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To improve ROI of a marketing channel, focus on targeting the right audience, optimizing ad creatives, analyzing data regularly, and testing different strategies.
Target the right audience based on demographics, interests, and behavior
Optimize ad creatives for better engagement and conversion rates
Analyze data regularly to identify trends, patterns, and areas for improvement
Test different strategies such as A/B tes...
The effectiveness of a campaign is analyzed by measuring key performance indicators (KPIs) and conducting A/B testing.
Identify and track relevant KPIs such as conversion rate, click-through rate, return on investment (ROI), and customer acquisition cost.
Compare the campaign results to benchmarks and historical data to assess performance.
Conduct A/B testing to test different variables such as messaging, visuals, an...
Preventive measures for regression assumptions not met
Check for multicollinearity among independent variables
Transform variables if they are not normally distributed
Consider using non-parametric regression methods
Use robust regression techniques to handle outliers
Collect more data to improve model performance
Time series analysis components include trend, seasonality, cyclicality, and irregularity.
Trend: Long-term movement or direction of the data.
Seasonality: Regular patterns that occur at specific intervals.
Cyclicality: Repeating patterns that are not necessarily at fixed intervals.
Irregularity: Random fluctuations or noise in the data.
Examples: Trend in stock prices, seasonality in retail sales, cyclicality in econo...
Handling missing values is crucial in data analysis. Various techniques like imputation, deletion, or prediction can be used.
Use imputation techniques like mean, median, mode to fill in missing values.
Consider using predictive modeling to estimate missing values based on other variables.
Delete rows or columns with a high percentage of missing values if they cannot be accurately imputed.
Use advanced techniques like...
Outliers can be detected using statistical methods like Z-score, IQR, or visualization techniques like box plots.
Calculate Z-score for each data point and identify points with Z-score greater than a certain threshold (usually 3 or -3).
Use Interquartile Range (IQR) to identify outliers by determining data points that fall below Q1 - 1.5 * IQR or above Q3 + 1.5 * IQR.
Visualize the data using box plots and identify p...
Tuple is immutable and fixed in size, while list is mutable and can change in size.
Tuple is created using parentheses, while list is created using square brackets.
Tuple elements can be of different data types, while list elements are usually of the same data type.
Tuple is faster than list for iteration and accessing elements.
Example: tuple = (1, 'a', True), list = [1, 2, 3]
To sell a product, you need to understand the customer's needs, highlight the product's benefits, and create a sense of urgency.
Identify the customer's needs and pain points
Highlight the unique features and benefits of the product
Create a sense of urgency or scarcity
Provide social proof and testimonials
Offer incentives or discounts
Use persuasive language and storytelling
Address objections and offer solutions
Follow...
Regression is a statistical technique used to understand the relationship between a dependent variable and one or more independent variables. Multicollinearity occurs when independent variables in a regression model are highly correlated.
Regression helps in predicting the value of the dependent variable based on the values of independent variables.
Multicollinearity can lead to issues in interpreting the coefficien...
Multicollinearity is a phenomenon in which two or more predictor variables in a regression model are highly correlated.
Multicollinearity can lead to unstable estimates of the coefficients and make it difficult to determine the effect of each predictor variable on the outcome.
One way to tackle multicollinearity is to identify the highly correlated variables and consider removing one of them from the model.
Another a...
I appeared for an interview in Jan 2025.
Market research is the process of gathering, analyzing, and interpreting information about a market to make informed business decisions.
Market research helps businesses understand their target audience and competitors
It involves collecting data on consumer preferences, trends, and buying habits
The purpose is to identify opportunities, minimize risks, and optimize marketing strategies
Examples include surveys, focus grou...
Ipsos provides market research and consulting services to help clients understand consumer behavior and trends.
Market research
Consulting services
Consumer behavior analysis
Trend analysis
Mystery shopping is a market research technique where individuals pose as regular customers to evaluate the quality of products and services.
Mystery shoppers are hired by companies to assess customer service, product quality, and overall customer experience.
They visit stores, restaurants, or other businesses anonymously and provide detailed feedback on their interactions.
The goal of mystery shopping is to identify area...
Proficient in Microsoft Office suite with experience in creating presentations, reports, and spreadsheets.
Proficient in Microsoft Word for creating documents and reports
Skilled in Microsoft Excel for data analysis and creating spreadsheets
Experienced in Microsoft PowerPoint for creating presentations
Familiar with Microsoft Outlook for email communication and scheduling
I appeared for an interview in Jan 2025, where I was asked the following questions.
I appeared for an interview in Jan 2025.
I have 5 years of experience in analyzing large datasets to extract valuable insights and make data-driven decisions.
Analyzed customer behavior data to optimize marketing strategies
Built predictive models to forecast sales trends
Utilized machine learning algorithms to improve product recommendations
Presented findings to stakeholders in a clear and actionable manner
Questions related to work experience in data science field.
Asked about previous projects worked on
Inquired about specific data analysis techniques used
Discussed challenges faced and how they were overcome
I applied via Referral and was interviewed in Oct 2024. There were 2 interview rounds.
Evaluate machine learning model by analyzing metrics like accuracy, precision, recall, F1 score, ROC curve, and confusion matrix.
Calculate accuracy to measure overall performance of the model.
Use precision to evaluate the proportion of true positive predictions among all positive predictions.
Consider recall to assess the proportion of true positive predictions among all actual positives.
Calculate F1 score as a balance ...
I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.
Normal 10 Mcq questions
Advantages and disadvantages of GenAl
A subquery is a query nested within another SQL query, used to retrieve data based on the results of the outer query.
Subqueries can be used in SELECT, INSERT, UPDATE, or DELETE statements.
Example: SELECT * FROM employees WHERE department_id IN (SELECT id FROM departments WHERE location = 'New York');
Subqueries can return single or multiple values.
They can be correlated (dependent on the outer query) or non-correlated (...
posted on 25 Jul 2025
I appeared for an interview before Jul 2024, where I was asked the following questions.
Reversing a string involves printing characters from the end to the start, with the last index printed first.
To reverse 'hello', start from index 4 (last character 'o') and end at index 0 (first character 'h').
The reversed string of 'hello' is 'olleh'.
In Python, you can reverse a string using slicing: 'hello'[::-1] results in 'olleh'.
In Java, you can use StringBuilder: new StringBuilder('hello').reverse().toString() gi...
This SQL query retrieves three specific columns for individuals aged between 30 and 40.
Use the SELECT statement to specify the three columns you want to retrieve.
Utilize the WHERE clause to filter records based on the age range.
Example: SELECT name, age, email FROM users WHERE age BETWEEN 30 AND 40;
I applied via Referral and was interviewed in Aug 2024. There were 2 interview rounds.
Basic aptitude questions
I applied via Approached by Company and was interviewed in Apr 2024. There was 1 interview round.
I appeared for an interview in Nov 2024, where I was asked the following questions.
I am a passionate research intern with a background in biology and a keen interest in data analysis and scientific discovery.
Currently pursuing a degree in Biology with a focus on molecular genetics.
Completed a summer internship at XYZ Lab, where I assisted in research on gene editing techniques.
Skilled in data analysis using Python and R, with experience in statistical modeling.
Participated in a collaborative project ...
I want to join Ipsos to contribute to impactful research that drives decision-making and enhances understanding of consumer behavior.
Ipsos is a global leader in market research, providing insights that shape strategies for businesses.
I admire Ipsos' commitment to innovation, such as using advanced analytics and technology to gather data.
The opportunity to work with diverse teams and clients across various industries ex...
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The duration of Ipsos interview process can vary, but typically it takes about less than 2 weeks to complete.
based on 48 interview experiences
Difficulty level
Duration
Research Executive
158
salaries
| ₹5.9 L/yr - ₹10.2 L/yr |
Analyst
152
salaries
| ₹5.6 L/yr - ₹9.4 L/yr |
Senior Research Executive
125
salaries
| ₹8 L/yr - ₹14 L/yr |
Senior Analyst
87
salaries
| ₹7.5 L/yr - ₹12 L/yr |
Data Analyst
87
salaries
| ₹4 L/yr - ₹9 L/yr |
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