Back of the envelop eCommerce object and event schema transformationsBack of the envelop example of eCommerce object and event schema transformations

What is Commerce Schema?

Commerce Schema is an open source, community-driven initiative to help SaaS, digital agencies, and eCommerce brands align on a shared data model and translation layer for eCommerce objects and customer events.

Why Commerce Schema Matters

  1. eCommerce SaaS is exploding. Interoperability is key to our shared success. Common data schemas, or even just shared translation models, remove friction in building integrations.
  2. Customer data strategies are becoming increasingly more critical to DTC brands. As paid advertising channels built on 3rd-party data falter, brands are relying more heavily on first-party and zero-party data collection and integration. Understanding these models and transformations is crucial to both eCommerce engineers and marketers.

Challenges with Customer Data and Event Structures

The need to build as a lightweight specification, documentation tool, and community was born from our experience implementing attribution tracking solutions for eCommerce brands — first as consultants, and later as the founders of a new customer data platform for eCommerce.

Example #1: What Is value on a GA4 purchase Event?

Even a question as simple as “What Shopify Storefront API variable should I use to populate the value property on a Google Analytics purchase event?” takes time to answer, and there is no consensus on the solution. Should you use Shopify’s subtotal variable? Or should you use total_price?

And then, what if an engineer is being asked to re-platform this attribution tracking script from Shopify to BigCommerce? First, you have to understand Google Analytics’s event specification, then check that the correct Shopify Storefront API variable was used, and finally map that Shopify variable to a BigCommerce Stencil variable to confirm the same values are flowing into Google…

And this is the simplest example of this overarching challenge.

Example #2: How Do You Structure Product Review Events?

How do I send Product Review events to my marketing automation platform via my CDP?

Today, few review platforms have direct CDP integrations. Even fewer CDPs have a detailed specification for a product_reviewed event. And the data formats that email marketing platforms need to consume such events are often buried in API documentation.

To build this integration, an engineer and marketer have to collaborate on the design of a data tracking plan that supports the flow of data above, then research and understand the review platform’s APIs, then translate the review object into a JSON payload that the CDP can consume, then test the payload against a JSON schema validation tool listening for CDP events, then test that the marketing automation platform received the correct data in the correct formats. (Whew!)

And if you’re an in-house team that doesn’t think about this stuff all day long, you first have to figure out what all the heck we’re talking about when using terms like data tracking plans.

What Commerce Schema Unlocks

Once SaaS, agencies, and brands have a shared vocabulary and understanding of these object and event schemas, our ability to build value together will skyrocket. Moreover, all sorts of ancillary benefits and use cases for shared schemas can be unlocked.

Example #1: New, Shared Analytics Templates

If we’re all using the same, or at least similar, customer event structures, it’s easier for agencies and brands to generate, share, and compare analytical models, including funnel analyses, customer flows, and retention analytics charts.

Example #2: DBT Models for Blending Warehouse Data

If we simply have a shared understanding of, say, what properties are on an Order Object, regardless of the eCommerce platform, then we can pull data from different SaaS platforms into a data warehouse, and blend it using open source DBT packages — speeding up analytics teams and accelerating the adoption of advanced DBT solutions like the Fal project.

What Commerce Schema Is Not

This is important: Commerce Schema is not an effort to get all SaaS products and teams to agree to build their software against a single, shared data model or API specification.

BigCommerce will have their APIs and definitions of an order object, a customer object, a refund object, etc. And Shopify will have somewhat different APIs and object definitions. Same with CDPs like Fueled, Segment, mParticle, RudderStack and so forth…

But what Commerce Schema should be is a tool for traversing these schemas and deriving the lineage between eCommerce objects, the APIs that expose those objects, and the translation of customer events from various event sources to event destinations.

How Commerce Schema Will Work as a Community Initiative & Software Application

With community engagement and financial sponsorship, Fueled will seed

  1. We will hire a full-time data engineer/community organizer to do this research, manage stakeholders, and collect feedback on the proposed schema.
  2. We will build an open source tool (under the GPL3 license and hosted on GitHub) for organizing this data.

Open Source Application Architecture

We’re still working out the architecture of this open source software application, but we’re excited about the possibility of leveraging Redwood.js with a Neo4j graph database…

Goals for designing this application include:

  • The ability to visually explore the lineage of event data from various sources to their different destinations.
  • The ability to query how a specific eCommerce object is leveraged across various CDP source/destination events.
  • The ability to version object, API, and event definitions.
  • The ability to generate JSON Schema and/or OpenAPI documentation from the Commerce Schema database application.

How You Can Help


First and foremost, we need community engagement:

Financial Sponsorship

We are looking to raise $200K in project sponsorships to hire a full-time organizer for 12 months, and to release an MVP of the application within 90 days of kicking off this initiative.

Our sponsorship tiers will be:

  • Gold: $25K (2 opportunities)
  • Silver: $10K (10 opportunities)
  • Bronze: $5K (10 opportunities)

Financial sponsors will receive:

  • The right to promote this project in their marketing efforts.
  • Logo placement on
  • Acknowledgement on the associated GitHub project(s).
  • Ongoing shoutouts on social channels, such as LinkedIn and Twitter.
  • Opportunities to co-market and collaborate on thought leadership and content.
  • Sponsorship recognition at working group events and meet-ups.

Financial sponsors will not receive:

  • Equity in Fueled (Sponsorship is not tied to any sort of investment in Fueled. All sponsorships will go toward the people hours required to build and maintain this community and tech platform.)
  • Prioritization or preferential treatment when collaborating on object/event definitions. This will be a collaborative effort across SaaS, agency, and brand professionals.

Additional FAQs

Why Commerce Schema and not eCommerce Schema?

The majority of use cases for currently relate to online eCommerce. However, with brick and click on the rise (i.e., the integration of eCommerce sales channels with brick-and-mortar sales channels), we’re seeing more use cases for omni-channel customer engagement metrics and event tracking. For example, we’re seeing merchants track their point-of-sale events in Google Analytics 4.

Why Is Fueled Leading This Initiative?

Fueled is a customer data platform for eCommerce. Candidly, we can’t scale our product without collecting, organizing, and maintaining this data dictionary. So, we’re gonna do this work with or without a broader community. 😇

Coming from the open source world (old school Drupallers …) and having led similar initiatives for almost 20 years, our team believes we can create more value for ourselves, our partners, and the DTC eCommerce brands we love, by solving this problem as a community.


Let’s get the discussion going! Excited to hear what y’all think. Please spread the word.

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