A Tale of Two Commerce Protocols

In previous posts I discussed the advent of Agentic Commerce and how that is primed to become the new way to shop for products online.

In order to enable the AI platforms to be aware of your brand presence and product information there are a number of strategies and techniques, specifically GEO (Generic Engine Optimization) and AEO (Answer Engine Optimization), that can attract the AI bots to prefer your brand and recommend your products within the many conversations that customers are now having with AI applications.

GEO is a broad strategy that involves a number of techniques that involve changes in how you write product content and optimize your websites so that AI will pick you first as the authoritative source for the answers within the Agentic Commerce experience.

Very recently a couple of new developments have emerged that both sound like it’s attempting to answer a similar question. Namely OpenAI’s Agentic Commerce Protocol (or ACP) and Google’s Universal Commerce Protocol (or UCP).

OpenAI’s ACP is an open, cross-platform protocol designed to enable shopping and payments directly within AI assistants, independent of any single platform or user interface. It allows AI agents to discover products via merchant-provided feeds, surface accurate pricing and availability, and autonomously initiate checkouts on the user's behalf without redirecting them to an external website.

The checkout process uses secure, delegated payment tokens (which are single-use, time-bound, and amount-restricted), while ensuring that the merchant retains full control over settlement, refunds, chargebacks, and compliance. The first implementation of this protocol is the Instant Checkout experience within ChatGPT.

Google’s UCP is a new open standard designed to establish a common language that allows AI agents, businesses, and payment providers to work together across the entire shopping journey from product discovery to post-purchase support. They also have massive Industry Endorsement collaborating with the likes of Etsy, Shopify, Best Buy and Walmart (US) who are either implementing, or have gone live with AI Agents.

While it is designed to be compatible with other agentic protocols, UCP is initially rolling out exclusively on Google-owned surfaces, such as Search AI Mode, Google Shopping, and the Gemini App. It enables shoppers to buy from eligible retailers directly during product discovery without leaving Google, utilizing Google Pay for seamless transactions while the retailer remains the seller of record.

Why ACP/UCP are More Helpful Than AIO/GEO

While Artificial Intelligence Optimization (AIO) and Generative Engine Optimization (GEO) are critical strategies, they are fundamentally focused on top-of-funnel visibility. AIO and GEO ensure that an AI model correctly parses, embeds, and cites your brand as the "source material" when answering a user's question. However, simply getting found is only the first step of the commerce journey.

ACP and UCP are arguably more helpful because they bridge the gap between discovery and execution, transforming the entire commercial funnel:

• Moving from Recommendation to Action: AIO/GEO might prompt an AI to recommend your product, but the user still has to navigate to your site, browse, add to cart, and manually checkout. ACP and UCP grant the AI "agency" to act on the user's intent and execute the purchase directly within the conversational interface.

• Frictionless Shopping: Traditional e-commerce is linear and rigid (search → browse → filter → product page → cart → checkout). ACP and UCP collapse these steps into a natural dialogue, drastically reducing friction and lowering cart abandonment.

• Capturing Immediate Revenue: By allowing shoppers to move from intent to purchase without breaking context or leaving the app, these protocols turn high-intent discovery moments directly into revenue.

In short, AIO and GEO help AI talk about your product, but ACP and UCP allow AI to buy your product on the customer's behalf.

Which one to choose?

Both OpenAI's Agentic Commerce Protocol (ACP) and Google's Universal Commerce Protocol (UCP) share the same overarching goal: to reduce friction in the shopping journey by allowing AI agents to handle product discovery and checkout seamlessly, without redirecting the user to an external website.

However, they differ significantly in their execution environments, how they handle payments, and their initial scope.

OpenAI’s Agentic Commerce Protocol (ACP)

• Design & Environment: ACP is an open, cross-platform protocol built to enable shopping and payments directly within AI assistants. It is designed to be independent of any single platform, user interface, or distribution surface. Currently, its primary implementation is the "Instant Checkout" experience inside ChatGPT.

• Payment Mechanism: ACP initiates checkout on the user's behalf using delegated payment tokens. These tokens are highly secure because they are single-use, time-bound, and amount-restricted.

• Merchant Role: In this model, merchants maintain complete control over the transactional backend, retaining responsibility for settlement, refunds, chargebacks, and compliance.

Google’s Universal Commerce Protocol (UCP)

• Design & Environment: UCP is pitched as a new open standard designed to support the entire shopping lifecycle, from product discovery and buying to post-purchase support. However, unlike ACP's cross-platform focus, UCP is initially being rolled out exclusively across Google-owned surfaces, including Search AI Mode, Google Shopping, and the Gemini App.

• Payment Mechanism: Instead of delegated tokens, UCP leverages Google Pay to complete transactions natively during product discovery, with PayPal support planned for the future.

• Additional Features: Alongside UCP, Google launched a feature called "Business Agent," which allows retailers to engage shoppers conversationally and enable direct purchases right within Google Search.

The Core Differences

• Where the Shopping Happens: ACP enables agent-led commerce primarily across the OpenAI ecosystem as a standalone destination, while UCP currently focuses on reducing checkout friction specifically within Google's massive search and discovery surfaces.

• Coexistence Over Competition: Google designed UCP to be compatible with other agent-to-agent standards and protocols. This means the two protocols are not necessarily meant to replace one another, but rather to coexist. UCP helps convert high-intent shoppers who are actively searching on Google, while ACP opens the door to new demand where AI chat assistants act as the shopping destination.

So it’s not like the old VHS/Beta video wars of the 80s. The question isn't which protocol "wins" it's whether your product data (and infrastructure) is ready to feed both. The reality is that you may need to support a multi-protocol ecosystem, just like supporting Apple Pay, Google Pay, and PayPal today. We are entering a multi-agent, multi-protocol world where structured product data is the "source code" of commerce.

Measuring Success in the Age of GEO

I am back after missing a week due to the day job! So, you devised your perfect GEO/AEO strategy and started writing your product content in conformance with the methodologies outlined in previous posts . Now comes the million-dollar question: Is it actually working?
Auditing your performance in the age of AI is tricky because the old scoreboard (Google Analytics) might be lying to you. Traffic might go down while your brand awareness goes up—simply because the AI answered the customer’s question without them ever needing to visit your site.
Here is a no-nonsense, friendly guide on how to audit your GEO and AEO efforts, the tools you can use, and how to fix the cracks in your strategy.

1. The "Ego Surf" Audit (Ask the AI)

The simplest way to audit your standing is to go directly to the source. You need to see if the "Generative Engines" (ChatGPT, Perplexity, Gemini, Claude) actually know who you are. Also, bare in mind that the AI models don’t reindex as often as the Google Search Index, so this is a long game.
The Action: Treat the AI like a potential customer.
Brand Audit: Ask, "What is {Your Company Name}?" or "What does {Your Company} sell?" If the AI hallucinates or says "I don't have enough information," you have an AIO (AI Optimization) problem. It means your digital footprint is too small or inconsistent.
Category Audit: Ask, "Who provides the best Service in {City}?" or "Compare {Your Product} vs {Competitor}".
The Goal: You aren't just looking for a mention; you are looking for sentiment and accuracy. Does the AI recommend you? Does it cite the right features? If it recommends a competitor, analyze why—is their pricing clearer? Do they have more reviews?

2. The Metric Shift: From Clicks to "Inclusion"

In traditional SEO, we obsess over Click-Through Rates (CTR). In AEO and GEO, we care about Source Inclusion and Visibility Scores.
Zero-Click Visibility: You need to track how often you appear in "Featured Snippets," "People Also Ask" boxes, or AI overviews. Tools like AIOSEO (for WordPress) or SEMrush can help track these specific SERP features.
Position-Adjusted Visibility: This is a fancy term for a simple concept: Did the AI mention you early in its answer? Research suggests that visibility is measured not just by if you were cited, but where and how much of your content was used. You want to be in the first paragraph of the AI’s script, not a footnote at the bottom.

3. The Toolkit: What to Use

You don't need to invent new technology to do this, but you do need to use existing tools differently.
AIOSEO (All In One SEO): If you are on WordPress, this plugin has a "Search Statistics" module. It helps you track keyword rankings specifically for content performance and identifies "content decay" (when your old posts stop ranking and need a refresh).
Using tools such as AIClicks and Profound, track AEO performance and monitor which products appear in AI citations, which content gets extracted most often, and what language patterns work best. Use these insights to refine your content templates, adjust attribute structures, and improve descriptions across similar products. Once you identify effective AEO patterns.
Question Research Tools: Use AnswerThePublic, SEMrush, or even your own customer support tickets. These tell you exactly what questions people are asking. If you aren't answering these specific questions on your site, you are invisible to the Answer Engine.
GPT-4 (as an Auditor): You can actually feed your content into ChatGPT and ask it to evaluate it against Google’s E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) standards. Ask it, "How would you rate this article’s authority compared to Competitor {URL}?".

4. Corrective Actions: How to Fix Your Strategy

So, you audited your site and the AI is ignoring you. Here is how to get its attention.

Fix #1: The "Answer First" Adjust (AEO)

If you aren't winning featured snippets or voice search results, your content is likely buried.
The Fix: Rewrite your headers as questions (e.g., "How long does a drill battery last?") and provide the answer immediately in a concise, 40–60 word paragraph directly underneath. No fluff, no backstory. Just the answer.
Technical Boost: Use Schema Markup (like FAQPage schema). This is code that screams to the robot, "Here is the answer!" Tools like AIOSEO can generate this for you without you needing to code.

Fix #2: The "Citation Magnet" Move (GEO)

If the AI summarizes the topic but doesn't mention you, your content lacks authority signals.
The Fix: Add hard data. Don't say "Our software is fast." Say, "Our software processes data 30% faster than the industry average," and cite a source or internal study. Adding citations and statistics can increase your visibility in AI answers by 30-40%.
Quote Experts: Include direct quotations from industry leaders or your own experts. AI loves to pull quotes to build its "script".

Fix #3: The "Consensus" Cleanup (Off-Page Audit)

This is the big one. AI doesn't just trust your website; it trusts what the rest of the internet says about you. If you have great content but terrible reviews on Yelp or G2, the AI might skip you.
The Fix: Audit your N.A.P. (Name, Address, Phone) across all directories. Inconsistency confuses the AI. Then, actively drive happy customers to leave reviews on third-party sites. The AI looks for "consensus" across the web to verify you are a legitimate recommendation.

Summary Checklist

Ask the AI: regularly prompt ChatGPT/Perplexity to see how it describes your brand.
Track Snippets: Monitor how often you appear in "People Also Ask" or AI Overviews.
Inject Facts: Audit your top pages—if they are full of fluff, replace them with stats, tables, and direct answers.
Check the Vibe: Ensure your off-site reviews and directory listings are squeaky clean.

If you do this, you stop chasing clicks and start building the "influence" that gets you cited as the expert, but remember that this is built over time. Be patient!

Mastering the Art of Answer Engine Optimization (AEO)

Think of Answer Engine Optimization (AEO) as a sub genre of GEO which I explored in my previous post while we walk through some of the details and have a closer look into what it’s all about…

The Cheat Sheet: AEO vs. GEO

Before we dive in, let’s clear up the alphabet soup. Both strategies want AI to notice you, but they play different positions on the field.

• AEO (Answer Engine Optimization): This is about being the direct answer. When someone asks a specific question (e.g., "How long does a drill battery last?"), you want the AI to read your specific sentence verbatim as the solution. It’s about winning the "Featured Snippet" or the voice answer on Alexa/Siri.

• GEO (Generative Engine Optimization): This is about being the recommendation. When someone asks a complex question (e.g., "Best drills for contractors"), you want the AI to synthesize your content with others and cite you as an authority in its custom-written essay. It’s about influence and reputation.

Think of it this way: AEO is writing the summary on the back of the book so the librarian can instantly answer a quick question. GEO is ensuring your book is cited in the librarian's research paper.

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AEO: The Art of the "Zero-Click" Win

We are moving toward a world where people don't want links; they want answers. If your customer asks, "Why is my power drill not working?" they don't want to read your company history. They want to know if they need to replace the battery.

AEO is the art of structuring your content so clearly that an AI (like ChatGPT, Google’s AI Overview, or Siri) looks at it and says, "This is the perfect answer," and serves it up on a silver platter, often without the user ever clicking your website.

Here is the playbook for getting your content chosen as the "Answer."

1. The "Answer First" Rule (Don't Bury the Lead)

To reiterate what I discussed in my previous post, LLMs (Large Language Models) are impatient. If you write a 2,000-word blog post where the actual answer is buried in paragraph twelve, you lose.

• The Move: Identify the specific question your customer is asking and answer it immediately in a clean, 40–60 word paragraph at the very top of your section.

• The Example: Let's say you run an HVAC company.

• Bad AEO: Starting with "Drilling into steel and concrete is one the most challenging mediums that stress your drill operability…..."

• Good AEO: Create an H2 header: "Why is my power drill not working?" Immediately follow it with: "The most common reason for a power drill not working is due to poor battery health after a long period of heavy usage."

• Why it works: You gave the AI a perfect, bite-sized snippet it can steal and read aloud to the user.

2. Product Titles & Descriptions That Actually Talk

Generic product pages are AEO killers. If you just list "Model X Drill" and a price, the AI has nothing to say. You need to anticipate the follow-up questions.

• The Move: Rewrite descriptions to proactively answer questions about specs, usage, and problems.

• The Example:

• Bad AEO: "Cordless Power Drill. High quality."

• Good AEO: "This Cordless Power Drill features a 20-hour battery life on a single charge and is water-resistant, delivering a massive 1,400 in-lbs of torque"

• Why it works: You just answered "How long is the battery?", "Is it water-proof?" and “How much torque does it have?” in one sentence. The AI can now match your product to those specific queries.

3. The Q&A Format (FAQ Pages on Steroids)

AI models love the "Q&A" format because it mimics how they are trained. You can force your way into the conversation by structuring data exactly how the AI wants to see it.

• The Move: Create "Question/Answer" pairs. Don't just rely on paragraphs; use an FAQ list where the question is an H3 header and the answer is body text.

• The Example:

• Q: "Is the Milwaukee FPD3 a hammer drill?"

• A: "Yes, the Milwaukee M18 FPD3 is a percussion/hammer drill designed for drilling into brick, concrete, and masonry."

• Why it works: You are literally feeding the robot the script. This creates "prime fodder" for AI overviews and voice search results.

4. Speak the Robot’s Language (Schema Markup)

This is the technical bit, but it’s crucial. You need to use code to tell the search engine exactly what it is looking at. This is called "Schema." and we will visit this in future posts, it’s something at the top of my list to understand further.

• The Move: Use "FAQPage" schema or "Product" schema. This puts invisible labels on your content that shout, "Hey Google, this text here is a price," or "This text here is an answer to a common question."

• The Result: It makes it incredibly easy for the engine to index your content as a verified answer, drastically increasing your chances of showing up in rich results and AI summaries.

The Bottom Line

AEO is about utility. It’s about accepting that your website might not be the destination anymore—it’s the database the AI uses to do its job. Be concise, be factual, and answer the question before the user has a chance to scroll.

Getting to grips with Generative Engine Optimization (GEO)

In the next few posts I am going to break down several new (new to me) concepts in the world of AI, that are especially important to anyone attempting to sell products online. In my last post I set out the main features of the Agentic Commerce landscape, however in order to break into that world you need to understand how that can actually be done. And the first concept is a content strategy called Generative Engine Optimization (GEO).

In the traditional world of promoting your brand or products you used to fight tooth and nail to be the top blue link on Google by employing SEO (Search Engine Optimization) tactics to your content. Well, the game has changed. If SEO is asking to be put on stage, GEO is asking to be the script the speaker reads from. So, in this post I’ll try and lay out the basics on what GEO is and how you can actually win at it without needing a PhD in computer science.

What on Earth is GEO?

Generative Engine Optimization is the art of convincing AI engines, like ChatGPT, Perplexity, and Google’s AI Overviews, that you are the most trustworthy, relevant source to mention when they build an answer for a user.

In the good old days (which is now reaching back as far as 2023), you wanted a click. Now, you want "influence." You want the AI to read your content, understand it, and synthesize it into its answer, hopefully citing you as a source. The goal isn't just ranking; it's getting recommended by a machine that acts like a smart friend giving advice.

Here is the cheat sheet on how GEO shakes up the old SEO playbook.

1. The Goal: Clicks vs. Influence

• SEO (Old School): The goal is to rank your website at the top of a list of "blue links" so a human clicks on it and visits your site.

• GEO (New School): The goal is to get your content read, understood, and synthesized by the AI into the answer itself. You aren't just trying to get a visit; you are trying to be the source the AI quotes to sound smart.

2. The Tactics: Keywords vs. Credibility

• SEO: You focus on keywords, backlinks, and meta tags to tell the search engine what your page is about.

• GEO: You focus on "citation-worthiness." This means using hard statistics, direct quotes, and authoritative facts so the AI trusts you enough to build its script around your content.

3. The Result: A List vs. A Conversation

• SEO: Produces a directory of options for the user to sift through.

• GEO: Produces a single, conversational answer that solves the user's problem immediately—often without them ever needing to leave the search interface (a "zero-click" interaction).

The Playbook: How to Win at GEO

You can’t just stuff keywords into a page and pray anymore. You have to create content that AI loves to read and summarize. Here is how you accomplish that.

1. Be the "Comparison" Expert

AI engines love synthesis. If a user asks, "Milwaukee Power Drill vs. Makita Power Drill" the AI looks for content that weighs the pros and cons so it can build an answer.

• The Move: Don’t just talk about yourself. Create honest comparison pages, "best of" lists, and detailed reviews.

• Example: Instead of a page that just says "We have a wide range of power drills" build a page comparing your drill selection against pricing, performance, specifications such as actual battery life and torque. If you do the heavy lifting of comparing options, the AI is more likely to use your analysis.

2. Feed the AI Facts and Stats (It Loves Data)

Generative engines are hungry for authority. They trust numbers more than vague marketing fluff.

• The Move: Add citations, quotations, and specific statistics to your content.

• Example: Don't write, "The power drill packs a lot of torque" That’s fluff.

• Better: Write, “Engineered with a POWERSTATE™ Brushless Motor that hammers out a massive 1,400 in-lbs of torque….”.

• The Result: Research shows that just adding citations can significantly boost your visibility in AI answers. If you can find an independent article like a scientific journal explaining why torque is important for drilling, it shows that you have done research and that your claim is grounded in reality.

3. Structure Your Content Like a 5-Year-Old Needs to Read It

We will look deeper into optimizing your pages to better suit AI scanning in future posts, and also the use of Schema Markup to help that layout. If your website is a wall of text, the AI might skip it. It needs structure to parse information quickly 8.

• The Move: Use clear headings, bullet points, and tables. Break it down.

• Example: If you are selling a product, use a table to list benefits and features rather than burying them in a paragraph. This makes it incredibly easy for the AI to scan your page and say, "Aha! Here is the answer," and pull that data into its response.

3. The "Inverted Pyramid" (Answer First)

AI is impatient. When scanning for an answer to cite, it prioritizes information found at the top of the section. If you bury the lead, you lose the citation. This is sometimes called "Position-Adjusted Visibility".

• The Goal: Answer the user’s question immediately, then explain the details.

• Example:

• Scenario: You are an HVAC company writing about "Why is my AC blowing warm air?"

• The Move: Do not start with a story about summer heat. Start with a 40–60 word paragraph that lists the top three reasons (e.g., dirty filter, low refrigerant, frozen coils).

• Why it works: LLMs (Large Language Models) grab that clean, concise paragraph to form their summary. If you make it easy for them to "steal" your summary, they will cite you as the source.

4. Get the "Crowd" to Back You Up (Citations Everywhere)

This is the part most businesses miss. AI doesn't just trust you; it trusts what everyone else says about you. This is the "Corroboration & Authority" principle. If your website says you are the best, that's marketing. If Reddit, Yelp, and a "Top 10" listicle say you are the best, that's a fact.

• The Move: You need to be mentioned in places other than your own site. This includes Reddit threads, "Top 10" listicles in your niche, and review sites like G2 or Yelp.

• Example: If someone asks an AI for the "which is the best percussion drill for industrial use?" the AI checks listicles and directories. If you aren't on those third-party lists, you likely won't get recommended, even if your website is beautiful.

• Why it works: When an AI constructs an answer, it looks for consensus. If you appear across multiple authoritative sources, the AI feels "safe" recommending you,.

5. Leverage "Agentic" Content

This ties into a topic for my next post. We are heading toward "Agentic Commerce," where AI agents do the shopping for people. To get picked, you need to answer specific questions which follow a subtly different strategy of Answer Engine Optimization (AEO).

• The Move: Create "Question/Answer" pairs and detailed use cases.

• Example: Instead of a generic product title like "Cordless Drill," broaden your description to answer the inevitable questions: "This Cordless Percussion Drill can drill into Wood, Concrete, and Steel with a battery life of 8 hours". You are proactively answering "What can it drill?" and "How long does it last?" before the user even asks.

The Bottom Line

GEO is about making it easy for the machine to trust you, your brand and your products. If you are transparent, fact-based, widely cited across the web, and structured clearly, the AI will reward you by making you part of the conversation. Don't just be a link - be the answer.