Author: Olaf Kopp
Reading time: 5 Minutes

What is the Google Shopping Graph and how does it work?

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The Google Shopping Graph is an advanced, dynamic data structure developed by Google to enhance the online shopping experience. It integrates a vast amount of product information from various sources, including websites, reviews, inventory lists, and prices, to provide users with up-to-date and comprehensive information about products they search for online.

The Google Shopping Graph is the equivalent of the Knowledge Graph just for products.

How does the Google shopping graph work?

Here’s how the Google Shopping Graph works:

  1. Integration of Diverse Data Sources: Google collects product information from a wide range of merchants, brands, and other sources. This includes product details, prices, availability, reviews, and seller information.
  2. Dynamic Updating: The Shopping Graph is updated in real-time to reflect the latest information on price changes, stock levels, and new product reviews. This means users have access to the most current information when making decisions about their online purchases.
  3. Personalization and Recommendations: Based on search queries and user behavior, the Google Shopping Graph can deliver personalized product suggestions and deals. It can identify what users are searching for or need and present them with relevant products that match their interests.
  4. Integration into Google Services: The Shopping Graph is deeply integrated into other Google services, including Google Search and Google Shopping. This allows users to search for products directly through Google, make price comparisons, and complete purchases without leaving the platform.
  5. Support for Merchants and Brands: The Google Shopping Graph offers merchants and brands enhanced opportunities to showcase their products and connect with potential customers. By providing accurate and up-to-date product information, they can increase their visibility and improve sales opportunities.

Google’s Shopping Graph is the counterpart to the Knowledge Graph.

Product data and their relationships are organized in nodes and edges, where the nodes, the respective product entities and the edges represent the relationships to each other.

In summary, the Google Shopping Graph offers a powerful platform that helps users efficiently find and compare products, while simultaneously supporting merchants and brands in showcasing their offerings. By leveraging advanced technologies and integrating extensive data sources, it contributes to optimizing the online shopping experience for all parties involved.

What are the data sources for the Google shopping graph?

According to Google’s statements, possible sources are:

  • Youtube videos
  • Manufacturer Websites
  • Online shops and product detail pages (PDPs)
  • Google Merchant Center
  • Google Manufacturer Center
  • Product tests
  • Product reviews
Data sources Shopping Graph

For me the most important ressources are the merchant center and the structured and unstructured info on product detail pages. There should be the main focus for optimizing for the shopping graph.

Since the Google Manufacturer Center is rather unknown, here are some explanations.

What is the Google Manufacturer Center?

The Google Manufacturer Center is a tool offered by Google to give manufacturers the opportunity to feed detailed product information directly into Google’s shopping database. This information can then be displayed in various Google services, such as Google Shopping or in Google search results. The aim of the Manufacturer Center is to improve the display of products and increase the visibility and accuracy of product information, which can ultimately lead to a better customer experience when shopping online.

Manufacturers can upload information such as product images, titles, descriptions, variants, features and other specific details to the Manufacturer Center. This helps them maintain control over the branding of their products in the online environment. By providing accurate and comprehensive data, manufacturers can also increase the likelihood that their products will rank better in relevant searches.

The Manufacturer Center is particularly useful for brand owners or licensees who want to advertise their products directly on Google. It complements other Google advertising tools such as Google Ads and is an important resource for optimizing product presence in e-commerce.

Why the shopping graph should be the focus spot for ecommerce SEO?

The introduction of SGE rolls out a new era for e-commerce SEO.

“That’s because this new generative AI shopping experience is built on Google’s Shopping Graph, which has more than 35 billion product listings — making it the world’s most comprehensive dataset of constantly-changing products, sellers, brands, reviews and inventory out there.” Source: https://blog.google/products/shopping/shopping-graph-explained/

This switch puts the optimization of the shopping graph into the focus of e-commerce SEO.

The Shopping Graph as an ecommerce-specific addition to RAG

Google introduced the new Shopping experience as an interplay between Shopping Graph and LLMs. The methodology here is Retrieval Augmented Generation (RAG) with Graphs.

RAG stands for “retrieval-augmented generation” and is a technique in artificial intelligence, specifically in natural language processing. RAG combines two main components: information retrieval and generative language models.

The goal of RAG is to improve the quality and relevance of answers generated by language models by retrieving additional information from an external data source and using it to generate answers.

How RAG works:

  • Retrieval: First, a search query is made to an external database to find relevant information. This can be a collection of texts, databases, graph databases or any other form of unstructured and structured data.
  • Augmentation: The retrieved information is then fed as context into the generative model, which then generates a detailed and informed response.

The Google Shopping Graph can be a valuable source of information for RAG-based systems, especially in ecommerce and online shopping applications, such as search engines.

Here are some possible roles of the Shopping Graph in a RAG system:

  • Improving product research: For a product-specific query, a RAG system could pull relevant information from the Shopping Graph to generate more precise and contextually appropriate responses. For example, it could integrate specific product recommendations, availability data or pricing information.
  • Personalized recommendations: The Shopping Graph could be used to generate personalized shopping recommendations based on the user’s specific interests and behavior stored in the Shopping Graph data.
  • Supporting interactive queries: In an interactive chatbot scenario, the Shopping Graph could help respond to follow-up questions by providing additional product details or alternative suggestions based on the initial recommendations.
  • Ratings and reviews integration: The Shopping Graph could also be used to include ratings and reviews in the generated responses, increasing the recommendations’ quality and usefulness.

Overall, the Shopping Graph can be key in optimizing RAG-based systems such as Google’s AI Overviews through its rich and structured information about products and their relationships.

About Olaf Kopp

Olaf Kopp is Co-Founder, Chief Business Development Officer (CBDO) and Head of SEO & Content at Aufgesang GmbH. He is an internationally recognized industry expert in semantic SEO, E-E-A-T, LLMO, AI- and modern search engine technology, content marketing and customer journey management. As an author, Olaf Kopp writes for national and international magazines such as Search Engine Land, t3n, Website Boosting, Hubspot, Sistrix, Oncrawl, Searchmetrics, Upload … . In 2022 he was Top contributor for Search Engine Land. His blog is one of the most famous online marketing blogs in Germany. In addition, Olaf Kopp is a speaker for SEO and content marketing SMX, SERP Conf., CMCx, OMT, OMX, Campixx...

COMMENT ARTICLE



  • Fabian

    13.06.2024, 10:12 Uhr

    Thanks Olaf for the great article.
    One question about the Manufacturer Center for a specific situation:
    If a manufacturer with an online shop is not able to set up the Merchant Center and Google Shopping due to legal restrictions: Do you think it makes sense to feed the Manufacturer Center with product data to improve visibility in SGE and normal product search results?
    All the best,
    Fabian

    Reply

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