As a digital marketer, I use SQL every single day. And looking back on my career so far, it would be fair (though a bit reductive) to say that I could define my career by two distinct periods: before I learned SQL and after I learned SQL. The two periods are distinct for three main reasons:
- After learnings SQL I am faster at gaining insight from data
- After learnings SQL I am able to make decisions based on more data
- As a result, I’ve been making better marketing decisions—and I have seen the traffic, conversion rates, and ROI to prove it. (Thanks to SQL)
If you’re at a crossroads in your career and you find yourself asking, “what coding language should I learn,” here is my case for SQL.
What is SQL (for Digital Marketing)
When you see SQL you might think it means “Sales Qualified Lead” but more commonly, SQL stands for “Structured Query Language.” It is a programming language that allows you to retrieve (or update, alter or delete) data from relational databases. (Relational is just a fancy word for a database that stores data in tables.)
It’s kind of like ordering from McDonald’s. SQL is a language – a specific set of instructions – that you use to specify the results you want, the way you want them, in the quantity you want. Basically, SQL allows you to have your data your way.
How is SQL Used in Business
SQL has two main uses: applications and analysis. Applications (apps) from CandyCrush to Instagram store content and data about users in databases and then use it to create an experience (like keep track of how many comments you have on an Instagram post). On the other hand, you can use SQL for analysis in the same way you can sort, filter, and pivot data in Excel. (except with a lot more data)
What’s the difference between SQL and Excel?
Remember when you learned your first Excel formula? Pivot tables? VLOOKUP? You probably through you could take on the world! SQL is like that times 100. SQL and Excel are similar because they both allow you to analyze, manipulate, and make calculations, and join data in tables.
The biggest difference between Excel and SQL is that you can analyze exponentially more data exponentially faster with SQL but you can’t update the data in SQL quite as easily. Also, SQL commands define how you want your data table to look when the data is retrieved so you are working with entire tables rather than individual cells. The benefit of this is that you don’t have to worry about making mistakes when copying formulas (and the analysis errors that come with that.) On the whole, I’d say SQL is much better than Excel, most of the time.
SQL Example in Marketing
This example shows an ROI analysis using SQL code that you would use to calculate how many customers you’ve acquired per country since the beginning of 2020, and the Facebook Ads spend that was spent in that country.
The example does the following:
- Aggregate a table of customers into a table of countries and customer counts who have become customers since January 1st, 2020.
- Joins that table with another table that contains Facebook Ads data by day
- Filters in only Facebook Ad spend data since January 1st, 2020
- Aggregates this all into a single table that has three columns: country, count of new customers from that country, and the ad spend for that country.
The good news is, this is about as complex as SQL gets. Pretty much everything else in SQL is just a variation of this.
Is SQL worth Learning?
In a word, yes. There is a practical reason and a conceptual one. The conceptual one is that learning SQL, like learning data structures or other programming languages, will expand how you think about data. It will help you organize data for analysis more efficiently and help you structure your thinking about how to answer questions with data. So even without a database, SQL can help you work with data.
The practical reason for learning SQL is that it allows you to gain insight faster, from more data, and come to better conclusions. That is true if you are analyzing keywords for PPC or SEO, analyzing how leads flow through your sales funnel, analyzing how to improve your email open rates, or analyzing traffic ROI.
Here are just a few good reasons.
- You’ll spend less time trying to export and import data into spreadsheets
- You’ll be able to replicate your analysis easily from week to week or month to month
- You’ll be able to analyze more than 10k rows of data at once
- You can use BI tools to build dashboards with your data (and always keep them fresh)
- You’ll be able to merge bigger datasets together faster than VLOOKUPs
- You won’t have to ask for help from IT people, DBAs or engineers to get data out of a database or data warehouse for your analysis
How long does it take to learn SQL?
With dedication, you can develop a strong foundation in SQL in five weeks. I recommend Duke’s SQL class on Coursera to go from zero to usable SQL skills in less than two months. With that class and a couple of books about PostgreSQL, I was on par with most analysts at Postmates (except I had the context about the data!). A few months later I learned enough to record this SQL demo with SEM data.
There are even good Android/iPhone apps that will help you learn the syntax through repetition. The class I recommend below (Data Manipulation at Scale: Systems and Algorithms) for Python also touches on SQL so it’s a double whammy and Python Anywhere also features hosted MySQL, so that’s a double-double whammy!
If you are looking for a short but substantive overview of SQL, this video from Free Code Camp is pretty good. I’m not suggesting you’re going to know how to write SQL in four hours, but at least you will get the gist.
All that being said, like many programming languages, learning SQL is a continual practice because, after learning the language, you can expand into managing a database rather than just analyzing data in a database. You can also pair your SQL skill with other programming skills to make all sorts of interesting applications! The good news, for the most part, it’s like riding a bike, once you learn it, you don’t really forget it—but it will take you a bit of time to re-learn a wheelie.