Hi everyone, this topic is for sharing Preparation guidelines and interview experience for Kantar Analyst
The Analyst at Kantar involves a multi-stage assessment and interview process, designed to evaluate both technical skills and business proficiency. Below is a summary of the process and key points from the interviews you provided:
Assessment Test Rounds:
Round 1: Aptitude Test (as experienced in one process)
Discussion on current experience, projects, and business management knowledge.
Conceptual questions on regression (MLR, multicollinearity, ridge, logistic) and basics from R, Python, and Excel (lookups, pivot tables).
May include a few riddles/logic questions.
Technical Round (Fundamentals)
Basic analytics concepts such as “What is data analytics?” and “What is data blending?”
Case Study Round
Domain: Marketing research and advertising.
Expectation: Structure the problem, analyze data/context, derive insights, and present actionable recommendations.
HR Round
Topics: Salary expectations, expectations from the role, and location preferences.
Technical/Analytics Concepts
What is data analytics?
What is data blending?
Explain multiple linear regression.
What is multicollinearity and how do you detect and handle it?
What is ridge regression and when would you use it?
Explain logistic regression.
Programming/Tools (R, Python, Excel)
In Excel, how do you perform lookups (e.g., VLOOKUP/XLOOKUP/INDEX-MATCH)?
How do you create and use Pivot Tables in Excel?
In R/Python, how would you implement regression models?
In R/Python, how do you prepare and manipulate data for analysis?
Business/Management Concepts
What business management concepts are you familiar with, and how do they apply to analytics work?
Experience/Project Discussion
Walk me through your current experience and key projects.
Situational/Case Study (Marketing Research & Advertising)
Solve a case study in the marketing research/advertising domain: define objectives, structure your approach, derive insights, and provide actionable recommendations.
Aptitude/General Knowledge
Questions on USA geography and demographic facts.
Puzzles/Riddles/Logical Reasoning
Riddle or logic-based questions to assess problem solving.
HR/Personality/Behavioral
What are your salary expectations?
What are your expectations from the job role?
Do you have any location preferences?
Interview Preparation Tips
Brush up on basic data analytics concepts and terminology (including data blending).
Revise regression topics thoroughly: multiple linear regression, multicollinearity (detection and remedies), ridge regression, logistic regression.
Practice R/Python fundamentals and be ready to discuss how you implement and evaluate models.
Strengthen Excel skills, especially lookups (VLOOKUP/XLOOKUP/INDEX-MATCH) and Pivot Tables.
Prepare for an aptitude segment on USA geography and demographics.
Be ready to walk through your projects and articulate impact and business context clearly.
Practice structuring case studies in marketing research and advertising; focus on insights and recommendations.
Work on communication and confidence; present answers clearly and concisely.
Research Kantar and the Analyst role to align your responses.
Prepare a well-researched salary range and be clear about location flexibility.
If you have attended the process from your campus, pls share your experiences here; Please follow guidelines
Application Process: Applied via LinkedIn and was interviewed in April 2024.
Interview Rounds:
Round 1 - Aptitude Test:
Questions Asked: USA geography demographics.
Your Approach: Prepared by reviewing basic geography and demographic data related to the USA.
Outcome: Passed the round.
Round 2 - One-on-One Round:
Questions Asked: Questions about current experience and business management knowledge.
Your Approach: Highlighted relevant experience and demonstrated understanding of business management concepts.
Outcome: Successfully cleared the round.
Preparation Tips:
Focus on basic geography and demographic knowledge, especially for the USA.
Brush up on business management concepts and be ready to discuss your experience in detail.
Conclusion:
The interview process was straightforward, with a mix of aptitude and knowledge-based questions. Being well-prepared in the mentioned areas helped me clear the rounds smoothly. For future candidates, I’d recommend thorough preparation on the topics mentioned and practicing clear communication during the one-on-one round.
Application Process: I applied via the company website and was interviewed before August 2020.
Interview Rounds:
Round 1 - HR Interview:
Questions Asked:
Tell me about yourself.
Share a movie story.
Your Approach: I kept my introduction concise and focused on my relevant skills and experiences. For the movie story, I chose a film I was passionate about and narrated its plot in an engaging way.
Outcome: I passed this round.
Preparation Tips:
Don’t get into this shit. (Note: This seems to be a candid remark from the candidate.)
Conclusion:
The interview was straightforward, but the candidate’s final remark suggests dissatisfaction with the process or role. Future candidates should research the company thoroughly and align their expectations before applying.
Application Process: I applied via a referral and was interviewed before October 2022.
Interview Rounds:
Round 1 - Resume Shortlist:
Questions Asked: N/A (Resume-based shortlisting)
Your Approach: Ensured my resume was crisp and highlighted relevant skills and experiences.
Outcome: Successfully shortlisted for the next round.
Round 2 - Technical Round:
Questions Asked:
Tell me about your analytical skills.
Prepare SQL, Python, Power BI, and whatever is mentioned in your resume.
Your Approach: Focused on demonstrating my analytical skills with examples and ensured I was well-prepared for technical questions related to SQL, Python, and Power BI.
Outcome: Awaiting feedback.
Preparation Tips:
Keep your resume concise and tailored to the role.
Brush up on technical skills like SQL, Python, and Power BI if mentioned in your resume.
Conclusion:
The interview process was smooth, and the questions were aligned with the job requirements. Make sure to thoroughly prepare for technical rounds and present your skills clearly. All the best to future candidates!
Application Process: I applied via a referral and was interviewed before April 2023.
Interview Rounds:
Round 1 - One-on-one Round:
Questions Asked:
Questions regarding my projects.
Questions about multiple linear regression, multicollinearity, ridge regression, and logistic regression.
Technical questions from R, Python, and Excel (e.g., lookup, pivot table).
There might be some riddle questions as well.
Your Approach: I focused on explaining my projects clearly and brushed up on regression concepts beforehand. For technical questions, I relied on my hands-on experience with R, Python, and Excel.
Outcome: Passed this round.
Round 2 - Case Study Round:
Questions Asked: The case study revolved around marketing research and advertisement companies.
Your Approach: I structured my analysis logically, focusing on key insights and actionable recommendations.
Outcome: Successfully cleared this round.
Round 3 - HR Round:
Questions Asked:
Expected salary and expectations from the job role.
Your Approach: I was honest about my salary expectations and aligned my career goals with the role.
Outcome: Cleared the HR round.
Preparation Tips:
Have a strong grasp of regression concepts (multiple linear regression, multicollinearity, ridge regression, logistic regression).
Be confident and work on your communication skills.
Practice technical questions related to R, Python, and Excel.
Conclusion:
Overall, the interview process was thorough but fair. Being well-prepared technically and having clear communication helped me succeed. For future candidates, I’d recommend focusing on both technical and soft skills, as both are equally important for this role.
Application Process: Applied through an online job portal.
Interview Rounds:
Round 1 - Situational Judgment Test:
Questions Asked: Situational questions where I had to arrange tasks in priority order.
Your Approach: I carefully analyzed each scenario, considered the urgency and impact of each task, and prioritized them accordingly.
Outcome: Passed this round and moved to the next stage.
Preparation Tips:
Maintain eye contact during the interview.
Avoid saying “I don’t know”—try to frame your response even if you’re unsure.
Conclusion:
The interview was a good learning experience. I realized the importance of staying composed and thinking logically under pressure. For future candidates, I’d recommend practicing situational judgment tests and working on communication skills.
Application Process: [Application process details not provided]
Interview Rounds:
Round 1 - Technical Round:
Questions Asked:
Estimate the number of kgs of paneer used in Bangalore every day.
Easy to medium SQL queries.
Your Approach:
For the guesstimate question, I broke down the problem by estimating Bangalore’s population, the percentage of people who consume paneer, and the average consumption per person.
For the SQL queries, I ensured I understood the problem statement clearly before writing the queries and double-checked for syntax errors.
Outcome: [Outcome not provided]
Preparation Tips:
Prepare well for guesstimates and SQL.
Be thorough with whatever you have mentioned in your resume.
Application Process: The application process involved submitting an online application followed by two interview rounds: a technical round and an HR round.
Interview Rounds:
Round 1 - Technical Round:
Questions Asked:
What is data analytics?
What is blending?
Your Approach:
For the first question, I explained data analytics as the process of examining datasets to draw conclusions and identify patterns. For the second question, I described blending as the technique of combining data from multiple sources to create a unified dataset for analysis.
Outcome: I successfully passed this round and moved on to the HR round.
Round 2 - HR Round:
Questions Asked:
What are your salary expectations?
Do you have any location preferences?
Your Approach:
For the salary question, I provided a range based on industry standards and my research. For the location question, I expressed flexibility while mentioning my preference for the current location.
Outcome: The HR round went smoothly, and I received positive feedback.
Preparation Tips:
Brush up on basic data analytics concepts and terminology.
Research the company and role to align your answers with their expectations.
Practice answering common HR questions to build confidence.
Conclusion:
The interview process was straightforward and well-structured. I felt prepared for both rounds, but I could have researched more about Kantar’s specific projects to tailor my answers better. My advice for future candidates is to focus on clarity and confidence in your responses, especially in the technical round.