Company and Industry Research Before a Data Analyst Interview: What You Actually Need to Know

Preparing for a data analyst interview requires more than practicing SQL and technical questions. You should understand how the company makes money, its core products, the industry it operates in, the KPIs that define success, and how those pieces connect to potential business problems you may be asked to analyze.

Beyond everything you're about to read in this article, I think one of the most important things in a world where AI is taking over more and more tasks is simply to become really good at what you do.

Do the research. Learn the business. Show the interviewers that you're not just another candidate.

That's the starting point.

Why does company research matter specifically for a data analyst interview?

Being an analyst is a little different from many other professions, and I'll explain what I mean.

Take an electrical engineer, for example.

They went to university and studied electrical engineering for four years. What do they understand now? Electrical engineering.

Where are they most likely to get their first job? Probably somewhere related to electrical engineering. That's what they studied, and that's the field they understand.

Analysts are different.

You don't really study to become an analyst of one specific business. You enter an industry, start learning how that industry works, and combine that knowledge with the theoretical and technical skills you've already developed.

Take an analyst working at a credit card company.

Did they get a degree in credit cards? Take a credit card course? Write a seminar about the credit card industry?

Probably not.

They joined the company, started learning the things that specifically matter in that industry, and gradually became capable of creating value for the business.

After spending enough time there, they could absolutely move to another industry. But at the beginning, they would probably create less value than they did in the credit card company, simply because they don't understand the new business as well yet.

So what am I trying to say here?

As an analyst interviewing for a role, one of your biggest advantages is showing that you have the potential to start creating value relatively quickly.

If you're interviewing at an insurance company and you have incredible technical skills, build fantastic presentations, and your dashboards could win the World Dashboard Championship - but you don't know what a premium is, you're going to have a very hard time impressing the interviewer.

Part A – Know the Company

How does the company actually make money?

This is one of the core questions you should be able to answer before walking into an interview.

And sometimes the answer looks much simpler than it actually is.

Let's take a classic example everyone knows: Amazon.

You could say:

"Amazon makes money by selling products online."

That's not technically wrong.

But it's far too shallow for a candidate who wants to show that they actually researched the company.

A little research would show you that Amazon sells products directly to consumers, but it also earns fees from third-party sellers, sells cloud services through AWS, charges customers for Prime subscriptions, and has several other revenue streams.

And each of those businesses can have completely different metrics behind it.

Without understanding that, you could potentially miss major parts of the business, and that's not something you want happening during an interview.

What are its core products and services?

Once you understand how the company makes money, the next step is understanding what it actually offers its customers.

The goal isn't to memorize a list of every product or service the company has.

You want to understand the main ones well enough that, if needed, you could explain what they do, what problem they solve, and which people or companies actually use them.

Let's continue with Amazon.

Knowing that AWS is Amazon's cloud platform is already a good start.

But you want to stand out, so spend a little more time understanding what that actually means.

If you understand that AWS allows companies to use infrastructure and technology services such as storage and databases without having to build and manage all of that infrastructure themselves, you're already showing a much better understanding than someone who simply says:

"AWS."

And stops there.

How much detail should you know about the company?

This is important.

In the example above, I used Amazon, one of the largest companies in the world, with a huge range of businesses and an almost endless amount of information available online.

Researching Amazon is relatively easy because the information is everywhere.

But you won't always interview at companies like Amazon.

You might interview at an early-stage startup, a smaller local company, or a business that simply doesn't have much public information available.

Interviewers at those companies aren't going to expect you to magically know information that doesn't exist publicly.

But you should still do your best with what you have.

Start with the company's website and extract anything useful you can find: what the company does, examples of how people use the product, the services it provides, and the business activities it talks about.

As a junior analyst, I'd even jump into the company's careers page.

Open job descriptions can sometimes tell you much more about a company than you'd expect - what teams exist, what they're working on, what technologies they use, and sometimes even which business problems they're trying to solve.

Then go outside the company's website.

Look for articles, interviews, funding announcements, founder interviews, or other mentions of the company online.

For smaller companies, I think the best approach is usually a combination of what the company chooses to tell you about itself + what you can learn from external sources.

And when information isn't easy to find, doing this research becomes even more valuable.

Part B – Why Does Every Industry Have Its Own Success Metrics?

Once you understand the company itself, it's time to understand the world it operates in.

Every industry defines success a little differently.

Naturally, that means the metrics analysts and managers care about will also be different.

For example, think about two completely different businesses: a gaming company and an e-commerce company.

At a gaming company, one of the things you may care about most is whether players continue coming back to the game over time.

That's why metrics such as Retention, DAU, MAU, and ARPU can become a major part of the company's business language.

At an e-commerce company, on the other hand, you may spend much more time looking at Conversion Rate, Average Order Value, Repeat Purchase Rate, or GMV.

That doesn't mean an e-commerce company doesn't care about retention.

And it doesn't mean a gaming company doesn't care about conversion.

The point is that different business models have different behaviors driving their success, and therefore different metrics tend to receive more attention.

And this is exactly where your interview preparation comes in.

You don't need to walk into an interview knowing every KPI that exists in the industry.

In fact, memorizing a long list of acronyms without understanding what sits behind them won't help you much.

If anything, memorizing metrics without understanding what they actually mean can make you sound like a parrot - and that's definitely not the impression you want to give.

Your priority should be to know a few of the important KPIs and be able to explain, at least at a basic level, what they mean.

Your goal is to understand:

What matters to this business, how does it measure success, and why?

If you're interviewing at a gaming company, for example, it's not enough to know that Retention measures how many users return to the game.

You want to understand why that matters.

If lots of players download the game but stop playing after a few days, the company will have a difficult time building a stable user base, generating long-term engagement, and ultimately monetizing those players.

Suddenly, Retention isn't just another formula you memorized before an interview.

It's a number telling you something important about the business.

And that's exactly the distinction I want you to take from this section:

Don't learn KPIs just so you can explain what they are. Learn them so you can understand what they're telling you about the business.

Once you understand that, it also becomes much easier to deal with questions you didn't prepare for.

If an interviewer asks why you think the revenue of a certain game decreased, you can already start thinking from a business perspective:

Are there fewer active players?

Did Retention decline?

Are the same players still playing but spending less money?

Did the percentage of paying players change?

You still don't know the final answer.

You don't have the data.

But you're already speaking the language of the business.

What KPIs should you know, by industry?

Accordion will open here by industry

Sources & further reading: The metrics above are common industry metrics rather than a universal checklist. Definitions and usage may vary between companies.

Part C – Turn Your Research Into Hypotheses Before the Interview

So far, we've talked about researching the company, understanding its business model, and learning the important metrics in the industry it operates in.

But if you finish your research with nothing more than a list of facts about the company, you've only done half the job.

The goal isn't to walk into the interview and recite how the company makes money or list its main KPIs.

The goal is to use everything you've learned to start thinking about the business before the interview even begins.

Let's take a simple example.

Imagine you're interviewing at a large delivery company.

During your research, you learn that the company delivers packages for businesses, charges for each delivery, and operates a large network of couriers and logistics centers.

Great.

You've learned something about the company.

Now take it one step further.

Imagine that tomorrow you discover the company's average delivery time has increased by 20%.

What could explain that?

Maybe delivery volume increased significantly, but the number of couriers didn't grow with it.

Maybe the problem exists only in one geographical area.

Maybe one of the logistics centers is operating less efficiently than usual.

Maybe pickup times from customers have increased.

Or maybe average delivery time increased because the mix of deliveries changed, and the company is now handling more long-distance deliveries than before.

Right now, you have no way of knowing which explanation is correct.

And that's not the point.

You just created hypotheses.

Instead of walking into the interview only knowing that delivery time is an important metric for a delivery company, you're already starting to think about what could cause it to change, how different parts of the business could affect it, and where you would start looking for the problem.

That's exactly the kind of thinking you want to practice before an interview.

After you've finished researching a company, I recommend opening a document and trying to answer a few simple questions:

• What kinds of business problems might an analyst at this company be asked to solve?
• If one of the company's key metrics changed significantly tomorrow, what could explain the change?
• Which part of the business would I investigate first, and why?
• How would I break the problem into different groups or segments to understand where it's coming from?
• What information would I need to test whether my hypothesis is correct?
• What different explanations could lead to the same result I'm seeing?

You're not trying to predict the exact questions you'll get in the interview.

And just as importantly, don't fall in love with your hypotheses and start treating them like facts.

You're simply training yourself to do something analysts do all the time:

Take what you know about the business, generate possible explanations for what's happening, and then think about which data you would need to determine whether those explanations are actually true.

And to me, that's the difference between researching a company just to check a box and using that research to prepare like a serious analyst.

Because at the end of the day, the interviewer probably won't be that impressed that you memorized the delivery time the company promises on its website.

They'll be much more impressed if, when they ask you why delivery times have increased, you already know how to start thinking about the answer.

Part D – Want to Actually Practice This?

Good research can help you walk into an interview understanding the company and the business world it operates in.

But ultimately, the best way to improve your business thinking is to actually practice it.

And that's one of the main reasons we built DataBiz.

Instead of solving another SQL exercise that starts and ends with the data, DataBiz puts you inside a Case Study with a complete business environment.

You get real data, analyze it yourself, and then deal with problems that require you to understand the business first, and only then start analyzing.

Each Case has an AI trained specifically on the business world you're working in.

It knows the company, the data, and the problem you're trying to solve, and it can challenge your thinking throughout the process - from the questions you ask to the conclusions and recommendations you eventually make.

The goal isn't to teach you another tool.

The goal is to give you a place to practice the part of the job that's much harder to learn from theory alone:

How to think like an analyst inside a real business.

Part E – Get the Free Data Analyst Pre-Interview Research Template

Reading about how to research a company is one thing.

Opening your laptop before an interview and knowing exactly what to look for, what actually matters, and what to do with all the information you find is another.

That's exactly why we built the DataBiz Pre-Interview Research Template.

It's the template we wish we'd had when we first started preparing for interviews: a structured process that takes you from your initial research on the company and industry to the point where you're already starting to think about the business questions and problems you might encounter during the interview.

We've covered many of the important topics in this article.

But we've kept a few things exclusively inside the template.

It includes additional questions we recommend researching before an interview, some less obvious places where you can find useful information about the company, and a few of the smaller things we know can make the difference between a candidate who "read a little about the company" and one who walks into the interview actually understanding the business they're interviewing for.

All you need to do is take the template, choose the company you're interviewing with, and work through it step by step.

We've already built the structure. You just need to do the research.

Leave your email below and we'll send you the full template for free.

FAQ

How much time should I spend researching a company before a data analyst interview?

There is no fixed amount of time you should spend researching a company before an interview.

For most interviews, 1–3 focused hours can be enough to build a solid understanding of the business, although more complex companies may require more.

The goal isn't to research everything you can possibly find.

You should reach a point where you can explain what the company does, how it makes money, what its main products are, which KPIs matter to the business, and start thinking about the types of problems its analysts might work on.

Once you can do that comfortably, additional research will usually have diminishing returns.

Do I need to memorize company numbers before the interview?

No.

You don't need to memorize dozens of company numbers before a data analyst interview.

It can be useful to remember a few important figures that give you a sense of the company's scale or performance, but understanding the relationships between numbers is much more valuable than memorizing them.

For example, knowing the exact number of customers isn't nearly as useful as understanding which customer segment is the largest, what drives revenue, and which metrics could indicate whether the business is growing or struggling.

Understand the business first. Memorize only the numbers that help you understand it.

What should I research if I'm interviewing at a startup with very little public information?

If you're interviewing at a startup with limited public information, focus on extracting as much business context as possible from the information that does exist.

Start with the company's website and product pages.

Then look at its LinkedIn page, founders, open job descriptions, funding announcements, interviews, news coverage, and any public product documentation you can find.

Job descriptions can be particularly useful.

A startup may reveal very little about its internal operations publicly, but its open positions can tell you what teams it's building, which technologies it uses, which markets it operates in, and sometimes even which business metrics matter to it.

You won't always find every answer.

That's fine.

Your goal isn't to know things that aren't public, it's to show that you made the effort to understand the business with the information available to you.

Should I research the company's competitors before the interview?

Yes, but you usually don't need to perform a full competitive analysis.

Knowing two or three important competitors can help you understand the market the company operates in, how its product is positioned, and what might differentiate it from other companies solving the same problem.

More importantly, ask yourself:

Why would a customer choose the company you're interviewing for instead of one of its competitors?

If you can answer that question, you've probably learned something meaningful about the company's product, customers, and competitive position, rather than simply memorizing a list of competitor names.

What if I have no previous experience in the company's industry?

That's completely normal, especially for junior analysts.

You don't need to become an industry expert before the interview, but you should understand the fundamentals of how that industry works.

Learn the basic business model, important terminology, major KPIs, typical customers, and the main factors that drive success in that industry.

Then start using that knowledge to think analytically.

Ask yourself what could cause an important KPI to change, what hypotheses you would investigate, and which data you would need to test them.

The interviewer knows you haven't spent three years working in their industry.

Your goal is to show that you can learn a new business, understand what matters, and start asking relevant questions relatively quickly.