on your technical abilities, including data analysis, SQL queries, and your familiarity with marketing analytics.

You may also be asked to work on take-home assignments involving product metrics, data visualization, and analytical techniques pertinent to Evercommerce’s business environment.

Onsite Interview Rounds

If you succeed in the virtual interview, you will be invited to the onsite interview rounds. Typically, these involve multiple interview sessions assessing various competencies, including technical skills, problem-solving abilities, and cultural fit.

For the Growth Marketing Analyst role, expect to present any take-home assignments you were given. These presentations are an opportunity to showcase your analytical thinking and how your work aligns with Evercommerce’s goals.

Quick Tips For Evercommerce Growth Marketing Analyst Interviews

• Know the Market: Evercommerce operates in a fast-paced, ever-changing market. Familiarize yourself with their existing marketing strategies and think about how you can add value.
• Be Data-Driven: The role heavily relies on data analytics. Brush up on your quantitative skills and make sure you're comfortable with data visualization tools.
• Prepare Behavioral Examples: Evercommerce values candidates who can demonstrate their cultural fit. Practice your responses to behavioral questions to align them with the company's core values.

Typically, interviews at Evercommerce vary by role and team, but commonly Growth Marketing Analyst interviews follow a fairly standardized process across these question topics.

• Write a SQL query to select the 2nd highest salary in the engineering department. Write a SQL query to select the 2nd highest salary in the engineering department. If more than one person shares the highest salary, the query should select the next highest salary.

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list. Bonus: What's the time complexity?

• Write a function missing_number to find the missing number in an array. You have an array of integers, nums of length n spanning 0 to n with one missing. Write a function missing_number that returns the missing number in the array. Complexity of \(O(n)\) required.

• Write a function precision_recall to calculate precision and recall metrics from a 2-D matrix. Given a 2-D matrix P of predicted values and actual values, write a function precision_recall to calculate precision and recall metrics. Return the ordered pair (precision, recall).

• Write a function to search for a target value in a rotated sorted array. Suppose an array sorted in ascending order is rotated at some pivot unknown to you beforehand. You are given a target value to search. If the value is in the array, then return its index; otherwise, return -1. Bonus: Your algorithm's runtime complexity should be in the order of \(O(\log n)\).

• Would you suspect anything unusual about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Would you consider this result suspicious?

• How would you set up an A/B test for button color and position changes? A team wants to A/B test changes in a sign-up funnel, such as changing a button from red to blue and/or moving it from the top to the bottom of the page. How would you design this test?

• What steps would you take if friend requests on Facebook are down 10%? A product manager at Facebook reports a 10% decrease in friend requests. What actions would you take to investigate and address this issue?

• Why might job applications be decreasing while job postings remain constant? You observe that the number of job postings per day has remained stable, but the number of applicants has been steadily decreasing. What could be the reasons for this trend?

• What are the drawbacks of the given student test score datasets, and how would you reformat them? You have data on student test scores in two different layouts. What are the drawbacks of these formats, and what changes would you make to improve their usefulness for analysis? Additionally, describe common issues found in "messy" datasets.

• Is this a fair coin? You flip a coin 10 times, and it comes up tails 8 times and heads twice. Determine if the coin is fair based on this outcome.

• Write a function to calculate sample variance from a list of integers. Create a function that outputs the sample variance given a list of integers. Round the result to 2 decimal places. Example: Input: test_list = [6, 7, 3, 9, 10, 15] Output: get_variance(test_list) -> 13.89

• Is there anything fishy about the A/B test results with 20 variants? Your manager ran an A/B test with 20 different variants and found one significant result. Evaluate if there is anything suspicious about these results.

• How to find the median in a list with more than 50% of the same integer in O(1) time and space? Given a list of sorted integers where more than 50% of the list is the same repeating integer, write a function to return the median value in (O(1)) computational time and space. Example: Input: li = [1,2,2] Output: median(li) -> 2

• What are the drawbacks of the given student test score data layouts? You have data on student test scores in two different layouts. Identify the drawbacks of these layouts, suggest formatting changes for better analysis, and describe common problems in "messy" datasets.

• How would you evaluate the suitability and performance of a decision tree model for predicting loan repayment? You are tasked with building a decision tree model to predict if a borrower will repay a personal loan. How would you evaluate whether a decision tree is the correct model for this problem? If you proceed with the decision tree, how would you evaluate its performance before and after deployment?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which a random forest generates its forest. Additionally, discuss why you might choose random forest over other algorithms like logistic regression.

• When would you use a bagging algorithm versus a boosting algorithm? You are comparing two machine learning algorithms. In which scenarios would you use a bagging algorithm versus a boosting algorithm? Provide examples of the tradeoffs between the two.

• How would you justify using a neural network model and explain its predictions to non-technical stakeholders? Your manager asks you to build a neural network model to solve a business problem. How would you justify the complexity of this model and explain its predictions to non-technical stakeholders?

• What metrics would you use to track the accuracy and validity of a spam classifier for emails? You are tasked with building a spam classifier for emails and have completed a V1 of the model. What metrics would you use to track the accuracy and validity of the model?

Embarking on a journey with Evercommerce as a Growth Marketing Analyst promises an exciting career filled with opportunities for professional development and impact. To gain deeper insights into the company, explore our comprehensive Evercommerce Interview Guide, where we've covered various interview questions you might encounter. Additionally, check out interview guides for other roles such as software engineer and data analyst to get a broader understanding of Evercommerce's interview processes.

At Interview Query, we equip you with the knowledge and confidence needed to excel in your interviews with tools, insights, and strategic guidance tailored for success. Dive into all our company interview guides for comprehensive preparation. Should you have any queries, feel free to reach out to us.

Good luck with your interview and your journey with Evercommerce!