If you are on a revenue team at a Product-Led Growth startup, you’re faced with the herculean task of trying to figure out which users to connect with to drive upsell and expansion revenue. Users are signing up on a daily basis for your product - many using personal emails - and it’s up to you to figure out which users will convert.
In our experience empowering revenue teams at Product-Led Growth startups, one of the most important measures for a user’s potential value is how they are using your product.
However, as we all know, startups are in constant motion, and it’s hard to get access to the data you need, when you need it, and in the format that you need it in.
Knowing a bit of SQL can help jumpstart your process towards data-driven decision making, so we’ll dive into some basics in this two part blog series. Part One will be all about getting down the basics and setting you up for success, then we’ll dive into the details in Part Two. For some simple steps to getting started with creating the right framework for data-driven decision making, check out our blog post A 5-Step Plan to Enable Data-Driven Decisions for Revenue Teams at Developer Tools Startups.
Note: if you want to skip writing SQL, but still want the results, Correlated can help.
What is SQL?
SQL is a language used to query data stored in a database. Most companies have a production database that stores user information, and they funnel product metrics into a data warehouse (like Snowflake). You typically don’t want to be directly querying a production database, because if you mess things up, accidentally drop tables, or run a really long running query that crashes the database, the engineering team is absolutely going to come find you. There are also a variety of security reasons why you wouldn’t want access to the production database - with more power comes a lot of responsibility.
How do I connect to a SQL Database?
There are three common ways to connect to a SQL Database:
- Using developer tools like a terminal or a database management client
- Using applications like Mode Analytics that connect to the database, but provides a nice interface for you
- Using a Cloud Data Warehouse interface provided by Google, AWS, or Snowflake (etc). You’ll need to work with your data team or engineering team to get access.
I’m connected. Now what?
First, you want to understand the “schema” of your database. It’s easiest to understand a schema in relation to Excel.
Typically, you’ll be querying a single database and combining different tables together to get the entities and attributes you want.
How to Google Effectively
Ok, so to make things more complicated, not all SQL is created equal. Oracle’s version of SQL is slightly different from PostgreSQL which is slightly different from MySQL etc etc. At a high level, everything is similar, but if you get an error while you’re writing your queries, it’s likely a syntax issue. In this post, we’ll use PostgreSQL syntax. When you’re Googling for answers on how to do something (don’t worry, we all do it), make sure you specify what type of SQL database you are using so that you get an accurate example.
Congrats! Now you’ve got the groundwork set. In part 2 of this post, we’ll dive into exactly which SQL queries you should be using: 4 SQL Queries to Find Customer Engagement and Expansion Opportunities
Interested in learning about how Correlated can help your PLG company uncover expansion and upsell opportunities?
Sales and revenue leaders at PLG companies, like yourself, are faced with unique challenges. Using tools like Correlated can help sales and marketing teams identify new accounts that are ready to convert, or can help to notify your team for expansion and upsell opportunities.
If you’re interested in learning more about how we can help, schedule a demo here!