Retailgentic | Consumer Behavior & Retail Trend

This week Scot goes on a markets deep dive with one of Wall Street's leading internet analysts. It’s a tour through the mega-cap playbook (Meta, Amazon, Google, eBay, Shopify) and how professional investors are actually pricing the agentic-commerce shift. Colin covers over $12 trillion of market cap across five names alone, so this is the view from the models, the channel checks, and the trading desk.

This is a wide-ranging, numbers-forward conversation about where the money moves as agents become the buyers and which companies Wall Street thinks come out ahead. 

Highlights:
𝗧𝗵𝗲 𝗦𝗣𝗘𝗘𝗗 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: Baird’s formula for internet winners: Scale, Product, Engineering, Efficiency, and Data. Nail all five, and the competitive advantage compounds.
“𝗟𝗲𝘁 𝘁𝗵𝗲 𝗮𝗴𝗲𝗻𝘁 𝗱𝗼 𝘁𝗵𝗲 𝘄𝗮𝗹𝗸𝗶𝗻𝗴”: Colin explains why skeptics are dramatically underestimating the size of the opportunity.
𝗠𝗲𝘁𝗮 𝗶𝘀 𝘁𝗵𝗶𝘀 𝘆𝗲𝗮𝗿’𝘀 𝘁𝗼𝗽 𝗽𝗶𝗰𝗸: Colin’s highest-conviction AI bet is Meta driven by WhatsApp business agents, Meta AI, and unmatched consumer reach. (Last year’s pick: Google.)
𝗠𝗼𝗱𝗲𝗹𝘀 𝘄𝗶𝗹𝗹 𝗯𝗲𝗰𝗼𝗺𝗲 𝗰𝗼𝗺𝗺𝗼𝗱𝗶𝘁𝘆: The real value won’t live in foundation models, it accrues to the platforms, applications, and distribution layers built on top.
𝗔𝗺𝗮𝘇𝗼𝗻’𝘀 𝗼𝗻𝗲-𝘄𝗮𝘆 𝗱𝗼𝗼𝗿: By opening its catalog to AI agents, Amazon may have crossed a line it can’t reverse and that could strengthen its ecosystem even further.
“𝗖𝗹𝗼𝘀𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗲𝘆𝗲𝘀 𝘁𝗼 𝘁𝗵𝗲 𝗯𝗶𝗹𝗹𝗯𝗼𝗮𝗿𝗱𝘀”: If AI agents skip search results and category pages, they also skip the ads, putting pressure on retail media’s biggest revenue stream.
𝗪𝗵𝗼 𝗼𝘄𝗻𝘀 𝘁𝗵𝗲 𝗮𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗲𝗱 𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝘄𝗶𝗻𝘀: The long-term winners will control identity, payments, checkout, and fulfillment, not just discovery.
𝗪𝗵𝘆 𝗪𝗮𝗹𝗹 𝗦𝘁𝗿𝗲𝗲𝘁 𝗶𝘀 𝗻𝗲𝗿𝘃𝗼𝘂𝘀 𝗮𝗯𝗼𝘂𝘁 𝗦𝗵𝗼𝗽𝗶𝗳𝘆: AI could bypass storefronts and even Shop Pay. That uncertainty alone is enough for investors to discount the stock.
“𝗪𝗲’𝗹𝗹 𝘀𝗲𝗲 𝗶𝘁 𝘁𝗵𝗶𝘀 𝗵𝗼𝗹𝗶𝗱𝗮𝘆”: Colin expects agentic commerce adoption to meaningfully accelerate after Q4, even a one- or two-point lift on today’s numbers would be significant.
Colin is one of the sharpest lenses out there on how the market is actually pricing all of this. Enjoy the conversation!

Timestamps:

3:28 Meet Colin Sebastian
5:04 20 years of history & the Wall Street event
7:00 From bartender to Baird
7:56 Baird's coverage universe & "TMT"
9:29 The GTA VI mega-launch call
11:12 Buy side vs. sell side, explained
13:52 The SPEED framework & top picks
16:16 What is agentic commerce?
20:05 Sizing it: trillions & consumer surveys
22:42 Meta's social-graph advantage
25:05 Amazon's walled garden & the one-way door
29:40 Google, UCP & why models get commoditized
32:36 eBay's used-goods moat
39:44 Retail media networks at risk?
44:33 OpenAI, ads & the closed-loop logic
48:36 Payments: PayPal, stablecoins & who wins
51:57 Protocols: UCP vs. ACP
52:23 Why Wall Street is nervous about Shopify
👉 Connect with Colin: https://www.linkedin.com/in/cosebastian/
👉 Learn more about Baird: https://www.rwbaird.com/
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

This epsiode is a platform-and-stats deep dive: Scot gets Mani to pin down what agentic commerce actually is (with a four-stage framework that’s the cleanest map we’ve heard), then pulls out a run of genuinely wild numbers on what Shopify is seeing across millions of merchants, before going deep on the catalog, the protocol soup, and everything that shipped in the Spring ‘26 Edition.

Highlights:
Crawl, walk, run, fly: The framework of the episode. Crawl is AI-driven discovery (the biggest, most impactful stage today); fly is fully discretionary, budget-based buying. Mani’s verdict on where the industry actually is: “somewhere between walk and run today.”
8X traffic, 13X orders: Shopify’s Q1 numbers… AI-driven traffic to merchants up 8X year over year, and orders through those channels up 13X.
AI buyers just hit harder: New buyers who discover a merchant through AI order at roughly twice the rate of organic search, are about 50% more likely to convert, and spend about 14% more per order because they show up deeper in the consideration funnel.
70% of AI orders are long tail: About 70–71% of AI-attributed orders last year fell outside the top 100 product categories. Models “don’t need to learn how to reach for the small merchant, they just need to learn the intent of the buyer.”
2X on fresh data: The Shopify catalog, over a billion products across millions of merchants, converts about 2X better than stale or scraped data, thanks to real-time pricing and availability straight from the merchant.
A “7 out of 10 at everything”: On how AI is reshaping product, design, and engineering roles.
The non-merchant-of-record era: Don’t become the marketplace reselling goods, just be the interface to the merchant. The merchant keeps the customer relationship and runs their own checkout.
UCP was a “labor of love”: Shopify was at the genesis of the Universal Commerce Protocol.
Sidekick, Pulse & Autopilot: Sidekick usage is up about 4X year over year; Pulse turns Shopify’s data into proactive recommendations right on your admin homepage; and the guiding principle stays “always put the control in the merchant’s hand.”
B2B may reach “fly” first: By 2030, Mani splits the world into DTC and wholesale/B2B and bets B2B, where both sides transact professionally and obsess over efficiency, may hit full automation before consumers do.
Mani’s four stages are the cleanest map of agentic commerce we’ve heard, and the numbers behind them are frankly staggering. And as he reminds us, we’re still in the early innings. Enjoy the conversation! 
Timestamps:
03:55 Welcome; watching Shopify's rise from ChannelAdvisor
04:38 Mani's path to VP of Product at Shopify
06:37 The Wish / ContextLogic founding story
08:18 Vibe coding and "AI makes everyone a 7 out of 10"
11:10 What Mani owns across the commerce loop
12:42 Non-merchant-of-record channels (ChatGPT, Gemini)
13:45 Defining agentic commerce
14:44 The crawl / walk / run / fly framework
17:50 The stats: 8X traffic, 13X orders, +50% conversion, +14% AOV
20:03 Out-of-the-box UCP compatibility and agentic storefronts
23:10 The Shopify catalog superpower (2x conversion)
26:40 WebMCP and the protocol stack (AP2, x402, Web Bot Auth)
29:15 UCP: Shopify's labor of love
32:24 Top things merchants should do to win
35:28 The escalation "escape hatch"
37:24 Word of mouth and the long tail, 70% of AI orders
42:41 Spring '26 Edition: Shop app, Ship & Pick Up, Pulse, Autopilot
48:10 Where it all goes by 2030: B2B vs DTC
52:29 Wrap-up

👉 Connect with Mani Fazeli: https://www.linkedin.com/in/mcfazeli/
👉 Learn more about Shopify: https://www.shopify.com/
👉 And check out the Shopify newsroom blog here
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

Kartik Hosanagar wears a lot of hats: Wharton professor, serial entrepreneur, angel investor, and now co-founder of an applied AI lab building simulation tools for AI search. Scot and Kartik land in almost exactly the same place on where agentic commerce is heading, but they get there from opposite directions: Scot on gut and operator instinct, Kartik on research. The result is a wide-ranging conversation about treating AI as a customer, the levels of agentic commerce, and what brands should actually be doing this week, this quarter, and this year.

Highlights:
AI is a new customer category: Once shopping goes agentic, Kartik argues you have to ask of AI what you ask of any customer: how do we inform it, persuade it, and what biases does it have? 
The driverless-car model: Agentic commerce has levels 0–5, just like autonomous vehicles. Level 5 is “buy the shoe and make sure it arrives in a week” hands-off; Instacart-style automation and AI-enabled discovery are lower levels and we’re already in the era.
The funnel got outsourced: Top-of-funnel work customers used to do themselves like discovering brands and building a consideration set is now done by AI, so shoppers arrive far later in the funnel. Discovery is “fundamentally transformed.”
4 words → 60 words: From his CommerceNext keynote, average search went from about four words on Google to about 60 words on the first ChatGPT turn, then multi-turn. Nobody types “men’s running shoes” anymore; shoes show up on conversation turn seven.
UCP, ACP and the protocol wars: Kartik explains Google’s UCP (product feeds today, transactions later), why OpenAI backed off ACP instant checkout, and reads Amazon joining UCP as “testing the waters,” not a strategy reversal
Counterfactual simulations: Bodhium builds “digital twins” of ChatGPT and Gemini and spins up virtual worlds where your site looks different, testing a thousand hypotheses in minutes to find what makes AI answers more accurate and favorable. Market research, but for AI.
The today / this quarter / this year roadmap: Now: audit conversations, visibility, and which bots read your site. This quarter: build simulators and a UCP/MCP workstream. This year: scale it with agentic workflows. 
Two front doors: Kartik doesn’t think websites disappear, but “a website is not the right front door for an agent.” Expect a human web door and an MCP door for agents, plus omnichannel behavior where each feeds the other.
Kartik calls himself an "agentic commerce maximalist," and after this conversation you'll see why... the research and the gut instinct point the same direction. Enjoy the conversation.

Timestamps:
03:04 Welcome: the "renaissance man" background problem
03:49 Kartik's cocktail-party version: academic + entrepreneur, Yodle
04:36 The Yodle / Milo mobile-social-local era (and Fidji at OpenAI)
06:05 Wharton AI Center and what Kartik researches
07:37 The thesis: AI search is more than another channel
10:08 Defining agentic commerce: the driverless-car levels
12:34 UCP, Gemini, and why Amazon joined
15:55 Amazon vs. Walmart strategies (Rufus vs. Sparky)
16:29 Bodhium Labs: what it is
17:00 The AEO/GEO problem: guesswork and the Reddit trap
18:56 Research-led counterfactual simulations
21:02 The long tail: multi-turn conversations replace keywords
22:49 CommerceNext keynote: 4 words to 60 words
24:57 The "AI is just another channel" misconception
26:48 Shopper trust: high for discovery, not for checkout
28:15 You can't fully control what AI thinks about you
30:51 The roadmap: today, this quarter, this year
34:41 Rufus, Sparky, UCP, and MCP endpoints
36:37 Does agentic commerce grow the pie or shift it?
38:32 Do we still need websites? Two front doors
40:39 Where to find Kartik: LinkedIn and Substack
👉 Connect with Kartik: https://www.linkedin.com/in/kartik-hosanagar-22272115/
👉 Learn more about A Human’s Guide to Machine Intelligence: https://www.amazon.com/dp/0525560882?lv=shuf&channelId=500&plpRedirect=mhFallback
👉 Visit his substack: https://hosanagar.substack.com/
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

This is a report deep dive, and Deloitte gave Retailgentic the exclusive first look at brand-new research: hundreds of senior merchant leaders and a thousand-plus recent online shoppers, both sides of the counter, with trend data from two years back layered in. The result is a map of where brands and consumers see the same picture and where they see completely different ones. And the data is fresh, fielded this spring, analyzed over the last month, unveiled here.
They describe exactly what those leaders do differently, and why it pays off. You want the edge? This is it.
Highlights 
The basics are the new battleground: Accurate search, real inventory visibility, clear delivery dates, easy returns are no longer differentiators, just expected. And a majority of consumers say brands haven’t improved on them in two years.
The perception gap: Only 16–18% of consumers rate brands “excellent,” while brands rate themselves in the low-to-mid 30s, a false-confidence gap that’s driving under-investment where it matters.
57 definitions of personalization: the “golden term” has “probably 57 different definitions”, but ~70% of consumers say personalized experiences genuinely matter. Get it wrong and you hurt trust more than you help.
14–15 loyalty programs: 99% of surveyed brands offer one and 80% of customers belong to more than one, the average U.S. consumer is a member of 14–15 but active in only four or five. “You are fighting for head space.”
The cashback gap: Over half of consumers say cashback is the loyalty benefit they’d value most but only 14% of brands offer it. Customers want financial value and simplicity; brands keep adding tiers and complexity.
The leaders’ payoff: Consumers spend 34% more with the brands that nail the basics + personalization + sticky loyalty, 57% will try a new product from them, and 55% will recommend them to family and friends.
Efficiency over experience: The two top-reported benefits merchants cite from AI aren’t customer-facing at all, they’re better decision-making and greater efficiency. Brands are getting their own house in order first.
Machine-readable product data: Product content is still “teeny tiny” and over-optimized for the keyword era, even as LLMs collapse the old 20-tabs-and-a-spreadsheet decision into one answer. If the data isn’t there, the agent won’t infer it, it just gives what’s available.
Connecting the dots: Data, loyalty, and AI in isolation aren’t enough; the winners execute across all three and make deliberate choices about the purpose of the store vs. the site vs. the app vs. the LLM.
Fresh data, both sides of the counter, and a clear-eyed read on the gap between what brands think they’re delivering and what shoppers actually feel. Bobby and AP brought the goods. Enjoy the conversation! 👇

Timestamps:
01:57 An exclusive first look
06:12 Meet Bobby Stephens & Apurva Pangam
07:19 AP's background: 20 years in commerce
08:01 Bobby's background — buyer to footwear founder
09:29 Where they fit in Deloitte's retail team
10:18 Inside the report: methodology
12:32 The consumer side — the basics
14:47 The perception gap & false confidence
15:50 Personalization: 57 definitions
17:30 On-site agents: Rufus, Sparky & TSA
20:02 Playbooks, CDPs & the customer P&L
21:21 AI for operational efficiency
25:40 Making product data machine-readable
26:38 Answer engines & the decision collapse
29:34 Loyalty: everyone plays, few win
33:52 Who's winning: profiling the leaders
38:44 Connecting the dots
40:18 Closing & where to find the report
👉 Check out the report: https://www.deloittedigital.com/us/en/insights/research/b2c-commerce-experiences.html
👉 Connect with Bobby Stephens: https://www.linkedin.com/in/bobby-stephens-digital/
👉 Connect with Apurva Pangam: https://www.linkedin.com/in/apangam/
👉 Learn more about Deloitte: https://www.deloitte.com/
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic

This one's a research deep dive. Forrester just published "The State of Agentic Commerce" for Q2 2026, a client-only report built on a fresh consumer survey, and its headline read like a splash of cold water: the hype is running past reality. 
We invited principal analyst Chuck Gahun on Retailgentic to defend that framing, walk through Forrester's (strict) definition of agentic commerce, and separate what consumers are actually doing from what the market keeps promising. 

Highlights 
Shopping vs. buying: Forrester defines agentic commerce as “shopping or buying experiences that include AI agents acting autonomously on behalf of consumers, buyers, or sellers”, and until buying is involved, they call it conversational commerce, not agentic commerce.
The 38 / 17 gap: Among consumers familiar with answer engines, 38% use them for product discovery but only 17% complete purchases, a trust gap Chuck says is the single thing holding agentic commerce back.
Who’s liable?: When something goes wrong on an answer-engine purchase, 44% of consumers said they’d hold the answer engine itself liable, a sign of how many guardrails, policies, and return paths still have to be built.
The Amazon corollary: “On Amazon, I’d let my kids, my friends, my family have my credit card and go shopping.” That same trust does not yet transfer to ChatGPT or Gemini, closing that gap is the whole game.
The merchant verdict: “We’re not telling anybody to wait. We’re telling them to go in strategically while the commerce trust angle is catching up.”
Machine advantage: Forrester’s four-quadrant merchant framework (agentic fit, machine advantage, operations, and organizational adaptability) pushes brands to build content strategy for machines, not just humans.
The SKU mountain: The hardest conversation in the field, “you need to upgrade 100,000 SKUs,” and the merchant answers that one SKU takes six months, so “this is gonna take infinite years.” Protocols like OpenAI’s ACP and Google’s UCP keep changing underneath them, on an exponential curve.
Old B2B PDFs are gold mines: Those spec-heavy, JavaScript-free product pages everyone mocked turn out to be exactly what agents want, and Chuck says B2B (business & industrial) is actually taking off faster, with a report prediction that 20% of B2B moves to human-authorized, agent-executed transactions by year-end.
Death of the retail website?: A companion Forrester paper argues the website isn’t dead, it’s becoming a repository of data for agents. By 2030, Chuck expects “dual optimization”: machines bring the shopper, and the site’s only job is to convert them.
Less traffic, 3X conversion: Organic traffic is down, but answer engines filter the traffic so well that conversions are up.
A sharp, honest look at where agentic commerce actually is right now: the trust gap, the merchant playbook, and a few 2030 predictions worth arguing about. Enjoy the conversation

Timestamps:
03:47 Meet Chuck Gahun, Forrester principal analyst
05:03 Chuck's background: two decades, Sapient, the services side
07:57 How Forrester's commerce team is structured
10:52 Defining agentic commerce: shopping vs. buying
12:37 Conversational commerce vs. the strict definition
13:49 Semi-autonomous vs. autonomous (the dog-treats test)
14:38 Inside the answer-engine consumer survey
15:47 The numbers: 38% discover, 17% buy, 62% research
16:22 Beyond retail: healthcare, travel, government
19:48 Figure 1: owned vs. not-owned, four levels
21:47 The trust gap and who's liable (44%)
24:37 Marketplaces, merchant of record, and returns
27:52 What Forrester tells merchants: don't wait
29:57 Product fit, profitability, and the ACP/UCP specs
31:58 Figure 3: the four-quadrant framework & machine advantage
35:53 The SKU problem and exponential change management
38:35 The B2B surge prediction
41:25 2030 predictions & death of the retail website
46:32 Less traffic, higher conversion: the 3X surprise
47:18 Where to find Chuck, events, and outro
👉 Connect with Chuck: https://www.linkedin.com/in/chuckgahun/
👉 Learn more about Forrester: https://www.forrester.com/
👉 Get the report: https://www.forrester.com/report/the-state-of-agentic-commerce-q2-2026/RES195671
🧠 Want to stay ahead in AI commerce? Subscribe and follow along:
📰 Subscribe to the free Substack: retailgentic.ai
📺 Watch episodes on YouTube & Subscribe for updates: https://www.youtube.com/@Retailgentic