Hi! I’m currently looking for a remote opportunity, preferably in Shopify product listing. I also have experience with customer support, inventory tracking, order monitoring, and data entry. I’d love the opportunity to contribute to your team!

You can contact me on WhatsApp +639555680027

Thank you!

I have been looking at AI tools for ecommerce lately, and it feels like every vendor now claims their product id hallucination free.

That sounds great, but isn't hallucination kind of a built in limitation of LLMs? They generate the most likely next token they don't actually know whether something is true.

So I am curious what these companies really mean when they make the claim. And they relying on retrieval from a product catalog, adding strict guardrails, or just refusing to answer when the model isn't confident? or is it mostly marketing for technology that's still capable of getting things wrong?

For anyone who's actually deployed these at scale, how reliable are they in practice? Do they genuinely avoid making things up, or is it more about reducing the number of bad answers rather than eliminating them entirely?

Recently been getting a couple of claims but I realize it takes so much time to handle each one. What do you guys do? Any apps you use or internal process you’ve built?

Grand Rising, Shopify Pros. Our company makes large agricultural products that vary by length. The add-on options' pricing also changes based on the length selected, and it has made it very difficult to configure our Shopify on the back-end.

Example: The user wants to order a product of a certain length, plus an add-on feature. That added feature will cover the full length of the unit, so the base price per foot of add-on needs to be multiplied by the length selected to get accurate pricing.

This is trivial in a spreadsheet, and we do use a spreadsheet for custom quotes, but we would like to replicate that ability as a purely customer-facing selection set on Shopify.

Some add-on apps we have tried and their results (NOT ADVERTISEMENTS):
Globo Product Options - currently used, works ok. Requires a massive matrix of product sets and is horrible to maintain - cannot do any formula calculation.
Hulk Product Options - recommended by several AI tools and well-reviewed in app store - would not integrate with out Shopify for some reason
Apippa Custom Pricing - promises formula-based calculation, but does not support any 'IF' statements.

Any suggestions or help would be appreciated!

Running into this a lot lately.

The customer is close to buying, but the question is just specific enough that collection filters and standard copy do not fully solve it.

Examples are things like which serum works for oily but sensitive skin, whether a certain item works for a very specific use case, whether a product fits with another one they already own, or which version to buy if they are right between two options.

These are not rare enough to ignore and not simple enough to hard-code everywhere.

For people on Shopify, how are you handling that middle layer?

Running a Shopify dropshipping store, live for about 6 weeks now. Here's the full picture, trying to be as transparent as possible because I'm genuinely stuck.

Timeline:
First 4-5 weeks: ran ATC-optimized campaigns, ~$650 spent total across multiple ad sets and creative angles. Decent engagement the whole time (best cost-per-link-click around $0.70-1, CTR in the 10-17% range depending on the creative). Got 26 real Add-to-Carts. But the site had an actual cart bug during this period — some sessions had broken checkout flow, double add-to-carts — so I don't fully trust that data.

Fixed the bug, rebuilt the entire landing page from scratch (long-form advertorial style, follows a structured copywriting framework), then tested Purchase-optimization for 3 days on the clean setup. Day 1 was great (CTR 3.3%, $0.69 CPC). Day 2-3 the CPC spiked hard ($5-10), so I killed it — with zero purchase history ever, I figured I'd never hit the ~50 weekly events needed to exit learning on that objective anyway.

Went back to ATC on the clean funnel with my two historical best creatives (a receipt-style static image and a UGC testimonial video, both previously proven at $0.65-0.81 cost-per-click). Less than 3 days in on this clean run: CTR 16-19% and 9-11% on the two ad sets, CPC $0.50-0.70, already 14+ Add-to-Carts.

The actual problem: Still zero purchases. Not one, ever, across any campaign, any angle, in 6 weeks.

What I've already ruled out:

• Checkout technically works — I've done a full real test purchase myself, completed it, and confirmed the Purchase event fires correctly in the pixel.
• Payment methods are all there (Apple Pay, PayPal, Google Pay, cards), Shop Pay express checkout available.
• The brand shows correctly at checkout (logo, not generic).
• Shipping cost/policy is clearly communicated on-site and on the landing page, not a surprise at checkout.
• I checked the cart→checkout funnel breakdown recently: out of ~52 sessions, 19% added to cart, but only ~6% even reached checkout — so there's a real drop-off between cart and checkout start, not just at the final payment step. I just found and fixed one likely cause (a cross-sell item in the cart drawer that was confusing about what's already included in the main product, which was quietly increasing the perceived price by ~25% for anyone who added it), plus fixed a discount threshold that wasn't applying to single-item purchases. Too early to know if this moves the needle.

Constraints:

• Meta account is capped at ~$40/day total (business verification not possible right now on my end), so I can't just "spend more to get more data" as a lever.
• Limited overall budget, so I can't afford months of pure trial and error.

What I'm trying to figure out: is this still a volume issue (too few Add-to-Carts to expect a statistically meaningful number of purchases yet), a trust gap specific to checkout for a new/unknown brand, or something in the offer itself that Add-to-Cart behavior doesn't reveal? Genuinely not sure where to focus next, and would rather ask people who've actually dealt with this than guess.

If you've been through something similar — where did the real problem end up being, and how did you find it?

Hi r/ShopifyeCommerce - I'm Paul and I follow the e-commerce industry closely for my Shopifreaks E-commerce Newsletter. Every week for the past 5 years I've posted a summary recap of the week's top stories on this subreddit, which I cover in depth with sources in the full edition.

Let's dive in to this week's top e-commerce news from Edition #287...

STAT OF THE WEEK: China's live-commerce market reached roughly $900B in 2025, according to a report from consumer-intelligence firm NIQ. That's nearing the size of all U.S. e-commerce, which sat at an estimated $1.23T the same year.

DoorDash launched a direct integration with Shopify, available as a native sales channel in the Shopify App Store, that lets U.S. merchants with a brick-and-mortar presence add their product catalog to the DoorDash marketplace. For example, a local sporting goods store can leverage the integration to sell tennis balls and other sports equipment via the DoorDash marketplace, and then have the orders picked up and delivered same-day by a DoorDash driver. The integration does not enable merchants to offer local fulfillment by DoorDash on orders processed through their Shopify stores. This still requires third-party middleware applications like LionWheel or Shipday, which plug into the DoorDash Drive API. (Or merchants can of course tap into the API themselves through a custom solution.) One other thing to note is that although DoorDash bills the app and integration as “Free” — they do of course take a commission on marketplace orders, which can range from 15% to 30%. That said, merchants are allowed to set channel-specific pricing through the app to offset DoorDash's commission, without changing the pricing in their main storefront. The integration is now live in the U.S., with international expansion planned in the coming months.

TikTok is piloting a managed-services program in the U.S. that hands it control over most of a seller's Shop operations for a fee, according to documentation viewed by Business Insider. The program will handle key marketing tasks like hiring creators, running ad campaigns, testing ad creatives through its GMV Max tool, and optimizing product listings. Sellers will only be responsible for listing their products and sending free samples to influencers, while TikTok does most of the other heavy lifting. The serve costs just a mere $10,000 non-refundable flat fee investment plus a 10% to 20% commission per sale, depending on the brand's product category. Plus ad spend, I'd imagine? Business Insider didn't specifically mention who pays ad spend (the seller or TikTok), but given the commission range, I can only guess that it's charged separately. The program, which is set to kick off in August, is open to both U.S. sellers and international sellers who market and ship to the U.S., and puts TikTok in direct competition with its own Shop agency partners — the same ones it leaned on heavily to get the U.S. business off the ground since 2023.

Amazon warehouse managers are overriding, disabling, or dodging the company's new automated staffing software, prompting plans for stricter enforcement, according to internal documents and Slack messages seen by Business Insider.Last month, I reported that Amazon is testing software that reassigns warehouse workers to different sections of the facility in real time as package volumes shift. Well, as predicted, no one really likes having a computer algorithm tell them how to do their job. So the managers have not been using it, much to the dismay of Amazon. It turns out that getting managers to trust software to make decisions, while still holding the managers accountable for those decisions, is a difficult ask. Plus, what manager wants to give preference to an algorithm that is likely being positioned to take their jobs? I feel like companies aren't even hiding it anymore. Regardless, the days of ignoring your algorithmic overlords are over. Amazon wrote in one planning document, “Hard enforcement is the end goal for 2026.” Amazon called the story's premise wrong, saying it's piloting the tools at a small number of U.S. sites to give managers better information rather than replace their judgment, and that the quotes came from an early-stage planning document. I guess we'll see though.

Shopify rebuilt its Collections tool to give merchants more granular control over which products are listed. In the old days (last week LOL), you could only “Include” items based on their product type, tag, status, and other properties. Now, you can also “Exclude” items based on their properties. Additionally, Shopify opened up the ability to use multiple sources, target specific variants, connect to apps and external workflows, and hand-pick items alongside your automation rules. The ability to pull sources from apps, not just your product catalog, is an especially big feature. You can now, for example, rely on apps to track bestsellers or trending products and feed that data into your Collection to populate it with products, instead of having to do it manually. The new Collections API technically rolled out in June, so you might have seen developers talking about it during the past month, but Shopify just now launched the merchant-facing admin experience. Do you want to know the one thing you STILL can't do though? Include or Exclude items based on their Stock Levels from ONE particular fulfillment location! Please build this Shopify...

New York's Department of Financial Services proposed rules to license and supervise BNPL providers operating in the state, opening a 60-day public comment period through September 14. The proposal would require BNPL lenders to get licensed, send monthly billing statements, cap late fees at $8, and set up dispute-resolution processes, according to Bloomberg Law. If this sounds familiar… I've covered the proposal of these new rules on several occasions during the past year or so. New York Governor Kathy Hochul signed the BNPL Act into law back in May 2025 as part of her FY26 budget, but the statute wasn't self-executing. It handed NYDFS the job of writing the actual rules before any of it could take effect. NYDFS floated a preproposal draft in February, took informal feedback through March 5, and has spent the months since reworking it into the version published last week. February was a trial run, and this is the formal proposal that actually gets adopted. From here, comments close September 14, NYDFS reviews them and publishes a final Notice of Adoption, and the rules take effect 180 days after that. Once they do, BNPL lenders already operating in New York get 45 days to file a license application if they want to keep serving customers while it's pending. So Klarna, Affirm, Afterpay, and Block are now on a clock that runs out sometime in 2027.

Squarespace launched a new set of tools aimed at helping merchants create demand for their limited edition product drops and capped-capacity service bookings. For example, a hot sauce maker could release 200 bottles of a seasonal batch that he wants to build hype around, or a barber might open up eight chairs for a Saturday they don't normally work. New tools include: 1) Reserved Cart that holds item for a set time with a built in. 2) Low-inventory scarcity badges. 3) Quantity Limits to stop a single buyer from wiping out the entire stock. 4) A Mini Cart Checkout shortcut that lets customers view their cart and start checkout without navigating away from the page. 5) Express Checkout, which surfaces digital wallets for one-click purchases. And 6) Pay Links, which let merchants share a direct path to checkout via text, social, e-mail, or QR code. The new tools are native to Squarespace's platform and don't require any external plugins to manage the frontend features, inventory, or checkout. They're available globally now, though which ones you get depends on your subscription plan.

Last Tuesday, Stripe and private equity firm Advent International made a joint offer to buy PayPal for $60.50 a share (more than $53B), a roughly 28% premium to PayPal's most recent closing price before the offer was made. If approved, the two companies would jointly own PayPal with equal stakes rather than break it up. Two days later, Reuters reported that PayPal's board saw the $53B takeover bid as undervaluing the company, noting that it would also likely face regulatory and financing hurdles. The board is expected to meet today (Monday) to discuss the offer, though sources say acceptance isn't likely. I first reported on the potential offer in March, back when it was just a rumor reported by Bloomberg. This was about one month after PayPal announced the appointment of Enrique Lores as its new President and CEO, right as he was taking the reins. I'm highly against the merger. It's bad for merchants, bad for consumers, and overall bad for the market. PayPal should outright reject the offer (which they might have already done by the time this edition publishes). And if they were to accept this or a subsequent better offer, it should be blocked by antitrust regulators in the U.S. and EU as anticompetitive.

BNPL merchant fees get passed to all U.S. consumers through higher prices, regardless of whether they use the financing, according to a report by Protect Borrowers, a consumer-debt advocacy group formed in 2018 by former CFPB officials. Fees on BNPL purchases can run as high as 3x what a credit card transaction would cost, and 10x what a debit card transaction runs, and those transaction fees are a big way the BNPL companies make money. The report states that the "costs borne by merchants for BNPL partnerships are ultimately passed onto all Americans, regardless of whether or not they use BNPL, through higher prices." The only problem with the report is that it's based on observation, not data, which trade groups like the American Fintech Council and Financial Technology Association immediately attacked. The problem is — BNPL fees, inflation, tariffs, corporate greed — who can tell anymore what's specifically contributing to prices rising? With or without BNPL, they seem to be going up and up and up either way.

commercetools launched two standalone modules, Core Commerce, which handles enterprise cart, order management, checkout, and B2B, and Product Catalog, which spans product modeling, pricing, inventory, and catalog across millions of SKUs. The move unbundles its core transactional and data engines for the first time to offer independent modules, both of which run on commercetools Sphere, the API-native, headless foundation layer the company unveiled in June to govern autonomous AI shopping agents and handle machine-to-machine transactions. This allows brands running on legacy stacks like SAP Hybris or Oracle ATG to keep their current backend logic and ERP integrations, but leverage commercetools to replace their likely slow and cumbersome catalog or checkout flows. Took them long enough!

Phia, the AI shopping startup co-founded by Phoebe Gates and her former college roommate Sophia Kianni, is taking heat after a Bloomberg investigation accused it of stealing creator commissions. The browser extension allegedly overrode other affiliates' referral codes during checkout and inserted its own, claiming credit and commissions on purchases that it played no part in driving, which is a tactic that other extensions like PayPal's Honey have been accused of doing in the past as well. Impact-com suspended Phia's account after finding its conduct inconsistent with platform policies and is now reviewing affected transactions, while Awin says it's reviewing the case. The company blamed a recent code release for the commission misattributions, which it says only impacted a subset of users, and said that its team worked overnight to mitigate and resolve the problem once notified. Given the high profile of the founders, I can only imagine that this will result in a class-action lawsuit against Phia from creators it wronged, unless the affiliate networks themselves step in to correct the misattributed commissions.

U.S. importers got back $49.2B in tariff refunds in June, more than double the $22B returned in May, pushing the federal budget deficit to $120B for the month and reversing the $27B surplus the administration touted a year earlier as proof the tariffs were working. Gross customs collections came in at $23.6B against those refunds for a net outflow of $25.6B, and total June receipts fell 6% to $496B in a month that's normally flush with quarterly tax payments. CBP told the Court of International Trade it had repaid $86.3B of the roughly $166B owed as of July 10, with another $121.75B accepted for processing. Over 8,000 approved refund declarations are still sitting unpaid because CBP doesn't have working bank details for the importers. Refunds started flowing in May after the Supreme Court struck down Trump's IEEPA tariffs back in February, and unpaid balances accrue interest at 6% for corporations and 7% for individuals, compounded daily.

More than 160 privately held U.S. enterprise software companies worth at least $1B are now under pressure to sell, nearly double the number on the same list a year ago, according to The Information. Venture firms have shifted their money into AI, while public software stocks like Atlassian, ServiceNow, and Asana have seen their market cap nearly cut in half in a year. Meanwhile, mega-IPOs from OpenAI and Anthropic threaten to absorb investor demand, leaving these startups with a sale as their likeliest exit to deliver cash returns to their investors. Ryan Lund of Houlihan Lokey said, “Buyers are struggling to really understand what is the terminal value of some of these businesses, so the market is stuck. The attractive acquisition targets for [major buyers] are those accelerating on AI.” This was demonstrated by Salesforce's recent $3.6B acquisition of Fin, formerly Intercom, after it launched AI agents that answer customer questions and handle tasks like refunds.

Alexa for Shopping doesn't care about Amazon product rankings or ads, according to a study of 12,810 recommendations across 1,963 non-branded queries run by AI-optimization vendor Autopilotbrand-com and reported by Marketplace Pulse. Researchers posed “best of” questions like “what is the best queen mattress?” against the bare category search, and found 63.9% of Alexa's picks fell outside the organic top 10 for the matched term, with 40.9% not appearing on the visible results page at all. Only 14.3% of picks were running a sponsored listing on that search page, and 83% of those already ranked organically anyway, indicating that buying ads isn't a first-class ticket to AI recommendations, at least for now.

eBay made its eBay Live rate card public for the first time, pricing the invite-only livestream format in the U.S. at a combined 8.9% plus $0.30 per order in most categories and 6.9% for coins, bullion, and eligible sneakers, according to Liz Morton at Value Added Resource. Both rates fold in a 2.9% payment processing fee and sit below the 13.6% final value fee that non-Store sellers pay on standard listings, with Live commission capped at $100 per item, no insertion fees, and a Promoted Listings General waiver. UK rates run slightly lower at 6.42% and 8.42% plus £0.30, and both markets are temporarily cutting the fixed fee to $0.10 or £0.10 on orders of $10 or less through December 31, 2026. eBay's rate undercuts Whatnot, which charges 8% commission plus an additional 2.9% + $0.30 processing fee, but comes in higher than TikTok Shop, which charges a flat 6% that includes payment processing.

Google added personal AI avatars to Vids, its Workspace video tool, letting users generate a digital double that mirrors their appearance and voice from an uploaded selfie and voice recording. It also brought Gemini Omni to Vids, allowing users to turn a written prompt and reference images into video with background swaps, lighting fixes, effects, and step-by-step edits instead of restarts. To prevent people from making videos of public figures or other random people, the avatars are bound to the user's own likeness and Google account, carry invisible SynthID watermarks, and reach only users 18 and older in certain regions. The updates push Vids past its original workplace-presentation role toward an all-in-one video platform, putting it in closer competition with AI-avatar startups like HeyGen, Synthesia, Captions, and D-ID, months after OpenAI shut down its video app Sora.

In other Google news… The company is expanding connected apps in AI Mode for Search, letting users in the U.S. securely link and act on external services directly inside AI Mode, an option it previously offered only in the Gemini app. For example, a shopper planning a dinner party can push an AI-built grocery list straight into an Instacart cart and check out in a few taps on Instacart's app or site. Or a merchant prepping a weekend promo can ask Canva for banner templates with their theme and dates already filled in, then tap through to finish the design in the app. Rollout begins this week and stays limited to the U.S. for now, though Google says it is working with a range of partners and expects to add more apps and reach more countries soon.

A 24-year-old Philadelphia entrepreneur named Mohamed Coulibaly allegedly took more than $1M from three former NFL players by persuading them to invest in fake Shopify stores, according to a Barron's investigation by Jacob Adelman. Investors put in at least $50,000 each for prebuilt online stores, which Coulibaly promised would return their principal after six months, plus 80% of any profits from the sites. However, the investigation found that many orders shown to investors were manually entered into Shopify, creating the appearance of successful online stores despite having little customer traffic. One site logged over 360 orders against 90 visitors, including a $5,000 order from a supposed Luxembourg customer for 100 desktop humidifiers and 120 USB cup warmers, but the guy living at that shipping address told Barron's he never bought a thing. Isn't that the oldest trick in the book — the old “ready-made Shopify store” scam? But usually, it targets little old ladies and other retirees. This is the first I've heard of anyone tricking millionaire pro athletes with it. Coulibaly denies any fraud and says the article presents disputed allegations as established fact.

Apple Maps is barring home services like plumbing, electrical, HVAC, pest control, roofing, locksmiths, and general contracting from its upcoming ads program, along with crypto ATMs and bail bonds providers, with medical-services ads evaluated case-by-case, according to its newly published Advertising Services policy effective July 14. The exclusions suggest Apple is limiting Maps ads, which are expected to launch this summer in the U.S. and Canada, to businesses with a physical location customers actually visit, such as restaurants, shops, hotels, and salons, unlike Google, where Local Services Ads are one of its largest local categories. Also unlike Google, Apple Maps ads will only show a single ad per search, marked with a blue halo around the location pin and labeled as an ad in the list of Suggested Places, with interaction data kept on the user's device.

TikTok Shop is being flooded with AI-generated product demos, avatars, and creator duplicates, creating friction between creators, brands, and TikTok itself, according to The Wall Street Journal. The platform's AI Video Maker lets sellers and creators auto-generate shoppable video clips, and TikTok's policy permits fully AI content as long as creators add an on-screen disclosure tag and avoid false claims. Affiliate creators who demo real products say the easily generated AI clips are siphoning ad spend and sales, prompting brands like SharkNinja to ban AI content and strip commissions from affiliates who use it. The challenge for brands is that TikTok Shop's open affiliate setup lets any creator promote any product without brand approval, meaning brands can't stop the original post, regardless of their own AI policies.

Google Images launched a new Pinterest-style gallery UI that lets users save images to collections, similar to how Pinterest lets you save images to boards. It also launched a new feature in AI Overviews that turns a text prompt into a custom visual that users can then use as the basis for discovery, letting them skip writing out a description of the concept. For example, a shopper who wants a pair of khaki travel pants with built-in plastic lining to defend against their Cyclospora-induced explosive diarrhea can generate that exact pair and then use the AI-generated image to hunt down the closest real product. Both features roll out over the coming weeks, with the gallery starting on U.S. desktop and image generation reaching all regions that already support AI Mode image creation.

OpenAI's chatbot advertising is projected to fall about 90% short of its own 2030 revenue target, according to Emarketer. OpenAI projects ad revenue of $2.5B this year and $100B by 2030, figures it shares with investors to demonstrate how ads and subscriptions can eventually cover its heavy capital spending. However, Emarketer instead expects all U.S. standalone chatbots combined, including ChatGPT, Microsoft Copilot, Google AI Mode, and Amazon Alexa for Shopping, to generate under $1B in ad income this year and just $5.41B by 2030, a far cry from OpenAI's own projections just for itself — though Emarketer scopes its number to the U.S. while OpenAI's target doesn't mention a region, which suggests OpenAI's is a global figure. ChatGPT Ads are still in trial mode, so there's not a lot of data to go on for either OpenAI or Emarketer to make projections, other than OpenAI recently saying that its U.S. ads pilot surpassed $100M in ARR six weeks after launch. If I had to choose, I'd bet that in four years the true number will land closer to OpenAI's projection than Emarketer's estimate. These AI companies will make sure of it. What's your prediction?

In lawsuits this week…

• OpenAI asked a federal judge to dismiss a proposed class action lawsuit that accuses it of passing private user data about health and finances to Meta and Google via their advertising and analytics pixels. The company argues that lead plaintiff Amargo Couture consented to the disclosures by accepting its privacy policy when creating an account.
• Google search users are urging a federal judge to let their antitrust suit proceed, arguing that Google's deals to be the default search engine on Apple's Safari and Android devices blocked rivals offering more privacy, fewer ads, or payment for users' searches and data. The filing responds to Judge Rita Lin's order that they show real injury or face dismissal, with plaintiffs now claiming that Google monetized their queries, data, time, and attention without paying them, and cut off their access to those alternatives.
• X Corp and a group of music publishers led by Sony, Universal, and Warner Chappell ended their three-year music licensing battle, filing joint stipulations to dismiss both the publishers' copyright suit and X's antitrust countersuit with prejudice, meaning they cannot be refiled. Back in June 2023, the music publishers sued X for more than $250M over infringement of roughly 1,700 works, while X countersued in January 2024 accusing them of colluding through the NMPA to force industrywide licenses at inflated rates. Neither filing discloses settlement terms or whether X will now license their music.
• Temu is facing a proposed class action in California federal court alleging it sent spam e-mails that used forged headers, spoofed sender domains, and misleading subject lines to lure consumers to its site, where it planted tracking pixels without consent. The case claims violations of California's anti-spam and Trap and Trace laws and seeks $1,000 per spam e-mail plus punitive damages and an injunction.
• Google is facing a class action lawsuit from book publishers and authors that accuses it of training Gemini on works they had supplied for limited uses like Google Books and Google Scholar, not AI training. Plaintiffs, who include Hachette Book Group, Cengage Learning, Elsevier, and novelist Scott Turow, claim Google knowingly engaged in the practice and stripped copyright management information from the works to conceal its training sources.
• Meta is facing a federal lawsuit from 26 current and former employees alleging it used a “constellation of internal AI systems,” including its Metamate assistant, keystroke monitoring, and AI token usage dashboards, to build the termination list for the roughly 8,000 jobs it cut starting May 20, disproportionately hitting workers with disabilities or on protected medical or parental leave. Plaintiffs, all notified of termination after taking or requesting leave or a disability accommodation, say those systems relied on metrics like performance ratings, productivity, and AI-token consumption that someone on protected leave cannot accumulate.

• TikTok is facing a proposed class action lawsuit alleging that it exposed the personal information of 2.4B users in a June 2026 data breach, including names, usernames, e-mail addresses, phone numbers, dates of birth, gender, language, and location. The case accuses TikTok of negligence, invasion of privacy, and unjust enrichment, arguing that the company failed to implement adequate security despite knowing it was a high-value target.

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  In layoff news this week…

• Two Amazon delivery companies in the San Francisco Bay Area are shutting down operations and laying off nearly 170 drivers. Neither company stated a reason for closing, and the notices don't say whether Amazon is closing those delivery stations outright or simply bringing in different contractors. DSP shutdowns like these are routine, with Amazon contractors in Virginia, Tennessee, and Quebec filing similar notices over the past year.

• Alphabet Workers Union led more than 100 Google employees in a rally at the company's Mountain View headquarters, handing CEO Sundar Pichai and three other senior executives a 4,500-signature petition for stronger job protections. Petition demands include guaranteed payouts for anyone cut, a chance to leave voluntarily before forced layoffs, scrapping forced-distribution performance ratings, and letting workers convert severance into extended paid leave.

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  In corporate shakeups this week…

• Meta is hiring AWS senior VP Dave Brown, who is ending a nearly 19-year run at Amazon, to work on its data center build-out, according to the WSJ. Brown joins Meta Compute, Zuckerberg's infrastructure initiative, as the company aims to spend up to $145B in 2026 capex. Dave Treadwell, a top executive from Amazon's e-commerce division, will take over the AWS group.

• Anthropic hired Tom Blomfield, co-founder and former CEO of UK neobank Monzo, as a member of technical staff on its compute team, with Blomfield taking a leave of absence from his partner role at Y Combinator. He reports to co-founder and chief compute officer Tom Brown to work on compute availability, joining a 2026 hiring run that also pulled Andrej Karpathy from OpenAI and John Jumper from Google DeepMind.

• Anthropic posted a job for a director of investor relations at a base salary of $425K to $600K to build the company's “investment narrative” ahead of its fall IPO. The director will serve as a primary point of contact for institutional investors and advise leadership on how major decisions are likely to be received, working alongside IR head Kenneth Dorell, who joined from Meta in June.

• Microsoft security chief Hayete Gallot has replaced at least eight senior executives and cut several hundred roles from the 10,000-person security group since taking over in February, according to The Information. Gallot is reorganizing the business around AI security products to capitalize on corporate fears of AI-powered hacking, telling staff in a memo that the industry is being reimagined from the ground up.

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  Sen. Mark Warner released a discussion draft of the AI AGENT Act, which would require large online platforms with at least 50M U.S. customers, like Amazon, Google, Meta, and Apple, to build an interoperable interface so any outside AI agent a consumer picks can operate on the platform. For example, the law would require that Amazon allow third-party agents to shop on its marketplace, instead of pushing users to Alexa, which is exactly what Perplexity is fighting for. The second part of the law would require providers to register their agents with the FTC, as well as protect user data, keep real-time records of their activities, and avoid acting against the user's interests. One could argue that allowing third-party agents into their system goes against acting in the user's best interests, which puts the two parts of the law at odds with one another, and I'm sure Amazon and others will use that argument. The act remains a discussion draft, not a bill headed for a vote.

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  Remember when Coupang had a data leak that exposed personal information of 33M customers? And how South Korean regulators fined the U.S.-listed company $409M over the incident? Well, U.S. Republicans are pissed about the fine and are accusing South Korea of discriminating against American firms, weaponizing rules against Coupang, and putting disproportionate burdens on U.S. companies, according to Reuters. The House Judiciary report ties the fine to a broader pattern, citing previous actions against Google, Apple, Microsoft, and Qualcomm, and takes aim at South Korea's proposed platform legislation modeled on the EU's Digital Markets Act. The U.S. also points to a trade agreement clause requiring Seoul not to discriminate against American firms on digital services. South Korea's position is that it enforced its own privacy law against a company that broke it, noting the fine covered illegal data collection and reporting failures beyond the breach itself, and that its regulator has fined Korean firms and U.S. firms alike.

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  PayPal launched Pay in 30 Days in the UK, letting eligible customers pay the full amount for an online purchase up to 30 days later with no interest, sign-up fees, or additional charges on eligible purchases between £1 and £900. The payment option complements PayPal's existing Pay in 3, which splits a purchase into three payments at checkout and over the following two months. The move came a day before UK BNPL came under FCA regulation on July 15, which now requires lenders to be FCA-authorized, run affordability checks on every purchase even under £50, notify customers immediately when they miss a payment, and offer support to anyone falling into financial difficulty. Consumers also gain access to the Financial Ombudsman Service and Section 75 protection on purchases over £100, making the lender jointly liable with the merchant if something goes wrong.

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  The European Commission issued Google two sets of binding specification measures under the Digital Markets Act, spelling out how the company must open its platforms to competing search and AI services. The first measure requires that Google let rival AI assistants tap the same Android device features it reserves for Gemini, so competitors can actually challenge Google's AI services, feature for feature. The second measure requires Google to hand rival search engines the large-scale query, ranking, and click data that only its search engine can amass. I previously reported these remedies as pending, tied to a binding decision expected this month, but now they're official. Google faces daily penalties or fines up to 10% of global annual revenue if it fails to comply. Google can now appeal to the EU General Court, though it hasn't announced plans to do so yet. However, doing so wouldn't pause compliance anyway, with search data sharing due by January 2027 and Android interoperability by August 2027.

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  Speaking of troubles in the EU for Google… Germany's media regulator, ZAK, ruled that Google's AI Overviews and Perplexity are subject to the country's media laws, treating AI-generated summaries and chatbot answers as content the providers create themselves rather than third-party material. ZAK, which represents Germany's 14 state media authorities, said the EU Digital Services Act's liability shield does not apply and that prominently displayed AI Overviews unfairly disadvantage third-party media by pushing traditional link lists down the page. The decision follows a Munich court ruling that Google could be directly liable for false statements from AI Overviews, which Google plans to appeal. The ruling, which came from investigations already in progress, doesn't currently include OpenAI, Anthropic, or other AI chatbots, but ZAK chairman Thorsten Schmiege's language puts them squarely in scope, saying the regulator “will consistently apply German media law to them from now on.”

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  🏆 This week's most ridiculous story… What would you do if you received a $16 million invoice from Anthropic for your AI usage? Or how about a $1.5 trillion charge estimate from Amazon Web Services?! That's what happened to users last week after both platforms experienced insane billing issues that sent erroneous bills and charge estimates to customers worldwide. Anthropic confirmed that it sent invoices ranging from $1.67M to $16.6M to a South Korean Claude user, despite being on the free tier with no billable API usage. The company made so many repeated charge attempts that his bank blocked his primary credit card, which took days to resolve. Meanwhile, AWS started showing users estimated charges for tens or hundreds of billions of dollars in their dashboards, with one as high as $1.5 trillion. Question: If these billing errors were only caught because of how ridiculous they were, what about the other smaller ones? Is it possible users are spending exponentially more for AI usage than they should be, with no way to audit their bills?

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  Plus 16 seed rounds, IPOs, and acquisition of interest including Whatnot buying Shaped and Uber ragreeing to acquire Delivery Hero.

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I hope you found this recap helpful. See you next week!

PAUL

Editor of Shopifreaks E-Commerce Newsletter

PS: If I missed any big news this week, please share in the comments.

I'm just getting started, but I can't make the training phase math....math.

If I'm targeting a cost-per-purchase of $50, it seems I need to spend 6-weeks and $4,500 before I'm out of the learning phase per ad set.

Assumptions:

1. Need 50 purchases per week to exit learning.
2. Can't increase budget by more than 20% every 4 days or triggers re-learn
3. Ideally want 5 purchases over 4-7 days at no more than 2.5x target CAC to test creative.

If I was targeting a cost-per-purchase of $50, that means I'd test the creative at $100/day.
To exit the learning phase, I'd need to be spending $715/day.
Increasing at 20% every 4 days, that takes 45 days.
That's $4,500 spent before stable delivery.

Am I missing something?

Start with higher spend?
Do bigger increases?

Metrics:

I've spent about $15k on META ads over 10 weeks (just started business). AOV is $60, COGS is roughly 50%. LTV is higher, as it's a subscription food product. The website is www.planetprotein.co if that helps.

Hello guys. I made an online business on shopify which is working good, Im expecting to receive a payout on my revolut personal account 3k€, want to know if there’s a risk that revolut block my money. Also want to know if there’s any alternative banks that u use for your ecom without problem. Is it Swissquote a good bank ? Any suggestions

I'm advising an app, primarily growing through the Shpoify app store. Ads were working handily for them until March, 20% of all installs. Then just fell off a cliff, now ads make up 5% of installs. Increased bids, new campaigns, nothing. They're asking me for advice, anyone know what to do?

Email recovery barely works when half your customers don't check email. Curious what other store owners are doing — are you using WhatsApp at all? Any apps actually working for you or is it a mess?
Running a store targeting Morocco/Algeria/Egypt and feeling like I'm leaving a lot of money on the table.

We still do most of our restaurant outreach manually, so I've been curious whether AI tools are useful for this kind of work. Most examples I find are about SaaS companies, but selling to restaurants feels very different. Customer lists change, priorities shift, and a lot of communication is still personal. Has anyone used AI in this type of sales workflow and found it genuinely useful? Did it save time or improve results, or did you going back to your usual process?

We're running a Shopify store and want to start shipping through India Post, but I can't seem to find a proper way to integrate it with Shopify.

Has anyone here been able to do this? Is there any software, app, API, or third-party tool that works well with India Post? Or is everyone just creating shipments manually?

Would love to know how you're handling order syncing, label generation, tracking updates, etc.

Any suggestions or experiences would be really appreciated. Thanks!

I just started and launched my store and am currently running meta ads, I have interactions with my store just no sales. Can anyone point me in the right direction? Here’s my store itsblendly.myshopify.com

We've been using Collective as a supplier for a few months, and recently added a trusted brand to our shop as a seller (our first attempt). However, I cannot get the issue of shipping profiles sorted out. Our issue is this: we have a flat rate policy of $7 shipping below $59, and free shipping on everything above that. However, when we added a $75 collective product, and a $2.79 product from our own shop to cart, it engaged a $5.79 shipping charge (the policy of the supplier) for the collective portion, and free shipping from us.

I've gone through a round of support, with the live advisor suggesting setting up a "custom" profile that was essentially a bucket of all our products EXCEPT the collective, and the collective profile. It did not work. Today we received a follow-up from the technical team-- "The behavior of the checkout determines based on the total order, and not for each product/fulfillment. This means that regardless of the settings or fulfillment of each product, as long as it meets the eligibility and condition for your shipping rate." This strikes me as illogical, given the concept of split shipping, but this is our first time connecting on this side of the equation.

Are we doing something wrong? 

Why it is showing "No shipping rates"?

Running a DTC medical-ish apparel brand in Sweden (Meta only, ~€200-300/day). Looking for people who've been through something similar.

Setup:

• CBO campaigns, fully broad, no targeting or exclusions at all
• Mix of branded UGC + native-style video covering top/mid/bottom funnel
• Same campaign structure across both batches

Timeline:

• Batch 1: April 15 to May 16. Weak creatives, low expectations. 1.97 ROAS over the period. Break-even is 1.79, so barely profitable. Paused everything on May 16 because we sold out.
• Batch 2/3: live again from June 19 to today (July 16). Significantly better creatives, same structure. 1.63 ROAS over the period.
• First few days of the relaunch in june ran at ~3.5 ROAS.
• We then had to pause everything for about 12 hours. When we turned the ads back on the results were gone, and they haven't come back since. Sitting at ~1.5 ever since, July alone is at 1.43.

I'm not putting much weight on the pause itself as the cause, because we've since run completely new campaigns in a totally fresh ad account and got the same result. So whatever this is, it isn't something that lives in one campaign.

What I've tried:

• New campaigns with different creatives
• Re-enabling the old creatives from previous period, which didn't give results.
• Budget increases to let the algo re-explore
• Completely fresh ad account with new campaigns

None of it moved the number. Better creatives than batch 1, and we're performing worse than batch 1.

What I'm actually unsure about:

1. Does a new ad account reset anything meaningful?
2. Seasonality. Batch 1 ran mid-April to mid-May. Batch 2 is running mid-June to mid-July, which in the Nordics means half the country is on vacation, and our apperal might not fit the season, although google trends dont show any major hit in searches during the summer season. I might be comparing two completely different demand environments?
3. Sample size on the 3.5 roas. It was three days on a fresh creative batch. Early spikes regress. Possible that number was never real.

Questions for anyone who's been here:

• Anyone selling to an older demographic in the Nordics or similar markets: how bad is June/July /August for you specifically?
• Does anything else explain better creatives producing worse ROAS than the batch they replaced?
• If a fresh ad account changes nothing, where would you look next?
• What's the diagnostic order you'd actually run here?

Any input appreciated. I'm out of ideas on how to proceed.

Thanks in advance.

We're running a Shopify store and want to start shipping through India Post, but I can't seem to find a proper way to integrate it with Shopify.

Has anyone here been able to do this? Is there any software, app, API, or third-party tool that works well with India Post? Or is everyone just creating shipments manually?

Would love to know how you're handling order syncing, label generation, tracking updates, etc.

Any suggestions or experiences would be really appreciated. Thanks!

I own a small business that is performing steadily, and I am now planning to expand into the US market. I would appreciate guidance on setting up international payments using Razorpay and the steps required to launch a US-focused store.

I’ve been playing around with Shopify Sidekick (and keeping an eye on Pulse), and I’m trying to figure out if I’m just using it incorrectly or if my skepticism is justified.

Right now, they’ve made it freely available, but it feels pretty obvious that the endgame is to normalize our reliance on it and eventually put it behind a paywall. Aside from basic, somewhat mundane tasks like generating product SEO tags and writing basic descriptions, I really don’t see much practical use in it for my day-to-day.

Maybe I’m just not prompting it right or missing some hidden features, but I’m highly doubtful I’ll be opting into a paid tier for what it currently does.

For me, a tool like this would only be truly valuable if it could handle longer, more complex workflows. For example:

• Automatically analyzing what my top competitors are doing on social media.
• Identifying which of their posts/campaigns are actually successful.
• Taking those insights and helping me apply them directly to my own store’s marketing and social strategy.

That’s the kind of actionable, time-saving value that would make me happily pay for a tool. But right now, it feels like a glorified text generator for meta descriptions.

So I’m throwing it out to the community:

1. Am I using Sidekick wrong?
2. Is anyone actually getting deep, measurable value out of it right now?
3. What advanced workflows are you running that make it indispensable before the inevitable paywall hits?

Would love to hear your experiences or any tips on how to push it beyond the basics.

Trying to connect my meta business portfolio to shopify. It says I need a professional instagram account which I have. What I don't have, is a facebook account because business accounts only link to a page, not an account. So why the hell is the only option to login into a facebook account??

I'd post this in the regular shopify sub but I apparently don't have enough karma

We're running a Shopify D2C brand, and as our email list has grown, Klaviyo has started to get pretty expensive. We're mostly using it for sending campaigns/newsletters. What are you using these days?

If you've switched from Klaviyo, what did you move to? How's your experience been so far? Anything you'd recommend (or stay away from)?

Would really appreciate hearing what's worked for you. Thanks

I'm looking to add an AI Chatbot to my Shopify store that can answer customer questions about product, sizing, and order status, and help point people to the right items while they're browsing.

There are a ton of these AI chatbots out there now, so i'm not sure which ones actually integrate well with Shopify and are worth it. Anyone using one you'd recommend?

Ideally something that understands my store and answers based on my products, not just generic replies

Looking for a way to sell my excess inventory? any good ideas?