SpaceXAI Enters the Agentic Commerce Arena?

One of my most ‘unlikely to come true’ 2026 predictions was “X/Grok get into the game” (number 8 if you are keeping track).

With the SpaceX IPO roadshow starting this week, this item flew under the radar of all the activity going on around SpaceX. Gopuff released a pretty unique and powerful AI assistant powered by Grok. It’s not really a general-purpose shopping piece inside their Answer Engine, but to pull this off, Grok has to gain a deep understanding of their product catalog and the shopper behavior.

That means that all the pieces are there to up-level the Grok shopping experience. After the IPO, the pressure will be on for Grok/SpaceXAI to add a bunch of features and what better feature to add that’s totally in Elon’s wheelhouse (remember who founded PayPal?) than..Agentic Commerce for the holidays! let’s see - 174 days until Thanksgiving 🦃! Here’s the hype video→

Juniper Research’s Agentic Commerce Forecast

Juniper Research’s $15T global forecast for agentic commerce puts them in the same strike zone as Morgan Stanley (20%), PayPal(25%) and Bain (15-25%). Another datapoint that re-enforces the ‘consensus’ around Agentic Commrce being a material share of e-commerce by 2030.

Link here.

Nielsen IQ: 42% of Consumers Now Use AI to Shop

Nielsen IQ is the gold-standard of data companies and their panel is second-to-none. They released a set of updated consumer AI behavior data. The highlights:

• 42% of consumers have used at least one AI tool to shop within the past month

• 17% have used AI for product recommendations

• 10% have used a voice assistant to purchase and/or reorder items

• 19% use a subscribe or auto-replenish feature for repeat purchases

• 10% have engaged with an AI-powered shopping assistant

• 5% have used fully autonomous AI agents to place orders on their behalf

Survey data is making it clear that the Research→Find shopper journey in Agentic Commerce has officially gone mainstream. Now the question is how fast does Buy follow? I think we’re going to see some really interesting data come out of Holiday 26 - but we’ll have to wait until Q1 2027 to see it.

Link to details here.

Similarweb: AI Ads Webinar- A Treasure Trove of Data

Another company with great panel data is Similarweb. They recently had a webinar that went really deep into Agentic Ads and there was a truckload of new data I haven’t seen before. Here’s a sample of two slides I found particularly intriguing:

6X deeper AND 17 turns - wow! Also the intersection of AI and ads is going to generate SO MUCH ad inventory it’s going to be insane.

Ads in AI are actually generating commercial intent in addition to reacting to it!

If this is a topic that you’re interested in, I’d flag this one as ‘must watch’.

Accompanying presentation is here:

Similarweb Webinar Ai Ads 5 25 26

24.3MB ∙ PDF file

Download

Download

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Bessemer Venture Partners: The Rise of the Delegated Buyer

Bessemer is a large top-tier venture capital fund that publishes some great content. They dropped a big Agentic Commerce thesis article that’s worth a read if you’re newer to the space and want a pretty tight recap of everything. It’s got a good hook: “The rise of the delegated buyer.”

Link here:

Walmart’s Sparky Makes Big Moves

Our friends at Digital Commerce 360 had a good summary of Walmart’s quarterly conference call where they spent a lot of time talking about some new Sparky data.

• 100% increase in weekly active users in the last quarter

• 40% improvement in answer quality

• 35% higher AOV vs. non-Sparky users

• Added in-store and reorder capabilities

• Expanded from GM into everyday essentials

Details here on Sparky’s Great quarter!

McKinsey: Agentic Commerce Autonomy is a Curve, Not a Switch

File this under: “things I’ve been saying for 18 months” 😄, but seriously it’s good to see McKinsey come around to the same conclusions. In short:

• We’ll get to autonomy soon

• But even then consumers will use Agentic Commerce in various ways (zero/research/find/buy/autonomous/etc.) depending on the tool they want for the shopping mission vs. the false binary of ‘all autonomous or it’s a hallucination’ mindset.

Link here.

Horizon: 82% of Consumers Use AI for Product Research

Here’s a bonus early-June survey from Horizon:

• 82% of consumers have used AI for product research or comparison

• 64% have used AI for price tracking

• 62% have used AI for research

• 90% report satisfaction with AI-assisted shopping experiences

This slide packs a big punch 🤜:

Detailed PDF here:

Agentic Commerce Building Trust In The New Era Of Ai Shopping Futures Report (1)

820KB ∙ PDF file

Download

Download

Link here.

News Summary

Stepping back, two big themes jump out from May’s data and news items:

1. Consensus is forming on the 2030 number. Morgan Stanley, PayPal, Bain, and now Juniper all in the 15-25% of e-commerce zone. Different ways they all get there, same triangulated result.

2. Consumer behavior continues to show Agentic commerce Adotion . NIQ at 42%, Horizon at 82% for research, Similarweb at 460M users and $1K+ brands buying ads, Walmart’s 35% AOV lift on Sparky. We are well past ‘is this real?’ and into ‘will it stay on exponential’ territory…

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This week we have a rare doubleheader. We sat down with two Salesforce leaders back to back to help us unpack the company’s big June release, headlined by the launch of its newest platform, Storefront Next.

Nitin Mangtani is the Executive Vice President and General Manager at Salesforce, a few more things in his title than the last time he was on the show (check it out here). Nitin ran Google Shopping for years before founding PredictSpring, a point-of-sale company that Salesforce acquired in 2024. Two years in, he now oversees the full commerce stack: storefront, point of sale, and order management.

Lennart Stevens is the Vice President of Product Management for Agentforce Commerce at Salesforce, making his first appearance on the show. Lennart has spent nearly two decades in commerce, almost all of it on the partner side. He was one of the early implementation partners for Demandware (the platform Salesforce acquired and rebranded as Commerce Cloud), so he’s seen the customer’s side of every platform migration in the book. Salesforce brought him in to carry that customer perspective into the product, and his purview now covers Storefront Next, checkout, and the new commerce applications framework.

Listen/Watch Our Interview:

First up is Nitin, who walks through the full sweep of the June release and makes the case for why, taken together, it's Salesforce's biggest commerce release in five years. Then Lennart takes us deeper into the agentic guts, one of our favorite parts.

The two interviews rhyme in one important way: both leaders insist that agentic commerce on your owned-and-operated channels matters just as much as showing up in ChatGPT and Gemini. As Nitin puts it, skipping your own shopper agent is like the old days of saying "I participate on Google Shopping, but I don't have search on my website." Highlights below.

Highlights

• Biggest release in five years: Nitin frames the June release as Salesforce Commerce’s biggest swing since he arrived.

• “It’s 2026, let’s combine the two together”: The forced choice between enterprise-grade and easy-to-launch is a false distinction that can be engineered away.

• The acquisition cheat code: Rather than spend five years building modern AI search in-house, Salesforce bought Cimulate. It now powers every shopper agent prompt, and it’s available even to non-Commerce Cloud customers.

• “This code should be written by Claude prompting and not by you”: Storefront Next ships you to the 90% point out of the box; the last 10% is vibe-coded. Migration utilities plus Claude Code shrink what used to be a capital-T front-end project.

• Live in under 30 minutes: Lennart’s demo path: name the storefront, connect a code repo, click go, and you’re previewing a high-performance site in under half an hour.

• You need your own Rufus AND to play off-site: Both guests hammer the distinction between agentic commerce on owned-and-operated channels and syndicated commerce via UCP on Gemini, OpenAI, and beyond. One without the other is like being on Google Shopping with no search box on your own site.

• Focus is magic: Nitin consolidated 20 initiatives down to 4–5, runs two-week iteration cycles instead of two-year PRDs, and credits that discipline (plus AI-native development) for the release’s scope.

• Advisor and confidant: Lennart’s favorite anecdote… a jewelry brand found customers were more comfortable asking an agent “how big should the ring be, how much should it cost?” than asking a friend.

• Checkout wisdom from Nitin: Stop offering eight payment options. “Just put Apple Pay on your PDP” four options max, on a good day.

The era of choosing between enterprise and easy looks like it's ending and the agents are coming either way. Enjoy the conversation.

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May 20th at Google Marketing Live, before the high-level strategic chat with Nick Fox, SVP of Knowledge and Information at Google (you can read/listen to that one here), I was also able to to sit down with friend of Retailgentic: Ashish Gupta, VP & GM of Merchant Shopping at Google.

Ashish was on the pod back on March 19th which was a very popular episode. He’s a Google Fellow, which is an extremely rare and hard earned engineering distinction inside of Google, and he runs the merchant side of Google’s Commerce focused team.

The org has two tightly-coupled sides: a consumer group and a merchant group. Ashish runs the merchant side. That’s the side that owns the feed, UCP, Merchant Center, and now the new AI performance insights. I got to also meet many of the folks on the consumer side - we’ll work to get one of them on the pod next!

This interview was recorded right after his fireside chat with Augustina Sartori, Head of Agentic Commerce @ Ulta Beauty) at GTL. In that chat , he laid out the 4 things merchants should do right now:

1. Product feeds

2. Data strength

3. AI campaigns,

4. Agentic infrastructure (i.e., UCP).

In this interview we discuss we dig deep into all 4 for you as they are super-important and should be foundational to your Google Holiday 2026 strategy:

• The 6 new conversational attributes — just launched, live now in the supplemental feed (FAQs, related items, popularity rank, document links, additional variants, item group). Why they exist, how to use them, and the “best sales associate in your store” analogy for how AI surfaces are now expected to behave

• UCP’s expansion into new verticals — food delivery and travel. Why now, and why the “U” in Universal Commerce Protocol is doing real work

• Loyalty in UCP via Google account linking — your Ulta $10 reward shows up at checkout. Critical for merchants who don’t allow guest checkout

• Data strength — bringing first-party loyalty data into Gemini / AI Mode surfaces so loyal customers see more of the brands they love

• AI Max & P-Max and the new ad formats showing up across AI surfaces (and YouTube)

• AI Performance Insights coming to Merchant Center — the new Share of Voice metric, why the funnel doesn’t behave like a normal funnel (it can actually widen deeper in), and how Google is moving from a “click/keyword” company to an “answer engine” company

• The keyword vs. long-tail question — in an answer engine world, is there even such a thing as a “popular search term” anymore? (Ashish’s answer is interesting to this one!)

What’s neat about doing these back-to-back is you get both layers in one day. Nick’s interview is about framing: how Google thinks about AI Mode vs. traditional Search, the Innovator’s Dilemma, the ~5 prior attempts at “transactions on Google” and why this one is different, and trust at the intersection of answer engines and AI ads. Ashish’s interview is the merchant-facing manifestation of all of that: here’s exactly what’s shipping, here’s what to put in your feed, here’s how we’ll measure you.

Read both together and you get a pretty complete picture of what Google is doing with agentic commerce in 2026.

Listen/Watch My Interview with Ashish:

If you want to watch, you can see it on YouTube here:

Or you can Listen here for wherever you listen to pods (Apple Podcast, Spotify, Overcast, etc..) OR you can listen directly from this post here:

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May 20th at Google Marketing Live, I was very fortunate to be able to sit down for ~20 minutes with Nick Fox, SVP of Knowledge and Information at Google. Earlier in the day he had a fireside chat with Ben Smith, Editor-in-Chief Semafor:

That was a great conversation and you can watch/listen to that talk here→

Later that afternoon after I had time to reflect on this conversation, I had a ~20min interview with Nick.

It’s not often you get to sit down with one of the top execs (Nick reports directly to CEO Sundar Pichai) at a ~$5T company so I worked a lot of strategic topics into a short time (~20mins).

As always, I approach these interviews with you, the audience, in mind. What would YOU ask? For context, before the interview, I had a super detailed and important, but tactical Agentic Commerce / UCP/Universal Checkout discussion with Ashish Gupta (coming soon!), so for this one flipped into high-level strategic mode.

In this interview we discuss:

• How does Nick ‘frame’ AIO/AI Mode/Gemini

• Will AI Mode/AIO and traditional search transition from traditional to AI Mode or will they merge, or ‘other’ down the road?

• Google’s had ~5 previous attempts from the Froogle era to today for ‘transactions on Google’ - why is this the moment they are getting super serious about it?

• Navigating the Innovator’s Dilemma

• Finally, managing trust at the intersection of ‘Answer engines’ and ‘AI Ads’

Listen/Watch My Interview with Nick:

If you want to watch, you can see it on YouTube here:

Or you can Listen here for wherever you listen to pods (Apple Podcast, Spotify, Overcast, etc..) OR you can listen directly from this post here:

Want to Learn More About Agentic Commerce?

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Sorry to pummel your inbox/notifications so much in the last 24hrs, one last Google I/O/GM! There’s just one more post hitting this time tomorrow then we’ll peace out until next week, promise! (Editor’s note: unless some really earth shattering news hits which can happen at any time these days!).

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Don’t miss our previous Google I/O coverage which this builds on:

• Google Announces Universal Cart here.

• Our awesome interview with Suresh (Senior Director of Product, Consumer Shopping) here.

2026 Google Marketing Live (5/20/26) Drops More Agentic Commerce News, Let’s Dig In!

Today Google is announcing four more Agentic Commerce news items. Let’s just jump right into these.

1: Conversational Attributes

If you remember our Agentic Commerce Optimization framework (above), we introduced a best practice of not only beefing up your current attributes (steps 3/4/5) but also expanding your existing attributes (step 6). Well today Google formalized that by announcing support for what they call Conversational Attributes. Think of this as a supplemental datafeed you can send to GMC in addition to your core attributes that enhances what the buyer may want to know about your products. Examples here could be: What occasion is it optimal for, what does it pair well with, what does

I’m excited by this one because Google is helping Merchants break out of keyword jail and laying down a very clear breadcrumb trail that product-level storytelling is where we’re going. I imagine this is just the start.

Want to learn more? Check out this Google Merchant Center help article here.

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2: Shoppable YouTube Ads Fueled by UCP and Datafeeds?!

Long-time readers know I love datafeeds! And this is a really cool marriage of UCP/Universal Cart/ads and datafeeds. Honestly it feels like with the right content and an expansion into pulling in influencers, this could give Tiktop shops a run for the money. Here’s a video showing an example of an Etsy video that has this turned on.

In the video, which is an ad, we see a bunch of gift ideas. Under the video is shoppable products that match the items that are recommended in the video. The user clicks on the “Monstera Tote Bag” and directly from the Youtube video ad enters the Universal Cart and buys the item with one click. Serendipitous commerce at it’s finest and now we know one example of Universal Cart on the YouTube surface!

3: AI Performance Insights

For the merchants out there frustrated at the lack of visibility into everything happening our soon-to-be zero-click World, Google has an answer. In Google Merchant Center, there’s a new AI Performance Insights section detailed here:

You can see lots of goodies in this short video, I’m looking forward to spending more time with this puppy today in one of the hand’s on sections and will report more on it as I’m sure every brand and retailer I know can’t wait to get their hands on this one:

• Share of voice

• Competitor’s average share

• Funnel performance across Discovery→Evaluation→Purchase (I prefer Research→Find→Buy but close enough!)

There’s even some sub-context like ‘did they search for product specs or user reviews, did they compare products, etc.’ and what are some terms (keyword jail!) people are using - this one I’m pretty skeptical about, but will reserve judgement until I see it IRL.

4: Expansion of UCP to Food and Travel Industries

Finally, less relevant to this audience, but highlights my theory about Amazon’s threat being the horizontal-ness of Agentic Commerce, Google is expanding the UCP tent to include Food and Travel companies and announced the addition of a whopping 14 new logos to the already busting-at-the-seams UCP partners logo slide(s)→

Open Questions from GIO and GML

Finally, as I spend time today at GML, I’m chasing down answers to the questions from yesterday, plus I’m sure there will be more added to the list from today’s additional four big items:

1. Googlers talk about Universal Cart being available on surfaces like Gmail and YouTube - what’s that actually look like IRL? What are the use cases that merchants can think about and start experimenting with?

2. Universal Cart is coming this Summer - that’s typically June/July/August - that’s a long window in AI-time, early/mid/late Summer?

3. I haven’t heard Google, at least the Agentic Commerce team, talk about AG2 in a while, and suddenly it popped back up in the context of the new consumer agent called Gemini Spark. What’s that all about that.

4. Loyalty (via identity linking) was part of the UCP features announced back on March 19th (details here) but kind of missing here? Even though if you read Vidhya’s blog post very carefully it says that Universal Cart uses “loyalty information”, but it’s not like the Copilot UCP-based loyalty linkage we saw with Target back on April 22 (here if you missed it).

5. (new) Will Conversational attributes grow over time, any other product-level storytelling you see coming to UCP/Gemini?

Sneak Preview of GML

We have two special interviews planned to record later today we’ll release tomorrow, stay tuned.

Also here’s the map of the pavilion/festival area→

If yesterday’s Google I/O was a theme park for nerds, this is a circus for digital marketers. I’ve seen 10 signs with ROAS, PMAX and Agentic Commerce on them. LETS GO! 🧐🎸

I’m particularly interested in the ‘Think’ section -notice 👀 the “Product Bar/Retail and “Retail in the AI Era” sections - I’ll be logging a good bit of time there ;-)

Today at Google I/O, in her part of the larger keynote, VP/GM of Ads and Commerce, Vidhya Srinivasan announced a raft of Agentic Commerce items with the anchor new feature being Universal Cart (covered by Retailgentic here and her blog post here and the keynote on YouTube here).

Google I/O Lots of Cool New Agentic Commerce Features…But We Have Big Questions!

After Vidhya’s keynote comments, I was left with these questions that I know merchants will have too:

• Googlers talk about Universal Cart being available on surfaces like Gmail and YouTube - what’s that actually look like IRL? What are the use cases that merchants can think about and start experimenting with?

• Universal Cart is coming this Summer - that’s typically June/July/August - that’s a long window in AI-time, early/mid/late Summer?

• I haven’t heard Google, at least the Agentic Commerce team, talk about AG2 in a while, and suddenly it popped back up in the context of the new consumer agent called Gemini Spark. What’s that all about that.

• Loyalty (via identity linking) was part of the UCP features announced back on March 19th (details here) but kind of missing here? Even though if you read Vidhya’s blog post very carefully it says that Universal Cart uses “loyalty information”, but it’s not like the Copilot UCP-based loyalty linkage we saw with Target back on April 22 (here if you missed it).

That’s a lot of questions - I only had 30mins with Suresh, so had to pick and choose, but we covered some good ground. The good news is I have two more interviews scheduled for Wed 20th at Google Marketing Live and will work them all in.

Listen/Watch My Interview with Suresh:

If you want to watch, you can see it on YouTube here:

Or you can Listen here for wherever you listen to pods (Apple Podcast, Spotify, Overcast, etc..) OR you can listen directly from this post here:

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Greetings LIVE From Google I/O!

Greetings from sunny Mountain View California where we’re all waiting here for the big keynotes and other festivities to kick off. Google I/O is foreign to us in the Retail/Brand world because it’s a developer conference for super hard core cracked devs. Well, guess what, AI is mashing up all our Worlds and here I am for the first time at one of the largest developer conferences out there. Later in the day I’ll be posting some pics and video to show you the scale of this thing. It’s a scale that I haven’t seen since the late 90’s Microsoft Visual C++ days and the engineers here are in a Agentic AI induced frenzy.

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This year Google is smooshing together their Ad conference, Google Marketing Live (GML) . Today, Tuesday May 19, one of the top topics at the keynote (I’m sure we’ll get new models and there’s an OpenClaw-ish agent called Spark coming that we’ll cover in another post later) and then Agentic Commerce takes the main stage. Then Tomorrow, Wed May 20th we go to GML

It will be two days chock full of announcements, live demos and we’ve secured some killer ✨EXCLUSIVE✨ interviews for Retailgentic readers that we will post as fast as we can. Because of this our posting frequency this week will be quite unusual, but we want to keep our reputation of getting you the fastest and deepest Agentic Commerce news so you have an edge.

Today we had advanced release of the biggest feature coming out today: Universal Cart.

Note this is not live today - they are saying: “Rolling out this Summer”. But we’re going to see live demos, so I’m thinking ‘early Summer.” - a question I’ll be definitely digging into for you.

Google Universal Cart: Intelligent, Proactive, Multi-dimensional, Multi-item, Multi-merchant Delivers “Agentic Superpowers for Shoppers”

There’s a lot to unpack here, let’s start with a list of all the features in the new Universal Cart and then I’ll show you examples. We’ve talked about the idea of Universal Carts back in January when we found evidence that ChatGPT was about to release theirs here. The TL;DR - before Agentic Commerce many tried, all failed. Google has 100% nailed it by building it on UCP.

Google’s Universal Cart (GUC) features:

• Multi-item - Agentic Commerce carts to-date have been single item single cart. GUC is multi-item - in fact it’s kind of a ‘lazy cart’ - you can throw stuff in there as you shop as almost a wait list and then checkout at your leisure. It’s persistent and follows you across devices and sessions. Almost like your shopping buddy - always there for you to sling it a product, hold it there and it will keep it safe for you and help you proactively.

• Multi-merchant - GUC is multi merchant. Working on a new outfit for a Summer trip across 5 retailers, throw it all in one cart and see it all together.

• Intelligent - Once you add an item to the cart, it can tell you about the price history of that product, if that product is frequently out of stock (‘hey you may want to check out now’), etc.

• Proactive - Let’s say you new Macbook Neo in your cart and you get a webcam too. GUC will check the compatibility, noticed that the webcam is USB2 and Neo doesn’t have a port for that and flag the incompatibility.

• Multi-dimensional -In addition to the above, it is aware of your wallet. I am a big Amex user and they have great offers and other discounts and cash back/points multipliers that are near impossible to use because they are locked at amex.com - they should be at the point of purchase, now they can be. GUC will surface these things when it detects them. Previously Google also announced partnership with our friends at Klarna and Affirm for BNPL, so that’s another dimension you can leverage here.

• Multi-surface - This is going to be live across not only AI mode and Gemini, but also Gmail and Youtube.

• Merchant friendly - Through all of this it maintains merchant-of-record and I imagine soon we’ll get loyalty program connectivity (this is part of UCP, Copilot has implemented it, Google hasn’t yet, seems like they wanted to nail cart first - this is going to be my top question I ask).

Before we get into some examples, we have an important Retailgentic ‘Agentic Commerce Players” update.

Agentic Commerce Levels of Autonomy Update

While it’s only Q2 and early at that, we’re going to make a mid-year update to our tracker:

Updates:

• ChatGPT: Down a level ☹️ - First, we have to move ChatGPT from Level-3: “Buy” back down to “Level-2: Find” - yes they have ChatGPT apps, but that experience is so terrible, we couldn’t live with ourselves having it in the same category as obviously superior offerings. ChatGPT - there’s still time to get back in this thing - wake up!

• Gemini: Up a level 😄 - We’re also calling it- with the announcement of GUC, we’re “3.0’ing” Google/Gemini and moving them as the first competitor to reach Level-4: “Advanced Buy”. We would have liked to see Loyalty in there, but we all know it’s on the docket, so we’re going ahead and moving them as the mountain of other features really fulfill our vision of what “Advanced Buy” could look like when we first published this in early 2025.

Now, let’s dig into some examples and bring this to life.

Note: these are static images provided by Google, I’ll be posting more when we get into the live demo/hands on parts of the days.

Example 1: Multi-Item and Multi-Merchant

Here we see a lot going on - we’ve got two merchants, Target and Ulta - in the Target part we have two items from Target a hat and a gardening kit - both are 5% off (presumably with a coupon or red circle?). Notice the new ‘checkout option’ where you can buy via UCP or xfer the cart over to Target.com

Then we have Ulta - we can only see one item, but it could be 100. All multi-item shipping discounts and what-not are detected and applied here exactly as they would be in the downstream cart.

Example 2: Intelligent

In this example, GUC has 2 products from Wayfair and tells us this desk is a pretty good deal and this would be an opportune time to buy this puppy before that price creeps up (it’s at a 30 day low).

Example 3: Proactive

Here we see two proactive vignettes:

• Vignette 1 - We’re building a gaming PC at Bestbuy throw some components in the cart and it detects an incompatibility.

• Vignette 2 - We have 2 items in our cart and there’s a discount with our Target Circle Credit card (ah-ha!)

Example 4: Multi-dimensional

By ‘multi-dimensional’ - what I mean is it cares more about price. Other dimensions important to me as a shopper are: speed of delivery, price of delivery, stock level, price trend, payment method discounts/special offers, price trend, etc. GUC is pulling all of this in and it’s already smart and will only get smarter.

What’s Next…

Later today I’m going to be posting some thoughts at the end of the day and then we’ll be back at it tomorrow at GML with some early interviews coming your way too as we produce them.

Happy Agentic Commercing! 🚀

Bonus - here’s the map of cool stuff I’ll have access to later today. It’s like a theme park for nerds LET’S GO! 🤓🤓🤓🤓🤓

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Elizabeth Lachhar, Executive Vice President of the Americas at Rezolve Ai, is a senior enterprise leader focused on bringing agentic commerce technology to retailers, brands, and large organizations across North and South America.

In her role, she works directly with major companies to adopt AI-driven commerce systems, spanning everything from search and personalization to checkout and loyalty.

Before joining Rezolve AI, she built her career at major technology companies including Microsoft, Google, and Oracle, where she led large-scale digital transformation projects for global enterprises, particularly in retail, consumer goods, and hospitality.

Today, she helps enterprise retailers and brands adopt agentic commerce, leads go-to-market and growth across the Americas, works across executive teams in commerce, marketing, IT, and finance to implement AI systems, and focuses heavily on driving real-world ROI with deployments that can often be realized in as little as 12 weeks.

Listen/Watch Our Interview:

In this episode, we unpack Rezolve AI’s end-to-end agentic commerce platform, including its closed retail-trained LLM, Brainpower, and modules across search, discovery, conversational commerce, checkout, and loyalty.

A lot of the agentic commerce conversation focuses on offsite experiences like ChatGPT, Perplexity, Gemini, and other AI shopping agents. But there’s another major shift happening onsite, where retailers are rethinking search, merchandising, conversational commerce, checkout, loyalty, and personalization for an AI-native world.

Elizabeth brings a deep enterprise background from Microsoft, Google, Oracle, and more, and now works with retailers, brands, food service, hospitality, and B2B companies navigating this transition.

Highlights

• Why onsite agentic commerce matters just as much as offsite AI shopping agents

• How Rezolve AI approaches search, merchandising, conversational commerce, checkout, loyalty, and geolocation

• Why closed, retail-trained LLMs may matter for hallucination, security, and enterprise trust

• How conversational commerce can help retailers move beyond flat, 2D ecommerce experiences

• Why B2B discovery is a major agentic commerce use case

• How loyalty, memory, and past purchases can create better personalization

• What retailers are asking about right now: security, compliance, fraud, ROI, and partner strategy

• Why Elizabeth believes agentic commerce is already here, not years away

• What Generation Alpha could mean for the future of shopping experiences by 2030

Agentic commerce is also about rebuilding the onsite experience so retailers can understand, personalize, transact, and convert in a world where consumers expect commerce to be faster, smarter, and more conversational.

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Or, we have a video version on YouTube (make sure to subscribe!) →

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One Amazon Assistant to Rule Them All: Welcome to the “Alexa for Shopping” Era:

Amazon announced today they are combining Rufus and Alexa+ - their two separate shopping agents have now been combined into one named Alexa for Shopping.

All devices, the Amazon website, mobile apps and Echo devices will all be moving away from Rufus and/or Alexa to the new brand: Alexa for Shopping.

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Shared Context/Memory Across All Surfaces

Amazon examples of how your shopping preferences and contexts can be multi-modal/multi-device-al.

Use Case 1 (Web→Device Example)

One example is - let’s say you setup an alert for a Nintendo Switch 2 that is frequently out of stock using the Alexa for Shopping on your desktop website Amazon.com. That evening at 10pm you are home and your Echo device has a notification that the Switch 2 is now available and you can order it from the device.

Use Case 2 (Device→App Example)

In this example, you could be talking with Alexa on your Echo Show with your 16yr old to think through different science fair projects and choose the project. Then when you are on the Amazon app on your phone ordering some dog treats, Alexa for Shopping prompts you with a list of products you’ll need for that science experiment - you remember you forgot to order them earlier in the day and you throw them in the cart and the arrive over-night with the dog treats. Alexa for shopping remembered this context that started on an Echo device and surfaced it on the mobile phone app during a standard shopping session.

When Will Alexa for Shopping Role Out and What Does it Look Like?

Amazon says that over the coming week this will role out and the Rufus icon will be replaced by an Alexa icon across all surfaces. We know that Prime Day is coming in June this year, so this will all be rolled out before Prime Day I imagine.

Right now in the US as of 8am ET for me on the website it’s switched over (see above) in the website, but not on the mobile app.

On the help docs they do show the mobile app will look like a stylized ‘Alexa a’→

All Amazon customers can use Alexa for Shopping for free when signed into their account, no Echo device, Alexa app, or Prime membership required.

On the PDP and under the hero image there’s a sparkly treatment.

Here’s the hero page on the help docs for the new Alexa for shopping:

🔮This Move Was Predicted Over a Year Ago!?!🤔

If this all sounds oddly familiar to you, Amazon 1P “Rufus Whisperer”, Andrew Bell, found an Amazon patent over a year ago and from that patent predicted that this exact move would happen - as one prediction maker to another - that’s a 💯 prediction! (details here, here and here). Wow - mad respect to Andrew on 🎯 this one! 🫡

Other Rufus Alexa for Shopping Updates.

Note: Some of this was covered already in previous posts through leaks and early discoveries here and here.

• Unified Search Bar (semi-covered already) - You can now ask Alexa for Shopping questions right in the Amazon search bar and it recognizes when you’re asking a question and Alexa for Shopping and routes it to Alexa for Shopping to help answer it — from general questions like “What’s a good skincare routine for men?” or “How to plan a unicorn-themed birthday party,” to product comparisons like “Breville Barista Express vs Pro” or “Compare Kindles,” to order inquiries like “When did I last order AA batteries?” or “Where is my order?”

• New Compare Products Functionality - Compare products from search results: Select multiple products directly from your search results and Alexa for Shopping will compare them side by side, helping you quickly evaluate features, prices, and reviews to find the best option.

• AI Overviews (covered) - Get AI overviews in search and on product detail pages: Alexa for Shopping surfaces AI-generated overviews at the top of search results in the Amazon Shopping app, giving you a quick summary of a product category and what to look for before you start browsing. You’ll also find AI overviews on product detail pages to help you make more informed purchase decisions. The feature is already available to millions of customers and rolling out to all U.S. shoppers.

• Price History Updated to 1 Year - Check product price history for up to a full year: Tap “Price History” on any product detail page or ask Alexa for Shopping for the price history to see how the price has changed over the past year on hundreds of millions of products in Amazon’s store.

• Schedule Routine Purchases: When chatting with Alexa for Shopping, tap the “+” icon next to the message bar to create a Scheduled Action, such as adding healthy kids’ snacks to your cart each month, restocking regular household items like pet food, paper towels, and detergent, alerting you when your favorite author releases a new book, or getting gift ideas ahead of family and friends’ birthdays and holidays. You can also get more specific with prompts like “Add this sunscreen to my cart if the price drops to $10 and I haven’t purchased it in the last 2 months.” Alexa for Shopping handles the product research and will either notify you or add relevant items directly to your cart — as a one-time action or on a recurring schedule — so all you have to do is review and check out.

• Easy Add to Cart: Effortlessly add items to your cart: Alexa for Shopping can search past orders and add them to your cart or quickly build new carts with conversational directions. Say things like “add my regular dog treats” or “add my frequently ordered cleaning products” or “add my favorite protein bars to my cart,” and then check out with a tap.

• Personalize Your Experience/Memory: View and update details like family members, pets, interests, dietary needs, and more by simply asking Alexa for Shopping what it knows about you. This is live today: prompt this: “Review my shopping preferences”.

• Custom Shopping Guides - Learn about new product categories and items: Whether you’re making a big purchase like a TV or exploring a new product category for the first time, Alexa for Shopping can create a custom shopping guide that compares features, prices, and reviews across Amazon and the web based on what matters most to you.

Analysis: Why Now and What’s the Strategic Move Here?

Why now? This makes logical sense- two shopping assistants is one too many and the use cases make a ton of sense.

Amazon, for the first time in 20+ years faces a competitor, Agentic Commerce, facing them on two fronts:

1. A frontal ‘selection assault’ from a group of 5+ powerful and large attackers.

2. A flanking ‘horizontal assault’ via a super-assistant attack also the group of 5+ attackers.

That’s a lot of ‘incoming’ attack vectors for a company that has run over all the big retailers with barely a speed bump.

What’s the strategic move?

While on the surface this may feel like a re-brand, I think it foreshadows something much bigger. Amazon’s just announced ‘embrace and extend’ UCP strategy is designed to counter the ‘selection attack’.

The horizontal assault is tougher to counter and is illustrated here:

In his Q2 remarks, Jassy was very specific to say that the Amazon vertical shopping experience will always be superior at shopping vs. horizontal, but this doesn’t make a ton of sense, because yes it will always be a better shopping experience, but it will increasingly lose the battle of “overall context”. This shows us they are thinking a lot about this.

Here’s why it’s a threat.

People are telling ChatGPT about their trips, their car shopping, their kids, their meal plans, their finances, their business plans, their health care issues and fitness regiment. That’s a list of 8 shopping-adjacent contexts that Amazon is totally blind t, but ChatGPT can use to help you find products. They are sneaking up on Amazon from the side. Oh let’s talk about your skin-care - 5 turns in and you’re buying a beauty product not even sold on Amazon - this is Amazon’s worst nightmare.

Before ChatGPT none of this was a concern as none of this shopping-adjacent was collected in one place that even threatened shopping Expedia, WebMD, etc were, if anything, Amazon associates. Now here’s the first time that’s not the case, consumers love it, they are innovating at an insane pace and to make matters worse, you have 6 mega cap companies going after this opportunity. This is not a typical a 2-dimensional flanking diagram, it’s a 6-headed hydra coming at you on a 3-D chess board.

How Do You Defend Against a Horizontal Super Agent?

The best way to de-risk the horizontal agent threat is to…Expand Alexa to be YOUR horizontal super agent. Use your shopping wedge to go wide before the attackers can create a wedge into your high gound.

My prediction is over the next year we’re going to see Amazon take Alexa wide/horizontal by adding health, travel and other features to have an answer to both the product selection attack and horizontal personal assistant attack they now face from Agentic Commerce and the Answer Engines.

What’s Next?

Will these new attack vectors work? Too early to call, Amazon’s in a great position and it’s strategy reaction here feels appropriate and it’s rapid compared to the emergence of the threat. This Holiday will be an interesting battle in the war and we’ll be reporting on it from the front lines. Stay tuned.

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Note: Brands pictured here were listed on the DSS website as speakers, but representative of the types and size of brands in the audience.

I was invited by the awesome folks at Salsify to attend the Digital Shelf Summit 2026 and to deliver a keynote at the opening day to ‘set the stage’ for the theme of the event.. you guessed it: Agentic Commerce. We had permission to record that and will be publishing it as a podcast next week, stay tuned. I also gave an interactive Agentic Commerce Optimization Workshop:

I started the session by going deep on one SKU, a Silk vanilla almond creamer, in what we call an Agentic Commerce Audit. This process illustrates the patterns that you start to notice patterns about how the engines talk about your products. You can take the positives and negatives patterns and apply what you learn in one SKU to every product in your catalog. The deep-dive stuff was fun, but the best part of these sessions is always the Q&A. Brands asked the questions that are actually on their minds → not strategy or theorticals but , the real tactical “what do I do Monday morning” after this conference questions.

Q1: How Fast Are LLM Training Cycles Moving?

The background for this question was part of my setup for the workshop. Part of ACO strategy for brands that don’t sell direct to consumer (commonly called 1P/Wholesale or B2B Brands) is to make sure their purely informational websites have all the correct metadata outlined in our ACO strategy (introduced here). While this doesn’t drive direct sales, the agents pull in the data that improves the product-level results from retailers selling their items. Because the 1P agents (Rufus/Sparky/TSA) are build on models like OpenAi/Claude/Gemini, they will pick up this data in their training data and it will go into ‘long term memory’.

With that, background, here’s the answer:

The training window is closing in faster than you’d think, and they’re accelerating. Training cycles used to be 18 months → then a year → now we’re at about six months for a foundation model refresh (Claude is here, I think everyone will catch up this next cycle).

And that’s just the base model. The RAG / web-index layer that lives at your 1P partner is the part that actually pulls in your fresh product content and that updates constantly. Anthropic, OpenAI, Google, Perplexity, CoPilot, META → they all have crawlers hitting your site in something close to real time.

Want proof of where any engine stands? Ask it directly: “What’s your training cutoff?” You’ll get a real date back. As of this writing:

ChatGPT 5.5:

Claude Opus 4.7:

Gemini 3.1 Pro:

Takeaway: Belt and Suspenders: Publish to your content to your website for training data longer-term AND make sure you optimize what you send your retailers. This puts your product data in the ‘short-term’ memory and the ‘long-term memory’.

Q2: There are Two Schools of Thought: Flood the Zone With Brand Content (AEO/AIO) or Go Deep at the Product Level. Which is Right?

I’m going to sound like a broken record and we’re already on Question 2, but, you guessed it - you should do both.

AEO/GEO is the awareness/sentiment piece - usually managed by your PR/marketing/brand team and not product-level content.

ACO is the product-level where you make sure your product-level content is beefed up for the LLM era and you’ve optimized it over several iterations across your 1P agents and the big 6 answer engines. This optimizes the part of the funnel involving products, and thus your product catalog: Research→Find→Buy.

AEO gets your brand mentioned in the conversation. Product-level optimization gets your SKU onto the offer card. Two different pieces of real estate, and you want to win both.

The AEO-leader, Profound, style of “pump out a thousand pieces of brand content” approach is directionally fine. Brand-story level content builds the brand-mention (sentiment) layer. But if your Attributes, supplemental attributes, reviews and FAQs, distributed viadata feeds aren’t in shape, no amount of brand-level content saves you when a shopper says “I’m remodeling my kitchen and need a built-in espresso machine.”

The best news is ACO is both more actionable and faster to see action, and thus more measurable too.

Q3: What about Grok? Does it have a merchant center yet?

Not yet. Here’s the scorecard as of now →

ChatGPT → has one, it’s still gated, but should be open for online signup soon.

Gemini → The existing Google Merchant Center

Copilot → has one tied to the Copilot merchant center.

Perplexity → has one-ish, routed through PayPal, a little squishy on how to get access - there’s some chaos over at PayPal these days and merchants are getting mixed messages and delays.

Anthropic → rumor is working on it, nothing announced.

Grok → nothing.

But I’d bet on Grok showing up to this party. The infrastructure is too obvious to skip, and X is too motivated to monetize. Give it two quarters to get through the API.

Q4: Are Retailer Walled Garden Agents like Rufus and Sparky Bleeding Signals Back into the Open Agents (ChatGPT, Gemini)? Can Optimizing for one Hurt the Other?

Yes, there’s cross-pollination - but it doesn’t go this way, it goes the other way. Because these are walled-off retailes

Rufus is most likely a Claude derivative sitting on Anthropic’s model. Sparky sits on OpenAI’s model. So when you optimize for ChatGPT, ~90% of that work is automatically lifting Sparky too. Same foundation model, same eating habits. When you optimize for Claude, you’re long-term (training data) getting benefit in Rufus.

A large % that is additive is the retailer PDP and behavioral signals. Signals like what shoppers actually click, search, and buy inside Amazon or Walmart. That part you can’t reach from outside.

So yes you can feed the foundational models, the foundational models feed into the models underneath the retailer agents into their long-term memory. Then your PDPs come into their short-term memory.

Q5: How do you Optimize for a Retailer that Doesn’t Have an on-site Agent yet - A Grocery Retailer, for example?

Manually, retailer by retailer. For now.

You have to partner with your retail partners and ask them: “Can I add an FAQ block to my PDP on your site? Can I push metadata to the PDP? Can I expand my product description fields? Every retailer’s PDP is, at the end of the day, an HTML page. There’s always a way to inject the content the agents will want.

The good news: I’m calling it: every major retailer will ship an agent within ~12 months. Albertsons is out. The Krogers, Targets, and Lowe’s (grocery) of the world are all heads-down on this. → This is a problem that’s actively solving itself.

Do what you can today. The surface area expands automatically.

Q6: Do we really have to supplement each retailer’s “agent diet” by hand?

Short answer - for the next few quarters, yes. But here’s the framing that changes that math:

Your website is doing 80% of this work for you. The engines crawl your DTC site, ingest your metadata, pull in your FAQs, digest your reviews, and forklift all that data into their vctor databases. That index then powers every agent downstream, retailer-owned or not.

When those agents do launch, it’s largely going to inherit the product intelligence you already published on your own site. Also, everything you do today, will pay further dividends down the road because everything your organization learns about ACO will apply to LLMs now and into the future. The underlying love of natural language won’t change.

For a non DTC brand your website went from a 1 to a 9.5 on a scale of 10. It’s not a vestigial brochure anymore. It’s the source feed for the entire agentic ecosystem.

Q7: 🤯 How do you Handle AI-Generated Fake Reviews? How do you Even Know What’s Real Anymore?

This is the gnarly one, and it’s getting worse fast. Three angles →

(1) Verified-purchase signals → Tie every review to a real transaction, the Amazon model. By far the strongest verification of a review, and the hardest to fake. If you’re not running DTC, lean on retailers who do this well.

(2) AI-detection tooling → There are services that score text for AI-generation probability. They’re imperfect but improving. Your review platform (e.g. Bazaarvoice, PowerReviews, Yotpo) should be building this into their stack right now. Talk to your rep and ask what they’re shipping.

(3) Owned content as anchor → When the review pool gets polluted, your owned, brand authoratative content (FAQs, structured product data, schema.org metadata) becomes a bigger share of the engine’s truth. The brands that invest heavily here are building insulatation.

The bigger picture? Review trust is going to get harder before it gets easier. Brands with verified-purchase ecosystems and strong owned-content programs are going to dramatically outperform. Plan accordingly. Start today.

These seven questions map directly to where every brand should be focused right now: training cycles, AEO vs. product-level, engine coverage, cross-pollination, prompt engineering, retailer agents, your DTC site as foundation, and review integrity.

Stay tuned for incoming news on this broader topic later this week 🤫 🚀

Let’s start with the big news, then go over the ‘why’ plus the ‘what does it mean’ and then wrap with the Amazon Frenzy 😵💫.

Introducing Product Feed Campaigns

Long-time Retailgentic friend Joe was poking and prodding at the ChatGPT Ad management user interface and was able to surface this feature. Note in the past this has indicated, this is a feature either coming soon for a test or already being tested by an audience using what’s called a feature flag that allows a vendor to ‘opt in’ one set of customers in a feature and the others don’t see it.

Background: Retailers and brands are able to upload datafeeds to ChatGPT now through their Merchant Center. Many brands/retailers may have multiple feeds and it’s good data hygiene for feeds to have a unique identifier (feed ID)

The first tell is here in the Ad Campaign creation flow, there’s a new ad type:

Here we have a pretty typical ‘campaign builder user interface with a 3 step wizard:

1. Create Campaign

2. Create Ad Group + Ads

3. Review

4. (Publish!)

Once ‘Product feed’ is selected as the ad type, the ad builder moves to step 2

Product Feed ID and Product Filters?!

Here’s what step 2 looks like:

Now we see the ability to create ad groups inside of the campaign, but with the exciting new twist, they are built on a Product Feed foundation.

Here’s how it works:

• First, you have to provide the product feed id (see backgrounder above for why).

• When the feed is found the UI pings Merchant Center and tells you there are X products loaded from that feed (in this example, 1,284).

• Then you can either run those ads against the whole feed (highly unlikely - see Analysis section for why), or you can carve off a set of products and run ads against that subset. ChatGPT is calling this ‘Product filters’ and the help text says: “Choose Product attributes to narrow which feed items can serve in this ad group.”

Available Product Filters

When you click on the Product filters selector you get 6 filter choices (today - I’m sure this will expand rapidly):

• Product Category - Here you can choose to advertise shoes, accessories, men’s, women’s whatever. and it’s a multi-picker.

• Brand - You can choose to runs ads against specific brands.

• Seller - This is a third-party marketplace setting. Etsy is an early launch partner with all the Agentic Commerce companies, so my bet is they are a design partner here and this was added at their request. They have some featured sellers they want to promote or they have a list of sellers that are paying to be promoted (down in the Etsy merchant center) which would allow Etsy to ‘pass them up’ to ChatGPT for ads.

• Rating - You may want to run ads against highly rated products (this is a weird one, I bet nobody uses it).

• Color - Also a weird one, nobody runs ads against ‘red’ only.

• Condition - A huge growth area in ecommerce is ‘circular fashion’ or recommerce. This feels like a setting where you could run ads against your new and recommerce categories or exclude refurbs if you were an electronics retailer, etc.

Long-time ecommerce marketers will immediately see that there are some key atributes obvious missing! We’ll cover that in the Analysis section.

‘Stacked’ Product Filters

In this example, we’re only going to run ads for products that meet three criteria: Brand=Adidas, Condition=New, Category=Trail shoes. That’s a pretty narrow ad group, but maybe it’s hiking season or we’re running a special promotion in partnership with Adidas. Regardless of why, it shows the power of ‘stacking’ filters like this.

Final Step: Ad Creative

Now you need to give ChatGPT a ‘recipe’ for how to merge in your product data with the ad creative. Do you want the product image? if so, which one? Do you want the brand mentioned, the color, the condition, the price, etc?

This simple ‘builder' allows you to do that create a mail-merge like setup where your product data feed data is married with the ad creative template to generate a pragmatically individualized ad for each SKU.

Now that you’ve seen what it looks like in teh UI, let’s analyze what this means for ChatGPT, the Digital Ad market and Agentic Commerce.

Analysis of ChatGPT’s Product Ads Feature

If you’re not familiar with this concept, the first question you may have is:

Why would you want to run ads against a datafeed?

The challenge marketers in ecommerce have is four-dimensional:

• Scale: Your average brand has 2-20k SKUs and the average retailer has 20k-100k+ SKUs

• Price Variation: Your price in that assortment most like varies wildly from sub $10 to over $300 or higher. (30x delta)

• Margin variation: Your margin (either $ or %) for these products is usually not 100% correlated to price or color, or category.

• Ad Copy: Creating bespoke Ad copy for 2-100k SKUs is tedious if not impossible.

Therefore ONE CPC ad for all your products doesn’t work. You’d be significantly overpaying for your $5 pair of socks and under investing in your $300 hand held vacuum cleaner.

The Solution:

The solution is you chunk up the datafeed into pieces that have similar margin/revenue/ROAS goals (and conversion rate) into a bucket and bid the same across that bucket. BOOM! Product Ads are born.

Complexity Awaits

The hidden complexity challenge of this approach is advertisers start to request near infinite ways to slice the data into buckets - what about by price range, what about by margin, what about X/Y/Z? May of these interfaces then either go into that being in the datafeed, or totally algorithmic (e.g. Google PMAX, etc.) where the advertiser just has to trust that the algorithm will hit their blended goal.

One last point:

Why is ChatGPT Moving so fast on ads?

I can boil this down to one picture:

According to Axios and The Information, OpenAI raised their last round on projections of $100B ad revenues by 2030. To put that number in perspective here it is against where the Big Ad Three are today:

ChatGPT is starting at 0. It took Amazon, with their giant distribution 20yrs to get to $70b (started in 2006). It took META 12yrs and Google 17-18. Can they do it? We’ll see. Life on the exponential only guarantees one thing: predictions are very very hard for humans to wrap their heads around.

Amazon’s Job Posting Frenzy

Earlier in the week, Joe found this job posting on Amazon’s website→

Retailgentic friend, Jason Del Rey covered this in the Aisle here (usually paywalled but his one is free - try it out and sub!)

Both Joe and JDR are assuming this means that Amazon is about to embrace one of the Agentic Shopping Engines like Gemini, ChatGPT, Perplexity, Meta, Claude, etc. The most eye popping part of the job listing is this part, that I think is causing the frenzy: “leading and mentoring technical programs for an engineering org of 40 people" within one of three specialized teams. More on that in a sec.

I’m going to diverge on this one and take the ‘under’. Let’s parse through the job listing closely with a bit of background first:

Background

Key datapoints for my thesis from the last 60 days:

• 3/11: Amazon Expands the Shop Direct program - adds a merchant center and we’ve heard though the grapevine they are out selling this program to brands not on Amazon (1P or 3P) aggressively. In fact Tuesday I’ll talk about Amazon being at Digital Shelf Summit which has to be a first.

• 4/28: Amazon announced they have joined UCP - Way back then (haha) I predicted a UCP checkout will be what replaces the browser-based Buy-for-me implementation that is a sub-set of Shop Direct. (I suggest they brand it UCP-for-me ;-) )

• 4/29: In the EPIC Quad Earnings Day Jassy was 100% NOT complimentary on ‘horizontal search engines’ and was giddy over Rufus. They also mentioned Shop Direct in prepared remarks/PR.

One more background item. Amazon has a famously different management setup than traditional companies - they believe in a flat org with lots of two-pizza teams tackling opportunities with loose coordination. The role that sits off independently and attempts to herd these cats is called the TPM role. It’s quite unusual role and I’ve never seen anything like it. It’s also insanely hard because you are held accountable for shipping things and hitting KPIs, but none of the people report to you. It’s best described as a ‘influence and persuasion’ job with a mix of project management. Want to learn more? Amazon’s job site has a complete guide the the TPM role here.

Amazon is playing Defense, not Offense here.

To summarize the Retailgentic 4/28 article into one picture:

I believe Amazon sees UCP/Agentic Commerce as a threat - a viable alternative to Amazon 3P with cheaper economics, but most importantly, a set of great inventory that is not available on Amazon. (The left side of the diagram).

By really leaning into Shop Direct and UCP they ‘eat’ the threat by making the selection effectively available to the Amazon shopper via Amazon.com and taking away any reason what-so-ever to leave the Amazon ecosystem. In business strategy this is called ‘Embrace and Extend (and sometimes…Extinguish).

My Big Amazon TPM Agentic Commerce Prediction….

My prediction sits on the fact that Amazon could easily have 40 devs working on both Shop Direct (SD) and Buy-For-Me/UCP programs. You could sketch-out people working on: Merchant Center, SD sales support, SD account management, SD feed processing, SD→ Rufus integration, SD→ Search integration, SD→Mobile, SD/BFM front-end, SD/BFM back-end, etc. Heck maybe you even want to integrate it with Alexa+. That’s like $10m to protect the $743B (TTM as of Q1) cash cow? Jassy can find that in the couch cushions up in Jeff’s old office.

Therefore, I believe this TPM person is coordinating the Shop Direct teams rapid growth in functionality and merchants as well as the move from the browser-based checkout in Buy-For-Me to the UCP which has the side benefit of allowing them to slurp up all the delicious selection that currently sits outside the Amazon Empire.

What confuses me the most is the stated fact in the ad that it’s 40 people across 2-3 teams. That’s a range of 13-20 people per team. Those are either massive pizza’s or they now have a 3-4 pizza team rule. I have heard from insiders that after Covid and RTO the previously religious 2-pizza team rule has flexed a lot.

Only time will tell, but the good news is I can guarantee you we’ll know before November 26th (🍗)! Stay tuned.

Microsoft - Welcome to Retailgentic!

In this episode, we sit down with Michele Fisher (Global Director, Business Strategy for Retail & CPG) and Atanu Ghosh (Director of Agentic Commerce & AI Innovation), who sit at the intersection of Azure AI, Copilot, and real-world retail and brand Agentic Commerce implementations.

They’re in constant conversations with global retailers and brands trying to figure out what actually changes when AI agents become the customer.

Listen/Watch Our Interview:

This conversation dives into how Microsoft is thinking about agentic commerce as a full operating model shift, not just a feature or channel.

From Copilot shopping to data infrastructure to ads inside LLMs, the discussion connects the dots between:

Highlights

• Conversational discovery is fundamentally different from search: The way people talk about brands inside AI systems looks nothing like traditional keyword behavior, and most companies have zero visibility into it.

• Agentic commerce is not one thing, it’s an operating model shift: Microsoft defines it broadly: agents participating in discovery, decision-making, and transactions, not just checkout.

• Copilot + catalog + data = the new commerce stack

• Ads are changing from persuasion to evaluation: Agents don’t care about creative. They evaluate structured data, trust signals, and relevance.

• Loyalty becomes infrastructure, not a program

• The “frontier firm” is the North Star: A future where humans and agents work together across workflows, not just AI acting as an assistant.

• Protocols like UCP matter more than people realize: Open standards enable discoverability across surfaces and prevent fragmentation in agent-driven ecosystems.

• The funnel is collapsing

If your brand is still thinking about traffic as the starting point, you’re already behind.
In an agentic world, discovery happens before you ever see the user, and increasingly, without them.

🎧 Listen wherever you get your podcasts: Spotify, Apple, etc.

Or, we have a video version on YouTube (make sure to subscribe!) →

Check out the materials we discuss:

👉 2025: The year the Frontier Firm is born

Want More Awesome-sauce Agentic Commerce Content?

Stay on top of what’s happening in agentic commerce, from the tools powering it to the founders building with it by following us across platforms:

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Up first, Google as been absolutely COOKING, as we say in the AI World, and we have two new feature Leaks that we’ve discovered that we wanted to share.

Editorial note: As with past leaks we’ve surfaced, these could very well be tests that don’t become perfect or change substantially. We surface them as more ‘directional’ information than ‘this is coming to production soon’. Only when the companies make formal announcements do we know we’ve crossed that threshold.

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Leak 1: We Spotted Google’s New Ad Unit Live in the Wild

On Feb 11th, we covered the Google blog post that focused on UCP being live in AI Mode, but in that same blog post, Google announced a new Agentic ad format that I coined Agentic PLAs (still don’t know the official name). As a refresher here it is.

Here it is:

In this example, we did a search for a popular beauty product - a makeup palette and clicked on one of the items. The offer card is now clearly segmented into two sections:

• Sponsored stores - In this example (super-sized in the middle) there are 4 stores (Belk, Macy’s, Ulta, Poshmark) that are paying to be sponsored and featured above the..

• All stores - here we have BOTH the sponsored stores listed again and then non-sponsored. In this example (bolding indicates sponsored): Macy’s, Sephora, Ulta, Belk, Nordstrom, Dillard’s. (Poshmark is in there, cut for brevity).

My guess from the screen shot in the blog post was that there would be only one sponsored store, this is quite a surprise first that there are more than one and second that they are duplicated in the ‘all stores’ - they get both top-billing and ‘re-billing’ again. This is quite a valuable ad unit, it’s not clear how much the merchant’s are paying for it and in what format (CPM/CPC/?)

Leak 2: Google moves UCP-powered Agentic Commerce checkout to ‘main Google’! 🤯

This one is wild! Previously, the UCP product search experience live in ‘AI Mode’, not Gemini mode or what I call core or traditional Google mode. In core Google mode, there was the traditional Google shopping experience.

Now somewhat reliably across devices, logged in, not logged in, we are seeing the AI mode UCP-powered shopping experience show up for core google.

In the example above, I’m looking for a Star Wars rug and here we see the Wayfair listing has a fully functional UCP Buy button activated. Example:

Leak 3: Rufus: RAIOs→ Rufus AI Overviews

This one is thanks to our super-sleuth Joe. For certain ‘vague’ searches in the core Amazon search engine, they are now showing what looks relatively similar to a Google AI Overview - or what we’re calling Rufus AI Overviews. Here’s a screen shot and a video of how it appears→

Note that it is clearly labeled: “AI results’ and it has a SKU that is surfaced. Up in the top left there’s also what we call an ‘escape hatch’ back to the OG experience. My guess is they are now using an AI to example inputs into the search box and starting to route them to different tools - ‘trad search results’ is tool 1 and now we have tool 2: “AI results” that seems to receive search terms that are ‘largely information or vague’ requiring more context.

Here’s a video for how they show up:

Leak 4: Rufus: Skip search go directly to Rufus

We discovered this one with a happy accident. I was entering a prompt in rufus and the focus had changed to the search when I wasn’t watching. The result - a long prompt resulted in the search box ‘auto routing’ (the third tool?) the search term (which was an accidental prompt) to Rufus→

The short video is the best way to see this one in action.

The Theme of These Leaks

Leaks 2, 3 and 4 share a common theme I’ve been wondering about. Here’s the logic path:

• Both Google and Amazon on their quarterly earnings calls in Q4 and Q1 have talked about the high conversion rates of Gemini and Rufus, later in this report we’ll have some third-party data that supports this.

• Therefore, if you have a better experience than the old one, wouldn’t you want to at least test or start moving more significant percentages of your traffic to that new upgraded experience?

• EVERYTHING in our world rotates around the holiday selling season. Therefore the best time to test the theory is in the relatively slower May/June/July and even August time before we ramp into Q4.

I believe these leaks, are testing this theme. If you’re Google and Amazon you want to start learning about what happens when you pour hundreds of millions instead of single/double-digit millions and even into the billions of queries into these newer systems. Questions they would want to answer:

• Do they higher conversions and economics continue with scale

• Do they systems scale well, or do they get more expensive and slow with massive scale?

• How do you run some tests that prove without a show of a doubt the causality of the lift. For example, was it self-selecting higher intent shoppers that caused the higher conversion or via random sampling - where they don’t have the choice - A and B have the same dynamics?

We’ll know if these are going well if/when we see a big move toward Rufus and AI Mode/UCP taking increasing percentages of traffic heading into Holiday 26.

Speaking of Rufus: Fresh Sensor Tower Data

In Feb we had Retailgentic friend Ian Simpson from Sensor Tower on the pod and he introduced their fresh Holiday 25 data here:

Late last week Sensor Tower dropped more data here. Two charts tell the story:

Here we now can see two quarters worth of data. And what’s super interesting is, as you’d expect with extreme seasonality the volume of sessions has dropped from peak (25%), but counter-intuitively you are seeing the conversion rate LIFT from that period from 26^ to 35%. Historically conversion rates peak during peak holiday season and then back off significantly more than traffic declines because there is less urgency outside of holiday.

Over that 6 month period of time we’ve been cataloging here on Retailgentic the massive improvements and features Amazon has been rolling out relentlessly in Rufus. There’s obvious ones (like new user interface features) and this indicates less obvious changes- the data quality, speed and algorithm of Rufus has to be improving at the same time to generate these counter-cyclical results.

Finally, Sensor Tower revealed this data:

Rufus shoppers are 2.74X more likely to purchase vs. a shopper without Rufus interactions. As mentioned in the leak section, if this stat is true and you’re amazon and GMV is the core driver of your economic engine - you want more more more traffic going through Rufus and if it holds, all of it. We just don’t see conversion rate bumps like this in ecommerce. Big companies invest millions for .5% in their search engines. This equates to 247% increase in conversion rates. At Amazon’s scale, if this holds and if the causality is the Rufus experience, this feature alone could double Amazon’s GMV. That’s two big “IFs” which I think is what they are likely testing with Leaks 3 and 4.

SimilarWeb AI Ads Report

Keeping on this theme of interesting new ‘observed data’ reports, SimilarWeb came out with detailed analysis of ad performance across ChatGPT, Gemini and Google AI Overviews. It’s a great report and pretty dense. My TL;DR, these new ads are nascent and already showing signs they are more performant than traditional search. Once they are optimized on the RLAIF exponential feedback loop, by Holiday 2026, we could also see Agentic Ads scale up as well as search changes.

Attachment Ai Advertising Insights From Real User Behavior (1)

2.78MB ∙ PDF file

Download

Download

Anthropic Releases Detailed Claude Observed Usage Data

If you recall, OpenAI released some usage data back in October of 25 and we had OpenAI Chief Economist, Ronnie Chatterji on the pod to discuss:

At that moment in time, it was disclosed that ChatGPT has 2% of prompts related to products/shopping.

In the Anthropic report here. they show that 6% of the conversations fall into ‘consumer’ which anthropic describes as “Product comparison + purchase decisons. Rental decisions. Vehicle purchase and repair.

Like the ChatGPT data, when you dig into how this classification, it reveals to me that this is understating the shopping queries. The way it works is they look at the START of the multi-turn conversation. Fo an example, if someone starts talking about say their weight, this classifies as a ‘health/wellness’. But let’s say on turn 3 the answer engine suggests they try some protein bars, a heart/sleep monitor, etc. Products are surfaced and purchased. You guessed it, still Health/Wellness.

The engines take privacy so seriously they are reluctant to point a categorizer at anything but the first convo, but I believe the unintended impact of this is an understating of the Consumer bucket.

They don’t really dig into the data other than this chart. We have a theory at Retailgentic (one of my 2026 predictions) that Anthropic will enter Agentic Commerce. If you look at their jobs area, you’ll see they have three vertical teams.

You’ll note that the number 1 category (Healthcare) now has a team and the number 4 (Financial) has a team. How long before they get to number 6? Could they already be there and just not transparent about it? If they are going to do something, we’ll see it before Holiday 26.

It’s a Wrap

I realize that’s a LOT to digest in one update, but this is how we’re going in Agentic Commerce - these are the top seven items we wanted to surface because on the surface they may seem tactical, but they point to the bigger strategic direction we’re going to see Agentic Commerce go in the next 2 quarters.

Good morning Retailgentic readers! Today the big news in Agentic Commerce comes from our own backyard. Before we get into the details, a little backstory for everyone…

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A long time ago in a galaxy not too far away (in North Carolina actually)….

Editorial note: Yes it’s not May 4th anymore, but shouldn’t EVERY day be Star Wars day?

James, Cameron, Derek and I (all ChannelAdvisor alumni) started ReFiBuy way way (this story takes place in AI time) back in January of 2025 with the idea that Agent-based systems (agentic we call it now) could solve some of ecommerce’s hardest problems. We had an inkling that the best application of these solutions could be what we now all call Agentic Commerce.

We were fortunate to raise a pre-seed round and announced that in mid-March. Fun fact, it was led by ChannelAdvisor’s B investors, G20. We then quickly launched our first product Commerce Intelligence Engine at the first RetailClub in September of 2025

As we entered 2026 and after Google’s big splashy UCP news at NRF, we knew the time had come to not only double down, but super-de-duper quadruple down on Agentic Commerce Optimization.

In early March we started the process of raising a Seed round.

ReFiBuy’s Seed Round Details

Today we are announcing that we’ve raised a Seed round. What we’re most excited about, that I’m pretty sure for the first time ever, all four of the early stage RetailTech/EcommTech investors have invested in one company! Let’s start with the new RetailTech/EcommTech investors:

• New Road Capital Partners - New Road led the round and we’ve really enjoyed getting to know everyone at the Bentonville based firm and already learned a ton from them. Everyone at New Road eats, sleeps and breathes retail from the back office supply chain to the frond-end user experience and all the pieces in the middle. New Road has a big investment theme around Agentic Commerce and found us through their research

• Ridge Ventures - Based out of Silicon Valley, Ridge has had an Agentic Commerce Optimization investment thesis since July 2025 (maybe earlier, that’s when they first reached out to us). They are avid Retailgentic readers and it’s been fun to debate the nuanced details of ACO, strategy, how the market is moving with the team. We’re really excited to work with Alex, Eli and the rest of the crew at Ridge Ventures as we work towards building ReFiBuy to the next phase.

• Silicon Road - Also new this round, and based out of Atlanta, Silicon Road is self-described as focused on CommerceTech. Their DNA goes back to founder Sid’s company SPI that was a full-service tech solution partner focused on retail from the go-go years of 1994-2016. From there it’s about as Atlanta as you can get with the ATDC, lots of Georgia Tech, Coke and orange aprons around. We were introduced shortly after our pre-seed by a mutual connection and have enjoyed getting to know this team more deeply.

• Commerce Ventures - Another Silicon Valley firm, the name Matt Nichols may be familiar to the Retailgentic podcast audience as he’s been the guest for not only one but TWO of our top rated/viewed/downloaded pods (here and here if you want to catch up). As their name implies, they are also 100% focused on CommerceTech. They also publish a ton of great strategic thought pieces on the future of retail/digital like their Commerce Continuum framework. Independently, but very similar to New Road, Ridge, Commerce Ventures has had a long-time thesis around ACO. Like G20, Commerce Ventures has been with us since the earliest days and we’re thankful for their support!

Outside of the CommerceTech focused investors, our good friends in Boston, G20, continued their early support by contributing materially to this round in in both capital as well as advice and wisdom through the process. Also out of Atlanta, Knoll Ventures continue to be very supportive and participated in both our pre-seed and the seed. Finally we were able to add the Silicon Valley ex-Googler run firms: VELA Partners (who uses and an AI to find and score companies!) and Incubate Fund that has deep relationships with brands, retailers and tech companies in Japan. We also had the support from many angel investors in the industry which is great to be working with so many OGs - thank you!

Thank YOU!

Many of our customers have come either directly from the Retailgentic community or via word-of-mouth from Retailgentic subscribers. Thank you for your support. Every time you like, forward, comment or engage with our content, it gives us important feedback for where the industry is going that helps keep us out there on the bleeding edge making sure we are researching the latest and greatest so we can pass on what we find to you. The content engine then feeds directly into the product roadmap.

What Does This Mean for Retailgentic!?

Great question, I’ll wrap up and hand this one over to huge Retailgentic fan, Kylo Ren to explain our strategy in very detailed terms for Retailgentic going forward.

May the Force be with you…ALWAYS!

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Stephan Ritter is Director of Commerce Transformation at Deloitte, where he leads agentic commerce initiatives across Europe. With a background spanning digital agencies, global eCommerce rollouts, and customer experience strategy, Stephan now sits at the intersection of AI, commerce, identity, and data. He has become a leading voice on how brands and retailers should adapt as AI agents reshape how products are discovered, evaluated, and purchased.

Listen/Watch Our Interview:

In this episode of Retailgentic, Stephan breaks down how agentic commerce is evolving globally, with a particular focus on Europe’s rapid adoption.

We explore why AI-driven shopping is accelerating faster than previous technology shifts, how brands are already losing visibility without realizing it, and what practical steps companies can take today to stay competitive.

From product data strategy to protocol wars to the future of loyalty, this conversation offers a clear view of where commerce is heading next.

Highlights

• Discovery is the new battleground: If your product is not readable, trustworthy, and rich in context for AI agents, it will not be recommended.

• Agentic commerce starts before checkout: The most important shift is happening in discovery, comparison, and decision-making, not the final transaction.

• Europe is moving differently, not slower: Adoption among younger consumers in markets like Germany is already very high, with many using AI in shopping workflows.

• Product data is now infrastructure: Years of optimizing for search engines are being replaced by the need to structure data for AI systems.

• Loyalty and identity are becoming core systems: Future commerce will depend heavily on how well brands manage identity, value, and customer relationships across AI ecosystems.

• Protocols are evolving fast: Systems like UCP and MCP are shaping how agents interact with product data, pricing, and checkout layers.

• Small experiments already create visibility gains: Even limited API exposure or structured data improvements can increase inclusion in AI-driven recommendations.

• Agentic commerce is accelerating existing problems: Many of today’s challenges, like poor data quality and disconnected systems, have existed for years but are now becoming urgent.

Agentic commerce is already reshaping how products are discovered today, and the brands that adapt fastest will define the next era of retail.

🎧 Listen wherever you get your podcasts: Spotify, Apple, etc.

Or, we have a video version on YouTube (make sure to subscribe!) →

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Welcome to the Retailgentic MAG4 Mega Earnings Agentic Commerce Report! (…said in my best monster truck announcer voice)

In a first ever in the history of internet stocks (confirmed with my Wall St buddies!), we had the four public companies we watch the closest here at Retailgentic report earnings and host their calls in the 120min window from 4-6pm today. It was insane! Look CNBC had to go to the rare 4 box!

Even good friend of Retailgentic, Wall St. analyst Gene Munster, who is usually the calm in the earnings storm, had his mind blown live on CNBC!

(Seriously though, watch this segment, it’s A+ and talks about, well you’ll see).

Who Was the Winner with Wall Street?

The table above shows the after hours moves in the stock at around 8pm ET which tells you how Wall St. reacted. Google was the only one of the three that had what is called a clean beat and raise and Wall St. loved it sending shares up 7%. Remember this is a $4T market cap stock so UP 7% is about 5 Targets (by market cap math) worth of market cap added.

Meta was the loser on this short-term sentiment measure dropping a similar amount to the downside (7%). More on that later, let’s look at…

Who Was the Agentic Commerce Winner?!

CNBC and Gene are going with:

This Retailgentic ‘Agentic Commerce mentions’ scoreboard tells the same story. We went to work when the last call was done on tallying the mentions of ‘agentic commerce’ and surprisingly Amazon came out on top. Perhaps it was because they joined the UCP alliance and released 8 big Rufus features right before earnings? In any case they won on that super-un-scientific dimension:

Let’s go from least mentions to most and dig into what was said. If you add it up that’s 20, yes 20 Agentic Commerce mentions so this is going to be long, but for such a historic moment in time, we think it’s important to really capture this moment in all it’s grandeur.

For each section, we’ll highlight three different areas that are all part of the earnings mosaic: Press release mentions, prepared remarks mentions and Q+A questions that mentioned Agentic Commerce. One editorial note, we are favoring speed over perfect, these are preliminary transcripts - the gist is right, but every word may not be perfect.

At the end we’ll roll it all together into some conclusion.

Google’s Q1 Earnings Agentic Commerce Mentions

Google’s press release is very financially oriented, but in prepared remarks they added this from Philipp Schindler, senior vice president and chief business officer

“AI Mode already surfaces organic product recommendations based on a user's query, and we're now testing a new ad format that displays retailers who sell those recommended products. In addition, the retail industry is rapidly coalescing around the open source Universal Commerce Protocol, or UCP, we launched in January in partnership with the ecosystem. Last week, we welcomed Amazon, Meta, Microsoft, Salesforce, and Stripe as new members to the UCP Tech Council. They join founding members Shopify, Etsy, Target, Wayfair, and Google to further accelerate the transition towards an agentic future. Partners like Sephora and Macy's have joined companies like Ulta Beauty, who are already rolling out UCP and can now redefine consumer journeys from discovery to checkout. Ulta Beauty just last week launched agentic commerce within AI Mode and Search and the Gemini app.”

Question (Eric Sheridan, Goldman Sachs):

“Philipp, to bring you into the conversation, you referenced UCP and there’s been a lot of industry inertia around UCP very quickly. Talk to us a little bit about what UCP means. For the services business as agent to commerce scales in the years ahead. Thanks so much.”

Answer: (bolding is my own)

“Look, I mean, we’re in the early stages of the agentic era. Agentic is more than just completing transactions. We all know this. We see agentic experiences as additive. And it will really transform how we shop from discovery to decisions while helping, obviously, brands differentiate themselves. Our goal is really to remove the grunt work of shopping. So consumers can focus on the enjoyable parts. For decades, you could either shop fast or smart.

And I think with agentic commerce, you no longer have to actually choose between speed and certainty here. The universal commerce protocol, a new open standard for agent e-commerce that works actually across the entire shopping journey from the discovery to the buying and the post purchase support that we just talked about.

It was really co developed with the industry leaders, including I mentioned Shopify, Etsy, Walmart and so on. And we’ve received tremendous feedback so far from hundreds of top tech companies, payments partners, retailers really interested in integrating. It will help power a new checkout experience in AI mode and search and the Gemini app and allowing shoppers to actually check out from select merchants right as they’re researching on Google.”

Question: (Ross Sandler, Barclays):

“Just following up on the last question on agentic shopping. So it seems like we’re at the point in time where this is actually going to start happening finally. So, Philipp, just to elaborate a little bit, as you try, as you look at carrying the AdWords business from kind of the old way of doing things to this new agentic friction with shopping way, how do you see the price and volume kind of growth trends for core AdWords evolving as, as you start implementing more agentic workflows in search?”

Answer: (Philipp again)

“Look, our number one focus is obviously on the user experience here. I think, the most important part in this is, what I mentioned before. We are carefully designing the space in the agentic workflows for the users to actually see the valuable components, within that shopping journey. The second you have the space, you obviously have the ability, for interesting app advertising models. I think it’s also worthwhile noting that, beyond just the traditional agents, there is a lot of additional ways we can actually use AI to improve the shopping experience. You can think about it like our apparel try-on tools, that is now available in the U.S. You can think about Google Lens.”

Meta’s Q1 Earnings Agentic Commerce Mentions

In her prepared remarks, META’s CFO, Susan Li, said the following:

Last, I want to touch on our commerce efforts. People discover products on our platforms through ads and organic posts, with brands increasingly turning to creators to promote their products. This is contributing to rapid growth in our partnerships ads product, with its revenue run rate more than doubling year-over-year in Q1 to $10 billion. To support the product discovery and purchasing happening through creators, we're expanding our solutions beyond ads. Last month, we rolled out our affiliate partnerships offering on Facebook to more test partners, so creators can tag products from participating retailers on their posts and earn a commission when someone makes a purchase. We have also started testing similar experiences on Instagram. We see a real opportunity to help people more easily discover and buy products within our services, particularly as we incorporate AI deeply across our platforms.

Then in Q+A, the first question, and this is going to sound like deja vu…

Q: Eric Sheridan, Goldman

Thanks so much for taking the question. Maybe if I can build out on one of the topics that was discussed in the prepared remarks, but just the opportunity set that sits in front of the company with respect to putting agentic compute in front of both consumers and enterprises. You’ve long been associated with sort of the consumer landscape, and I am curious about how you’re thinking about extensions of the media engagement parts of your business model and the commerce parts of the business model to become more agentic over time. What do you see also as the opportunity set that sits in front of you across SMBs and enterprises where historically you maybe haven’t had as much product velocity? Thanks so much.

Zuck answers:

Of course, as we are able to build out more agentic capabilities, you know, enabling agents to help people be more productive, but also agents for businesses and enabling, frankly, those agents to interact with each other, and, you know, build what we hope will be a thriving commerce ecosystem on our platform. You know, I would say some of these are a little bit further out, you know, especially in that latter category of things. Again, the focus is on building personal super intelligence. You know, building a consumer agent that can work for you and help you get things done. That right now is a consumer experience that we're focused on, but we think there will be clear monetization opportunities over time. You can imagine commission structures or a premium offering.

Question: Ken Gawrelski with Wells Fargo

First, you talked on the Muse Spark launch, you talked about 2 categories or 2 verticals. You talked about health and wellness and shopping. Could I dive a little bit and ask you to dive a little deeper into the latter on the shopping and commerce side? Were there any learnings, you know, in the 2021-2022 phase where you pushed deeper into commerce on Instagram and on Facebook? Any learnings from that period that you might apply? Is there an opportunity for a next-gen marketplace-type business in commerce?

Ok, this one was music to my years - he tied together their plans for the future, but also some of the mis-steps in the past as well as pulling in marketplaces 👨‍🍳😘 question Ken!

This one is a really great answer, and I think you’ll get more out of listening to it here:

If you really want to read it: (it’s a 4min answer!)

I might give you a somewhat loftier answer to the question. You're asking about shopping. I think it's sort of an interesting example of the way in which the work that we're doing is different than what I think others are doing out there. You know, these products, AI agents get better when you fully optimize the stack. That's why we believe that we need to be a company that builds frontier models in addition to building the agents. You of course, need to build your infrastructure in order to be able to do that well. We're undertaking this large investment to be able to do that top to bottom.

I think a lot of the way to think about the investment that we’re making is a bet that the individual things that people care about and that people are going to be more important in the future. That’s sort of like I think it should be a pretty obvious thing to say, but I think so much of the rhetoric around AI in the industry is around, like, a company trying to build some kind of centralized thing that, like, does all the productive work in society in some way or something like that. That just is very different from how we see the world. Like, our vision for the future is one where society makes progress by individuals pursuing their own aspirations.

Some people care about big, grand things like curing diseases, and a lot of people care about personal things like finding the right shirt for my daughter. I just think that we’re gonna build things that help deliver this vision for personal agents for people. I think that part of the lane and what is interesting and differentiated about what we’re doing is that that’s just so different from how I hear everyone else talking about the work that we’re doing. Even though I think some of these ideas, they seem like they should be so obvious, I actually think that our approach of trying to empower individuals and building consumer things is just in the details extremely different from what others are doing.

Shopping might be one kind of specific example that I think is gonna have interesting commercial implications, and I think people, consumers are going to like it. You know, I don’t hear any other labs out there talking about how they’re building an AI that’s really good at shopping. I think that the reason for that is not because shopping is the most important thing by itself, but because empowering people to do the things that matter in their lives, whether that’s local or understanding social context or shopping or personal health things or understanding what’s going on around them visually, which is gonna be really important on the glasses. These are all elements of the personal super intelligence vision.

I think, like, a lot of this and when you're thinking about kind of the investment in Meta over time, I think you should think about it as coming down to these set of values. Around what do we want AI to do in society? If what you want it to do is empower individuals and build a world where the AI is in service to individuals' goals, then that is what we are going to build, and I think it's going to be incredibly valuable.

What’s funny about this one is it was a two-parter with part being a tactical question for Susan and she’s clearly a bit gobsmacked by Mark’s off-the-cuff monolog and to answer her question starts off with this lead in: “Gosh, I almost wish we could end on that answer.”

Amazon’s Q1 Earnings Agentic Commerce Mentions

Amazon had a hat trick: press release mention, prepared remark and TON of mentions in Q+A.

Let’s start with Q+A:

From Jassy’s prepared remarks:

Rufus, our agentic AI shopping assistant, continues to resonate with customers. Rufus can research products, track prices, and auto-buy products in our store when they reach a set price. Monthly active users are up over 115%. Engagement is up nearly 400% year-over-year.

He also echo’d the press release statement, we won’t duplicate that for brevity.

In Q+A the first question came from Brian Nowak (Where was Eric!?)from Morgan Stanley:

I have two questions. <cut for brevity> the second one, as you sort of think about milestones for Rufus and agentic commerce for you in 2026, what are you most focused on making sure you accomplish on the agentic side this year, just to make sure you stay at the nice edge of the agentic commerce offerings? Thanks.

Jassy answers: ( a long one!)

On the agentic commerce milestone question, you know, we are very bullish on what agentic commerce will look like. I think it's gonna be very good for customers in the long term. I think it'll be good for us too. You can see some of that focus from us in what we're building with Rufus. If you haven't checked out Rufus in a while, it really substantially improved over the last year, and we have a lot of customers using it.

As I mentioned earlier, you know, you see the monthly active users up over 115% in Rufus and the engagement up over 400% year-over-year. You know, I think, while I think there will be, we'll do a lot of work with third-party horizontal agents to try and make that customer experience better. By the way, I do think today it reminds me in some ways the stage we're in of what we saw in the early days of search engines, and they're trying to refer business to e-commerce. You know, it's never been a giant part of the referrals to our e-commerce business. Over the years, the experience got better.

What you see with agentic commerce is it's a small fraction of what we see with the search engine referrals, but the experience just hasn't gotten great with these third-party horizontal agents yet. They're not often able to get the pricing right or the product information right. They don't have any personalization data or any shopping history. We do wanna see that get better with third-party horizontal agents. We're having conversations with all those folks to try and make that better and find something that works for customers and all the companies. It'll be interesting over time which agents customers choose to use.

I happen to think that if you're going to a particular retailer that you like to do business with and you like to shop from, if they have a great agentic shopping assistant, you're gonna often start there because it's where you're doing your shopping. They have better product information. They have better information about what other customers like you are buying. You can make all sorts of changes to how your account and your shipping information is working there. You know, that's what we're aiming to make Rufus be, is we're aiming to have it be the best shopping assistant anywhere, and I think we're on that path.

Question: Shweta Khajuria with Wolfe Research

I have no doubt that Rufus could be the best shopping assistant available over time. For advertising opportunity, how do you view that if agents would be the ones taking action to shop? Thanks a lot.

Jassy Answers:

I think on the agentic commerce and how that impacts advertising, you know, I actually believe that we’re gonna like this for advertising. I think it’s gonna be good for customers, and it’s gonna be good for our business. I think first of all, the first thing to remember is the way that our Ads team has built tools and agents themselves is making it so much easier to do advertising.

You know, if you look at small, medium-sized businesses that had to take, you know, weeks and months to do creative and to pick the right audience, all that is just, it’s so much faster and so much easier because of our advertising agentic tools. You no longer have to take as much time or spend as much money building the creative. I think they’re gonna be a lot more advertisers with the rise of what’s happening in AI. If you look at the agentic commerce experiences, or you look at any of these agentic experiences, they tend to be multi-turn conversations, where you’re not interacting with one search and getting an answer. You tend to find that you’re asking questions, you’re narrowing questions, it’s asking you questions on what you want.

You know, in that process of having multi-turns, there are multiple opportunities to surface relevant products to customers, you know, many of which will be organic and some of which will be sponsored. You know, it also gives rise to opportunities like sponsored prompts. One of the interesting things that has been very successful for customers in our store has been when they ask certain questions, we give them a number of suggestions that are, that are, all created through AI. You know, we’ve gotten pretty good at also having sponsored prompts and that mix of questions and prompts that make it easy for people to keep digging deeper into what they’re interested in. I actually believe that, advertising will do well in a world of agentic commerce.

Headlines from Q1 Earnings

To summarize:

• Microsoft had other priorities this Q 🤷‍♂️

• Google is very bullish on the UCP momentum and took a minute to ‘spike the ball’ celebrating their big wins (at the expense of OpenAI’s ACP) and celebrating the big win with Ulta launching both on Gemini, but also using Google as their on-site agent partner.

• Zuck at META threw the gauntlet down that he thinks they are thinking about shopping in a different way than any other company and it’s going to be “really good at shopping”

• Amazon gave us three new Rufus datapoints this Q!→

  • 20% - The % of shoppers who interact with a Brand Prompt continue to conversion with that brand.

  • 115% - The growth in active users (probably a y/y measure).

  • 400% - Year-over-year growth in engagement

• Jassy frames Answer Engine Agentic Commerce as ‘horizontal agents’ (which is what we call it - 🤔. But he frustratingly still acts as if the experience is terrible (he cites wrong pricing and bad information) . I’m sure he’s pretty busy, but I think someone at Amazon needs to write him a 6-pager on why this is just 100% wrong.

• Jassy is beyond bullish on Rufus, he’s downright giddy by my read. To me that says, they are blown away by the conversion data coming out of Rufus (more on this later with some fresh hot data that dropped earlier today, so much Agentic Commerce news, not enough time!).

• On top of that, he’s just as jazzed about Ads in Agentic Commerce (Rufus)

Conclusion: Amazon, Google and META continue to be all-in on Agentic Commerce, continue to invest at a crazy pace in AI infrastructure, products, teams, etc. We are in a very strong setup for the rest-of-the-year heading into not only Holiday 2026, but an IPO season that could see SpaceX, OpenAI and Anthropic pushing to get public before EOY. 🚀🚀🚀🚀🚀🚀

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For More Information…

If you want more analysis on the Q1 results from Amazon, Meta, Microsoft and Google such as broader AI topics, backlogs, their insane AI Capex and all the broader topics, Jason and I are recording an episode this week, and we’ll drop that on the Jason and Scot Show soon.

Bonus charts for staying this long:

Meta capex: 🤯🤯 (spoiler alert - this is why the stock went down)

(this is microsoft)

And Google→🤯

This Wednesday (April 29th), we have a big first ever situation (in my memory at least). Four of the Magnificent 7 (aka Mag7) are reporting on the same day: Alphabet, Amazon, Meta and Microsoft. That means $14T of AI-powered market cap reports their first calendar year earnings in a < 12 hour window - it’s going to be a crazy news week to say the least.

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On the Amazon front, I predict in Wednesday’s report we are going to hear a LOT about Rufus because last week not only did they drop a ton of cool new features we will detail, but they also shocked the Agentic Commerce world by joining the UCP alliance!

Let’s start there and then jump into the new features.

UCP Flexes It’s Muscles

On Friday, April 24th at 11:05am (weird right?) Google issued this press release that Amazon, Meta, Microsoft, Salesforce, and Stripe have joined the UCP Tech Council. Stripe co-created ACP with ChatGPT, so that one hurts and we knew Microsoft already from their announcement and ‘first to launch’ a loyalty (Identity) implementation as covered here at Retailgentic.

Meta is also a bit of a surprise, because we’ve seen evidence they are engaged with ACP (the only company checking in code over there in a long time). Perhaps they are hedging or they tried both and voted with their feet - I suspect we’ll hear something on this one Wed.

The really shocker was Amazon being added to the list. My phone lit up like a Christmas tree - with people asking:

Ok, But What Does Rufus+UCP Even Mean?

All we know is Amazon was on a list, but if you marry this announcement with the features we’re about to go through it shows you a general direction that Amazon is going called.

Embrace, Extend and …..Extinguish?!

When the internet started soaring in popularity, led by the Netscape browser, Microsoft famously developed a strategy to take the internet protocols, embrace them, extend them and then extinguish the challenger companies by ‘out disrupting’ them. I believe Amazon is employing a strategy like this.

Here’s how I see them utilizing this here. First, let’s look at the classic Amazon Third Party marketplace flywheel:

At the heart of the flywheel is the magical world ‘Selection’. Amazonians are well aware that this little diagram is at the heart of Amazon’s growth over the last 20 years and it’s drilled into the training so deeply that anyone on the retail team can replicate this diagram blindfolded with one arm tied behind their back. Selection, selection selection.

Agentic Commerce’s Threat to Amazon: Selection

Up until today, if you wanted to get to the selection that isn’t in Amazon, you would have to visit hundreds to thousands of websites or use the non-transactional Google Shopping which isn’t really a ‘transactional’ threat. ACP and UCP threatens to challenge that. What if you can now find all of the stuff ‘not on Amazon’ in one location. What if the economics are so good, Amazon starts to bleed 3P sellers? That’s a threat worth keeping an eye on and looking the opportunity to embrace and extend to neuter the threat. Here’s a Venn diagram visualization:

If you’re Amazon, this is bad. As pictured, I’ve made it very small. but what if it grew, what is all the selection not in Amazon was in one place that at least checkout-wise was as awesome as Amazon. What if the discovery was a bit better too and didn’t have ads? Hmm, that’s a potential dagger to the heart of the flywheel - not good.

What Embrace and Extend looks like:

Boom! Not only have you addressed the threat (embrace) you’ve actually INCREASED Amazon’s key flywheel component: Selection. Amazon 1P+3P+UCP is « Amazon 1P+3P. How would it work? Here’s how.

Just recently (March 11) , we covered in detail here Amazon’s moves to expand the Shop Direct program to add datafeeds to the crawled solution. At the time it was interesting that there was not real mention of the Buy-For-Me solution. The first save of Agentic Commerce checkouts used ‘browser-based checkouts’ - Perplexity Buy with Pro, Google Buy for Me and Amazon Buy-For-Me. With the exception of Amazon Buy-For-Me have all been replaced by UCP or other non-browser solutions. My prediction is the final step here is Amazon will deprecate or slowly move to the background the Buy-For-Me and we’ll see UCP used to enable transactions in addition to or instead of Buy-For-Me on Shop Direct inventory.

Now you have no reason to shop on Google, for example here’s the “Gemini selection” Venn diagram:

Google Gemini’s inventory is just UCP, no Amazon 1P+3P. By being ‘read only’ with UCP meaning they won’t publish UCP datafeeds but will ‘consume’ the end points they starve competitors of a large percentage. Embrace, Extend, Extinguish - game over. Check and mate.

Amazon’s Flood of New Rufus Features

As a reminder, on Amazon’s Q4 2025 earnings call, Andy Jassy announced that Rufus is now available to 300 million active customers and is already driving roughly $12 billion in down-stream transactions. Days before the UCP announcement, Amazon via a post on the About Amazon / Amazon News blog site, they announced a raft of new features in Rufus. Let’s go through them in detail.

Rufus New Feature (RFN) 1: Scheduled Actions

The best way to see this one is to show you some examples. To get to Scheduled Actions, you press the new little Plus box (popularized by ChatGPT now used by everyone as a UI metaphor) and it only has ‘Scheduled Actions’ (today!).

If you just choose this you get these ‘prompt pill’ pre-canned suggestions:

My first line of thought - this is going to be great to get a jump on in-stock alerts! Well, turns out Amazon will only run a scheduled action once a day:

One nit-pick, if you’re only checking once a day at, say 6am or midnight or whatever, then you aren’t going to be letting me know ‘immediately’.

I then thought, what about price lowerings, there’s already a price tracker feature, but you can now use Scheduled Actions to set price alerts:

Finally, I had it set an alert for my Veggiedent’s to be on sale at their lowest price and an overall weekly deal tracker. Now when I say “show me my current actions” Rufus will help me manage my list:

When the alert fires, I get an email like this:

RNF2: Rufus Persistent Account Memory

If you’ve watched my Rufus videos, i’ve always find it kind of mind boggling that Rufus didn’t have access to my oder history. Amazon has fixed that, now Rufus is faster at finding an order than your order history. Let’s say I can’t remember exactly what I ordered, Rufus finds it instantly with natural language, no need to remember the specifics:

RNF3: Personalized Deals

Rufus also now has access to your wish list and Amazon browsing history in addition to your past orders. These feed into what they are calling Personalized Deals. You can ask Rufus some prompts like: What are the best deals for me? or even more specifically, “Are any items on my wishlist on sale?”

RNF4: Custom Shopping Guides

You can use Rufus to deep dive into topics you’re interested in. Ask Amazon any high level question about doing something and it will now piece together the products you need, punch out things you already have from your history and give you a detailed plan for how to use that plus anything new. Here’s an example where I asked Rufus hypothetically what I would need for a video blog: (edited for brevity and to save space).

RNF5: Easy Reorder

You can be specific or general such as: reorder dog treats or “reorder everything I used to make pecan pie” and Rufus will load your cart up for you.

RNF6: Shop Direct is Now Available In Rufus 🤔

I haven’t been able to recreate this one, so going to include Amazon’s stock screen shot here→

RNF7: Compare with Similar

On many PDPs under the hero image where there have historically been Rufus Prompt Pills, you will now see a ‘compare similar’ prompt pill. You can also manually ask this at any time. Here it is for some On shoes:

Here the Rufus UX is really restricted by the teenie tiny little left hand gutter space it has been allocated. Inside that one inch gutter is a comparison matrix that isn’t super useful because when I scroll i can’t see everything. They clearly need to rethink this UX. If I screen shot it and glue it together for you, here’s what it should look like→

When you see it this way, it’s a great feature, what an awesome table - but when you have to scroll to see 1/2 of the column you can’t tell what’s going on. The feature is significantly diminished by the UI limitation of the Rufus gutter.

RNF8: Personalized Product Summary

The final feature is another “PDP Prompt Pill” feature. In fact if you go back up to my shoe example above- there it is!

The response is kind of funny, can you tell I literally ran this search after the video blogging shopping guide example?

I’ve really got to hit those trails before my next big vlog shoot, phew. 🤪

Pulling it all together…

That’s 8 new awesome Rufus features that are Agentic (scheduled actions) and Personalized (7 out of 8).

The UCP announcement and the Rufus personalization family of features both have one thing in common: Single-directional Embrace and Extend.

• UCP - Allows Amazon to super-set all the UCP selection, but in a ‘pull not push’ model - You can shop all the inventory on Amazon, but only UCP everywhere else.

• Personalization Features - Your Amazon order history, your wishlists, past Rufus convos and also product browse history are Amazon exclusives. Gemini won’t be able to use these as input (well…if you connect your gmail account that receives your Amazon emails, maybe there’s a back-door to your order history, but it’s not as ‘clean’ as what Amazon has).

Will Amazon’s Embrace and Extend strategy work? Will they be able to push off the competitors at the gates, like Microsoft did with Netscape? We will see. Next up in Amazon-land we have the big Q1 news, we’ll be reporting on what we see there, buckle up it’s going to be a busy week in Agentic Commerce!

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Krystina Gustafson s the Co-Founder and Co-CEO of RetailClub, a next-generation event platform focused on the intersection of retail and AI. Prior to RetailClub, she spent seven years at Shoptalk, where she led content across the global event portfolio during a period of rapid growth.

She started her career in journalism at CNBC before moving into events, where she spent seven years helping build Shoptalk into one of the most influential gatherings in retail. Along the way, she’s worked closely with executives, operators, and innovators across the industry.

Today, she’s focused on one thing: helping the retail ecosystem navigate the shift to rise AI and what comes next.

Listen/Watch Our Interview:

Krystina talks to hundreds of retailers across the globe and is able to synthesize what she’s hearing into amazing conference content. In this episode she shares what she’s hearing from operators, board members, and data leaders on what is top of mind in their organizations. What are the biggest opportunities and what are the biggest fears?

At the same time, we explore how agentic commerce is reshaping traffic, discovery, and brand relationships and what that means for the future of ecommerce.

Highlights

• AI is forcing a full end-to-end transformation of retail

• Many companies are prioritizing the wrong AI initiatives, focusing on hype instead of P&L impact

• A growing concern: “dark” or untracked AI-driven traffic is already impacting performance

• Data strategy is becoming a core battleground: What do you give AI platforms? What do you get back? Do CRMs need to evolve entirely?

• The real unlock for AI shopping is complex, multi-step purchases (travel, events, planning)

• The industry is early, but pressure from boards and declining traffic is accelerating adoption

The future of retail will be defined by who applies it to the right problems.

🎧 Listen wherever you get your podcasts: Spotify, Apple, etc.

Or, we have a video version on YouTube (make sure to subscribe!) →

Want to Learn More?

Stay on top of what’s happening in agentic commerce, from the tools powering it to the founders building with it by following us across platforms:

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We're here to make sense of what’s next in retail + AI and bring you along for the ride. Subscribe and stay tuned!

In what appears to be a stunning reversal in our corner of the Agentic Commerce World, Microsoft casually dropped a blog post for Microsoft Merchant Center (MMC) that talks about their UCP support and announces Target.

This leaves ACP hanging by a thread with only ChatGPT supporting it (the datafeed piece) and META appears to be leaning ACP.

Let’s dig in!

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Background

Here’s a brief history of Microsoft CoPilot’s short-lift relationship with ACP:

• January 8, 2026 - CoPilot Checkout was announced and based on ACP.

• January 22, 2026 - In a Retailgentic exclusive, we discovered CoPilot Checkout live in the wild and demonstrated a live purchase from Anthropologie.

The Breakup Details

Here we are today a short 104 days and the breakup came in a blog post! Note: for comparison to Hollywood drama, this is longer than Kim Kardashian was married to Kris Mumphries which came in at 72 days.

The post is here and some of the details:

The top of the post has a good hook (note we’re not going to get to UCP for a while)

This is pretty good framing of the three eras of the web. About 40% down the page you see this (insert record scratch sound): (highlighting is our editorial addition)

What? Back in January, CoPilot was 100% aligned with ACP and here we see UCP. But the language isn’t exclusive “introducing support” could mean they support both?

New CoPilot Loyalty Experience

A bit further down is when we start to get an inkling on the ‘why’:

New CoPilot Agentic Commerce Ad Format: “Offer Highlights”

In this ad format, the merchant, based on deep context can surface/highlight something about the product in a sponsored listing in context. In this example they provide, the user is looking for a laptop in NYC and BestBuy has an “Offer Highlight” ad promoting in-store local availability and free Geek Squad Protection (red square and green arrow our addition):

Best Buy was announced as an early customer for this new ad unit.

Later in the article we’ll explore where ACP went, but let’s jump into the cool new thing here - Target’s loyalty link. As a reminder, this UCP feature (along with multi-cartwas just announced by Google March 19th (details here) and Google/Gemini is not live with the feature ye

CoPilot/Target’s UCP Loyalty Connection

Here’s how it works:

1. I Research→Find a Target product→

2. When you hit Buy, the usual checkout pops up but with an important twist!

3. When you click that→

This is a great customer experience, very clean and clear to the user. Plus as an avid Target Circle member, I like to see I’ll get ‘credit’ for these purchases.

4. Once you accept that, you are back at the checkout and your account with email (which is handy for those of us with a lot of emails).

That’s a really good implementation and it will be interesting to see what Google does.

Where’s Multi-cart?

The other big UCP innovation announced was multi-cart and it’s somewhat a bummer we also didn’t get our first UCP multi-cart ‘live in the wild’. We’ll now have a race between CoPilot and Gemini to cross the multi-cart winner’s line.

Where’s ACP?

To verify if this is CoPilot supporting ACP AND UCP or they have made a swap we checked out the Agentic Commerce landing page here.

On this page, they have some updated datapoints that are interesting and good to see Agentic Commerce so front and center. About half way down in the “Improve product visibility in Copilot”

You will see here in the higher-level docs, there’s no mention of UCP. Then I checked the MMC help area, here’s the results of the search for ACP:

Summary

What started out as a kind of boring blog post revealed:

• Microsoft CoPilot has abandoned ACP for UCP

• CoPilot’s new UCP checkout supports loyalty linking (identity)

• There’s an interesting new Agentic Commerce Ad Unit we’ll be watching: “Offer Highlights”

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Last week I was on a Wall St analyst ‘expert channel check’ call. The analyst has been a long-time reader of Retailgentic and one of his questions a the top of the call was:

“I’ve been following you on the J+S show and now Retailgentic and your predictions have gotten really good, like north of 80%, how do you do that?”

My answer was, there are three things that I work on to help improve my ability to predict where things are going:

• History/Incentives - I’ve been fortunate to have a front-row seat to the birth of paid-search, eBay, ecommerce, omni-channel, mobile, Amazon marketplace, social commerce, retail media networks and so-on. This history helps understand how big companies act, how the stakeholders in our industry react to change and what all the underlying incentives are. “Show me the incentives and I’ll show you the outcome” - Charlie Munger, Berkshire Hathaway

• Shots on goal - Doing the Jason and Scot show for 11yrs gave me a decade of getting use to making very public predictions and having to be graded on them. This gave me tough skin, humility and a good understanding of how to frame a prediction along with the time window.

• First Principle thinking - I would say the first 2 are 30% but the 70% comes from first principle thinking. History, incentives and practice matter, but first principle thinking I learned as being an entrepreneur for 30yrs. For many businesses, first party thinking goes back to physics or economics (incentives again). But for our industry, I realized about 10yrs into ChannelAdvisor that the ‘real’ first principle predictor for our industry is consumer behavior. Want to learn more about first principle thinking? Here are two good resources to get you going: (James Clear and Farnam Street).

Two Types of Consumer Behavior

In our industry there are two types of consumer behavior data:

• Observed Consumer Behavior Data - In our industry, observed data comes from a variety of areas:

  • Platform layer - Ecommerce platforms like Adobe, Salesforce, BigCommerce and Shopify ‘see’ every transaction through the union of their customer’s sites.

  • Infrastructure layer - Above and below the ecommerce layer there are opportunities to ‘see’ what consumers are doing from search engines, marketplaces, analytics platforms, etc. (examples: IBM, Adobe, Salesforce also have elements of this data)

  • Panel data - There are companies that work with consumers to get permission to monitor their behavior, they then aggregate that data to understand consumer behavior (Examples: Similarweb and Sonar Tower)

• Stated-preference Consumer Behavior Data - Stated preference is where a polling agency asks X consumers questions and then uses known statistical methods to ‘scale up’ the data to represent an audience. In our world, I look for:

  • Scale - n=1500 at a minimum (2k is preferred)

  • Audience - US online consumers

  • Recency - Agentic Commerce is changing so fast, you really need to look for not only when the survey results were published, but when the survey itself was conducted.

As my podcast partner Jason Goldberg would say, stated preference data is notoriously ‘tricky’ to the point of many times being unreliable. The classic example in our industry is if you ask consumers ‘would you like advertising’ they will say “no, I do not like advertising, I would never click on an ad”. How do you square that with Google, Amazon Ads and META.

Two ways to filter stated preference consumer behavior

Because stated preference, I apply two filters to the data:

1. Triangulation Filter - I like to accumulate 2-3 surveys that have similar topics, look at the ‘meta results’ and use that to triangulate to reality. This approach takes out the drift that comes from the underlying wording and ‘way’ the questions are asked.

2. Past/Present/Future Filter - Stated preference works best when you ask people what they have done and are doing. Where it gets especially fuzzy and unreliable is when you ask them about the future. Where it becomes totally unreliable is when you ask them about future economic decisions.

If we can ‘double triangulate that’s the best. What I mean by that is if we can find where observed behavior and stated behavior overlap, AND in the observed we’ve triangulated, and in the observed we’ve triangulated that’s the gold standard. Usually during the holiday period is the only time of year we can do that in ecommerce because the amount of data output cranks up.

For example in 2025, you may have noticed we would frequently in one post talk about a poll or two (stated preference) along with data from Adobe/Salesforce/Sensor Tower/Similarweb (observed behavior) - double triangulation!

Last week, Thursday, we had a big drop by Adobe for Q1 and in this post we’re going to double triangulate that data with 4 polls I’ve been accumulating from Q1 to get enough data to triangulate some stated preference data.

Four New Q1 2026 Consumer Behavior Polls

In this article, I’ll be referencing four Consumer Behavior Polls:

1. Adobe - In addition to the observed preference data we covered last week, Adobe also ran a stated preference poll of n=5,000 , US Online Consumers, Conducted March 2026

2. Harris/Quad AI Shopping Poll - Harris is one of the most well known polling companies in the US. Quad seems to have been the one to contract with them and sponsor the survey and publish the analysis. US consumers, Feb 2026, n=2180.

3. Visa - n=2,000 General Population US Adults, between 1/29/26-2/6/26

4. Morgan Stanley AlphaWise - I’ve been following this one since 2010 and I don’t know if it’s the longevity, the fact it’s a top-tier Wall St. firm building the survey and doing the analysis or what, but I’ve found it to be head and shoulders above all other polls - it’s my ‘go to’ stated preference data. For this dataset, n=2,000 US consumers aged 16-75, conducted 1/22/26-1/26/26

Four datasets, all within Q1 2026, all > n=2000 - this gives us a great foundation to ‘quadrilate’ on some data.

US Agentic Commerce Usage Trends

Let’s start by peeling the onion, starting on the outside. What do our four polls tell us about how consumers are using Agentic Commerce.

MS AlphaWise data above has time trend data from 10/25-2/26 and shows continued activity by consumers in the 20-40% range that ‘made a purchase’ based on an AI recommendation. Think of this as a Discovery signal. Usually in ecommerce we see a Holiday bump, then a Q1 slump, the a recovery with a new high in Q4 for the next Holiday period. Here we’re not seeing that. Note that Meta jumped 4% the most - remember that Product Cards rolled out in Q1 (we noticed them in early March).

That being said, the ‘Retailer-Specific AI tools’ section did see a bit of a Q4→Q1 decline for Sparky and TSA fell off a cliff with usage going from 43% down to 24% - a 19% drop, but interestingly Rufus is hanging in there at ~40%

The Visa poll lines-up stating:

It’s interesting Visa asked the ‘would not have considered’ question, I’ve long theorized that Agentic Commerce would accelerate overall ecommerce. This datapoint supports there is some incrementality here. It’s hard to tell if they were shopping for something already and found a new brand, or if it was totally organic. We’ll be watching the commerce data for information on that. If it’s going to happen, I think we’ll see it Holiday 26.

The Harris poll goes into some demographics and reasoning behind ‘why’ Agentic Commerce:

Finally, Adobe has AI Regular usage at 30%, 61% familiarity and ‘positive vibes’ at 73%:

How/Why Are Consumers Using Agentic Commerce?

What do consumers like/dislike about Agentic Commerce? This information helps us get to the underlying reason Agentic Commerce is popular.

The AlphaWise report goes through 10 different reasons, I pulled this one as it’s the largest - 40-55% of consumers are research products and/or price comparing.

The Harris poll has some more color on this:

These are some new reasons I haven’t seen before: decision fatigue reduction, staying on budget, spotting price inconsistencies and the top we’ve seen before: simpler interface. This last one speaks to the ‘broken-ness’ of the existing ecommerce search experience both at the individual retailer level and the google level. As retailers implement LLM/Agentic commerce type technologies on their websites, it will be interesting to see how this changes.

Trust and Agentic Commerce

Harris also had some trust questions that are interesting. This one across demographics caught my eye. 45% of all american’s trust AI over store associates with Millennials over-indexing at 60%.

Agentic Commerce Demographic Trends

This batch of polls produced a wealth of new demographic trend data for Agentic Commerce, here are the highlights:

Adobe has a both adoption data from GenZ to Boomers:

And then breaks the demos down across three ‘why agentic commerce’ questions:

This shows us that younger consumers, especially Gen Z and Millennials, are more likely to use AI assistants across the full shopping journey, from discovery to post-purchase. Confidence in AI-driven purchase decisions is consistently high across generations, but drops slightly among older cohorts, indicating trust gaps.

One other datapoint I noted is younger shoppers (Zillennials as I’ve heard many marketers say for GenZ+Millennials as a cohort) report Agentic Commerce is reducing returns (make sense, better research and decision making results in down-stream return improvement). This trend is strongest among younger shoppers, showing they are trusting the agents more and putting in the work.

Agentic Commerce and Ads

I always try and understand if a poll has a motive of some kind (back to incentives). I thought it was very interesting that the Harris poll really drilled in on that. I’ll also point out that these questions are definitely into the ‘future’ section I warned about and I’m sure the Agentic Commerce Naysayers are going to pounce on this. With those caveats here we go:

Yep, you can hear the soundbite now: 75% of consumers would lose trust in AI if there were ads. Who do you think would benefit the most from that datapoint being out there? I’ll give you a hint - think about some controversial superbowl ads from February….

On top of that the consumer survey around the AI companies showing the ads, the poll results are firing warning shot at brands saying: “If you advertise on this, you will destroy your trust too!”.

Personally, I’m going to take a wait and see approach on this. Brands advertise on Amazon, Meta, Instacart and Google and consumers keep coming back for more, so something doesn’t pencil here.

This is a shining example of the flaws with stated preference. I think ChatGPT/OpenAI totally know this is nuanced and they are going to delicately approach advertising and figure out ways to do it that are additive to the discovery and checkout experiences.

Agentic Commerce’s Impact on Social Media and Retail Stores

The Harris poll had some interesting data on the knock-on effects of Agentic Commerce.

This one caught my eye:

Perhaps this helps explain the urgency we’re seeing from Meta to enter the race. Consumers now have something to compare social media commerce to and are increasingly preferring Agentic Commerce.

The Harris poll picked up on three signals around physical stores:

First, they found that:

Putting on my first principle thinking hat here, ‘agree’ is a tricky word in polling, we’d have to see the wording of the question, (e.g. It’s probably something like: “shopping stores feels like a social activity, even if I’m alone: strongly agree/agree/neutral/disagree/strongly disagree and I bet they added the agree/strongly). The math works, but who would say: disagree or strongly disagree?

In any case, I’ve made a mental note to track this in future polls.

This next datapoint suggests that there are latent opportunities for retailers to leverage Agentic Commerce to acquire customers and harmonize/omni-channel them into the store through email sign-up or catalogs:

Finally, Harris found that 52-55% of Zillennials use Agentic Commerce while they are in-store to shop as a personal shopping assistant:

I recently witnessed my 19yr old daughter do this in an Ulta store - she pointed ChatGPT at a wall of lip-liner products with ChatGPT in voice mode and asked it which product met her three criteria and it said: brand x on the right three up from the bottom and four from the right. She referenced decision fatigue as the use case. Anecdotal, but another n=1 datapoint!

Summary

Highlights from this analysis:

• We talked about the two types of data and the importance of first-principle thinking and triangulating on data across the observed and stated preference datapoints. We looked at the intersection/highlights of four polls: Adobe, Harris/Quad, Visa, MS Alphawise

• 20-40% of consumers using AI are making a purchase through them.

• We did not see a ‘Q1 slump’ after a huge Agentic Commerce across the Agentic Commerce Engines, but we did see a pretty big drop in usage at Target Shopping Assistant and less of a decline at Sparky, but Rufus stayed robust at 36% (AlphaWise)

• In Q1, 40% of americans made a purchase they normally would not have considered using Agentic Commerce. (Visa)

• Generationally, 62% of GenZ’ers prefer AI powered shopping tools (Harris)

• The top reasons why consumers use Agentic Shopping: To spot pricing inconsistencies, reduce decision fatigue and they prefer the simpler user experience.

• 50-60% of Zillennials now trust Agentic Commerce more than a store associate

• As with previous surveys, Zillennials lead the pack in Agentic Adoption, but Boomers are up to 30-40% adoption where they have been below 20% historically.

• 70-76% of consumers rejected the idea of ads in Agentic Commerce saying they would lose trust if that rolled out and they’d also throw the brand under the bus too - this datapoint is suspicious at best.

• 39% (much higher for Zillennials) use Agentic Commerce as an in-store shopping assistant and 49% of all shoppers agree that if an AI shopping assistant recommended a newsletter or catalog, they would sign up.

When an What is the Next Big Data Drop?

Starting next week April 27-May 8, the companies we watch closely: Microsoft, META, Alphabet/Google and Amazon. Meta, Alphabet and Amazon all had comprehensive mentions on their last quarterly earnings referring to various aspects of Agentic Commerce. Here’s what we’ll be monitoring for and sharing here on Retailgentic to give you a bit of preview:

• META - Zuck said back 1/29/26 they would be releasing Agentic Commerce soon and they did - will they go into more for their Q1 earnings release?

• Google - Sundar highlighted their NRF release of UCP - will we get a progress report or a hint at things to come?

• Amazon - Jassy dropped that Rufus was used by 300m consumers, it increased the probability of purchase 60% and drove 10-12B of incremental revenue. We’ll be looking for an update and also Wall St. is eager to hear about the sponsored prompts testing.

• Microsoft - While not part of earnings, right after they announced their checkout and big push in a blog post, will we get an update/mention in earnings this time?

• Walmart - Retailers are on a different schedule, they will report more mid-May. Last Q the CEO John Furner touched on Sparky saying that half the mobile users had tried it. It’s time for Sparky to come to the web, we’re all waiting on that and looking for any indications about their ad test.

Google I/O

After earnings season we head right into Spring conference season with Google I/O set for May 20+21 in Mountain View. Last year this is when the now already obsoleted ‘Buy for Me’ was announced and they officially ‘Entered the Agentic Commerce arena’ - our coverage was here.

Details on Sources for this article

If you want to go deeper, here are the sources for the four polls mentioned in this article:

Morgan Stanley AlphaWise

This data is only available to MS clients, If you work for a public company, you probably have a relationship (ask the CFO or investor relations) and they can get the report for you. AlphaWise cuts across all their research, what you specifically want is this report by Brian Nowak, their internet analyst and friend of Retailgentic→ (don’t let the title misdirect you, the great AlphaWise data is in the back if you’re not excited about SMB advertising).

Visa Poll

Press release is here and the detailed report is here.

Harris Poll

Press release is here.

Coverage with anti ad messaging here and here.

Full PDF is here→

Quad The Harris Poll The New Rules Of Retail Trust In The Age Of Ai (1)

1.43MB ∙ PDF file

Download

Download

Adobe Poll

Announcement is here and the PDF is attached for your convenience:

Q2 2026 Ai Sourced Traffic Insights

2.3MB ∙ PDF file

Download

Download

Up Next on Retailgentic…

We’re working on an Agentic Commerce news update that will be out either Wed or Fri depending on how the week develops, stay tuned, lots to update you on in the rapidly evolving world of Agentic Commerce!

We also have our standard Thursday pod drop for your listening/viewing enjoyment as well!