Talk to Data: Best Practices for Effective Data Management

Collecting data is great and all, but it’s better when you can make it work for you. When it comes to pulling insights from all of the data your store collects, you need to understand how to harness and analyze that information. 

Our next generation of Triple Whale features an easy way to talk to your data, but it’s still important to say the right things to get the right answers. 

If you understand the basics of SQL (Structured Query Language), you’ll be ahead of the game when it comes to asking Moby specific questions about your data. With the basics under your belt, you’ll be better able to amplify your campaign effectiveness and refine target audiences to have better marketing outcomes. In this blog, we’ll break down the best practices for using SQL in marketing. 

The Importance of SQL for Ecommerce

When it comes to ecommerce businesses, there’s endless data points to collect and analyze. Even on Shopify alone, you’ve got product information, customer data, transaction data, inventory management, acquisition data, and behavior reports to consider. But today’s ecommerce store isn’t Snow Devil (the first-ever Shopify store, built by Shopify CEO Tobi Lütke), and plenty of things have changed since 2004.

The ecommerce stores of today (and the future) include countless integrations with other platforms for shipping insights, email marketing, advertising platforms, and customer service tools that multiply the amount of data you must manage with every addition. 

When using SQL, you can both organize and draw insights from your data using simple commands (read our introductory blog about SQL here). You can make it even easier on yourself by having Moby write the SQL queries for you. In short, SQL enables an ecommerce brand to make quicker, efficient decisions based on copious amounts of data while the code works its magic in the background. 

With a little SQL magic, ecommerce brand owners can: 

• Extract meaningful insights from customer and campaign data.
• Segment audiences for personalized marketing efforts.
• Measure the performance of marketing campaigns with precision.
• Perform complex data analysis without relying on IT or data teams.

By adding SQL to your skill set, you're not merely learning a programming language—you're empowering your marketing strategies with data-backed decisions (or… like we said… you can let Moby do it for you?). 

What Brand Owners and Marketers Can Do With SQL

Here are a few benefits for using SQL in the ecommerce world:

Data Management: As mentioned above, the vast amounts of data generated from the ecommerce platform in combination with the endless integrations needs somewhere to live that’s easy to retrieve and manage. A SQL database enables the data to be organized in a structured format that’s easy to query. Additionally, it’s always up-to-date, which means you wouldn’t be operating on old information. 

Customer Insights: When you extract relevant data from the database, you can use it to tailor marketing strategies, recommend specific products to specific customer cohorts, and improve the customer experience overall. For example, analyzing purchase history and previous shopping patterns can help an ecommerce business understand which products are most popular in specific audience segments.

Inventory Management: Being able to track inventory in real-time is an essential part of an ecommerce business. With SQL, you can monitor stock levels, orders, returns, and shipments. With clear information, businesses can make informed decisions about which products to restock, how they plan ahead for supply chain issues, and they can forecast future demand.

Reporting: Using SQL, a brand can generate reports and conduct subsequent analysis on sales trends, how engaged customers are, how specific products perform and more. With insights like these, a company can plan for the future, complete financial forecasting, and understand how well their marketing campaigns are working (to iterate in the future).

There are many more ways that SQL can be beneficial for brands and marketers, but we’ll keep it short and sweet to discuss some best practices for using SQL as an ecommerce brand. 

SQL Best Practices

1. Start with a Clear Goal

Before even writing a single line of code, you should know what you hope to achieve. Whether you’re assessing a recent campaign’s performance, segmenting an audience for targeted ads, or gauging the lifetime value of your customer base - you have to know the why before you get the what. Setting a clear goal allows you to structure queries more effectively to extract more useful insights. 

2. Keep Your Data Clean and Organized

If the data isn’t clean and organized, the insights won’t be, either. Having organized data that is consistently formatted will ensure you’ve got a well-structured database to analyze. Additionally, a regular review and clean-up of the database can ensure everything is accurate and functional.

3. Understand Your Database Schema

Similar to a blueprint for a house, a schema allows you (or anybody viewing your database) to understand how every component works together. The schema defines the structure of your data, and by having access to the schema you can write efficient queries. It’s like when you visit a new Airbnb and you check all of the cupboards and drawers before you cook a meal - you need to know where everything is before you start cookin’. 

4. Selectively Query Data

It might be fun to pull every piece of data using the SELECT * statement, but it’s better to request only the columns you require for your specific analysis. This will keep your queries running smoothly, and keep you focused on the objective at hand! 

5. Use “JOIN” for a Complete Picture

When it comes to marketing data, it’s often spread across multiple tables. For example, you might have demographic information in one, purchase history in another. In order to gain the comprehensive insights you need, you’ll need to use the ‘JOIN’ clauses to combine the related data from different tables.  

6. Use Aggregate Functions for Summarization

Aggregate functions like ‘COUNT’, ‘SUM’, ‘AVG’, ‘MAX’, and ‘MIN’ are super useful for summarizing data. You can quickly calculate metrics like the total number of conversions, average order value, or understand which channels are the highest-earning ones. 

7. Create Views for Repeated Use

If you’re running the same complex query frequently, you could create a view instead. A view is a stored query that you can reference similar to as if it were a table. This saves time and effort for recurring analyses. In Triple Whale, we call these Sequences, and they’re made to make your life easier!

8. Optimize Your Queries

As you continue to delve into writing SQL queries, you’ll find ways to make your queries more efficient. Some ways to do this include indexing, query caching, and avoiding any suboptimal functions can enhance performance, especially when working with larger databases. 

Conclusion

With SQL, the world of data analytics is your oyster (yes, that’s an oceanic pun). To truly master SQL queries and make the most of your data analysis efforts, it’s important to keep an eye on how the experts handle it. In our case, we’ve got Moby - and we can ask an endless number of questions to get useful insights out of our ecommerce data. Curious to learn more about how Moby works? Click here to be added to our waitlist - the future of data analysis is here!