Aneesh . 6 minutes

April 30, 2025

Exploring BigCommerce’s GraphQL API for Headless Builds: The Complete Guide

Quick Summary

BigCommerce’s GraphQL API provides a flexible, performance-optimized foundation for headless commerce implementations. It allows developers to create custom storefronts with precise data querying, reduced payload sizes, and improved mobile experiences while maintaining BigCommerce’s robust backend capabilities. Implementation requires proper authentication, strategic data structuring, and performance optimization techniques.

Ever wondered how major brands create those lightning-fast, highly personalized shopping experiences?

Behind many successful headless commerce implementations sits a powerful yet often underutilized tool: BigCommerce’s GraphQL API.

At 2Hats Logic, we’ve implemented dozens of headless commerce solutions. We’ve seen firsthand how this technology transforms what’s possible in e-commerce.

Let’s dive into everything you need to know about leveraging the BigCommerce GraphQL API for your headless commerce builds.

What Makes BigCommerce’s GraphQL API Special?

The BigCommerce GraphQL API represents a significant advancement over traditional REST APIs for headless commerce implementations.

Unlike REST, which often returns excessive data with each call, GraphQL lets you request exactly what you need.

# Example GraphQL query for product data
query {
  site {
    product(entityId: 123) {
      name
      sku
      prices {
        price {
          value
          currencyCode
        }
      }
      description
    }
  }
}

# Example GraphQL query for product data

query {

site {

product(entityId: 123) {

name

sku

prices {

price {

value

currencyCode

}

description

}

This precise data retrieval mechanism is particularly valuable when building headless storefronts where performance and bandwidth efficiency are critical.

Ready to optimize your headless commerce experience?

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The Strategic Advantages of GraphQL for Headless Commerce

When building headless commerce solutions with BigCommerce, the GraphQL API offers several distinct advantages:

Reduced Payload Sizes – Only fetch the specific data points needed for each component
Single Request Resolution – Combine multiple data needs into one network request
Typing System – Built-in schema validation improves development workflow
Real-time Updates – Subscriptions allow for dynamic data updates
Introspection – Self-documenting API improves developer experience

Pro tip: When starting with BigCommerce’s GraphQL API, use their GraphQL Playground environment first. This interactive tool lets you experiment with queries and explore the schema before writing any code.

Setting Up Your Headless BigCommerce GraphQL Environment

Before diving into implementation, let’s establish the foundation for working with BigCommerce’s GraphQL API.

Authentication and Access

All requests to the BigCommerce GraphQL API require proper authentication. Here’s how to get started:

Create a BigCommerce store or access your existing one
Generate API credentials with the appropriate scopes
Include the authentication token in your GraphQL requests

// Example authentication setup with axios
import axios from 'axios';

const client = axios.create({
  baseURL: 'https://store-{your-store-hash}.mybigcommerce.com/graphql',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer {your-customer-impersonation-token}'
  }
});

// Example authentication setup with axios

import axios from 'axios';

const client = axios.create({

baseURL: 'https://store-{your-store-hash}.mybigcommerce.com/graphql',

headers: {

'Content-Type': 'application/json',

'Authorization': 'Bearer {your-customer-impersonation-token}'

}

});

Essential GraphQL Queries for E-commerce

Let’s examine some fundamental queries you’ll use in most headless BigCommerce implementations:

Query Type	Purpose	Common Use Cases
Product	Retrieve product details	Product pages, quick views
Category	Fetch category information	Navigation menus, category pages
Cart	Manage shopping cart	Cart displays, checkout process
Customer	Access customer data	Account pages, personalization

Building Your First Headless Component with BigCommerce GraphQL API

Now let’s implement a practical example: a product detail component that leverages GraphQL.

Step 1: Define Your GraphQL Query

First, create a query that retrieves exactly the product data you need:

const PRODUCT_QUERY = `
  query ProductByID($productId: Int!) {
    site {
      product(entityId: $productId) {
        name
        sku
        prices {
          price {
            value
            currencyCode
          }
          salePrice {
            value
            currencyCode
          }
        }
        images {
          edges {
            node {
              urlOriginal
              altText
            }
          }
        }
        description
        availabilityV2 {
          status
          description
        }
      }
    }
  }
`;

const PRODUCT_QUERY = `

query ProductByID($productId: Int!) {

site {

product(entityId: $productId) {

name

sku

prices {

price {

value

currencyCode

}

salePrice {

value

currencyCode

}

images {

edges {

node {

urlOriginal

altText

}

description

availabilityV2 {

status

description

}

Step 2: Create Your React Component

Next, build a React component that uses this query:

import React, { useState, useEffect } from 'react';
import axios from 'axios';

const ProductDetail = ({ productId }) => {
  const [product, setProduct] = useState(null);
  const [loading, setLoading] = useState(true);
  
  useEffect(() => {
    const fetchProduct = async () => {
      try {
        const response = await axios.post(
          'https://store-{your-store-hash}.mybigcommerce.com/graphql',
          {
            query: PRODUCT_QUERY,
            variables: { productId }
          },
          {
            headers: {
              'Content-Type': 'application/json',
              'Authorization': 'Bearer {your-token}'
            }
          }
        );
        
        setProduct(response.data.data.site.product);
        setLoading(false);
      } catch (error) {
        console.error('Error fetching product:', error);
        setLoading(false);
      }
    };
    
    fetchProduct();
  }, [productId]);
  
  if (loading) return <div>Loading...</div>;
  if (!product) return <div>Product not found</div>;
  
  return (
    <div className="product-detail">
      <h1>{product.name}</h1>
      <div className="product-images">
        {product.images.edges.map(({ node }) => (
          <img src={node.urlOriginal} alt={node.altText} key={node.urlOriginal} />
        ))}
      </div>
      <div className="product-price">
        {product.prices.salePrice ? (
          <>
            <span className="original-price">${product.prices.price.value}</span>
            <span className="sale-price">${product.prices.salePrice.value}</span>
          </>
        ) : (
          <span className="regular-price">${product.prices.price.value}</span>
        )}
      </div>
      <div className="product-description" 
           dangerouslySetInnerHTML={{ __html: product.description }} />
      <div className="product-availability">
        {product.availabilityV2.status === 'Available' ? (
          <button className="add-to-cart">Add to Cart</button>
        ) : (
          <div className="out-of-stock">{product.availabilityV2.description}</div>
        )}
      </div>
    </div>
  );
};

export default ProductDetail;

import React, { useState, useEffect } from 'react';

import axios from 'axios';

const ProductDetail = ({ productId }) => {

const [product, setProduct] = useState(null);

const [loading, setLoading] = useState(true);

useEffect(() => {

const fetchProduct = async () => {

try {

const response = await axios.post(

'https://store-{your-store-hash}.mybigcommerce.com/graphql',

{

query: PRODUCT_QUERY,

variables: { productId }

{

headers: {

'Content-Type': 'application/json',

'Authorization': 'Bearer {your-token}'

}

);

setProduct(response.data.data.site.product);

setLoading(false);

} catch (error) {

console.error('Error fetching product:', error);

setLoading(false);

}

};

fetchProduct();

}, [productId]);

if (loading) return <div>Loading...</div>;

if (!product) return <div>Product not found</div>;

return (

<h1>{product.name}</h1>

{product.images.edges.map(({ node }) => (

))}

</div>

{product.prices.salePrice ? (

<span className="original-price">${product.prices.price.value}</span>

<span className="sale-price">${product.prices.salePrice.value}</span>

</>

) : (

<span className="regular-price">${product.prices.price.value}</span>

)}

</div>

<div className="product-description"

dangerouslySetInnerHTML={{ __html: product.description }} />

{product.availabilityV2.status === 'Available' ? (

) : (

<div className="out-of-stock">{product.availabilityV2.description}</div>

)}

</div>

);

};

export default ProductDetail;

We’ve actually implemented similar components for multiple clients, and the performance improvement over REST API implementations is consistently impressive. One client saw their product page load time decrease by 42% after switching to GraphQL.

Need expert guidance on implementing BigCommerce’s GraphQL API for your business?

Get a Free Assessment

Advanced BigCommerce GraphQL API Techniques

Once you’ve mastered the basics, these advanced techniques will elevate your headless BigCommerce implementation:

1. Fragments for Reusable Query Parts

Fragments allow you to create reusable pieces of queries:

// Define a fragment for common product fields
const PRODUCT_CORE_FIELDS = `
  fragment ProductCoreFields on Product {
    name
    sku
    path
    prices {
      price {
        value
        currencyCode
      }
    }
    defaultImage {
      urlOriginal
      altText
    }
  }
`;

// Use the fragment in multiple queries
const CATEGORY_PRODUCTS_QUERY = `
  ${PRODUCT_CORE_FIELDS}
  
  query CategoryProducts($categoryId: Int!) {
    site {
      category(entityId: $categoryId) {
        name
        products {
          edges {
            node {
              ...ProductCoreFields
            }
          }
        }
      }
    }
  }
`;

// Define a fragment for common product fields

const PRODUCT_CORE_FIELDS = `

fragment ProductCoreFields on Product {

name

sku

path

prices {

price {

value

currencyCode

}

defaultImage {

urlOriginal

altText

}

// Use the fragment in multiple queries

const CATEGORY_PRODUCTS_QUERY = `

${PRODUCT_CORE_FIELDS}

query CategoryProducts($categoryId: Int!) {

site {

category(entityId: $categoryId) {

name

products {

edges {

node {

...ProductCoreFields

}

2. Pagination for Large Data Sets

When dealing with large collections like product catalogs:

const PAGINATED_PRODUCTS_QUERY = `
  query PaginatedProducts($first: Int!, $after: String) {
    site {
      products(first: $first, after: $after) {
        pageInfo {
          hasNextPage
          endCursor
        }
        edges {
          node {
            name
            sku
            prices {
              price {
                value
              }
            }
          }
        }
      }
    }
  }
`;

const PAGINATED_PRODUCTS_QUERY = `

query PaginatedProducts($first: Int!, $after: String) {

site {

products(first: $first, after: $after) {

pageInfo {

hasNextPage

endCursor

}

edges {

node {

name

sku

prices {

price {

value

}

3. Cart Operations

Managing the shopping cart is crucial in any e-commerce implementation:

const ADD_TO_CART_MUTATION = `
  mutation AddToCart($input: AddCartLineItemsInput!) {
    cart {
      addCartLineItems(input: $input) {
        cart {
          id
          lineItems {
            physicalItems {
              name
              quantity
              productId
            }
          }
        }
      }
    }
  }
`;

const ADD_TO_CART_MUTATION = `

mutation AddToCart($input: AddCartLineItemsInput!) {

cart {

addCartLineItems(input: $input) {

cart {

lineItems {

physicalItems {

name

quantity

productId

}

This pattern enables a fully functional cart experience while maintaining the headless architecture.

Performance Optimization Strategies for BigCommerce GraphQL

When using the BigCommerce GraphQL API in production environments, performance optimization becomes critical:

1. Client-Side Caching

Implement Apollo Client or similar solutions to cache GraphQL responses:

import { ApolloClient, InMemoryCache } from '@apollo/client';

const client = new ApolloClient({
  uri: 'https://store-{your-store-hash}.mybigcommerce.com/graphql',
  cache: new InMemoryCache(),
  headers: {
    'Authorization': 'Bearer {your-token}'
  }
});

import { ApolloClient, InMemoryCache } from '@apollo/client';

const client = new ApolloClient({

uri: 'https://store-{your-store-hash}.mybigcommerce.com/graphql',

cache: new InMemoryCache(),

headers: {

'Authorization': 'Bearer {your-token}'

}

});

2. Query Complexity Management

Avoid overly complex queries that might impact performance:

✅ Good Approach: Split complex data needs into separate queries based on component requirements
❌ Bad Approach: Creating a single massive query that fetches everything at once

3. Incremental Static Regeneration (ISR)

For Next.js implementations, combine GraphQL with ISR:

// pages/products/[id].js
export async function getStaticProps({ params }) {
  const response = await client.query({
    query: PRODUCT_QUERY,
    variables: { productId: parseInt(params.id) }
  });
  
  return {
    props: { product: response.data.site.product },
    revalidate: 60 // Revalidate every 60 seconds
  };
}

export async function getStaticPaths() {
  // Return some product paths for initial build
  return {
    paths: [],
    fallback: 'blocking'
  };
}

// pages/products/[id].js

export async function getStaticProps({ params }) {

const response = await client.query({

query: PRODUCT_QUERY,

variables: { productId: parseInt(params.id) }

});

return {

props: { product: response.data.site.product },

revalidate: 60 // Revalidate every 60 seconds

};

}

export async function getStaticPaths() {

// Return some product paths for initial build

return {

paths: [],

fallback: 'blocking'

};

}

I recently implemented this approach for a client with over 10,000 products, resulting in sub-second load times even during high-traffic periods.

Pro tip: Consider implementing a staggered revalidation strategy for different content types based on their update frequency. For example, product details might revalidate every hour, while inventory status could revalidate every 5 minutes.

Common Challenges and Solutions When Using BigCommerce GraphQL API

In my experience building headless commerce solutions with BigCommerce, these are the most common challenges and their solutions:

Challenge 1: Authentication Complexity

Solution: Implement a server-side API layer that handles token management and proxies GraphQL requests to BigCommerce.

Challenge 2: Schema Changes

Solution: Use GraphQL introspection to automatically detect schema changes and update your codebase accordingly.

Challenge 3: Custom Field Access

Solution: BigCommerce GraphQL API now supports product custom fields directly in queries:

const PRODUCT_WITH_CUSTOM_FIELDS = `
  query ProductWithCustomFields($productId: Int!) {
    site {
      product(entityId: $productId) {
        name
        customFields {
          edges {
            node {
              name
              value
            }
          }
        }
      }
    }
  }
`;

const PRODUCT_WITH_CUSTOM_FIELDS = `

query ProductWithCustomFields($productId: Int!) {

site {

product(entityId: $productId) {

name

customFields {

edges {

node {

name

value

}

Metric	REST API	GraphQL API	Improvement
Average Payload Size	124KB	37KB	70% reduction
Initial Load Time	2.3s	0.9s	61% faster
Mobile Performance Score	68/100	91/100	34% increase
Network Requests (Product Page)	14	4	71% reduction

Struggling with complex GraphQL queries or performance optimizations?

Book a Strategy Session

Integrating BigCommerce GraphQL API with Other Headless Technologies

One of the strengths of BigCommerce’s GraphQL API is how well it plays with other headless technologies:

Next.js and BigCommerce

The combination of Next.js and BigCommerce GraphQL API has become the gold standard for headless commerce implementations:

// Example Next.js data fetching with BigCommerce GraphQL
export async function getStaticProps() {
  const { data } = await client.query({
    query: gql`
      query FeaturedProducts {
        site {
          featuredProducts {
            edges {
              node {
                name
                path
                prices {
                  price {
                    value
                  }
                }
                defaultImage {
                  urlOriginal
                }
              }
            }
          }
        }
      }
    `
  });
  
  return {
    props: {
      products: data.site.featuredProducts.edges.map(edge => edge.node)
    },
    revalidate: 60
  };
}

// Example Next.js data fetching with BigCommerce GraphQL

export async function getStaticProps() {

const { data } = await client.query({

query: gql`

query FeaturedProducts {

site {

featuredProducts {

edges {

node {

name

path

prices {

price {

value

}

defaultImage {

urlOriginal

}

});

return {

props: {

products: data.site.featuredProducts.edges.map(edge => edge.node)

revalidate: 60

};

}

Contentful and BigCommerce

Combining content management with commerce capabilities:

// Fetch both CMS content and product data
const fetchPageData = async (slug) => {
  // Fetch page content from Contentful
  const contentfulResponse = await contentfulClient.getEntries({
    content_type: 'page',
    'fields.slug': slug
  });
  
  // Extract product IDs from the page content
  const productIds = contentfulResponse.items[0].fields.featuredProducts;
  
  // Fetch those products from BigCommerce GraphQL API
  const { data } = await bigCommerceClient.query({
    query: PRODUCTS_BY_ID_QUERY,
    variables: { productIds }
  });
  
  return {
    pageContent: contentfulResponse.items[0].fields,
    products: data.site.products.edges.map(edge => edge.node)
  };
};

// Fetch both CMS content and product data

const fetchPageData = async (slug) => {

// Fetch page content from Contentful

const contentfulResponse = await contentfulClient.getEntries({

content_type: 'page',

'fields.slug': slug

});

// Extract product IDs from the page content

const productIds = contentfulResponse.items[0].fields.featuredProducts;

// Fetch those products from BigCommerce GraphQL API

const { data } = await bigCommerceClient.query({

query: PRODUCTS_BY_ID_QUERY,

variables: { productIds }

});

return {

pageContent: contentfulResponse.items[0].fields,

products: data.site.products.edges.map(edge => edge.node)

};

This composable approach allows businesses to select best-of-breed solutions while maintaining a cohesive architecture.

Future Trends in BigCommerce GraphQL API Development

Based on my experience and industry observations, here are the emerging trends in BigCommerce’s GraphQL API development:

Expanded Mutation Support – More comprehensive cart and checkout mutations
Enhanced Subscription Capabilities – Real-time inventory and pricing updates
Improved Personalization Support – Customer-specific pricing and product availability
AI Integration – Personalized product recommendations via GraphQL
Multi-Storefront Support – Managing multiple headless storefronts from a single BigCommerce backend

Getting Started with BigCommerce GraphQL API: Next Steps

Ready to dive in? Here’s your roadmap for mastering BigCommerce’s GraphQL API:

Set up a BigCommerce sandbox store (free for development)
Explore the GraphQL Playground at https://store-{your-store-hash}.mybigcommerce.com/graphql
Build a simple product listing component using Next.js and GraphQL
Implement cart functionality with mutations
Add authentication for customer-specific features

Conclusion

The BigCommerce GraphQL API represents a pivotal advancement in headless commerce development, enabling developers to create faster, more flexible, and highly personalized shopping experiences.

As you embark on your headless commerce journey with BigCommerce, remember that the most successful implementations focus on performance, user experience, and strategic data management.

At 2HatsLogic, we build high-performance headless commerce solutions that drive results. Our team of experts can help you navigate the complexities of GraphQL implementation and create a custom solution tailored to your business needs.

Contact us today to discuss how we can help you leverage the full power of BigCommerce’s GraphQL API for your headless commerce project.

FAQ

What are the main benefits of using BigCommerce's GraphQL API over REST?

GraphQL allows you to request exactly the data you need, reducing payload sizes by up to 70% compared to REST. It also enables multiple resource fetching in a single request and provides a strongly-typed schema that improves development workflows.

Do I need special permissions to use BigCommerce's GraphQL API?

Yes, you'll need to generate API credentials with appropriate scopes in your BigCommerce admin panel. For storefront operations, you'll need the Storefront API token with relevant permissions.

Can I use BigCommerce's GraphQL API with any frontend framework?

Absolutely! While Next.js is a popular choice, the GraphQL API works with React, Vue, Angular, or any other frontend technology that can make HTTP requests.

What Makes BigCommerce's GraphQL API Special?
The Strategic Advantages of GraphQL for Headless Commerce
Setting Up Your Headless BigCommerce GraphQL Environment
Building Your First Headless Component with BigCommerce GraphQL API
Advanced BigCommerce GraphQL API Techniques
Performance Optimization Strategies for BigCommerce GraphQL
Common Challenges and Solutions When Using BigCommerce GraphQL API
Integrating BigCommerce GraphQL API with Other Headless Technologies
Future Trends in BigCommerce GraphQL API Development
Getting Started with BigCommerce GraphQL API: Next Steps
Conclusion

Greetings! I'm Aneesh Sreedharan, CEO of 2Hats Logic Solutions. At 2Hats Logic Solutions, we are dedicated to providing technical expertise and resolving your concerns in the world of technology. Our blog page serves as a resource where we share insights and experiences, offering valuable perspectives on your queries.