A Marketing Analytics Specialist at Chewy plays a vital role in accelerating customer acquisition, maximizing customer lifetime value, and optimizing millions of dollars in marketing spend. Operating at the intersection of data science, digital marketing, and business strategy, this role is responsible for translating complex datasets into actionable insights that directly influence campaign performance. Whether you are working on paid media channels, organic search, or within the rapidly growing Chewy Ads team, your work directly impacts how millions of pet parents interact with the brand.

At Chewy, data is not just used to generate retrospective reports; it is the foundation of every strategic decision. As a Marketing Analytics Specialist, you will design measurement frameworks, build performance dashboards, and conduct deep-dive analyses to evaluate the efficiency of channels like Paid Social, Search, and B2B marketing. The scale of Chewy's operations requires analytical professionals who can handle high-volume transactional data while maintaining a sharp focus on the pet-centric customer experience.

This position offers a unique opportunity to shape the future of pet e-commerce. You will collaborate closely with marketing managers, product teams, and data engineers to build robust attribution models and run A/B tests that define the next generation of Chewy's marketing initiatives. It is a fast-paced, highly competitive, and intellectually stimulating environment where high analytical rigor is balanced by a shared passion for pets and innovation.

To succeed in the Chewy interview process, you must be prepared for a blend of technical, strategic, and behavioral questions. Interviewers want to see how you handle real-world marketing challenges, manipulate data, and collaborate across teams. The following questions are representative of what candidates face during the loop, based on real interview experiences.

Marketing & Domain Analytics

This category tests your understanding of core digital marketing channels, performance metrics, and analytical methodologies used to measure campaign success.

• How would you measure the incremental lift of a Paid Social campaign on Chewy?
• What key metrics would you track to evaluate the performance of a newly launched B2B marketing campaign?

Preparing for an interview at Chewy requires a balanced approach. You need to demonstrate sharp technical skills alongside a highly collaborative, proactive mindset. Successful candidates approach their preparation by aligning their technical experience with Chewy's customer-obsessed culture.

Role-Related Knowledge – You must have a strong command of SQL, data visualization tools, and digital marketing platforms. Be prepared to discuss how you write queries to extract user behavior data and how you transform raw metrics into clean, actionable dashboards.

Problem-Solving Ability – Chewy values candidates who do not just run reports but actively solve business problems. When presented with a case study or a hypothetical scenario, focus on structuring your thoughts logically, stating your assumptions clearly, and explaining the "why" behind your analytical approach.

Leadership & Communication – Analytical insights are only valuable if they lead to action. You need to prove that you can act as a strategic partner to marketing teams, translating data jargon into clear business recommendations that stakeholders can easily understand.

Culture Fit & Adaptability – The pet e-commerce space moves incredibly fast. Show that you are comfortable with ambiguity, open to feedback, and driven by a genuine passion for delivering exceptional experiences to pet parents and their pets.

The interview process for a Marketing Analytics Specialist at Chewy is designed to evaluate both your analytical depth and your behavioral alignment with the company's core operating principles. While the process is highly thorough, candidates often report that the experience can vary significantly depending on the recruiting team and the specific office location.

The process typically begins with an initial screening call with a Talent Acquisition representative. This conversation is conversational and casual, focusing on your background, career goals, and general alignment with the role. If you pass this stage, you will move on to hiring manager interviews and a technical assessment, which may include a deep dive into your SQL capabilities, case study discussions, or a presentation of your past marketing analytics projects. The final stages involve meeting with senior leadership and cross-functional stakeholders to evaluate your communication style and cultural fit.

The timeline above outlines the standard progression from your initial application to the final decision. Candidates should use this blueprint to pace their preparation, ensuring they focus heavily on core technical skills in the early stages before transitioning to strategic case studies and behavioral preparation for the final rounds. Keep in mind that turnaround times can vary, so maintaining proactive communication with your recruiter is key.

To stand out in the Chewy interview loop, you must demonstrate mastery in several core competency areas. Interviewers will drill down into these specific domains to ensure you can handle the complexity of their marketing data.

Marketing Attribution & Media Mix Modeling

Understanding how different marketing channels interact and drive conversions is critical for this role. You will be evaluated on your ability to measure channel efficiency and optimize media spend.

Be ready to go over:

• Attribution Frameworks – The pros and cons of rule-based vs. algorithmic attribution models in an e-commerce context.
• Media Mix Modeling (MMM) – How to use historical data to estimate the impact of various marketing tactics on sales.
• Incrementality Testing – Designing lift tests and matched-market tests to measure the true causal impact of ad spend.

Example scenarios:

• "How would you design a test to prove that our YouTube video ads are driving incremental purchases rather than just claiming credit for organic conversions?"
• "Explain how you would handle data discrepancies between Google Analytics and an ad platform like Meta Ads Manager."

Behavioral Performance (The STAR Method)

Chewy places a massive emphasis on how you work. You will face behavioral questions designed to test your resilience, teamwork, and execution.

Be ready to go over:

• The STAR Framework – Structuring your answers with a clear Situation, Task, Action, and measurable Result.
• Handling Ambiguity – Demonstrating how you make decisions and drive projects forward when data or requirements are unclear.
• Customer Obsession – Showing how your analytical decisions ultimately benefit the end consumer (the pet parent).

Example scenarios:

• "Tell me about a time you identified a data tracking error that impacted historical marketing reports. How did you resolve it and communicate the issue to leadership?"
• "Describe a situation where you had to prioritize multiple urgent analytical requests from different marketing teams."

Stakeholder Management & Communication

As a specialist, you will sit between technical data teams and creative marketing teams. Your ability to bridge this gap is a major evaluation factor.

Be ready to go over:

• Data Storytelling – Translating dashboard metrics into a compelling narrative that drives strategic action.
• Cross-Functional Collaboration – Working with product managers, engineers, and external agencies to align on goals.
• Influencing Without Authority – Using data-driven insights to guide marketing strategy even when you are not the decision-maker.

Advanced concepts (less common):

• Designing automated alerting systems for marketing anomalies.
• Integrating offline marketing efforts (like direct mail) with digital attribution models.

On a day-to-day basis, a Marketing Analytics Specialist at Chewy is responsible for turning raw marketing data into strategic growth. You will spend your time querying large databases to extract customer behavior trends, building and maintaining performance dashboards, and collaborating directly with channel managers to optimize campaigns.

You will play a major role in defining key performance indicators (KPIs) for channels like Paid Social, Search, and the Chewy Ads platform. This includes analyzing metrics such as click-through rates (CTR), conversion rates, return on ad spend (ROAS), and customer retention. Your insights will directly influence weekly and monthly budget reallocations, ensuring that Chewy's marketing dollars are spent as efficiently as possible.

Additionally, you will partner with data science and engineering teams to improve data infrastructure and tracking capabilities. Whether it is ensuring proper pixel implementation, refining attribution models, or building automated reporting pipelines, you will help maintain the integrity of the data that powers Chewy's marketing engine.

To be competitive for this role at Chewy, candidates must possess a strong blend of technical expertise, marketing knowledge, and communication skills.

• Technical Skills – Proficiency in SQL is highly critical; you must be comfortable writing complex queries, joins, and aggregations. Experience with data visualization tools (such as Tableau, PowerBI, or Looker) and web analytics platforms (like Google Analytics or Adobe Analytics) is required.
• Experience Level – Typically, 3+ years of professional experience in marketing analytics, business intelligence, or a highly analytical role in e-commerce or retail is expected.
• Soft Skills – Strong stakeholder management skills, a proactive problem-solving mindset, and the ability to articulate technical findings to non-technical partners.

Must-have qualifications:

• Strong SQL proficiency for data extraction and manipulation.
• Experience analyzing digital marketing campaigns (Paid Social, Search, programmatic, or email).
• Proven track record of using data to drive business growth or cost savings.

Nice-to-have qualifications:

• Experience with Python or R for statistical analysis and data modeling.
• Understanding of advanced attribution modeling or media mix modeling.
• Prior experience working in a fast-paced e-commerce or marketplace environment.