In the Product universe, it is very common to find Product Managers with different backgrounds , Design, Engineering, Agility and other business areas. In addition, we can also see people who are already hired as Associate Product Managers , starting their careers with a focus on Product.
But here I'm going to talk about a slightly more unusual background (at least within the Product bubble I live in, lol) which is Data. For most of my career, I was an analyst and manager of teams focused on data, working across the entire processing chain (obtaining, processing, visualizing and analyzing).
In this article I will discuss how this knowledge helped me in my career as a PM. Come with me!
data flow in a company
By starting my career in the Data department of a technology company, I acquired the hard skills necessary to understand the engineering, processing and visualization processes of a product's data. In the following topics, I will explain in more detail how this helps me today.
Dialoguing with data analysts
When you know the “other side” and need to make a request to a Data Ana greece mobile phone number lyst (to obtain information from a database, for example), it is much easier to provide guidance and also explain the context of what should be considered when obtaining the data. And this makes all the difference in ensuring that KRs, metrics and indicators are consistent with reality and reflect the current state of the business.
I've had peer PMs who struggled for a long time to get the information they wanted in a reliable way, or who ended up ignoring the metrics when validating a hypothesis, for example. As we know, this is a very dangerous thing.
So, the first tip is: understand the process . Understand everything from the database, to the visualization in a dashboard , observing how your product data is saved, how data engineers transmit it to analysts and, finally, how it becomes information .
And here it doesn't need to be the technical details of all these steps, but rather a macro understanding that helps you make requests in a richer and more assertive way. But it's worth saying that learning databases, SQL and data engineering concepts is something that certainly has a lot to add to a PM!
Being more independent in analysis
What if you need to turn around ?
Ahhh how beautiful it is to work in a well-structured company, with lots of resources, where each squad has all possible chapters at their disposal, with senior people to help and with all the necessary context…<3
I think a lot of people must have thought “wow, that would really be great”, lol. After all, the reality of many PMs is very, very different. Growing companies, very new and with areas still being structured and defined, seem to be much more common than the scenario in the paragraph above.
And it is precisely in these scenarios that knowing how to deal with data – even superficially – can make all the difference in the results of your product. Do you need to know a piece of information? Build your query , enter the result into a sheet and perform your analysis. Don't depend on anyone and do what needs to be done.
Here I have put together a list of concepts that you can study and master to know how to handle data in these more critical moments:
Database:
What is a database?
What is a Database Management System ?
Which DBMS does your company use?
How does the product database you manage work?
In which tables is which information saved?
How do these tables relate to each other?
SQL:
What is SQL?
What is a query ?
What is the basic structure of a query ?
What is the syntax of a query ?
How do I filter data using a query ?
How do I relate two or more tables?
How do I save the information returned from a query ?
How to optimize a query ?
General technical concepts:
What is a dataset ?
What is a data warehouse ?
What is a datalake ?
What is a dataviz tool ?
Metrics:
What are business metrics?
What are product metrics ?
What are UX metrics?
How do they relate?
Interpreting the numbers obtained
Another very important aspect in which the Data background helps me is knowing how to construct and analyze a number, understanding whether it makes sense and reflects what is expected for decision making.
For example, I will give you the following information:
“In October/22, the Product CSAT was 3.9.”
What is your first reaction when you see this number? If no questions came to mind , I can guarantee that this information is probably incomplete or wrong . Let's list some questions that need to be answered about this number to better understand its context:
Is this number good or bad?
What is the objective?
What is the market benchmark for a similar product?
How were the previous months?
What is the size of the population/sample that responded to the survey? What was this metric like in the same period last year?
Is an average a better way to visualize this data?
If we break it down by journey, do we have a pattern in relation to previous periods?
Is the data source 100% reliable?
These are some points you need to know so that you can make the best decision possible and interpret the numbers. Sometimes, a number that seems alarming is just the result of some specific instability that occurred during the period. If this is not mitigated, the risk of making a wrong decision – and often a very expensive one – ends up being high.
In a meeting, for example, it is always important to be aware of these questions that involve a number. These questions above work for almost any metric, and having clear answers to these questions is very important. The more answers you have, the more certain you will be about that information and what to do with it.
Conclusion
Invest your time in a study routine on data analysis and interpretation, because it will be worth it.
Understanding the process, knowing how to use it, and analyzing an indicator will provide you with great benefits. After all, in an area that is so focused on results, having precision in every piece of information at your disposal is essential.
Product is about working with results and results are numbers. To “celebrate adoption and not delivery” (this phrase is really cool!), you need to know how to measure adoption , even when you don’t have a data analyst on your team .
Master Product Analytics
Want to better understand the concepts in this article and go beyond metrics with your product? PM3, a leading Product school in Brazil, invites you to take the Product Analytics Course . This is your chance to learn how to deal with all types of Product data, through in-depth classes with qualified professionals and real cases from Brazilian companies.
You will learn how to efficiently monitor data to support your decisions and manage stakeholders , gaining more confidence in your career. And of course, you will have more confidence to talk to experts , guiding increasingly targeted analyses.
Access the full syllabus and check out the topics for each module!
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