Dailyhunt Business Analyst Interview Guide

Getting ready for a Business Analyst interview at Dailyhunt? The Dailyhunt Business Analyst interview process typically spans 5–7 question topics and evaluates skills in areas like data analytics, business problem solving, stakeholder communication, and designing actionable dashboards. Interview preparation is especially important for this role at Dailyhunt, as candidates are expected to demonstrate a strong ability to extract insights from diverse datasets, recommend data-driven solutions for product and business challenges, and communicate findings clearly to technical and non-technical audiences in a dynamic digital media environment.

In preparing for the interview, you should:

• Understand the core skills necessary for Business Analyst positions at Dailyhunt.
• Gain insights into Dailyhunt’s Business Analyst interview structure and process.
• Practice real Dailyhunt Business Analyst interview questions to sharpen your performance.

At Interview Query, we regularly analyze interview experience data shared by candidates. This guide uses that data to provide an overview of the Dailyhunt Business Analyst interview process, along with sample questions and preparation tips tailored to help you succeed.

Dailyhunt is India’s leading local language content discovery platform, offering news and information in 14+ Indian languages to millions of users nationwide. The company aggregates content from diverse sources, including publishers and media partners, to provide personalized news feeds and updates on current events, entertainment, and more. Dailyhunt’s mission is to democratize access to information and empower users by delivering relevant content in their preferred language. As a Business Analyst, you will help optimize user engagement and support data-driven decision-making to further Dailyhunt’s goal of connecting India through accessible digital content.

As a Business Analyst at Dailyhunt, you are responsible for leveraging data to drive strategic decisions that enhance user engagement and business growth. You will work closely with cross-functional teams, including product, marketing, and engineering, to analyze trends, identify opportunities, and recommend actionable solutions. Core tasks include gathering and interpreting data, creating reports and dashboards, and presenting insights to stakeholders. Your role is crucial in optimizing content strategies, improving operational efficiency, and supporting Dailyhunt’s mission to deliver personalized news and content experiences to its users.

2.1 Stage 1: Application & Resume Review

The process begins with a thorough screening of your application and resume, typically conducted by the HR team and business analytics hiring manager. The focus here is on your experience with data analysis, business intelligence, SQL proficiency, and your ability to interpret metrics and drive actionable insights. Expect your background in data-driven decision-making, dashboard creation, and campaign analysis to be closely evaluated. To prepare, ensure your resume clearly highlights relevant skills, successful analytics projects, and quantifiable business impact.

2.2 Stage 2: Recruiter Screen

Next, you’ll have an initial conversation with a recruiter, usually lasting 20–30 minutes. This step assesses your motivation for joining Dailyhunt, your understanding of the business analyst role, and your general fit with the company culture. You may be asked about your interest in content platforms, your ability to communicate complex data insights to non-technical stakeholders, and your alignment with the company’s mission. Prepare by researching Dailyhunt’s business model and articulating your passion for leveraging data to support business growth.

2.3 Stage 3: Technical/Case/Skills Round

This stage is typically conducted by a senior analyst or analytics lead and may include one or two rounds. You’ll be tested on your technical skills in SQL, data modeling, and business analytics, as well as your ability to solve case studies and analyze real-world business scenarios. Expect exercises on designing dashboards, evaluating campaign effectiveness, running A/B tests, and interpreting user behavior data. You may be asked to write queries, design data pipelines, or discuss how you’d measure the impact of a product feature or marketing initiative. Preparation should focus on hands-on practice with SQL, data visualization tools, and structuring business cases.

2.4 Stage 4: Behavioral Interview

A business leader or cross-functional manager will conduct this round, which evaluates your soft skills, teamwork, and adaptability. You’ll discuss past experiences collaborating with product, marketing, and engineering teams, overcoming challenges in data projects, and presenting actionable insights to diverse audiences. Emphasis is placed on your communication style, stakeholder management, and ability to make data accessible for decision-makers. Prepare by reflecting on situations where you drove business outcomes through analytics and navigated ambiguity in fast-paced environments.

2.5 Stage 5: Final/Onsite Round

The final stage often consists of a series of interviews with senior leadership, analytics directors, and potential team members. This round may include a mix of technical, business strategy, and behavioral questions, as well as a presentation exercise where you interpret complex data and recommend business actions. You’ll be expected to demonstrate your ability to synthesize multiple data sources, design metrics dashboards, and communicate insights clearly to executives. Preparation should include reviewing recent business analyst projects, practicing concise storytelling with data, and anticipating strategic questions relevant to Dailyhunt’s content platform and user engagement.

2.6 Stage 6: Offer & Negotiation

Upon successful completion of all rounds, HR and the hiring manager will discuss the offer details, including compensation, benefits, and role expectations. This step may involve negotiation around salary, joining date, and potential career growth opportunities within Dailyhunt. Prepare by researching industry benchmarks and clarifying your priorities for the role.

2.7 Average Timeline

The Dailyhunt Business Analyst interview process generally spans 2–4 weeks from application to offer, with each stage typically taking a few days to a week. Fast-track candidates, especially those with strong business analytics backgrounds or relevant industry experience, may complete the process in as little as 10–14 days. Standard timelines allow for flexibility in scheduling technical rounds and onsite interviews, depending on candidate and team availability.

Moving forward, let’s break down the specific types of interview questions you’ll encounter at each stage.

3.1 Product and Campaign Analytics

Business analysts at Dailyhunt are often tasked with evaluating product features, marketing campaigns, and user outreach strategies. You should be able to define success metrics, design experiments, and interpret results to guide business decisions. Expect questions that test your ability to measure impact, optimize campaigns, and communicate recommendations.

3.1.1 You work as a data scientist for ride-sharing company. An executive asks how you would evaluate whether a 50% rider discount promotion is a good or bad idea? How would you implement it? What metrics would you track?
Approach this by outlining an experimental design (such as A/B testing), specifying key metrics like conversion rate, retention, and revenue impact, and explaining how you would monitor for unintended consequences.
Example: “I’d set up a randomized control trial, track metrics including incremental rides, total revenue, and customer retention, and compare the test group to a baseline. I’d also analyze cohort behavior post-promotion to ensure long-term value.”

3.1.2 Every week, there has been about a 10% increase in search clicks for some event. How would you evaluate whether the advertising needs to improve?
Discuss how you would analyze click-through rates, conversion metrics, and attribution models to assess campaign efficiency.
Example: “I’d review weekly conversion rates relative to ad spend, segment users by engagement, and run regression analyses to determine if increased clicks translate to actual growth or just noise.”

3.1.3 How would you measure the success of an email campaign?
Focus on defining clear KPIs such as open rate, click-through rate, conversion, and ROI, and describe how you’d set up tracking and reporting.
Example: “I’d measure open and click rates, analyze conversion funnels, and compare campaign performance to historical benchmarks. I’d also segment responses to identify which user groups are most engaged.”

3.1.4 How do we evaluate how each campaign is delivering and by what heuristic do we surface promos that need attention?
Explain your approach to campaign performance analysis, including the use of heuristics and prioritization frameworks.
Example: “I’d set up dashboards with campaign KPIs, use anomaly detection to flag underperformers, and prioritize promos needing attention based on ROI and engagement metrics.”

3.1.5 What strategies could we try to implement to increase the outreach connection rate through analyzing this dataset?
Describe how you’d use data segmentation, behavioral analysis, and experimentation to improve outreach effectiveness.
Example: “I’d analyze connection rates by user segment, test personalized messaging, and run iterative experiments to optimize timing and content.”

3.2 Data Modeling and Experiment Design

This category covers your ability to design and interpret experiments, model business processes, and leverage data for strategic decisions. Be ready to discuss A/B testing, cohort analysis, and market sizing techniques.

3.2.1 Assessing the market potential and then use A/B testing to measure its effectiveness against user behavior
Lay out how you’d size the market, design experiments, and interpret user response data to guide feature launches.
Example: “I’d estimate market size using available data, run A/B tests on new features, and compare user engagement and conversion metrics between test and control groups.”

3.2.2 How do we go about selecting the best 10,000 customers for the pre-launch?
Discuss criteria for user selection, such as engagement, demographics, and predictive modeling, and how you’d ensure a representative sample.
Example: “I’d score users on activity and relevance, use stratified sampling to ensure diversity, and validate the selection against historical outcomes.”

3.2.3 How to model merchant acquisition in a new market?
Describe your approach to forecasting acquisition, using historical data, segmentation, and predictive analytics.
Example: “I’d model acquisition using logistic regression, segment merchants by region, and simulate various onboarding strategies to estimate market penetration.”

3.2.4 How would you approach sizing the market, segmenting users, identifying competitors, and building a marketing plan for a new smart fitness tracker?
Explain your structured approach to market analysis, user segmentation, and competitive research.
Example: “I’d estimate total addressable market, cluster users by behavior, analyze competitor positioning, and design a data-driven marketing plan.”

3.2.5 *We're interested in determining if a data scientist who switches jobs more often ends up getting promoted to a manager role faster than a data scientist that stays at one job for longer. *
Talk through your analytical approach—cohort analysis, survival modeling, and controlling for confounding factors.
Example: “I’d build cohorts by job-switch frequency, use Kaplan-Meier curves to estimate promotion timelines, and adjust for experience and company size.”

3.3 Data Pipeline, SQL, and Dashboarding

Expect questions assessing your ability to design scalable data pipelines, write efficient SQL queries, and build actionable dashboards for business users. Highlight your experience with automation and data quality management.

3.3.1 Design a solution to store and query raw data from Kafka on a daily basis.
Describe your approach to ingesting, storing, and querying large-scale event data, focusing on scalability and reliability.
Example: “I’d set up a Kafka consumer to ingest data into a distributed warehouse, partition by date, and design queries for daily analytics.”

3.3.2 Design a data pipeline for hourly user analytics.
Explain how you’d automate data collection, aggregation, and reporting for near real-time insights.
Example: “I’d build ETL jobs to process hourly user events, aggregate metrics, and update dashboards with fresh data.”

3.3.3 Design a dashboard that provides personalized insights, sales forecasts, and inventory recommendations for shop owners based on their transaction history, seasonal trends, and customer behavior.
Discuss how you’d architect dashboards to deliver actionable insights, using predictive models and user segmentation.
Example: “I’d integrate transactional and behavioral data, build forecasting models, and design intuitive dashboards with custom recommendations.”

3.3.4 Write a SQL query to calculate the 3-day rolling weighted average for new daily users.
Outline your use of window functions, handling missing dates, and weighting logic in SQL queries.
Example: “I’d use window functions to calculate rolling averages, join with date tables for completeness, and apply weight factors as needed.”

3.3.5 Write a query to calculate the 3-day weighted moving average of product sales.
Describe your SQL approach to calculating moving averages, ensuring accuracy and performance.
Example: “I’d partition sales data by product, use window functions for rolling sums, and apply weights to compute averages.”

3.4 Data Quality, Integration, and Reporting

Business analysts must ensure data reliability, resolve inconsistencies, and synthesize insights from multiple sources. Be ready to discuss your strategies for cleaning, integrating, and reporting on complex datasets.

3.4.1 You’re tasked with analyzing data from multiple sources, such as payment transactions, user behavior, and fraud detection logs. How would you approach solving a data analytics problem involving these diverse datasets? What steps would you take to clean, combine, and extract meaningful insights that could improve the system's performance?
Explain your data profiling, cleaning, integration, and synthesis process, emphasizing reproducibility and transparency.
Example: “I’d profile each dataset for quality, standardize formats, join on common keys, and run exploratory analysis to surface actionable insights.”

3.4.2 How would you approach improving the quality of airline data?
Discuss your approach to identifying data quality issues, implementing validation checks, and automating remediation.
Example: “I’d audit data for missing values and outliers, set up automated quality checks, and collaborate with source teams to resolve recurring issues.”

3.4.3 Calculate daily sales of each product since last restocking.
Describe your query design for tracking inventory and sales, using cumulative sums and event markers.
Example: “I’d use SQL to partition sales by product, reset counters at restocking events, and aggregate daily totals.”

3.4.4 Find all advertisers who reported revenue over $40
Explain your filtering and aggregation logic to identify top performers in a dataset.
Example: “I’d group advertiser data by revenue, filter for those exceeding the threshold, and present the results in ranked order.”

3.4.5 What metrics would you use to determine the value of each marketing channel?
Discuss your approach to multi-channel attribution, ROI analysis, and reporting.
Example: “I’d track conversion, cost-per-acquisition, and lifetime value by channel, and use attribution modeling to evaluate impact.”

3.5 Behavioral Questions

3.5.1 Tell me about a time you used data to make a decision.
Describe a situation where your analysis directly influenced a business outcome, emphasizing the impact and how you communicated insights.

3.5.2 Describe a challenging data project and how you handled it.
Share details about the obstacles you faced, your problem-solving approach, and the results achieved.

3.5.3 How do you handle unclear requirements or ambiguity?
Explain your process for clarifying objectives, engaging stakeholders, and iterating on solutions when details are missing.

3.5.4 Tell me about a time when your colleagues didn’t agree with your approach. What did you do to bring them into the conversation and address their concerns?
Highlight your communication and collaboration skills, showing how you built consensus and incorporated feedback.

3.5.5 Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?
Discuss strategies for simplifying complex topics, adapting your message, and building trust with non-technical audiences.

3.5.6 Describe a situation where two source systems reported different values for the same metric. How did you decide which one to trust?
Outline your investigation process, validation steps, and how you ensured data integrity.

3.5.7 How do you prioritize multiple deadlines? Additionally, how do you stay organized when you have multiple deadlines?
Share your prioritization framework, time management strategies, and tools you use to keep projects on track.

3.5.8 Tell me about a time you delivered critical insights even though 30% of the dataset had nulls. What analytical trade-offs did you make?
Describe your approach to handling missing data, the methods you used, and how you communicated uncertainty.

3.5.9 Give an example of automating recurrent data-quality checks so the same dirty-data crisis doesn’t happen again.
Discuss the tools and processes you implemented to prevent future issues and improve efficiency.

3.5.10 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Explain how you built a compelling case, presented evidence, and persuaded decision-makers.

4.1 Company-specific tips:

Get to know Dailyhunt’s mission, vision, and the unique value it brings as India’s leading local language content platform. Understand how Dailyhunt aggregates and personalizes news and content in over 14 Indian languages, and how this focus on localization shapes user engagement and business strategy.

Familiarize yourself with the digital media landscape in India, including key competitors and trends in content consumption. Pay attention to how mobile-first, regional language strategies drive user growth and retention in the Indian market.

Study recent product launches, partnerships, and marketing campaigns by Dailyhunt. Be ready to discuss how data analytics can help optimize these initiatives, measure campaign effectiveness, and inform future decisions.

Reflect on Dailyhunt’s user base—millions of diverse users across geographies and languages. Think about the challenges and opportunities this diversity presents for business analysis, such as segmentation, personalization, and measuring engagement across different cohorts.

Prepare to articulate why you are passionate about Dailyhunt’s mission to democratize information and how your analytical skills can help the company deliver relevant, accessible content to every user.

4.2 Role-specific tips:

Showcase your expertise in designing and interpreting A/B tests, especially for evaluating product features, marketing campaigns, and user outreach strategies. Practice explaining how you would structure experiments, define control and test groups, and select success metrics like conversion rate, retention, and incremental revenue.

Be comfortable with SQL and data modeling. Prepare to write queries that involve calculating rolling averages, aggregating user behavior data, and joining multiple tables for comprehensive business analysis. Demonstrate your ability to handle missing data, optimize query performance, and ensure data integrity.

Emphasize your ability to build actionable dashboards that provide clear, business-focused insights. Discuss your approach to selecting key performance indicators (KPIs), designing intuitive visualizations, and ensuring dashboards are tailored to the needs of both technical and non-technical stakeholders.

Practice structuring business cases and communicating recommendations clearly. Use frameworks to break down complex problems, segment user groups, and prioritize initiatives based on business impact. Be ready to walk through real-world scenarios where your analysis drove measurable results.

Highlight your experience integrating and cleaning data from diverse sources—such as user behavior logs, campaign data, and transaction records. Be ready to describe your process for resolving inconsistencies, standardizing formats, and extracting actionable insights from messy datasets.

Demonstrate strong stakeholder management and communication skills. Prepare examples of how you’ve translated complex data into simple, actionable recommendations for product, marketing, or leadership teams. Show that you can adapt your messaging for different audiences and build consensus around data-driven decisions.

Prepare for behavioral questions by reflecting on past experiences where you navigated ambiguity, handled conflicting data, or influenced decisions without formal authority. Think about how you prioritized deadlines, managed multiple projects, and automated routine data quality checks to improve efficiency.

Finally, bring a growth mindset and a passion for learning. Show that you are eager to stay on top of industry trends, experiment with new analytical techniques, and continuously improve both your technical and business acumen to help Dailyhunt succeed.

5.1 “How hard is the Dailyhunt Business Analyst interview?”
The Dailyhunt Business Analyst interview is considered moderately challenging, especially for candidates who may not have prior experience in digital media or content platforms. The process tests your technical proficiency in SQL, data analytics, and dashboarding, as well as your ability to solve real-world business problems, communicate with diverse stakeholders, and design actionable insights. Success depends on your readiness to work with large, diverse datasets and your ability to translate data into strategic recommendations in a fast-paced environment.

5.2 “How many interview rounds does Dailyhunt have for Business Analyst?”
You can expect 4 to 5 rounds in the Dailyhunt Business Analyst interview process. These typically include an application and resume review, a recruiter screen, technical/case/skills rounds, a behavioral interview, and a final onsite or virtual round with leadership and cross-functional team members. Each stage is designed to evaluate a different aspect of your technical, analytical, and communication skills.

5.3 “Does Dailyhunt ask for take-home assignments for Business Analyst?”
Yes, it is common for Dailyhunt to include a take-home assignment or case study as part of the technical or case/skills round. These assignments usually involve analyzing a business scenario, designing dashboards, or solving a data problem relevant to Dailyhunt’s business. The goal is to assess your ability to extract insights from raw data, structure your analysis, and present actionable recommendations.

5.4 “What skills are required for the Dailyhunt Business Analyst?”
Key skills for a Dailyhunt Business Analyst include strong SQL and data modeling abilities, proficiency in data visualization and dashboarding, experience with A/B testing and experiment design, and a knack for interpreting business metrics. You should also have excellent communication and stakeholder management skills, the ability to synthesize insights from diverse datasets, and a passion for digital media and user engagement analytics.

5.5 “How long does the Dailyhunt Business Analyst hiring process take?”
The hiring process for a Business Analyst at Dailyhunt typically takes between 2 to 4 weeks from application to offer. Fast-track candidates may complete the process in as little as 10 to 14 days, depending on availability and scheduling. Each interview stage generally takes a few days to a week, with some flexibility for technical rounds and final interviews.

5.6 “What types of questions are asked in the Dailyhunt Business Analyst interview?”
You’ll encounter a mix of technical, analytical, and behavioral questions. Technical questions often focus on SQL queries, data modeling, dashboard design, and experiment analysis. Analytical questions center on product and campaign analytics, business case structuring, and interpreting user engagement data. Behavioral questions explore your experiences collaborating with teams, communicating insights, handling ambiguity, and influencing decisions without formal authority.

5.7 “Does Dailyhunt give feedback after the Business Analyst interview?”
Dailyhunt typically provides feedback through the recruiter or HR contact after your interview rounds. While high-level feedback is common, detailed technical feedback may be limited. If you reach the later stages, you’re more likely to receive constructive input on your performance and areas for improvement.

5.8 “What is the acceptance rate for Dailyhunt Business Analyst applicants?”
The acceptance rate for the Dailyhunt Business Analyst role is competitive, with an estimated 3–5% of applicants receiving offers. The process favors candidates with strong analytical backgrounds, relevant industry experience, and a clear passion for digital content platforms.

5.9 “Does Dailyhunt hire remote Business Analyst positions?”
Yes, Dailyhunt does offer remote opportunities for Business Analysts, especially for roles involving cross-functional collaboration and data analytics. Some positions may require occasional visits to the office for team meetings or project kick-offs, but remote and hybrid arrangements are increasingly common.

• Related guides:
  • Dailyhunt interview questions
  • Business Analyst interview guide
  • Top SQL Business Analyst interview tips
  • What Is a Business Analyst? Career Path, Salary & Key Skills in 2025

Ready to ace your Dailyhunt Business Analyst interview? It’s not just about knowing the technical skills—you need to think like a Dailyhunt Business Analyst, solve problems under pressure, and connect your expertise to real business impact. That’s where Interview Query comes in with company-specific learning paths, mock interviews, and curated question banks tailored toward roles at Dailyhunt and similar companies.

With resources like the Dailyhunt Business Analyst Interview Guide and our latest case study practice sets, you’ll get access to real interview questions, detailed walkthroughs, and coaching support designed to boost both your technical skills and domain intuition.

Take the next step—explore more case study questions, try mock interviews, and browse targeted prep materials on Interview Query. Bookmark this guide or share it with peers prepping for similar roles. It could be the difference between applying and offering. You’ve got this!