Week 14 - AI agents hit checkout: ChatGPT shops for you, WTO tariff drama, and Amazon’s Big Spring push

Max: Welcome to the Checkout Point, your quick dive into this week's e-commerce buzz with me, Alex, powered by Blikett. These 20 minutes pack the latest trends, news and insights. Let's navigate the digital marketplace together. Ready? Let's go. Rachel: Hey everyone, welcome back to The Checkout Point. Speaker 3: Yeah, yeah, good to be back. If you care about profit and not just vibes, you're in the right place. Rachel: Vibes are off balance sheet anyway. Today, we've got a big one. Speaker 3: Right. So first up, ChatGPT as a storefront. OpenAI flirted with one-click autonomous buying, then tapped the brakes. Rachel: Yeah, and meanwhile Shopify, Walmart, Sephora, all piling into agentic commerce. We're talking like your olive oil reorders itself while you're cooking. Speaker 3: Which you literally did. My question is, what do you even measure in that world? Rachel: Exactly. Is it conversion, AOV, returns, margin risk, or who actually runs the store behind these agents? Speaker 3: And who owns the mistake when the bot blows up your return rate? That's where I start watching KPIs like a hawk. Rachel: Honestly, watching someone obsess over KPIs like a hawk, that's my comfort TV. I could do this all day. Speaker 3: Laughing. Sad, but true. Rachel: Then we're walking through a really practical framework. Go five rung AI ladder for merchants. Research, copy, creative, support, merchandising, and I get genuinely excited about frameworks like this, the kind that separate what should be automated from what actually needs a human calling the shots. Speaker 3: We'll compare Shopify's Tinker toolkit with Genstores don't worry, we'll do it all pitch and draw a hard line, AI on low consequence stuff, humans on pricing and brand risk. Rachel: If you've ever nerded out on CRO and unit economics like I have, I have this is the part where you're rewiring your playbook. Speaker 3: And later, global fun. The WTO eCommerce moratorium might end, which basically means new digital tariffs trying to quietly eat your margins. Rachel: We'll give you a three-step playbook to scenario plan, reprice, and actually talk to your customers without sparking a panic spiral email thread. Speaker 3: Plus, quick hits on Amazon's Big Spring Sale, Reddit's new shopping tools, and how not to torture margin chasing short- Short-lived promo bumps. Rachel: Alright, enough setup. Let's go. Speaker 3: Wow. Rachel: Let's get into Segment 1, agentic commerce and how ChatGPT just became your weird new store manager. Speaker 3: Buckle up, here we go. Rachel: Three easy ways to get your questions to us. Check the description for our web form, text us at 747-293-4612, or call the same number to leave a voice question. However you reach out, we can't wait to hear from you. Okay, so this is the moment where it stopped being theoretical for me. People are actually buying stuff inside ChatGPT now, not a demo, not a press release, real carts, real orders. Speaker 3: Yeah, this jumped from cute AI toy to actual storefront fast, but I want to see the metrics before I believe it's real. Rachel: Exactly. OpenAI basically backed off the pure one-click agent idea, that we'll just buy things for you in the background thing freaked people out. out loud. Speaker 3: Right, because like nobody wants a mystery box charge on their card. What went wrong there in your mind? Rachel: They skip the shopper brain. People want control. So now the flow is more guided. You say, I need running shoes, ChatGPT asks questions, shows options, you compare, then you choose. The agent helps, it doesn't secretly pull the trigger. Speaker 3: So it's moved from rogue personal shopper to helpful store associate. See it in your phone. Rachel: Yeah, and here's the wild part. Shopify stores plug right into that. The catalog, variants, inventory, all piped into ChatGPT as product options. Speaker 3: So as a merchant, my PDP is basically getting rewritten as a conversation. Rachel: Exactly. Instead of here's a grid of 48 products, the agent says, given what you told me, here are three that actually fit. Speaker 3: Okay, tell the olive oil story because this is the moment that stopped. stopped feeling theoretical for you. Rachel: Yeah, so I'm cooking, hands full of flour, realize I'm out of olive oil, I yell at my phone, order olive oil. The AI remembers my favorite brand, checks price across merchants, reads reviews, checks delivery time, and just buys it. Zero taps, zero apps. That's the moment I was like, okay, this is actually shipping. Speaker 3: And now we're basically there, which means the operations behind it have to be be bulletproof. Rachel: We're a half step away. Today, you'd say that to ChatGPT. It would surface a few options from Shopify merchants, maybe Walmart, maybe others. Ask this one and you say yes. That's the bridge between my messy kitchen and an actual merchant's checkout. Speaker 3: Somewhere a DTC founder is screaming, but what about my carefully crafted homepage? Rachel: Gone. The agent is the homepage, the PDP, the search bar. Speaker 3: So as a merchant, my new job is feed the Feed that agent clean catalog data, great descriptions, real inventory and stop hoping. Garbage in, garbage out. I learned that the hard way. Rachel: And structure the data. If your size chart is in some janky image or your materials are buried in a paragraph, the agent has nothing to work with. Speaker 3: This is where your CRO brain kicks in. For years you were like, feed the algorithm your best stuff. Rachel: Exactly. This is what I used to say in my CRO days: feed the algorithm your best stuff. Except now it's agents instead of Facebook. Messy data equals messy shelf placement. Period. Speaker 3: OK, zoom out. It's not just OpenAI and Shopify. Walmart has Sparky. Sephora's playing with AI shopping, too. What are they trying to do here? Rachel: They want the agent to carry the shopper from "I have a need" all the way to "cart is done," not just bolt a chatbot on the side. Speaker 3: Yeah, so no more chat bubble in the corner that answers FAQs. We're talking full journey, search, compare, recommend, add to cart. Rachel: Exactly. Walmart Sparky is like, I need snacks for a kid's birthday party. It builds a list, checks budget, swaps items. That is a cart building engine, not a support bot. Speaker 3: And Sephora's version is, I have oily skin, I'm on camera a lot, I hate heavy foundation, and it builds a routine with shades, with add-ons. Rachel: Yeah, merchants used to obsess over navigation. Is it in the header or the... After the sidebar, the agent says, "Forget the sitemap, just tell me your life and I'll figure out the basket. Speaker 3: Okay; but I live in the P&L; what metrics should merchants actually track here? Because the AI seems cool does not pay the bills. I need conversion lift, AOV and net margin, period. Rachel: Totally, and honestly the first metric I'd look at is conversion rate from agent conversation to cart completion. Does this flow close better than site traffic? Max: because if it doesn't we're chasing novelty not business yeah Rachel: And I'm immediately worried about attribution chaos. Who gets credit? The brand? Shopify? OpenAI? That matters when you're deciding where to spend money, and I've seen this movie at Walmart scale. Max: attribution is going to be a mess you might see direct orders spike while your paid channels look worse even though the same people are just finishing in ChatGPT Rachel: So I'd tell a merchant, treat this like a new performance channel. Track revenue and orders that originate from agent flows as their own line. Don't measure it, don't deploy it. Max: Yep, and then compare AOV from agent driven carts versus your normal site traffic. I'm betting these skew higher because the agent naturally reads your full catalog and cross sells intelligently. Rachel: I'm half with you: the agent is great at "Hey, you bought the serum—want the moisturizer too?" but it returns spike because the AI pushed the wrong shade or wrong size. that AOV bonus disappears. Max: That's fair. So your metric set is conversion rate, AOV, attach rate of recommended items minus return rate on those recommendations. That's your measurement framework. Rachel: Exactly. Don't just brag about AI-boosted AOV unless your net of refunds and customer support blowups. Max: AI-sold five upsell sounds great until those five come back with angry emails and shot margins. Rachel: Where I also worry is margin. If the agent always picks fastest shipping or most deluxe bundle, that might push customers into options that look great top line, but wreck contribution margin. Max: So merchants need rules, like "Don't offer this bundle if discount plus shipping drops margin below x" or "Prefer products with high review counts, not just high price. Rachel: Right. Think of it like merchandising guardrails for a super eager junior sales Speaker 4: person. Rachel: A salesperson who never sleeps. Max: Love that. They're good at talking, you're good at setting boundaries. Rachel: Okay, practical question: If I'm running a Shopify store right now, what's the first step to be ready for this ChatGPT storefront world? Max: Step one, fix your product data. Titles, tags, materials, use cases, all clean. Step two, rewrite descriptions in plain language that actually answers what your customers want to know. Will this fit my carry on? Is this safe for sensitive skin? Again, get weird with specificity. Rachel: And step three, from my side, define success-decide if this agent flow can drive x percent of revenue at y margin, I'll invest more in it. This isn't optional, it's how you avoid burning cash. Max: And Honestly, test it like a shopper; go into ChatGPT, talk the way your customers talk and see if you show up. Rachel: If you don't, that's your wakeup call-and it might be an expensive one. Max: The thing that keeps hitting me is, we're all obsessing Passing over the agent talking to the customer; but behind that, someone still has to run inventory, pricing, support, campaigns. Rachel: Yeah- if the front of the store is an AI, who's actually running the back of the store? Max: And how much of that can be AI too, before you blow up margins or your brand? Rachel: That's the question I want to dig into. AI owns the shopper conversation, but humans stay in the loop where the margin lives-that's the permission matrix. Thanks. Speaker 3: He wandered down the street, the Speaker 4: crowd of people growing thicker and thicker. Speaker 3: He was in a strange city, and he was looking for a place to live. Max: With that in mind, I want to flip to the inside of the store. Rachel: Yeah, like who's actually running the back office when the bot just dropped an order on you? Max: Exactly. So if you're listening and thinking, Cool, agents bring me customers, now what? There's a super practical AI ladder for merchants to climb. Rachel: Okay, ladder sounds manageable. Walk me through it fast. Max: Step one is research. Product ideas, keyword gaps, competitor angles. Have AI surface ten options on each, then you decide which. And which ones actually fit your brand and margins? Rachel: So this is like the intern that never sleeps, just cranking raw material, but only if your product data is already garbage. Garbage in, garbage out. Max: Yeah. Step two is copy. Product descriptions, emails, SMS, meta titles, the boring but profitable stuff. You still approve, you still tweak for brand. Rachel: Step three, I'm guessing, is creative. Max: Yep. Thumbnails, ad concepts, UGC script ideas. is even rough video storyboards. Not all of it ships, but it unblocks you. Rachel: And then support. That's tier one automation, and I'm fine with it if the policies are locked down and escalation paths are clear. Max: Right. Step four is support. Drafting responses, tagging intent, routing tickets. AI handles where is my order and how do I return with clear policies. Rachel: What's the last rung? Max: Basic merchandising. What should be homepage hero? What bundles actually move the needle? the needle. Stuff I spent years hunting for in Google Analytics back in my CRO days, except now AI does the grunt work. Rachel: So for a small team, if they just climbed that ladder, they'd already feel like AI is running half their day. Max: Exactly. You don't need a sci-fi warehouse of robots. You just need to stop writing every ticket reply from scratch at midnight. Rachel: Okay, now tie that to actual tools, because right now everyone's inbox is like, try this AI thing. I think it'll change your life. And I'm like, show me the unit economics first. Max: Yeah. So Shopify's new Tinker app is basically a big free starter box. It gives you access to a ton of mini tools and templates tied into your store. Product ideas, description generators, simple automations. Rachel: So like, I want to test a new bundle and it helps you wire the basics without custom dev. Max: Exactly. This is the feed the algorithm your best stuff philosophy. I've been preaching forever, except now it's agents instead of Facebook pixels. You draft ninety, approve the last ten percent, ship it. Rachel: And you like it because it's inside Shopify, not fifteen random Chrome extensions. Consolidation beats fragmentation every time. Whoever controls the plumbing controls the margins. Max: Yes, from a CRO brain, speed between idea and live test is everything. If Emergent can go from "That bundle might work" Speaker 4: to Max: To actual traffic in an hour that's the velocity advantage that moves real money. Rachel: Okay, now contrast that with Genstore, because their pitch is basically, "Why climb a ladder when the elevator runs the entire building for you?" And I'm immediately suspicious of the word "entire. Max: Yeah, their promise is wild: The idea is—you give the agent access to your catalog, ad accounts, email, support, even fulfillment rules. And it's supposed to optimize end to end. Rachel: So not just write copy, but decide budget, launch campaign, adjust bids, change pricing? Max: Exactly. In theory, it watches performance and acts like an operator, not a tool. Rachel: Okay, so from your CRO days, where do you actually feel okay letting something like that drive? Because I need to know where the down side is contained. Max: Ads is the easiest entry point—not brand strategy, just Speaker 4: - Max: Just create variations and daily budget tweaks inside hard constraints you set up front, like "don't bid above x," "hit this ROAS floor," "don't touch hero Speaker 4: campaign," etc. Max: Grow SKUs—Guardrails, not free rein! Rachel: So you define constraints the agent plays inside the box. Max: Yeah, same with product descriptions. Let AI draft ninety percent, you approve the last ten. That is low risk, high time savings. Rachel: What about support? Where are the guardrails when the bot is deciding whether a customer actually qualifies for a refund or exception? Max: I'm comfortable with AI running tier one support on clear, policy driven scenarios. Orders. Order status, basic how to, standard returns. You only jump in when it gets messy or the customer is upset. Rachel: That lines up with what I've seen. You can automate a lot of where's my stuff without nuking your brand. Max: Exactly. Rachel: Now let me push. Where do you not want the robot touching the wheel? Max: Pricing experiments with no human oversight, that actually scares me. Margin exposure, returns floods, fraud risk, and agent chasing conversion through aggressive discounts, you wake up. You wake up with a trashed warehouse and zero profit left to defend. Rachel: Yeah, and it might juice short term numbers, then train customers to only buy at thirty percent off. We don't need AI making faster versions of expensive human mistakes. Max: Totally. Same on merchandising big bets: swapping homepage hero products, changing shipping promises, turning on free returns everywhere. That stuff should be proposed by AI but approved by a human. Rachel: I'd add approvals for anything that changes your risk profile. Well, return policies, fraud thresholds, even some post-purchase upsells. You might drive AOV and then quietly double your return rate. That's flying blind on actual margin. Max: Yeah, you get this illusion of efficiency while your net margin falls off a cliff. Rachel: So if I'm a merchant, my rule of thumb is AI can drive where the downside is time and mediocre copy. Humans stay in the loop where the downside is margin. An Inventory or Brand Trust Max: That's the right filter. Ask yourself, if this goes sideways, do I lose hours of work or do I lose years of brand equity? Then set AI permissions based on that risk. Rachel: And wherever you do let agents act, attach a simple KPI. This bot owns first response time and CSAT; this ad agent owns ROAS and new to file customers. No vague AI magic. Measure it or don't deploy it. Max: Yeah, agents need a job description, not a vibe. Rachel: Put that on a mug. Max: With that in mind, there's another constraint nobody selling cross-border can ignore. Rachel: You're talking about the WTO drama. Max: Yeah, you can have the smartest agents and automations, but if digital tariffs change, the math on global orders shifts overnight. Rachel: So next I want to dig into that eCommerce duties moratorium fight, because if that unravels, every pricing and margin model people just set with AI... has to be rerun. I've got battle scars from the old days of tariff surprises. Max: Yeah, I spent years hunting landed costs across currencies, VAT rules, de minimis thresholds during international expansion. Every policy shift broke something. This WTO mess is exactly that chaos turned way back up. Rachel: Stay with us, because this is the unsexy part that decides whether those shiny AI wins actually hit your bottom line. That's where I live. Max: All right—flip that script; we've spent all this time talking about AI protecting your margins, now policy's about to attack them! Rachel: Yeah, the boring sounding stuff that quietly nukes your P&L. Start with the WTO thing in plain English; no policy theater. Max: All right, no law school needed. There's this WTO e-commerce moratorium, fancy term for countries agreed not to slap customs duties on digital products and online trade. Rachel: So like downloads, SaaS, and cross-border digital services, right? Max: Exactly. It set a norm that you don't tax every tiny cross-border digital sale like it's a physical import, kept a lot of stuff zero duty by default. Then the U.S. and India got stuck and the whole thing nearly fell apart. Rachel: So what were they actually stuck on? Because that's where the real risk lives. Max: India said, we're losing tariff revenue as stuff goes digital- we want options. The U.S. said, if you tax digital, you break global eCommerce. No compromise to the whole thing nearly expired. Rachel: So, if it lapses, what changes for a merchant? Max: Your cross border orders stop being clean and start looking like regular imports governments can tax. Countries could add new tariffs on digital products and some will extend that logic to physical eCommerce too. Net effect: higher landed cost, weirder rules, more paperwork. Rachel: Uh, this is where my duties and taxes trauma from the Walmart days comes in. I spent years on this, mapped it, modeled it, thought we'd solved it, but policy never stops moving. Max: Oh yeah, I spent years hunting landed costs across currencies, VAT thresholds, de minimis rules. Every time a country changed one thing, we'd break conversion funnels for a week. This WTO mess, it's like someone turned the entire chaos dial back. I'll back up. Rachel: And the big risk is fragmentation. Each government tinkers with its own digital tariff rules. Your AI agent optimizes price all day, but if the policy moves overnight, you're flying blind on actual margin. Max: Okay, so you're a bigger operator hearing this, you're not going to solve geopolitics. What do you actually do on Monday? Rachel: On three moves: one, scenario planning, two, repricing rules, Three, transparent communication. That's the framework. Max: Love it. Let me tease those out from Ops side. Rachel: On scenario planning, you don't model every country—pick the top five by cross border volume and the ones where governments are loud about tariffs. Concentrate your math where it matters. Max: Yeah; top five countries by cross border revenue. Rachel: Mm-hmm. Within those, pick your high GMV SKUs and map it: Current Price, Landed Cost, Unit Margin. Add a column, What if another five to ten percent duty hits—that's your stress test bucket. Max: And highlight anything where that extra duty kills more than a third of your margin—those are your stress test SKUs, the ones where policy can actually blow up your unit economics and your P&L. Rachel: Exactly. Second lever is pricing rules: you don't want a human manually changing four hundred prices every time a policy guy sneezes. That's when you get garbage data and blind spend. Max: No vague AI magic-set guardrails. So you set guardrails up front; if new duty in country acts is under three per cent, we absorb it; between three and seven, we split it; above seven we reprice and communicate; system executes, human sets the rules. Rachel: And your system knows when to flip those switches. Max: Right. Rachel: Third is communication, where a lot of brands blow it. They hide costs and then wonder why repeat purchase rate tanks and brand trust craters. Max: Yeah, they hide the cost, hope nobody notices. Then get absolutely roasted on Reddit when customs fees hit. Great way to kill repeat purchase rate and destroy brand trust. Rachel: Firm—if your landed cost is going up, tell the customer at checkout. Better yet, test copy like "Includes new local import fee, no surprise bills at the door." Measure the conversion hit. It's usually smaller than you think. Max: That line alone can move conversion because you're making a trade: slightly higher price, zero surprise anxiety. And honestly, that trade usually wins. Rachel: One more for the large operator crowd: add up a policy risk column to your country's scorecard, not just CAC and AOV, but likelihood of new tariffs in the next year. That's how you actually score where to allocate inventory and logistics bets. Max: And you weight that into decisions like where to open the next 3PL or localize a pull store instead of shipping cross border. Rachel: Moving stock inside the country can be cheaper long-term than paying mystery duties forever. However, I modeled this at Walmart scale. If you're already near break-even, it works, but you need the volume. Max: This is where the AI talk from earlier comes back – let AI crunch the scenarios all day long, that's what it's good for, but a human makes the call: two points of margin? We eat it. Ten points? Absolutely not. Rachel: Right. Policy sets the playing field. Your job is deciding which games are still profitable. Max: And speaking of games being played, there's a completely different way Speaker 4: of doing business. Max: different one happening right now. Amazon's running Big Spring, training shoppers to expect heavy discounts, and Reddit's quietly building high intent shopping channels inside niche communities. Rachel: So next we should talk how to ride those waves for revenue without destroying the margins we just spent ten minutes protecting. That's the operator's real game. Short-term wins, long-term sanity. Max: Short-term wins, long-term sanity. Let's get into the promos and performance next. NEXT. Shifting gears, I want to hit this Amazon Big Spring Sale thing head on. Rachel: Yeah, go there, because my inbox is just like television screaming at me. Every discount is a margin question I need the math on. I can't operate in the dark. Max: Exactly. The simple reality: Amazon is training shoppers to anchor on heavy discounts for big ticket electronics in March and April. Those reference prices are now burned into their brains. Rachel: So if you sell TVs, headphones, laptops? You are now compared against Amazon's Spring Sale price, not your old list price. That's the new anchor—and it's brutal if you're not prepared. Max: Right, and even if you're not on Amazon, people anchor on that discount. They Google your brand, see your price, and go, "Hmm, feels high. Rachel: So what do you do if you cannot match those discounts without nuking margin? That's where most operators panic instead of think. Max: Two moves. First, protect your hero SKUs. That's where your real margin lives. Lives—discount the accessories instead; full-ish margin on the laptop, sweeter deal on the case, dock, warranty. Rachel: So basically shift the value story to the bundle, not the base item. Protect your hero margin, sweeten the accessories—that's real operating leverage. Max: Exactly. Second move, non price perks. Faster shipping, extended returns, maybe set up support on electronics instead of torching another ten per cent off your margin. Rachel: Yeah, service instead of straight margin burn, but measure the ROI on that service, don't just assume it sticks. Max: And here's where I get nerdy: track attachment rate, blended margin per order, and crucially refund rate on those promo orders, because margin is just theory until returns eat it. Rachel: Let me add one-liner contribution profit, not just ROAS. You might win the sale and lose on shipping or returns. That's money on fire, and you won't see it if you're staring at the wrong metric. Max: Totally. OK, swing to Reddit because this is the opposite energy: tiny budgets, super high intent. Rachel: Yeah! Reddit rolling out better eCommerce ad formats plus Shopify integration means you can actually target niche communities where people are already problem aware and ready to buy. High intent, low waste, that's the operator's dream. Max: Like VR home theater crew shopping receivers or the r/skincare addiction debating sunscreens? Rachel: Exactly—these people have ten tabs open before breakfast. Max: So if I'm a brand, how do I test this without lighting money on fire? I need a clear KPI and hard budget caps, or it's just spend with hope. Rachel: I'd start with one or two subreddits that literally describe your buyer profile. Run simple promoted posts. No fancy video production. Link to a tight landing page, not your home page. One variable at a time, always. Max: And set a hard experiment box. Tiny daily budget, say a couple hundred total, one clear KPI like cost per add to cart, measure it or don't run it. Rachel: Yes, and the creative has to sound like an authentic comment, not an ad. Tested three of these, this one actually solved my problem style. That's where the conversion happens. Max: And please, for the love of ROAS, use UTM tags. You want to see, did Reddit traffic bounce? Did they add to cart? Did they actually buy? If you can't track it, you can't repeat it. Rachel: Okay, so bring this home with a playbook. What are you testing this week if you run a store? And I mean real testing, not just spending. Max: On Amazon or your own site, A-B test two offers. Version A, smaller discount plus free shipping. Version B, bigger discount but shipping costs money. Measure margin per order and conversion rate. Rachel: Nice. That's real structured thinking. Max: Second test, bundle versus solo. Run the hero product standalone, then as a bundle with accessories that f***. Is it feel like a deal; watch AOV and attachment, but also watch return rate on those bundles. Rachel: OK, my side-on Reddit, one week probe, one subreddit, one message, one product. Cap spend, then judge it against your other prospecting channels on cost per Checkout initiated. Structured, measurable, done. Max: And if it works, don't scale ten x overnight; add one more subreddit, test one new creative, and keep your eyes on contribution margin. margin. Rachel: Exactly. Treat Amazon Sale as a pricing and offer lab. Treat Reddit as a targeting lab. Both need clear hypotheses and measurable wins, or you're just guessing. Max: If you do that, you're not chasing sale noise, you're running actual experiments that make your P&L smarter next quarter. Rachel: And that's how you survive promo season without your P&L getting torched. Structure beats hope. Measure it or don't run it. Max: All right, I think that's a good place to stop before an AI agent actually ships someone another bottle of olive oil while they're literally listening to this. Rachel: Please check your carts, people! But seriously, agentic commerce only works if shoppers still feel in control. That's the margin-safe version. Max: Yeah. One-liner takeaway, treat AI agents like a new performance channel with rails, but keep your... humans owning the calls that actually move your margin. Rachel: Exactly. If you remember anything, remember that. Start small on the AI ladder, measure revenue and margin from those flows separately (that's not optional), then level up. Max: And seriously, if this helped you map out your own AI ladder or figure out your promo playbook, hit subscribe so you don't miss the next breakdown. Rachel: Yeah, and share this with one operator friend wrestling with AI or margin pressure. We built this for people running the numbers at scale. Max: Plus it tells every algorithm out there, human and machine, hey, this is the good nerdy eCommerce stuff we're here for. Rachel: Thanks for hanging out with us during this weird in between phase where AI agents are almost running store operations. I've seen stranger things at scale, but not often. Max: We'll be back next week with more experiments, more plays you can actually run, and I promise at least one fired up rant about value. What about budget waste or margin loss? Rachel: Looking forward to it! Take care, and keep those margins healthy. It's the only math that really matters. Max: See you at the next Checkout Point.