How one can Get Your Product Pages Prepared for Agentic AI

Have you learnt how individuals are discovering your merchandise? Not way back, that reply was easy: Google, Amazon, or your web site’s search operate.

As we speak?

58% are utilizing generative AI instruments instead of conventional search.

Generative AI and agentic AI instruments are more and more frequent, enabling buyers to get fast, personalised suggestions. With this shift in search habits comes an growing significance to have agentic commerce-ready product pages.

This wouldn’t current an issue, have been it not for one easy truth: not one of the ecommerce leaders BigCommerce surveyed stated their product pages are completely prepared for agentic AI.

Most product pages are constructed for human readers, not for the structured information and alerts AI brokers depend on to floor merchandise.

People are nice, however with out agent legibility — the act of guaranteeing a web page has the appropriate schema, markup, and information fields — AI brokers gained’t be capable of floor your merchandise for the 58% already embracing AI-powered search.

Main gamers within the AI house are already specializing in this, with greater than 20 distributors partnering with Google to launch the Common Commerce Protocol (UCP), and OpenAI launching its personal Agentic Commerce Protocol (ACP).

The excellent news: You can begin getting your product pages prepared for agentic AI and agentic commerce right now.

The even higher information?

Early adopters have an opportunity to get forward.

What’s agentic AI?

At its core, agentic AI is any AI-driven system — like OpenAI, Gemini, Copilot, or Perplexity — that performs a job for a person by pulling from pure language and information.

Within the case of ecommerce, agentic AI can energy procuring processes, with customers in a position to punch in a request or ask for a suggestion, which the agent fulfills. Platforms like BigCommerce allow the structured product information these programs depend on to precisely floor and advocate merchandise.

A search engine can ship suggestions based mostly on the question entered by the person, their location, and their search historical past (relying on the search engine). The information that’s accessible a couple of explicit product completes the opposite half of the puzzle — AI does it finest to match essentially the most related product to the person’s search.

AI procuring brokers are able to giving extra private suggestions due to:

• Contextual information: Quite a few datasets, from product web page information to social media to product availability, that informs a selected product suggestion.

• Historic information: If the appropriate software programming interface (API) is in place, agentic AI can pull a consumer’s historic buy historical past from a retailer, additional informing and personalizing any suggestions.

• Actual-time information: Lastly, agentic AI makes use of real-time information, pulling in every little thing from the phrases somebody used, their sentiment, prior questions, gadgets of their cart, and extra.

The above is simply scratching the floor.

Already, AI can energy agentic funds for providers or merchandise by way of fast chat engagements, pull monitoring information for shipments, provide worth comparisons, and supply worth by way of your entire procuring journey.

Nonetheless curious how agentic AI is shaping ecommerce as an entire?

Don’t miss this piece on how agentic AI is driving a extra seamless procuring expertise.

Agentic AI appears to be like on the web and content material in a different way than people, so it ought to come as little shock that AI procuring workflows differ as nicely. Agentic AI procuring differs from human conduct by compressing the standard multi-step shopping for journey right into a single interplay.

A standard human-driven funnel often goes one thing like:

• Land on a product web page by means of advertising and marketing, social media put up, e mail, and so on.

• Click on the product and proceed searching or add it to cart

• Go to checkout and full the buying course of

An agentic AI procuring course of, however, appears to be like extra like:

Moreover, there’s the potential for agent-to-agent (A2A) commerce. On this scenario, somebody prompts an agent, which ends up in that agent prompting one other agent to finish a special set of actions.

For instance, a buyer might use one AI agent to assist them discover a product they want. That agent might then negotiate costs with one other agent, leading to a accomplished order.

Sound far-fetched?

See for your self how A2A commerce is already taking maintain, right here.

The position of product pages in agentic AI

Agentic-powered procuring assistants are clearly utilizing plenty of information to assist buyers discover their subsequent pair of trainers or new favourite wine. So, how do product pages match into this combine?

With a view to present their providers and assist folks full purchases, agentic AI pulls a couple of forms of product web page information:

• Structured: Catalog APIs, product feeds, SKUs, pricing information, and so forth.

• Semi-structured: Scraped product element web page (PDP) information, schema markup, and even HTML information from product pages.

• Unstructured: Buyer critiques, social posts, photographs, name recordings, and different user-generated content material.

Not solely are these AI assistants altering the product discovery course of, they’re altering what it means for retailers to have detailed product pages.

You’re now not writing product pages with solely your prospects in thoughts, but additionally numerous AI platforms. Any of your product feeds, APIs, or schema markup are truthful recreation to an agentic AI bot.

Psst. Don’t miss this in-depth look at how agentic AI finds merchandise.

How one can optimize your product pages for AI brokers

Initially, your product pages ought to all the time put the human first. Write for folks, converse truthfully and clearly, and let your model voice shine.

Okay, now that that’s out of the best way, how do you go about writing for ChatGPT, Gemini, Copilot, and the remainder of the gang?

At Commerce, we use a three-milestone framework to place agentic readiness into perspective:

• Shopper → Service provider: Is your information seen and full for the patron?

• Shopper → Agent: Can your merchandise be advisable confidently by AI?

• Agent → Agent: Can your infrastructure help AI-led transactions?

Merely put: agentic readiness means having product pages that are perfect for buyers and brokers.

Now, how do you get there?

#1 Enrich your product attributes and metadata.

Regardless of the supplier, agentic AI programs all the time depend on full, descriptive information that aligns with a consumer’s intent or immediate.

Fortuitously, the identical product fields that assist agentic AI fulfill a person’s request, additionally make for a greater person expertise in your web site.

Be sure that product attributes are clearly described and set aside, not buried in paragraph copy, clearly highlighting what supplies a product is manufactured from, its dimension, use circumstances, and so forth.

Notice the under instance and the way the left copy is mild and simple to overlook, whereas the appropriate makes use of daring font and clear, highly effective phrases.

When unsure, leverage instruments that will help you with this job.

For instance, Feedonomics can routinely help with Google Product Class assignments, whereas additionally producing agentic-ready titles, descriptions, options, and product metadata.

#2 Implement complete Schema.org structured information.

Schema markup information isn’t new, as structured information has been used to help with discovery by the likes of Google, Bing, and others for years.

However, the sport has modified.

You may’t neglect basic schema finest practices, however you should give on-site structured information, like JSON-LD markup, some love, too.

Do your due diligence by offering as a lot element as attainable throughout key Schema.org markup sorts:

As a basic rule of thumb, you must audit your prime 50 product pages in opposition to Schema.org core necessities, checking that the above fields are detailed and up-to-par.

#3 Write product content material for each people and machines.

As soon as once more, even when your aim is to be ready for when prospects use AI to seek out you, you continue to need to write content material that’s match for people, too.

You may accomplish this by placing into place a couple of practices:

• Write clear product titles that make sense within the context of a conversational question, and keep away from key phrase stuffing.

• Use descriptions to reply agentic questions, together with: Who is that this product for? When would you employ this? What downside does the product resolve? What makes the product totally different?

• Don’t disguise crucial product particulars inside PDF recordsdata, JavaScript-rendered content material, photographs, and different forms of recordsdata AI crawlers can’t entry.

As soon as once more, don’t be afraid to leverage instruments for help right here.

As an illustration, Feedonomics can routinely generate AI-optimized product copy, and at scale.

#4 Keep clear, standardized formatting throughout your catalog.

Consistency is essential the place successful over agentic AI is anxious. Ensure you use the identical formatting throughout:

Not solely is the above consistency vital for agentic AI, it additionally makes it simpler to include automation by way of product info administration (PIM) instruments and stock administration programs.

#5 Preserve your information synchronized and up to date.

Up-to-date information can solely ever be an excellent factor in ecommerce, powering automation, guaranteeing prospects get the most recent information when searching your retailer, and within the case of agentic AI — serving to AI discover essentially the most related outcomes for customers.

Repeatedly test that your pricing, stock, descriptions, and different datasets are up-to-date throughout the board.

There are numerous ecommerce instruments that may assist with near-real-time information syncs, from PIM for updating product descriptions to stock programs for updating inventory to Feedonomics, which routinely syncs product information throughout your platform.

Sustaining always-up-to-date information could sound like a giant ask, nevertheless it’s definitely worth the effort. Outdated information will result in a poor buyer expertise, destructive critiques, and additional deprioritization of your merchandise by AI.

#6 Prioritize critiques, rankings, and third-party validation.

Don’t neglect: AI brokers love unstructured information, together with critiques and rankings on third-party websites.

Ensure you’ve received a treasure trove of this unstructured information for brokers, and:

• Encourage prospects to go away product critiques

• Present low-friction overview varieties by way of e mail that make it simpler to go away suggestions

• Verify that AggregateRating is applied in your Schema markup

Bots aren’t the one ones studying critiques, nonetheless; 95% of buyers take a look at critiques whereas deciding on a product.

By pushing for extra critiques, you’re not solely serving to AI discover your web site, but additionally serving to prospects store with confidence.

#7 Guarantee multichannel consistency.

Agentic AI isn’t notably nice at enjoying a recreation of phone.

You want constant information and messaging throughout all fronts, in any other case AI may cross your merchandise up when fetching suggestions for customers.

Preserve costs, descriptions, availability, and different datapoints constant throughout all of your marketplaces, from your individual web site to Amazon to anyplace else your merchandise are offered to keep away from AI penalties.

That is one other space the place instruments might help.

Feedonomics focuses on utilizing your ecommerce platform as a single supply of reality, after which disseminating that info throughout your omnichannel presence.

Nonetheless want just a little extra context?

Concern not — uncover how agentic AI ranks and recommends merchandise right here.

UCP, ACP, and the rising protocol panorama

Agentic AI remains to be an emergent house, and with it are emergent protocols that intention to standardize how ecommerce manufacturers interact with the sort of AI.

Google and OpenAI provide their very own protocols with distinctive necessities and perks, however each intention to perform an analogous aim: present ecommerce companies with a solution to simply and meaningfully embrace agentic AI.

Google’s Common Commerce Protocol (UCP).

Google’s UCP was introduced January 2026, giving ecommerce companies a standardized strategy for leveraging agentic AI.

Google partnered main manufacturers within the ecommerce house to create UCP, with endorsements from greater than 20 companions. The tip result’s a protocol that options:

• A structured framework for agentic AI use whereas guaranteeing retailers personal their information

• Protection for the complete commerce journey, from uncover to checkout to post-purchase

• Native checkout help for Google Gemini and Google AI mode

• Compatibility with the Brokers Funds Protocol (AP2), Mannequin Context Protocol (MCP), and Agent2Agent (A2A)

UCP already lowers the limitations to entry for these eager to get into agentic AI. BigCommerce and Feedonomics are additional reducing these limitations by actively working towards full integration.

Need much more information on Google’s UCP? Get an in-depth take a look at UCP and what this implies for ecommerce, right here.

OpenAI’s Agentic Commerce Protocol (ACP).

OpenAI, recognized for ChatGPT and largely pioneering generative AI, can be providing a standardized approach for ecommerce manufacturers to leverage agentic AI with their ACP.

OpenAI’s ACP was launched in 2025 in partnership with Stripe, and focuses totally on Immediate Checkout inside ChatGPT.

The OpenAI ACP works by pulling from a service provider’s structured product information to energy the agentic aspect of issues, whereas Stripe features because the fee processor.

Study extra concerning the OpenAI ACP, and see how BigCommerce can seamlessly combine with this agentic effort right here.

What these protocols imply to your product pages.

Two protocols, two totally different firms, and probably extra protocols on the best way. What’s an ecommerce enterprise to do?

It is a uncommon second the place you don’t have to select — put together for each protocols as an alternative.

Every protocol focuses on totally different areas, with Google prioritizing a holistic commerce expertise and OpenAI prioritizing the checkout course of, however they every require clear product information.

By making ready for each you’re receiving a couple of advantages:

• A lot of the optimization required for ACP and UCP is protocol-agnostic, that means any of that work will doubtless carry ahead into future protocols that emerge as nicely.

• Each protocols require clear information, as does agentic AI as an entire. By making ready for these protocols you’re setting your self up for a smoother transition into an agentic AI-driven future.

• Many ecommerce platforms, like BigCommerce, profit from structured information, offering additional automation throughout workflows and additional effectivity positive factors in your finish.

In brief: there’s no hurt in specializing in each protocols.

Ultimately, you’re solely giving your self a aggressive benefit within the digital commerce house, and growing the possibilities of a smoother transition into any future protocols, as nicely.

How BigCommerce and Feedonomics make your product information AI-ready

Plugging into the agentic AI ecosystem can really feel overwhelming, nevertheless it doesn’t need to be.

Each BigCommerce and Feedonomics can simplify the method, whereas offering advantages that stretch nicely past agentic AI.

BigCommerce because the system of document.

Keep in mind all that structured product information agentic AI wants?

Effectively, BigCommerce isn’t only a complete ecommerce platform, however a unified, single supply of reality to your product.

BigCommerce can act because the system of document for agentic AI by offering:

• A complete SKU and product catalog

• A present supply of reality, because of real-time stock and order syncing

• Multi-storefront localization, supplying you with extra alternatives to floor in agentic outcomes

• Native Web optimization options, together with Web optimization-friendly URLs, automated sitemaps, and microdata

• Unified product catalog and SKU administration; real-time stock and order sync

• GraphQL Storefront API and REST administration APIs that help agentic patterns

Agentic AI requires clear, complete information, and BigCommerce might help you ship precisely that.

To not point out, BigCommerce empowers you to vary on the fly with headless commerce, increase by way of omnichannel efforts, and effectively handle your corporation irrespective of how large it will get.

Feedonomics because the execution and development engine.

BigCommerce can present a single supply of reality the place product information is anxious.

What about maintaining all that information clear and error free?

Feedonomics can syndicate information throughout greater than 100 channels, not solely stopping multi-channel development from ever limiting you, but additionally powering agentic AI with:

• Actual-time error monitoring and information QA

• Marketing campaign particular feed segmentation and product filtering for organizing information

• FeedAI: An clever Google Product Class task device utilizing machine studying

• GenAI instruments for producing agentic-ready product titles, descriptions, and options from metadata

Agentic AI searches excessive and low for the very best responses.

With Feedonomics, you’ll be able to extra simply handle your product presence throughout numerous channels, making it simpler for agentic AI — and people — to seek out you.

BigCommerce and Feedonomics: Agentic prepared right now

Thriving within the agentic commerce house requires information that’s each complete, and of top quality.

BigCommerce and Feedonomics aren’t any strangers to AI, having teamed up with Perplexity in 2025 to deal with AI readiness for merchandise.

This dynamic duo might help you prepare for agentic AI, too.

BigCommerce can present the muse, whereas Feedonomics might help you leverage your information to the fullest throughout dozens of channels.

Houzer, a U.S.-based kitchen sink and tap producer, is a robust instance of how BigCommerce and Feedonomics can work collectively to help scalable, high-quality product information.

With a long time of expertise promoting by way of marketplaces like Amazon, Residence Depot, and Wayfair, Houzer lacked a direct-to-consumer (DTC) ecommerce presence and relied on an outdated, largely informational web site. This made it troublesome to handle product information successfully, syndicate listings throughout channels, and help a rising, complicated catalog.

Already working throughout a number of gross sales channels, Houzer wanted a centralized system to launch a DTC expertise whereas sustaining consistency and accuracy throughout its product information.

By implementing BigCommerce as its ecommerce basis and integrating Feedonomics, Houzer was in a position to launch a totally practical DTC web site in beneath 60 days whereas centralizing and optimizing its product information throughout channels.

Now?

Houzer has remodeled its ecommerce operations, attaining: 

And, they’ve completed all this whereas sustaining constant, high-quality product information throughout its omnichannel presence.

“The platform itself permits a really fast standup of a totally practical V1 of their web site. That enabled us to take this legacy model and construct a completely new web site with a completely new enterprise mannequin in six weeks.”

The ultimate phrase

Agentic commerce isn’t taking place sooner or later — it’s right here proper now.

Not satisfied?

By 2030, agentic AI could possibly be enjoying a job in an estimated $3-5 trillion in transactions around the globe.

Agentic AI will solely develop in capabilities, and the aggressive edge it gives right now will change into commonplace the longer you wait. By taking steps to arrange your product pages for agentic commerce right now, you’re making ready your self for a future the place this know-how will probably be more and more vital.

Not solely this, however identical to the early days of Web optimization and firms who embraced finest practices, firms who contain themselves in agentic AI right now will solely change into extra well-known within the house over time.

Don’t tackle the burden of getting agentic prepared all by your self.

See how BigCommerce gives the only supply of product reality AI wants, whereas Feedonomics provides you the tactical scalability you should increase into the long run.

FAQs about product pages and agentic AI

What’s agentic AI in ecommerce?

Agentic AI in ecommerce is a selected sort of AI that responds to a buyer immediate, researching, evaluating, and even buying merchandise on their behalf as soon as a match has been discovered.

On the person finish, agentic AI is just like a chatbot, requiring textual content inputs. The place performance is anxious, agentic AI is way extra succesful than chatbots, nonetheless.

How do AI brokers consider product pages?

AI brokers function by combing by way of structured information, semi-structured information, and unstructured information. In apply, this consists of data from product feeds, schema, scraped PDP content material, and user-generated content material like critiques.

What structured information do I would like on my product pages for AI?

Agentic AI requires a number of sorts of structured information on product pages, largely pulled from Schema.org sorts, together with:

• Title

• Description

• SKU

• Worth

• Availability

• Evaluate/AggregateRating

• MerchantReturnPolicy

• Provide

Product information must be in JSON-LD format, as that is essentially the most broadly accepted and will increase the probability that agentic AI bots discover your merchandise.

What’s the distinction between UCP and ACP?

Google’s Common Commerce Protocol (UCP) is an in depth protocol, masking discovery by way of post-purchase, whereas OpenAI’s Agentic Commerce Protocol (ACP) focuses on the fee and checkout processes.

Whereas the 2 protocols differ, every of them requires structured product information. It’s attainable and advisable to adjust to each protocols, as this will increase your possibilities of agentic discovery.

How does Feedonomics assist with agentic AI readiness?

Feedonomics might help with agentic AI readiness by performing as a strategic lever to your product information, serving to with information enrichment, feed syndication throughout channels, real-time multichannel syncing, and AI instruments to streamline information refinement.

Feedonomics is on the forefront of AI readiness within the product sphere, with lively partnerships with Google, OpenAI, and others.

Do I must rebuild my ecommerce web site for agentic AI?

You don’t need to rebuild your ecommerce web site or replatform for agentic AI, however can as an alternative deal with optimizing your product information layer. BigCommerce can simplify this by offering an open structure that acts as a single supply of reality for product information, whereas Feedonomics can deal with the heavy information lifting with streamlined feed administration.