Agentic Commerce: Discover how to effectively integrate your products into the world of AI-powered shopping agents. With our comprehensive five-step plan for Smartstore retailers, you will receive a detailed guide to make your product data specifically available for AI systems. Learn how to maximize the reach of your products and position yourself at the forefront of modern shopping technology.

Foreword: The new commerce thinks dialogically

Online shopping is fundamentally changing. Instead of leaving customers alone with filters, categories, and checkout processes, AI agents come into play, which can completely take over the shopping experience – from understanding the search intent to automated purchase. Experts call this concept Agentic Commerce.

In the future, customers will no longer just say: "I'm looking for a black jacket," but instead:

"Find me a black softshell jacket for under 150 euros, ideal for hiking in autumn – no fast fashion, rather sustainable brands."

AI systems like ChatGPT, Perplexity.ai, or Google Gemini respond to such requests with concrete suggestions – provided they know your products.

For retailers using Smartstore, this means: Now is the time to prepare your product data so that it can be found, understood, and recommended by AI agents. How to do this is shown in our 5-step plan.

Step 1: Structure product data for AI

AI agents designed for product identification and comparison require well-structured and precise information. Only by providing clear, well-defined data can these intelligent systems function effectively and make accurate comparisons between different product options. Structured data helps AI agents capture relevant features and facilitates the comparison process, thereby improving the quality of the results.

Your tasks in Smartstore:

• Use uniform attribute identifiers (e.g., "Material", "Color", "Compatibility") in your catalog

• Optimize product titles and descriptions for natural language

• Use schema.org markup to provide structured data

• Include Alt-texts for images – many image AI systems use them

Practical example: Decathlon uses detailed, structured data in over 100 languages, including sustainability information, to be better indexed by Google Shopping AI.

Step 2: Provide product data feeds for AI systems

AI systems need access to current, complete product data, as this information is crucial for the performance and accuracy of the algorithms. Without a continuous flow of precise data, AI models cannot learn effectively or make accurate predictions. Furthermore, this access allows the systems to respond flexibly to market changes and adjust their analyses accordingly. A thorough and up-to-date dataset thus significantly increases the efficiency and added value of AI-supported applications.

Your tasks in Smartstore:

• Regularly export updated product feeds (CSV, XML, JSON)

• Use the Smartstore API for real-time provision of item data

• Product data* can be provided via its own feed endpoint, which can be read by AI applications (e.g., under smartstore.de/ai-catalog.json)

*This feed can be configured to include relevant product information, such as:

• Title and description

• Price and availability

• Categories

• Product images

• structured attributes (e.g., color, size, material)

Note on use by AI systems

Current large language models like ChatGPT or Perplexity.ai are not able to automatically recognize or periodically retrieve such feeds. Access to these data currently occurs only on request by users or through third-party applications explicitly programmed for this purpose.

Nevertheless, a structured product data feed provides an important foundation to:

• supply external AI systems with real-time data

• develop personalized agent solutions

• create the conditions for future integrations (e.g., via Agentic APIs)

Recommendation

We recommend that all store owners provide such a feed early on and update it regularly. This creates the technical prerequisites to make your products visible in AI-supported advisory systems and actively present in agent-controlled shopping scenarios.

Best Practice: Zalando has set up a developer portal through which AI systems and partner systems can retrieve structured data.

Step 3: Agentic SEO – writing for AI systems

In today's digital world, search engine optimization is undergoing a significant transformation. It is increasingly evolving towards a concept known as AI Engine Optimization (AEO). This change requires new strategies and approaches to meet the requirements of modern search engines.

Your tasks in Smartstore:

• Write FAQ formats as text blocks in product descriptions ("Is this jacket suitable for autumn tours?")

• Integrate comparison tables, use cases, and purchase recommendations

• Emphasize special features ("noise-reducing", "ideal for frequent drivers", "100% vegan")

Example: REI.com uses context-rich product descriptions ("Best for: Cold-weather bike commuters") – this helps AI systems with targeted product selection.

Step 4: Enable AI training & prompting

Take it a step further: Discover new opportunities that can help you enhance your business success. Train your own artificial intelligence to develop customized solutions and benefit from the comprehensive insights that the analysis of your specific product data can offer.

Your tasks:

• Create prompts and example dialogues ("Which windshield fits a BMW R1200 if I am tall?")

• Use GPT integration in Smartstore to train FAQ models directly in the backend

• Create an internal collection of AI-ready product questions & answers as a training basis for systems like GPT, Perplexity, Mistral

Role model: Amazon trains its internal AI "Rufus" with data from customer inquiries, product titles, and application contexts.

Step 5: Control, feedback & optimization

Only what we can actually measure can be specifically analyzed, monitored, and ultimately improved. By capturing concrete data, it is possible to check progress and make informed decisions to develop optimized solutions and ensure continuous improvements.

Your tasks:

• Track AI-based traffic (e.g., with UTM parameters from GPT links)

• Capture which questions lead users to your products

• Refine product data specifically at the application or target group level

• Use Smartstore Analytics & tools like Matomo for measuring success

Example implementation:

Matomo analyzes AI-generated traffic separately and creates specific product recommendations per target group (e.g., "Gifts for men over 50").

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Conclusion: Smartstore makes your products visible to AI

With Smartstore, you already have a future-proof platform to succeed in the age of Agentic Commerce. Thanks to its modular design, structured data exports, API interfaces, and GPT connectivity, you are well equipped to make your products visible to conversational AI. Whether via a GPT assistant, Perplexity dialog, or Google AI shopping – your products should be part of this new shopping world. With our five-step plan, you'll align structure, strategy, and visibility. And the best part: As a Smartstore retailer, you already have the tools that others still need to develop.

Do you have questions on this subject? Or would you like to send us your feedback? You can reach us via the contact form, by email at info@smartstore.com or by phone Monday through Friday between 10 a.m. and 4 p.m. at +4923153350.