Meesho Case Study Question Dec’21

Meesho Case Study Question

The following question has been asked in the second round of interviews for the Senior Business Analyst at Meesho. The same type of question was asked a couple of years back in Sapient and more companies, and it was published on The Data Monk long back. So, do practice the case study given below.

Topic – Recommendation of food items to a new customer in a restaurant

It was not the exact case study but was very very similar to the one given below

Meesho Case Study Question

Meesho Case Study Question


Punjabi By Nature, a restaurant in Bangalore, delivers and serves food to its customer. It has been in the business for the last 10 years. Recently the owner heard about Data Science and they want to leverage the opportunity in order to boost its revenue. The restaurant has been collecting the following data since the last 10 years:-
1. Name of Customer
2. Sex of Customer
3. Age of Customer
4. Food item code

Your job is to recommend 2 food items to a customer new to the restaurant. Answer the following questions:-

a. Looking at the data, provide 3 findings for the restaurant to boost their performance

Proposed Solution.

i. Food item combination can help you recommend a particular item. For example, if people prefer curd with Parathas, then you can recommend it
ii. A list of the most popular food item
iii. Looking at the customer’s age and sex you can decide what to offer to a new customer. If the data suggests that a girl in the age group 20-25 likes chocolate ice cream then you can recommend this ice cream to the new girl customer 

b. Think of 4 more data points that might help you with the analysis

Proposed Solution

i. Pincode of delivery
ii. Time of order
iii. Phone Number
iv. Date and Day of service 

c. Now, what else can you find out from this data?

Proposed Solution

i. Day of service can get you the popular food item on each day and weekend
ii. Pincode can help you identify if there is a demand for some specific food items in a particular area
iii. The phone number to inform about new offers
iv. Time of order can get you the time at which the restaurant should shoot a particular offer for a specific food item

Please attempt the question below and we will evaluate each solution.

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Understand these E-commerce metrics before applying

What is this blog about?

In this blog, e-commerce metrics, we will try to understand different things which are asked in a company that focuses on their website or application conversion. Web analytics is a way to understand the sentiments of your online users, why they are buying what they are buying and what they are not buying because by the end everything boils down to a user buying something on the internet.

So, in the blog “Metrics to know before applying to e-commerce companies” we will try to solve a few things for you that will make you comfortable when you apply to some of these companies

Target companies?

With this blog, you will be able to come up with a strong candidature in companies like Myntra, Amazon, Flipkart, OYO rooms, Facebook, Linkedin, etc.

e-commerce metrics
e-commerce metrics



So if you are already in the analytics domain or are looking forward to applying to one such company in the coming months, then do give a read to this blog.

What is the need of knowing these metrics?

When you apply to any of the e-commerce companies then there is an unsaid expectation that you should be aware of the things tracked, apart from that it’s always good to talk in the same lingua as used by your interviewer. Also, you will easily get some brownie points by explaining these points in the technical as well as case study rounds. These are the most important things to know after your technical expertise. Go prepared 🙂

Do I need any prior experience?

You are reading this blog on an online mode which means that you are well aware of the internet and that you know you are a visitor on this page. As long as you are comfortable with these points you do not need any other experience.

P.S. – We will also have a detailed video with live examples where you can understand concepts in a better way, if the link is not provided here, do check it out on our youtube channel i.e. The Data Monk

E-commerce metrics

Visitor – If you are reading this article then you are a visitor to our website

Unique Visitor – If you visit our website 30 times today then also you are only one unique visitor

Visits – Now you have made 30 visits to the website

Repeat visitor – Suppose The Data Monk defines the logic that a visit span is 30 days. If you come two times in the last 30 days then you are a repeat visitor

Return visitor – Suppose you came last time in Oct’21 and it’s currently Jan’22 then you are a return visitor

Views – number of times you visit a particular page is the number of views. Even if you refresh the webpage then also the number of views will increase

Session – If the admin of the website had defined a session to be of 30 minutes then accordingly a session id will be generated. Ex. you start at 11:00 in the morning and surf for 10 minutes, then come back at 4 in the evening, then a new session id will be generated for you

Bounce – If you close the website on the first page itself then it is termed as a bounce, though you will still be a visitor and your number of views will be 1

Click-Through Rate – The click-through rate refers to the percentage of people who click through a certain link compared to the total number of people who saw the link. For example, if 1,000 people see a Google ad and 10 of them click on that ad, that ad has a click-through rate of 1 percent. You should aim for a click-through rate on your Google Ads of about 3-5 percent

Impression – Number of times your advertisement or web link is shown to the customer on the online space. For example, when you google something then you get some sponsored links, you may get around 4-5 images at the top. It does. not matter if you click on these images or not, but there are impressions of these products. Suppose this same page is shown to 1000 people and only 10 people clicked on the one which is priced at Rs. 21900, then the CTR for the product id 1% with 1000 impressions and 10 clicks

Load Time – Load time refers to the amount of time it takes a page to appear when a user lands on it. About 30 percent of users will leave a website whose pages take longer than 3 seconds to load, so that number should be your benchmark. Optimize slower loading pages to maximize their speed.

Time on Page – Time spent by users on a particular page.

Session Time – What is the average time for which a user explores your website or app

Conversion – If you are selling a product then what is the conversion i.e. number of people entering the buy flow and the number of people actually buying something on the web portal.



What type of questions are asked in an interview (mostly in the case study round)?

You will b asked something like, “Think of the important metrics which you need to track for the CXOs to give them a glimpse of their daily business” or “What all the KPIs in an online market”

Now, once you know these 14-15 metrics then you are already 2 steps ahead of an unprepared candidate plus you have a lot of time to think of other derived metrics like a customer flow diagram, Customer Life Time Value (CLTV), the Failure rate of the final conversion page, etc.


Now you can start explaining things like:-

-Tracking the performance of the payment page

-What is the average bucket size of a customer

-Coupon code success rate

-Customer Life Time Value


If you have some more metrics which can be used to explain a fresher or beginner then do comment below.
Hope you liked the content of e-commerce metrics.

We will have the next blog on Customer Churn Analysis which is one of the most standard projects done in every e-commerce company and is very useful to understand before you appear for an interview

The Data Monk services

We are well known for our interview books and have 70+ e-book across Amazon and The Data Monk e-shop page . Following are best-seller combo packs and services that we are providing as of now

  1. YouTube channel covering all the interview-related important topics in SQL, Python, MS Excel, Machine Learning Algorithm, Statistics, and Direct Interview Questions
    Link – The Data Monk Youtube Channel
  2. Website – ~2000 completed solved Interview questions in SQL, Python, ML, and Case Study
    Link – The Data Monk website
  3. E-book shop – We have 70+ e-books available on our website and 3 bundles covering 2000+ solved interview questions. Do check it out
    Link – The Data E-shop Page
  4. Instagram Page – It covers only Most asked Questions and concepts (100+ posts). We have 100+ most asked interview topics explained in simple terms
    Link – The Data Monk Instagram page
  5. Mock Interviews/Career Guidance/Mentorship/Resume Making
    Book a slot on Top Mate

The Data Monk e-books

We know that each domain requires a different type of preparation, so we have divided our books in the same way:

1. 2200 Interview Questions to become Full Stack Analytics Professional – 2200 Most Asked Interview Questions
2.Data Scientist and Machine Learning Engineer -> 23 e-books covering all the ML Algorithms Interview Questions
3. 30 Days Analytics Course – Most Asked Interview Questions from 30 crucial topics

You can check out all the other e-books on our e-shop page – Do not miss it


For any information related to courses or e-books, please send an email to nitinkamal132@gmail.com