For years, Chinese ecommerce platforms seemed unstoppable. Companies like Temu, Shein, and AliExpress flooded Western markets with ultra-cheap products, helping drive billions in exports and reshaping online shopping.

But 2026 has been a different story.

Chinese low-cost ecommerce exports have now declined for five consecutive months, with April exports reportedly falling nearly 11% year-over-year. While the market remains much larger than it was just a few years ago, the momentum appears to be slowing.

A couple of major factors seem to be driving the downturn:

1. Rising shipping costs

The ongoing conflict in the Middle East has pushed jet fuel prices higher, making air freight significantly more expensive. Since many Chinese ecommerce sellers rely heavily on air cargo to deliver products quickly to Europe and North America, those increased costs are cutting into margins.

2. Weakening consumer demand

Inflation continues to pressure household budgets across many Western countries. Even shoppers who traditionally looked for bargain deals are becoming more cautious with spending. At the same time, sellers are being forced to raise prices to offset higher logistics and operating costs.

There are also regulatory challenges emerging. European governments have become increasingly critical of low-cost imports and are introducing new fees and screening measures that could make it harder for platforms like Temu and Shein to operate as efficiently as they have in the past.

The big question is whether this is temporary or the beginning of a larger shift.

Some analysts believe demand will rebound once geopolitical tensions ease and transportation costs stabilize. Others think the era of explosive growth for Chinese ecommerce may be slowing as regulations tighten and costs rise globally.

What do you think? Have you noticed higher prices on Temu, Shein, or AliExpress recently?

For years, Amazon was the go-to platform for ecommerce sellers. But lately, more and more sellers are expanding to TikTok Shop, Walmart Marketplace, and their own website. Not because they want to, but because they feel they have to.

The biggest complaint we see are Fees.

Between fulfillment costs, advertising expenses, storage fees, shipping surcharges, and various other charges, some sellers say Amazon is taking a significant chunk of their revenue. The latest fuel and logistics surcharges have only added to the frustration.

But this isn't just about money.

Many sellers are also tired of not owning their customer relationships. When someone buys from you on Amazon, they're Amazon's customer, not yours. That makes it difficult to build a loyal audience, collect customer data, or create long-term brand value.

Then there are the automation issues. Sellers regularly complain about listings being removed or accounts being suspended by automated systems, often leading to lengthy appeals processes. Add in return fraud, buyer scams, and increasing competition from low-cost overseas sellers, and it's easy to see why some merchants are looking elsewhere.

TikTok Shop has become an attractive alternative for brands that can leverage content and social commerce. Others are finding success on Walmart Marketplace or focusing on direct-to-consumer sales through their own websites.

That said, Amazon is still the dominant ecommerce platform. Thousands of sellers continue to thrive, and many are generating seven-figure revenues. But the growing number of sellers diversifying away from Amazon suggests the landscape may be changing.

Are Amazon's fees becoming a serious problem for your business? Have you tried TikTok Shop, Walmart Marketplace, or having your own website?

This week:

• Ulta’s AI chatbot is outselling its own stores
• Meta turns your DMs into a free sales team
• Your repurchase rate is probably killing your business
• Reddit just became a serious ad channel for Shopify stores
• The World Cup spending surge is already here

The Big Story

Ulta Gave an AI a Catalog of 25,000 Products. Here’s What Happened to Their Basket Size.

Ulta Beauty is a specialty beauty retailer with over 1,400 US stores and a catalog of more than 25,000 products.

In April 2026, the company launched Ulta AI, a conversational shopping assistant built on Google Gemini Enterprise, available on Ulta.com and its mobile app.

The idea is simple. A shopper describes what they want and the assistant surfaces products without requiring them to scroll category pages.

Q1 FY26 results landed this week and the numbers are 100% worth understanding this properly.

Ecommerce comparable sales grew mid-teens while physical store comps grew low single digits. The digital channel grew roughly four to six times faster than stores.

More importantly, the growth came from bigger baskets, not more shoppers. Average ticket rose 3.7% while transactions rose only 1.6%, meaning roughly 70% of the comparable sales growth came from basket size.

The question for your store is not “should I build a Gemini agent?” It is whether your growth problem is a traffic problem or a basket problem.

For most independent brands right now, it is a basket problem, and the tools to address it, smarter bundling, post-purchase offers, better product discovery, pay back faster than another round of acquisition spend.

What merchants should do with this:

• Ask yourself whether you have a traffic problem or a basket problem.
• Audit your post-purchase and cross-sell experience this week.
• Check your product descriptions for conversational language.
• Think about loyalty before you think about AI.

Keep reading

Weekly Metric

35% is the Average Repurchase Rate for Beauty Ecommerce Brands

That means nearly two out of every three customers you paid to acquire never come back.

The number comes from new benchmark data published by Decile, a customer analytics platform, and it sits alongside an equally uncomfortable companion stat: the average LTV to CAC ratio across beauty ecommerce is just 1.4x.

Every dollar you spend acquiring a customer generates $1.40 in lifetime revenue.

The deeper problem is structural. Beauty brands average an 84% first-order payback rate, which looks like a success metric until you see the 35% repurchase rate sitting behind it.

Teams are being rewarded for recovering ad spend fast, so that is what they optimize for, and the retention infrastructure never gets built.

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• Stop treating first-order payback as the north star metric. It measures the wrong thing.
• Track repurchase rate, churn, and sequential purchase behavior with the same urgency as daily revenue.
• Customers acquired through a well-designed Gift With Purchase program showed 78% higher lifetime value and a 10 to 20% greater repurchase rate within six months compared to those acquired without one.

This data is from beauty, but the pattern holds across categories. If your repurchase rate is below 40%, acquisition is not your problem.

Keep reading

Tool of the Week

Klaviyo

(Not sponsored) Klaviyo is an email and SMS marketing platform built specifically for ecommerce. It connects directly to your store data, so every email or text you send can be triggered by actual customer behavior: what someone browsed, what they added to cart, what they bought, and when they last came back.

This week’s Ulta story is ultimately a story about basket size and repeat purchase. Klaviyo is the tool most Shopify merchants already have access to that directly addresses both.

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• Abandoned cart and abandoned browse sequences that trigger automatically based on behavior, not manual scheduling. Klaviyo’s own data puts abandoned cart recovery at an average of 3 to 5% of otherwise-lost revenue.
• Post-purchase flows that send product education, cross-sell suggestions, and replenishment reminders timed to each product’s average repurchase window. This is the operational version of what Ulta’s AI assistant does at scale.
• Predictive analytics that surface which customers are likely to churn and which are heading toward a second or third purchase, so you can target both groups differently rather than blasting everyone.
• SMS flows that reach customers where email open rates have degraded, with conversion rates that consistently run two to three times higher than email for time-sensitive offers.

Try Klaviyo for free

Winning SKU of the Week

Text-to-Audio AI Tools

Text-to-audio AI is software that converts written text into spoken words using machine learning. You type something in, a voice reads it back.

That description sounds simple, but the technology has moved far beyond the robotic, monotone output most people associate with early text-to-speech.

Modern tools like ElevenLabs, Murf, and Play.ht produce voices that are expressive, natural, and in some cases indistinguishable from a real human recording.

The category has a 7,000% five-year search growth rate, which is one of the most aggressive search curves in any software category right now.

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• Product page video is one of the highest-converting content formats on DTC stores, and voiceover is the most common barrier to producing it at scale.
• TikTok and Instagram Reels with voiceover consistently outperform text-overlay-only content in watch time and completion rate.
• Customer-facing accessibility is increasingly a legal and reputational requirement. Brands that offer audio product descriptions and voiced checkout confirmations are ahead of where regulations are heading in both the US and EU.

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• Developers and SaaS builders pay for API access at volume, making this a recurring revenue category for tool resellers and integration builders.
• Individual creators and small business owners are the largest segment by account count, typically on $20 to $50 per month subscription plans.
• Enterprise contracts for call center and IVR deployments run into six figures annually, which is where the real margin lives for anyone building in this space.

Boring but Important

• France hits Shein with another €22 million fine: French authorities imposed two fines totalling more than 22 million euros, bringing the total fines against Shein in France to more than 210 million euros in under a year.
• Meta’s AI business agents are live on WhatsApp, Instagram, and Messenger: Meta’s autonomous agent can answer customer questions, book appointments, and close sales, with one million businesses already using it and a paid subscription tier coming in the months ahead. Map a DM workflow now while the tool is still free.
• Etsy’s new ad feature is paywalled at $25 a day: Etsy’s new Listing Strategies tool lets sellers assign individual goals to each advertised listing, choosing between greater visibility, lower click cost, or efficient spending. The feature is locked behind a $25 daily minimum, which shuts out most small independent sellers and costs $750 minimum just to run a 30-day test.
• Western brands are getting CEE ecommerce wrong: Western brands entering Central and Eastern Europe are assuming familiar checkout behavior and losing conversions because of it. Cash on delivery dominates in Romania and Greece, BLIK has 74% market share in Poland, and 3 to 5 day delivery is already below the floor that local marketplaces have set.

The Watchlist

• AI-generated ads need a two-week refresh cycle. Meta’s Advantage+ AI creative is burning out in 14 days versus the 45 days a real UGC video used to last. The CPA savings are real but the creative hamster wheel just got a lot faster.
• The World Cup is a fulfilment deadline, not just a marketing moment. Diamond Logistics is forecasting a 15 to 25% parcel volume spike across home entertainment, garden, electronics, and food. If you sell in any of those categories and your fulfilment is not locked in, the campaign spend will not matter.
• Reddit just made Dynamic Product Ads free and codeless for every Shopify merchant. Any Shopify store can now connect to Reddit Ads in minutes with no developer required, with EMEA retail advertisers reporting 7x ROAS on the platform.

That’s All for This Week.

The World Cup is days away, the spending surge is real, and the brands that put the work in before the first whistle are about to find out it was worth it.

The ones who did not are going to spend the next four weeks watching their competitors score while they scramble for warehouse space and carrier capacity.

Do not be the second team. Forward this to someone who needs it, go touch some grass, and we will be back Monday ready to do this all over again

Ulta Beauty just reported a strong quarter:
- $3.16B in sales (+11.1% YoY)
- Ecommerce growth in the mid-teens
- Physical store growth in the low single digits
- Average order value up 3.7%

The interesting part isn’t the revenue.

It’s that they launched an AI shopping assistant a few months ago, powered by Google Gemini, and it seems to be fitting into a much larger strategy.

Instead of forcing customers to browse thousands of products, shoppers can type something like:

“I need a foundation for oily skin under $40.”

The assistant narrows down options, recommends complementary products, and potentially increases basket size.

What’s interesting is that about 70% of Ulta’s comparable sales growth came from customers spending more per transaction, not from more people shopping.

That’s the part that caught my attention.

A lot of ecommerce brands are obsessed with acquiring more traffic when the bigger opportunity might be helping existing visitors find the right products faster and add more to cart.

Ulta is also expanding beyond its own website:
- TikTok Shop
- Uber Eats delivery
- Klarna integration
- AI-powered product discovery

They’re essentially betting that customers won’t always start their shopping journey on Ulta.com.

One thing I’m skeptical about though is regarding that every retailer is talking about AI shopping assistants right now, but very few are publishing actual performance data. Increased basket size and ecommerce growth are consistent with AI working, but they don’t prove it.

The real test will be whether these tools continue moving the needle six months from now.

For ecommerce operators, we would like to know, have you implemented AI product recommendations, shopping assistants, or conversational search on your store?

If yes, did you see measurable improvements in conversion rate, AOV, or revenue per visitor?

I came across an interesting take from a fulfillment provider operating across Central and Eastern Europe, and it highlights a problem that a lot of Western ecommerce brands seem to underestimate.

Many sellers expand into countries like Poland, Romania, Slovakia, or the Czech Republic assuming customers behave similarly to shoppers in Western Europe. Turns out that's often not the case.

Some examples:

- In Romania, cash on delivery is still hugely popular.
- In Poland, BLIK dominates online payments with around 74% market share.
- Customers often have strong preferences for specific local carriers.
- Address formats and validation requirements differ from what many Western stores are used to.
- Delivery expectations are extremely high thanks to marketplaces like Allegro, eMAG, and Alza. In many cases, next-day delivery isn't a premium feature.

According to Slovak fulfillment company isklad, many brands only realize these differences after conversion rates disappoint.

What stood out is that most market expansion discussions focus on market size, GDP growth, and ecommerce penetration. Much less attention gets paid to checkout behavior, payment methods, carrier preferences, and fulfillment expectations.

For anyone selling internationally, we want to ask you, what was the biggest localization challenge you encountered when entering a new market?

Did payment methods, shipping expectations, or customer behavior differ more than you expected?

Meta has officially entered the enterprise AI battle, and this could be one of its biggest moves yet.

The company just announced Meta Business Agent, an AI-powered assistant designed to help businesses automate customer support, qualify leads, schedule appointments, recommend products, and even close sales without human intervention.

According to Meta, more than a million businesses are already using the technology through WhatsApp and Messenger. Now the company is expanding it globally and making it available to businesses of all sizes.

Here’s what it can do:

- Answer customer questions 24/7
- Recommend products based on customer needs
- Schedule appointments automatically
- Qualify incoming leads
- Hand conversations over to human staff when necessary
- Generate daily business summaries
-Potentially close sales on behalf of the business

Meta also launched the Business Agent Platform, which allows companies to build and deploy custom AI agents connected to tools like Shopify, Zendesk, and hundreds of other business systems.

What makes this particularly interesting is that Meta is now competing directly with OpenAI, Google, and Anthropic for a share of the rapidly growing enterprise AI market.

And unlike many competitors, Meta already has access to billions of users through Facebook, Instagram, WhatsApp, and Messenger, giving it a distribution advantage that could be difficult to match.

If AI agents become as common as many analysts predict, businesses that start experimenting now could have a significant advantage over those that wait.

But we would like to know. Would you trust an AI agent to handle customer support and sales for your business, or would you still want a human involved in every step?

Etsy just launched a new feature called Listing Strategies, which lets sellers choose different ad goals for individual products instead of applying one strategy across their entire ad campaign.

On paper, it’s actually a useful update:
- Greater Visibility for bestsellers and seasonal products
- Lower Click Cost for low-margin items
- Efficient Spending as a balanced default option

But… you only get access if you’re spending at least $25/day on Etsy Ads.

Etsy is openly encouraging sellers to increase their budget to unlock the feature, and they recommend testing strategies for at least 30 days. That means a minimum spend of $750 just to see if the feature works for your shop.

For larger sellers, that may be reasonable. For many handmade creators, vintage sellers, and side-hustle shop owners, that’s a significant amount of money.

This also feels like part of a larger trend. Between mandatory Offsite Ads for shops over certain revenue thresholds and Etsy’s increasing focus on advertising revenue, the platform seems to be moving further toward a pay-to-play model.

The feature itself isn’t the problem. More control over ad spend is something sellers have wanted for years.

The question why are the best tools increasingly reserved for shops that can afford higher ad budgets?

We are curious what you think? Do you think Etsy is still prioritizing small independent sellers? Or is the platform becoming more geared toward larger, growth-focused businesses?

If you’ve been consistently shipping orders faster than your stated handling time, Amazon may start adjusting those settings automatically.

Amazon’s argument is simple: more accurate delivery estimates lead to more sales. The company claims that every day removed from a promised delivery window can increase conversions by around 5%.

Sounds reasonable. But…

The problem is that many sellers intentionally add buffer time to protect themselves from carrier delays, seasonal spikes, and late shipment penalties.

As a result, some sellers are already saying they’ll just hold orders until the last allowed day instead of shipping them early and triggering Amazon’s automation.

So Amazon’s attempt to speed up deliveries could end up slowing some of them down.

This also feels like part of a much larger trend.

Over the past few years we’ve seen:
- More fees
- More automation
- More performance metrics
- More seller decisions being made by Amazon

Each individual change seems justified on its own.

Taken together, it feels like third-party sellers have less control over how they run their businesses than ever before.

At what point does optimization become micromanagement?

Curious to hear from other sellers. Would you rather have Amazon set handling times based on actual performance, or should sellers be free to manage those settings themselves?

I came across some data from Decile about ecommerce brands (especially in beauty) and it honestly explains a pattern I keep noticing as a customer.

A lot of brands seem to be doing really well on the surface. They get me to buy once, sometimes with a discount, an ad, or a “first order offer,” and I’ll try the product.
But then… nothing.

No reason to come back. No real follow-up experience. No feeling that I should stick with them instead of switching to the next brand doing the same thing.

Apparently, this ties into something called the “first-order payback trap.”

From a customer point of view, it basically feels like this:

Brands are heavily optimized to recover the cost of acquiring me on the first purchase, so I get targeted hard, converted fast, and then I’m kind of forgotten unless I buy again on my own.

The problem is, that leads to an experience where:

I don’t feel any ongoing relationship with the brand
There’s little incentive or reminder to repurchase
Everything is focused on getting me in, not keeping me.

And it shows in behavior. A lot of brands only see a small fraction of customers ever come back for a second purchase.

What’s interesting is that the long-term numbers behind this are apparently not great, meaning customers are expensive to acquire, but brands aren’t getting enough repeat value out of them to make it sustainable.

From my side as a customer, it actually makes sense.

If I don’t feel:

- consistency
- personalization
- or any reason to stay engaged

…I’ll just move on to the next brand when I need something again.

What seems to work better (from the brands I do go back to) is:

- subscription options that actually make sense
- loyalty rewards that aren’t just gimmicks
- relevant product recommendations (not spam)
- good post-purchase experience, not just pre-purchase hype
- products that naturally fit into a routine

It feels like the shift that should happen is moving from:

“How do we get this customer to buy once?”

to

“Why would this customer keep coming back here instead of anywhere else?”

Curious if others notice this too, especially in beauty and skincare.

What do you think about this?

I recently compared two major enterprise ecommerce platforms and figured it’s worth sharing here since this comes up a lot when teams outgrow Shopify-like setups or move into enterprise builds.

Both are solid. But they’re built for very different types of companies.

Adobe Commerce

More of a traditional enterprise platform with a lot baked in from day one.

What it does well:

- Built-in ecommerce features (catalog, promotions, checkout, CMS tools)
- Faster setup compared to composable stacks
Easier for non-technical teams to operate day-to-day
- Large ecosystem and community support
- Strong integration within the Adobe ecosystem

Trade-offs:

- Can get heavy as complexity grows
- Scaling often requires careful performance tuning
- Less architectural flexibility than headless setups
- Costs tend to scale with GMV and order volume

Best fit:

Teams that want a strong “all-in-one” system without building everything from scratch.

Commercetools

Commercetools is basically the opposite philosophy: build everything via APIs and compose your own stack.

What it does well:

- Extremely flexible and modular architecture
- Scales cleanly since everything is service-based
- Great for composable commerce setups
- Lets you plug in best-of-breed tools for each function
- Strong enterprise-grade security and compliance

Trade-offs:

- Requires strong engineering resources
- No real plug-and-play experience
- Longer initial setup time
- Higher dependency on dev team for ongoing changes

Best fit:

Companies with mature engineering teams building long-term composable ecosystems.

What’s the difference?

Adobe = “Give me everything in one system”

Commercetools = “Let me build exactly what I want”

Neither is better universally, it really depends on how your org operates internally.

Our take

If speed and structure matter most, then go for Adobe Commerce.

If flexibility and long-term composability matter most, then Commercetools is for you.

Most teams don’t fail because of the platform, rather because they pick one that doesn’t match their internal capability level.

I’m curious how others here approach this. Have you actually moved from a monolithic setup like Adobe Commerce to a headless stack like Commercetools (or the other way around)?

What surprised you most (good or bad) after making the switch?

A recent ecommerce study found something interesting:

- 83.4% of retailers and 96% of brands believe AI will significantly influence purchasing behavior.
- Yet only 12% of retailers are fully confident their product data is ready for AI-driven commerce.
- Among brand manufacturers, that number is 0%.

As product discovery shifts from traditional search results to AI recommendations, product content is becoming much more than an SEO asset.

AI tools need to understand:
- What your product does
- Who it's for
- Why someone should buy it
- How it compares to alternatives

If your product pages are vague, poorly structured, or missing key information, AI may struggle to recommend them.

What's interesting is that product content creation and optimization is now the #1 AI investment area for both retailers and brands.

For those running ecommerce stores:

Have you noticed any traffic changes from AI search tools like ChatGPT, Gemini, Perplexity, or Google's AI Overviews?

And are you actively changing your product descriptions/content strategy to make products easier for AI to understand?

Curious to hear what others are seeing.

For the past year, I’ve seen countless discussions about AI search, AI Overviews, Gemini, ChatGPT shopping recommendations, conversational commerce, and what all of this means for brands.

But one of the biggest problems has always been this:
Nobody really knew how to measure success.

If your product appeared in an AI Overview, was recommended by Gemini, or surfaced through an AI-powered shopping journey, there wasn’t much visibility into why it happened or how often it happened.

That seems to be changing.

Google has announced a new AI Performance Insights feature for Merchant Center that will reportedly show brands:

- Share of voice in AI experiences
- Product attribute insights
- Product search term insights

Shopping funnel performance across AI-driven journeys
In other words, Google is starting to give brands actual data about how products are discovered through AI-powered experiences.

To me, this feels like a bigger deal than most people realize.
For years, SEO was built around Rankings, Impressions, Clicks, Keywords and CTR.

Now we’re entering a world where users don’t necessarily search in the traditional sense.

Instead of typing:
“best running shoes for flat feet”

Someone might ask:
“I’m training for a marathon and need comfortable running shoes under $150 that won’t aggravate flat feet. What would you recommend?”

The AI returns answers.

That completely changes how brands need to think about visibility.

What’s particularly interesting is that Google appears to be emphasizing product attributes as a major ranking factor inside AI experiences.

Which makes me wonder:

Have we spent the last decade obsessing over keywords while underestimating structured product data?

Because if AI systems are selecting products based on contextual understanding rather than exact keyword matching, then complete and accurate product information may become one of the biggest competitive advantages in e-commerce.

Another thing I find fascinating is the “share of voice” metric.

Brands are already tracking:
- Organic share of voice
- Paid share of voice
- Social share of voice

Now we’ll potentially have AI share of voice.

That sounds like an entirely new marketing KPI.
And if every retailer suddenly gets access to these insights, competition could get very interesting very quickly.

The brands that have spent years investing in clean product feeds, structured data, detailed product information, and strong catalog management might suddenly find themselves with a huge head start.

Meanwhile, brands relying on thin product descriptions and generic manufacturer copy could be in trouble.

My biggest question for everyone here:

Do you think AI product discovery will eventually become more important than traditional search rankings?

I came across an interesting warning from a UK logistics company that predicts parcel volumes could jump 15–25% in the weeks leading up to the 2026 FIFA World Cup, with some fulfilment centers expecting spikes above 30%.

What caught my attention wasn’t the prediction itself, but the argument they’re making:

A lot of e-commerce brands spend months planning campaigns, ads, influencer partnerships, email sequences, and promotions… but barely spend any time stress-testing the operational side of the business.

And honestly, they’re probably right.

Everyone talks about selling more. Very few people talk about what happens after the sale.

Think about how people actually shop during major sporting events:

- Last-minute TV upgrades
- Sound systems
- BBQ equipment
- Outdoor furniture
- Food and drink bundles
- Fan merchandise
- Party supplies
- Themed gifts

Most of these purchases are impulsive and time-sensitive.
Someone decides on Thursday they’re hosting friends on Friday night and suddenly wants next-day delivery. If that order arrives three days late, you’ve lost a customer no matter how good your marketing was.

One quote from the article stood out:

“A 200% increase in orders you can’t ship is worse than a 50% increase you can.”

That’s something I think a lot of founders learn the hard way.

I’ve seen brands celebrate record sales days on social media only to spend the next week dealing with:
- Delayed shipments
- Stock inaccuracies
- Customer support backlogs
- Carrier issues
- Refund requests
- Negative reviews

The other thing many people forget is returns.

If apparel, electronics, and event-related purchases spike during the World Cup, returns usually spike shortly afterward too. Everyone plans for the sales surge. Few plan for the reverse logistics nightmare that can follow.

So I’m curious:

For those running e-commerce stores, agencies, fulfilment operations, or logistics businesses:

1. Have you ever been caught off guard by a sudden demand spike?
2. What broke first in your operation? Inventory? Warehouse capacity? Customer support? Shipping carriers? Returns processing?

And if you’re preparing for the World Cup, Black Friday, or any other major sales event this year, what are you doing differently compared to previous years?

I’d be especially interested to hear from people who have gone through a situation where sales exploded but fulfilment couldn’t keep up.

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Reddit made its native Shopify integration globally available this week. It had been in alpha since early 2026 and is now open to every Shopify merchant worldwide, for free, through the Shopify App Store.

Three things it does:

• Connects your Reddit Ads account to your Shopify store in one authorization flow, no developer needed
• Installs the Reddit pixel automatically, no code, no touching your theme files
• Syncs your full product catalog including live pricing, images, descriptions, and inventory levels, and keeps it updated automatically

Once that is done you can run Dynamic Product Ads, which serve users the specific products from your catalog they already looked at. Retargeting, but native to Reddit.

The performance data

TransUnion ran a marketing mix model meta-analysis covering January 2023 through December 2025 across retail advertisers. A few numbers worth knowing:

In North America, Reddit delivered more than 2x the incremental ROAS versus the media plan average, at $12.52 per dollar spent. That is incremental ROAS, meaning the lift attributable specifically to Reddit, not blended with organic.

In EMEA, the average ROAS for retail advertisers was 7x. Over the same period, EMEA retail advertisers increased their Reddit spend by over 8x, while other paid social in the region lost 6% of advertiser investment in aggregate.

There is also a documented halo effect where 13% of Reddit's performance impact lifts the effectiveness of other channels in the media mix.

The results of the brand tests

Two Shopify brands tested the integration before global launch:

Ethnotek, an artisan backpack and accessories brand, used DPA retargeting and hit 4x ROAS versus their standard conversion campaigns, with cost per acquisition 40% below benchmark.

Under 5'10, an apparel brand, ran the same retargeting approach and came out at 7.7x ROAS versus standard conversion campaigns.

Worth being honest here: both figures are measured against Reddit's own standard conversion campaigns, not against a universal zero baseline. So the numbers reflect the uplift from DPA plus retargeting specifically. Still, that is a significant gap.

Why the audience is different

Reddit users are 62% more likely than the average American to be daily shoppers according to Morning Consult data. But more importantly, they are research-heavy buyers. Someone in r/ultralight is already three threads deep into gear comparisons before an ad ever reaches them. You are not interrupting their scroll. You are catching them mid-decision.

That dynamic works especially well for categories that have active subreddit communities: tech, outdoor, fitness, gaming, fashion, home goods, anything where people genuinely discuss and debate products before buying.

The honest caveats

The TransUnion study was commissioned by Reddit, so it is not independent third-party research. The meta-analysis blends multiple unnamed brands, so individual results will vary based on category, creative, targeting, and baseline brand awareness. ROAS can also compress as more advertisers enter the same auctions and competition rises.

Reddit also does not have Meta's volume. If your product has no natural community on the platform, the audience pool will be small and the numbers above probably will not transfer.

What this changes practically

Before this integration, setting up Reddit DPA required manual pixel implementation and building out a product feed. Not impossible, but enough friction that a lot of smaller merchants skipped it. That barrier is now gone. Free setup, automatic catalog sync, codeless pixel.

For any Shopify brand in a category with Reddit communities, there is no longer a cost or complexity reason to avoid testing it. The question at this point is just whether your category fits the platform.

Has anyone else noticed a major drop in checkout conversions this week?

On May 27, Shopify rolled out a checkout update without any advance notice to merchants. Instead of the usual straightforward checkout flow, customers are now presented with two options:

🟢 Pay as guest

⚪ Pay and save my info

According to several merchants, that extra decision point is creating confusion and causing significant checkout abandonment.

One UK-based merchant we spoke with reported:

• Conversion rate dropped by 50% in the UK

• Checkout drop-off doubled

• No warning, no changelog entry, and no option to opt out

The biggest concern is that merchants couldn't disable it, customize it, or even prepare for it.

For stores with older demographics, the impact appears to be even worse. One merchant said customers who previously saw a simple "Pay Now" experience now have to stop and figure out the difference between the two options before completing a purchase.

Many merchants believe the change is primarily designed to increase adoption of Shopify's Shop ecosystem and collect more customer accounts.

A few questions for other store owners:

- Have you seen any unusual checkout conversion drops since May 27?
- What country are you selling in?
- Are you using Shopify Payments or a third-party processor?
- Do you think Shopify should allow merchants to opt out of checkout experiments like this?

Would be interested to hear if this is affecting more stores or if the impact varies by niche and customer demographic.