Why Shopify Data Powers Your Growth Strategy

Shopify data analytics dashboard - shopify data

Summary

Shopify data includes product details, customer information, order history, sales metrics, and behavioral analytics stored within your Shopify store.
Merchants access data through built-in reports, export functions, the Data Exporter app, and developer tools like the Admin API and ShopifyQL query language.
Custom data structures can be created using metafields (for adding specific attributes) and metaobjects (for defining complex data models).
Advanced users use ShopifyQL for custom queries and Shopify Data Warehouse (Shopify Plus only) for combined multi-store analysis.
Proper data analysis helps identify sales trends, customer behavior patterns, inventory issues, and marketing performance to inform business decisions.

Shopify data is the complete collection of information your store generates every day. It includes everything from product details and customer profiles to order histories and sales performance metrics. This data tells you what's working, what's not, and where your next growth opportunity lies.

Here's what you can do with your Shopify data:

Track sales performance across products, channels, and time periods
Understand customer behavior through purchase history and browsing patterns
Monitor inventory levels and forecast demand
Measure marketing effectiveness by channel and campaign
Export data for tax compliance and financial reporting
Build custom reports using ShopifyQL or integrate with external analytics tools
Automate workflows based on specific data triggers

Most merchants start with Shopify's built-in analytics dashboard, which provides real-time insights without any setup. As your business grows, you can extend your data model with metafields and metaobjects, automate data tasks with Shopify Flow, or write custom queries using ShopifyQL. Shopify Plus merchants can access Data Warehouse for enterprise-level analysis across multiple stores.

The challenge isn't collecting data. Shopify does that automatically. The challenge is knowing which data matters and how to use it for better decisions.

I'm Steve Pogson, founder of First Pier, and over two decades I've helped hundreds of brands use their Shopify data to create growth plans that work. Here at First Pier, we've seen how the right data approach can improve a store's performance, and I'll show you exactly how to do it.

Infographic showing the flow from raw Shopify data (products, customers, orders) through analytics tools (built-in reports, ShopifyQL, Data Warehouse) to business decisions (inventory planning, marketing optimization, customer segmentation, revenue forecasting) - shopify data infographic

Shopify data terminology:

Your Store's Foundation: Core Data & Analytics

Every interaction on your Shopify store generates Shopify data. This includes everything from a customer viewing a product to completing a purchase. Shopify collects this information in real-time, providing reliable data that helps you make informed business decisions quickly. This immediate access to information means you can react to trends, address issues, and act on opportunities without delay.

For instance, understanding which products are frequently viewed but rarely purchased can help identify issues with product descriptions or pricing. Knowing your peak sales hours allows you to schedule marketing campaigns more effectively. The built-in analytics dashboard is your starting point, offering an overview of your store's performance without any complex setup.

Shopify Analytics dashboard showing key metrics like sales, sessions, and conversion rate - shopify data

The Main Types of Data in Shopify

Shopify organizes your store's information into several core categories:

Products: This includes details like product titles, descriptions, images, pricing, and availability. It's the foundation of your catalog.
Inventory: Crucial for managing stock levels, tracking product variants, and preventing overselling.
Variants: Specific options for a product, such as size, color, or material, each with its own SKU and inventory.
Customers: Information about your buyers, including contact details, purchase history, and location.
Segments: Groups of customers based on shared characteristics or behaviors, useful for targeted marketing.
Purchase history: A detailed record of every order a customer has placed, including items bought, dates, and total spend.
Orders: Comprehensive data on each transaction, covering items, payment status, shipping details, and fulfillment status.
Fulfillment: Tracks the journey of an order from processing to delivery.
Returns: Data on products sent back by customers, important for understanding product quality and customer satisfaction.
Collections: Organized groups of products, whether manual or automated, that help customers browse your store.
Marketing & Sales Channels: Data related to how customers find your store and through which platforms they make purchases, such as social media, email, or search engines.

Each of these data types offers specific information. For example, by analyzing customer data and purchase history, you can identify your most loyal customers, understand their preferences, and tailor future offers.

Using Built-in Reports for Quick Insights

Shopify's admin panel comes equipped with a suite of built-in reports that present your Shopify data in an easy-to-understand format. These reports are useful for quickly assessing performance and identifying trends.

Sales reports: These reports provide a detailed breakdown of your revenue, showing sales by product, channel, discount, and more. You can track gross sales, net sales, and average order value.
Acquisition reports: Learn how customers are finding your store. These reports show traffic sources, conversion rates by channel, and how effective your marketing efforts are at bringing new visitors.
Behavior reports: Understand how visitors interact with your store. Which pages do they visit most? How long do they stay? Where do they drop off? This data helps you improve user experience and site navigation.
Marketing reports: Measure the performance of your marketing campaigns. Track clicks, conversions, and return on ad spend for various channels.

Beyond your own store's data, you can compare your store's performance against industry benchmarks. Shopify provides benchmarks documentation that allows you to see how your metrics stack up against similar businesses, giving you context for your growth. This comparison can reveal areas where you're excelling and where there's room for improvement.

Customizing Your Data Model with Metafields and Metaobjects

Sometimes, the standard Shopify data fields aren't enough to capture all the unique information your business needs. This is where custom data comes in, allowing you to extend Shopify's core data models. Metafields and metaobjects are tools for adding specific attributes and creating custom data structures, making your product information more detailed and organized.

For instance, an apparel store might need to add care instructions to each product, while a beauty brand might want to track ingredient information for each item. These specific details don't fit neatly into standard product fields, but they are vital for customers and internal operations.

Shopify admin interface for creating a metafield - shopify data

What are Metafields?

Metafields allow you to define and associate custom fields with different parts of your Shopify store. Think of them as extra data points you can attach to products, customers, orders, collections, or even blog posts. They let you store information that isn't included in Shopify's default fields.

Use cases for metafields:

Care instructions: For clothing, you might add a metafield for "Washing Instructions" (e.g., "Machine wash cold, tumble dry low").
Part numbers: For electronics or industrial supplies, a "Manufacturer Part Number" metafield can be crucial for inventory and customer service.
Release dates: For books, music, or limited-edition items, a "Release Date" metafield helps manage launches.
Specific product attributes: Beyond the standard size and color, you could add metafields for "Material Composition," "Country of Origin," or "Dietary Restrictions" for food products.

By adding detail to your product listings, metafields provide more specific information to your customers and internal teams. They make your Shopify data as comprehensive as your business requires.

What are Metaobjects?

While metafields add single custom fields, metaobjects allow you to define and create custom data structures within Shopify. They are like mini-databases within your store, letting you group related custom fields together. This means you can create complex, reusable data entries that are stored separately from your main product or customer data, but can be referenced by them.

Use cases for metaobjects:

Influencer profiles: Instead of individual metafields for an influencer's name, social media links, and bio, you can create an "Influencer" metaobject. Each influencer would be an entry in this metaobject, and you could then link products to specific influencer profiles.
Featured ingredients: For a skincare brand, a "Key Ingredient" metaobject could hold detailed information about each ingredient (e.g., benefits, origin, scientific name). Products could then reference these ingredient entries.
Store locations: If you have multiple physical locations, a "Store Location" metaobject could store addresses, opening hours, and contact details. You could then link this data to relevant pages or products.

Metaobjects help you build more sophisticated Shopify data models, especially when you have data that is structured and needs to be referenced across multiple entities in your store. This capability is particularly useful for advanced content management and complex product catalogs.

Accessing, Exporting, and Automating Your Shopify Data

Beyond viewing reports in your admin, you'll often need to access, export, or automate your Shopify data for various purposes, from tax compliance to streamlining operations. Shopify provides tools and apps to handle these needs, ensuring you can use your data effectively.

Exporting Shopify Data for Compliance and Reporting

Exporting your Shopify data is essential for accounting, tax compliance, and in-depth analysis outside of Shopify's native environment. The platform offers built-in export functions, and for more specialized needs, the Data Exporter app is available.

The Data Exporter app is particularly useful for merchants who need to comply with specific international tax regulations. For example, it helps businesses provide transaction data for audits under Electronic Sales Suppression Tools (ESST) regulations in Australia, or to meet the requirements of Article 88 in France, or the GoBD principles in Germany. These regulations often demand detailed, auditable records of transactions.

The Data Exporter app allows data export from January 1, 2019, and onwards. If you need data from calendar years prior to 2019, you can use Shopify's native 'export orders' and 'export products' actions directly from your Shopify admin. For comprehensive data needs, especially for historical records, exploring third-party apps from the Shopify App Store can also provide solutions. Always consult with local legal professionals to ensure your business complies with all relevant tax regulations.

Automating Tasks with Shopify Flow

Shopify Flow is a tool for automating routine tasks and workflows based on your Shopify data. It lets you create rules that trigger actions when certain conditions are met, saving time and reducing manual errors. One of the most common and effective actions within Flow is "Get product data."

The "Get product data" action allows you to retrieve specific product information from your store, which can then be used in subsequent steps of your workflow. You can configure this action to sort data, limit the number of results, and apply complex queries to filter products based on various criteria, such as products updated in the last day or products with specific tags.

Automation examples using Shopify Flow:

Tagging products: Automatically add a "new arrival" tag to products when they are created, and then remove it after 90 days.
Inventory alerts: Send an internal email notification when a product's stock drops below a certain threshold.
Collection management: Automatically add products with a specific tag to a particular collection.
Identifying duplicate SKUs: If a new variant is added, Flow can check if any other variants use the same SKU and send an internal alert.
Tracking products on sale: Set a metafield on a product if at least one of its variants is on sale, which can then be used for dynamic collections or filtering.

These automations, driven by your Shopify data, ensure your store runs more efficiently. Here at First Pier, we have extensive experience setting up Shopify automation services to help businesses streamline their operations and focus on growth.

Advanced Analysis with ShopifyQL and Data Warehouse

For merchants and developers who need more detailed analysis and control over their Shopify data, Shopify offers advanced tools like ShopifyQL and the Shopify Data Warehouse. These are designed for sophisticated analysis, custom reporting, and managing large-scale operations, especially for Shopify Plus users.

Introduction to ShopifyQL: The Commerce Query Language

ShopifyQL is Shopify's specialized query language, built specifically for commerce. It is used for analytics and customer segmentation across the platform, allowing you to move beyond standard reports and build custom reports from your store's data.

Unlike general-purpose SQL, ShopifyQL abstracts away much of the underlying database complexity. It provides built-in support for common e-commerce patterns like time-series analysis, currency handling, and multi-store reporting. This means you can focus on what data you want to see, rather than how to retrieve it.

Key capabilities of ShopifyQL:

Query store data: Access data across sales, orders, products, customers, and sessions.
Analyze trends: Use built-in time-series support to understand historical performance and forecast future trends.
Build visualizations: Embed visualization instructions directly within your queries to render data graphically.
Create customer segments: Use sophisticated filtering to define and target specific customer groups.

ShopifyQL data sources:

sales: Detailed transaction data.
orders: Information about customer orders.
products: Product catalog details.
customers: Customer profiles and attributes.
sessions: Website visitor activity.

Use cases for ShopifyQL:

Segmentation: Identify customers who have purchased specific products or spent above a certain amount.
Trend analysis: Track the performance of a product category over the last quarter, comparing it to the previous year.
Multi-store reporting: For businesses with multiple Shopify stores, ShopifyQL can aggregate data across all of them (more on this below).

You can explore the ShopifyQL syntax reference for comprehensive documentation on keywords and capabilities.

Getting Started with ShopifyQL Queries

Writing ShopifyQL queries follows a clear, declarative structure. Every query requires two essential keywords: FROM to specify the data source and SHOW to select the metrics and dimensions you want to display.

Basic structure:

FROM salesSHOW total_sales

This simple query would show your total sales.

Filtering with WHERE:You can refine your results using the WHERE clause to filter data based on specific dimensions. For example, to see sales from a particular country:

FROM salesSHOW total_salesWHERE billing_country = 'United States'

Grouping with GROUP BY:To segment your metrics by different dimensions, you use GROUP BY. This helps you break down overall numbers into more specific details.

FROM salesSHOW total_salesGROUP BY billing_country

This query would show total sales for each country.

Time-based analysis:ShopifyQL is well-suited for time-based analysis. Keywords like TIMESERIES and DURING allow you to analyze trends over periods.

TIMESERIES: Distinguishes grouping by time dimensions (like month or day) and backfills dates where data gaps exist, ensuring a continuous time series.
DURING: Simplifies date filtering by allowing you to use named ranges like last_month, this_quarter, or bfcm2023.

Common query patterns:

Sales performance by period: Track gross sales, net sales, and total orders over time.
Top products with comparison: Identify your best-selling products and compare their performance month-over-month.
Regional breakdown: Analyze sales performance by country or region to understand geographical trends.
Customer acquisition trends: Track how new customers are acquired over weeks or months.

ShopifyQL provides a direct way to interact with your Shopify data, allowing you to build highly customized reports for informed decision-making.

For Large-Scale Operations: Shopify Data Warehouse

For eligible Shopify Plus stores, the Shopify Data Warehouse offers a tool for advanced data analysis. It's a service that provides access to your Shopify analytical data models across all your stores in a single SQL database. This is useful for large businesses managing multiple brands or regions.

Key features and benefits:

Combining data: Instead of pulling reports from individual stores, you get a unified view of your entire organization's performance.
Custom reporting: The Data Warehouse allows you to build highly detailed custom reports and dashboards using your preferred data analytics platforms.
Third-party data comparison: You can integrate and compare your Shopify data with external data sources (e.g., marketing spend, customer service interactions) for a more complete view of your business and true revenue recognition.

The Shopify Data Warehouse is designed for businesses that need to perform complex, organization-wide analysis, providing the flexibility to perform detailed analysis on their extensive Shopify data.

Frequently Asked Questions about Shopify Data

Navigating Shopify data can bring up many questions. Here are some of the most common ones I encounter.

What's the best way to start with Shopify analytics?

The best way to begin is by exploring Shopify's built-in analytics dashboard and reports within your admin. These tools provide real-time, reliable data without any setup, allowing you to make informed business decisions quickly. Focus on understanding key metrics like total sales, conversion rate, average order value, and top-selling products.

For Shopify Partners looking to help merchants improve their businesses, the 'Shopify Data & Analytics 101' course is a useful resource. This course teaches how data and analytics are used on the Shopify platform and how partners can use these tools. It's ideal for anyone with basic computer skills who wants to understand the fundamentals of Shopify data and its application.

Can I export all my historical data from Shopify?

You can export a significant amount of your Shopify data, but there are some considerations, especially regarding historical data. The Data Exporter app, while useful for tax compliance and specific data exports, typically allows data export from January 1, 2019, and onwards.

For data preceding 2019, you'll need to use Shopify's native 'export orders' and 'export products' actions available directly in your Shopify admin. These functions provide similar data to the app for older periods. Additionally, the Shopify App Store offers various third-party apps designed for comprehensive data export, which might meet specific historical data requirements not met by native tools or the Data Exporter app.

How do developers access and use Shopify data?

Developers have several tools to access and interact with Shopify data for building apps and integrations:

GraphQL Admin API: This is the primary API for programmatically interacting with Shopify data, offering extensive capabilities for managing products, customers, orders, inventory, and more.
REST Admin API: While GraphQL is increasingly preferred, the REST API remains available for many common operations.
Storefront API: Developers use this API to build custom shopping experiences and headless commerce solutions, allowing access to product, collection, and other storefront-related data.
Shopify Flow: As mentioned earlier, Flow allows for automated data retrieval and manipulation within workflows.
shopify-data component: This web component is used to display Shopify data directly on a page. It uses a query attribute with dot notation (e.g., query="product.title") to specify which data to display, finding the nearest matching context. It outputs plain text, which can then be styled with HTML. For instance, you could use <shopify-data query="product.descriptionHtml"> to display a product's rich text description. You can see more examples in the playground.

For comprehensive technical information on store setup, configuration, and custom development, developers can always refer to Shopify’s developer documentation. This resource is useful for understanding the intricacies of Shopify's APIs, libraries, and tools.

To Sum Up: Using Data for a Competitive Advantage

Understanding and using your Shopify data is no longer optional; it's fundamental to building a successful e-commerce business. From deciphering basic sales reports to customizing your data model with metafields and metaobjects, and even writing advanced queries with ShopifyQL, every step you take to engage with your data helps you make informed decisions.

The ability to analyze trends, understand customer behavior, manage inventory efficiently, and automate routine tasks based on concrete data is a key part of running a competitive business. It allows for continuous improvement, agile responses to market changes, and planning for future growth.

Here at First Pier, we work with brands and boutiques to use their raw Shopify data to create actionable plans. We help you not just collect data, but truly understand it, to help your business grow.

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