Why Customs and Returns Will Decide Growth

Cross-border e-commerce is becoming more complex in 2026 – and on multiple levels. From 1 July 2026, the de minimis rule which has allowed goods valued under €150 to enter the EU duty-free comes to an end. Going forward, a customs fee of €3 per item category will apply – more precisely, per tariff classification (HS code). A parcel containing products with different HS codes will incur the fee multiple times. From November 2026, an additional handling fee of €2 per consignment could apply.

The primary payment obligation lies with the seller, not the end customer, stresses our partner Spring Global Delivery Solutions, a specialist cross-border shipping provider. Under DDP (Delivered Duty Paid), the merchant covers the fee and delivers a fully costed final price. Under DAP (Delivered at Place), the buyer pays upon receipt – This can lead to refused deliveries and higher return rates. For merchants, DDP is the better choice – but it requires adapting pricing models and checkout systems.

“The new rule does not only hit the large Chinese marketplaces that have systematically benefited from the duty-free threshold”, says Stefan Böhler, Country Managing Director Spring GDS Germany: “It affects every merchant shipping from outside the EU into the EU – regardless of product category, country of origin, or order value.”

What merchants should address now:

●       Adapt checkout: customs fees must be shown as a separate line item – not buried in a generic “Taxes & Fees” field.
●       Rethink Incoterms: DDP protects the customer experience; DAP shifts the risk to the end customer – with consequences for conversion and return rates.
●       Review fulfilment location: a fulfilment hub within the EU is becoming an increasingly attractive option for merchants shipping regularly into the EU.
●       Standardise customs processes: paperless customs clearance and complete HS code datasets are an operational prerequisite, not an option.

Who is most affected

All merchants shipping from outside the EU into the EU are affected. The UK market is particularly relevant: since Brexit, shipments from Great Britain into the EU are treated as third-country imports. The new fee hits UK merchants directly and without exception, on top of the Brexit-related customs processes already in place. The same applies to merchants from Switzerland and Norway. The logical response for many: demand for fulfilment capacity within the EU is rising.

Cross-border scaling: where the real complexity lies

The customs rule is a symptom of a larger challenge. What is manageable when shipping to one or two markets quickly becomes an operational burden with serious internationalisation. Consider different carriers, different customs requirements, different consumer expectations.

Three operational prerequisites must be in place before cross-border growth becomes predictable:

●       Right carrier selection: access to a broad network with local last-mile carriers and out-of-home delivery options is essential.
●       Shop setup adapted: local specifics around checkout, payment methods, and customs communication must be clarified before go-live – not after.
●       Include local marketplaces: often the fastest route to becoming visible in a new market and building initial volume.

As Stefan Böhler from Spring GDS puts it: “As soon as brands internationalise, fulfilment complexity increases sharply. Only those who invest early in standardisation, integrated end-to-end processes and a flexible international warehousing strategy can scale successfully.”

Specialist providers like Spring GDS address this complexity with automated routing systems that select the right carrier for each parcel – based on format, weight, destination and service level.

International returns: cost factor or growth lever?

Many carriers treat returns as an optional add-on – more expensive than outbound shipping, negotiated separately, often handled by a different provider. For the end customer, this means uncertainty. And uncertainty costs conversion – frequently already at checkout, before the first parcel is even shipped.

What is structurally missing is a closed loop: outbound and return as an integrated, transparent unit – at the same price, through the same provider, without any break in the customer experience.

Stefan Böhler: “Customers only shop cross-border when they know that returns are easy, transparent and fast. Once this hurdle is removed, not only trust increases – so does the willingness to buy in new markets. For merchants, this means: fewer abandoned purchases and significantly faster scaling in cross-border business.”

What a closed-loop solution looks like in practice: label-in-the-box as standard, paperless return without customs forms for the end customer, transparent tracking on the return journey, and fast refunds as a prerequisite for repeat purchases.

The UK special case

For shipments to and from Great Britain, there is an additional requirement: returns are only seamless when the original outbound shipment was handled through a fully customs-compliant solution. Both directions require separate customs processes.

Many cross-border carriers offer outbound or return – rarely both as a closed, customs-compliant solution. Where this works, the process runs paperlessly on the basis of a single unified dataset. For merchants who regard the UK as a relevant market, this is the prerequisite for a returns-capable cross-border strategy.

Key Learnings

Cross-border e-commerce has not become easier in 2026. The real decisions are not made at the customs fee stage, but in fulfilment setup, carrier selection, and returns management. Those who think across all three dimensions before volume scales have a structural advantage.

●       From 1 July 2026: €3 customs fee per item category (HS code) on all e-commerce imports from third countries under €150. From November 2026, an additional €2 handling fee per consignment may apply.
●       The payment obligation lies with the seller. DDP protects the customer experience; DAP increases abandonment and returns risk.
●       UK, Switzerland and Norway are directly affected as non-EU countries – for UK merchants, the new rule layers on top of existing Brexit customs processes.
●       Cart abandonment frequently results from lack of transparency at checkout – customs fees must be shown as a separate line item.
●       Cross-border scaling requires a broad carrier network, locally adapted shop setup, and strategic use of local marketplaces.
●       Returns are a conversion factor: a closed loop – outbound and return from one provider at the same price – reduces abandonment and increases repeat purchase rates.
●       For UK: a fully customs-compliant outbound solution is a prerequisite for seamless returns – both directions must be covered from a customs perspective.

Der Beitrag Cross Border Logistics in 2026 erschien zuerst auf Marketplace Universe.

The optimization gap

Listings, ad spend, pricing, promotions — these are the areas most marketplace managers tune regularly. What tends to get far less attention is the inbox.

eDesk, a customer support platform built specifically for e-commerce sellers, handles more than 3 million customer conversations per month across thousands of seller accounts. One of the most consistent patterns they observe across that customer base is the gap between how much sellers invest in the commercial side of their operations and how little attention the support side receives — right until something breaks.

“Most marketplace sellers optimize for everything except inbox,” noted Gareth Cummings, CEO of eDesk, during the webinar How to Win More Sales on Marketplaces Without Losing Revenue in the Inbox, hosted by Marketplace Universe. “Ad spend, listings, pricing — these get tuned every week. Inbox operations? Often untouched.”

As a seller scales across more marketplaces and drives more traffic, inbox volume rises. Service level agreements (SLAs) start slipping. Message workflows that worked for three channels stop working for ten. Response consistency degrades. The compounding effect of those operational failures shows up directly in seller performance metrics — and that is where the revenue impact becomes hard to ignore.

Marketplace Universe Insight: The median eDesk seller operates across 17 channels (marketplace × country). 85% of sellers on the platform operate between 3 and 30 channels simultaneously. At that scale, inbox management is not a minor operational detail — it is a core business function.

Why seller performance is an operational question

Every major marketplace — Amazon, Zalando, bol, eBay, Kaufland and others — maintains a seller performance score. The exact methodology varies, but the inputs are remarkably consistent: response times, SLA compliance, review scores, claims and escalation rates.

These scores directly determine a seller’s visibility on the platform. Miss SLAs consistently and products rank lower. Miss them badly enough and a seller gets delisted entirely — with products sitting in fulfillment, no longer reachable by the customers they already paid to acquire.

Public holidays, weekends, and time zone differences can easily cause an SLA to be missed without a single agent making an error. Getting back on track requires actively demonstrating to the marketplace that the problem has been fixed. Meanwhile, the products are offline.

Pre-sales: the most underrated conversion driver

Much of the discussion around marketplace customer service focuses on post-purchase: returns, tracking queries, complaints. The pre-purchase window gets less attention — and according to eDesk’s platform data, this is where the biggest conversion opportunity sits.

Pre-sale questions look mundane: “Will this arrive before Friday?” “Is this compatible with X?” “Do you ship to Austria?” But buyers asking these questions are close to a purchasing decision. They are high-intent. They need an answer, not a follow-up.

eDesk’s data shows that sellers who respond to pre-sale questions within 15 minutes see a 40 to 50 percent conversion uplift compared to those who respond the same day or later.

“You’re in the mode to buy. It could be the evening or the weekend. If you can answer quickly, typically you’ll make that purchase. If it comes back the next day, you might have moved on. You’ve lost that sense of urgency.”
— Gareth Cummings, CEO, eDesk

Marketplace Universe Insight: 92% of webinar attendees said same-day response was their current standard for pre-sale questions. According to eDesk’s platform data, same-day is not fast enough to capture the conversion uplift — the threshold that makes a material difference is 15 minutes.

Hitting that window consistently across 10, 20, or 30 channels simultaneously is not straightforward. That is where prioritization logic and workflow structure become operationally critical.

The Pertemba case: what scaling to 160 marketplaces actually required

Pertemba is what Irene Epp, its Operations Support Manager, describes as “a bit of a unicorn.” The company does not sell its own branded products — it brings brands onto e-commerce marketplaces and manages the entire selling and service operation on their behalf, including all customer communications across all channels and languages.

The numbers alone tell a story:

• 160 active marketplace channels
• 1,000+ customer emails per day
• ~18 people in the entire customer service team

The operation started on Gmail, with messages processed sequentially and routing done by hand. Scaling to the current scope was not possible on that model.

“If you would need to log in and out of marketplaces — even if it takes only a minute — a minute times 130 is already a lot of time gone. Really not possible to do.” — Irene Epp, as pointed out on Marketplace Universe’s podcast Let’s Talk Marketplace, episode 145 (#LTM145)

Want to know more? Then check out episode 145 of our podcast “Let’s talk Marketplace”! In it, Irene Epp and Garth Cummings dive deeper into automation and how to handle channel expansion while keeping customers happy:

The shift to eDesk’s platform changed the structural logic entirely. SLA timers are set at the channel level, pre-sale tickets can be filtered into a dedicated queue, and AI-assisted translation handles incoming and outgoing messages across all languages — eliminating the need for language-specific hires at scale.

“We can prioritize our marketplaces on need. We can prioritize emails on need. For pre-sale questions, we set a filter and a standard SLA — I want it answered within an hour, that’s the maximum. With eDesk, changing the SLAs for specific tickets means they pop up on top for you,” Epp explained during the webinar.

What actually changed operationally:

Marketplace Universe Insight: Around 90% of all incoming queries fall into a handful of standard categories — where’s my order, I want to cancel, what’s my tracking number, how do I return this. Automation handles the volume. Human agents handle everything else.

Multi-lingual support is no longer optional

For European marketplace sellers, multi-lingual support is a structural requirement. Marketplaces in Germany, France, the Netherlands, Spain, Poland and elsewhere expect — and in many cases require — responses in the local language. Getting the tone wrong carries real consequences — Pertemba once had a strongly negative customer reaction simply from an automated message using the informal “du” instead of the formal “Sie” in German.

The Japanese market adds another layer entirely. Epp described receiving what read in translation as a polite message — only for Japanese-speaking colleagues to point out the customer was actually furious. “What they put in writing is not always what they are saying to you. For a Japanese person, they are so polite when they are mad. As a European or English speaker, you wouldn’t pick up on that culture.”

The practical solution at Pertemba is to cross-train all agents across all marketplaces and let AI-assisted translation handle the language layer in both directions.

“Even if one agent is sick or on holiday, we don’t have that hole and the scramble to not hit the SLA because we don’t have that skill in our team. That’s why we could expand to 160 channels — because yes, we have some Spanish speakers, Japanese speakers, German and French. But that’s it. We don’t need to hire for every language.”
— Irene Epp, Let’s Talk Marketplace #LTM145

Customer support as a business intelligence function

Irene Epp describes the customer service team as “the watchdog of the company” — the part of the business where problems surface first. A SKU with unusually high return rates, a carrier struggling with deliveries in a specific region, customers in a given market suddenly asking the same question: all of it arrives in the inbox before it shows up anywhere else.

Cummings offered a concrete example from eDesk’s customer base. A seller had a top-performing SKU by sales volume — but when they surfaced the support data, the picture shifted: that product was generating high returns, negative reviews, and suppressed rankings. The seller had been driving sales for a product that was quietly undermining their ability to sell on the platform.

“If you went and spoke to your customer support team today and asked them what are the top three things that are happening, they will tell you straight away — they’re dealing with this every day. And you probably will be surprised in terms of what you would hear,” Cummings noted during the webinar.

Scaling support without breaking the team

The operational argument for scalable tooling is not just efficiency — it is retention. Every agent who leaves takes knowledge of workflows, marketplace rules, escalation paths, and communication patterns with them.

“You can set your limits as high as you want, but you will find you’re replacing one agent after another. Because at some point they either burn out or they’ve had enough. It’s a stressful job. You get abuse. It’s not even the best-paid one. Keeping your team happy is very important — because every team member that leaves is knowledge that leaves.”
— Irene Epp, Marketplace Universe webinar

Epp’s model is to keep the team at around 80–85% capacity for most of the year, preserving headroom to absorb peak periods. At Pertemba, the core team has remained stable for three years across continued channel growth — a result she attributes in part to tooling that removes a significant portion of the manual cognitive load from agents.

A structured internal knowledge base, integrated into eDesk and searchable by any agent covering an unfamiliar channel, sits at the center of that stability. The more comprehensive it is, the more effectively both the team and the platform’s AI automation can draw on it.

Where to start: the one metric that tells you everything

Both Cummings and Epp converge on a simple starting point in the Let’s Talk Marketplace podcast: measure your actual response times.

“You’d be surprised sometimes — if you’re not tracking it and then you discover it can be days or longer. So that’s the first metric you should look at: how quickly are we getting back to our customers. And that will tell you a lot,” Cummings said.

Response time is the metric that reveals whether the structure is working. Once that is visible, the path toward fixing it becomes clear.

Key Learnings

• SLA compliance is a revenue question. Response times, reviews, and escalation handling feed directly into marketplace visibility scores — and missing SLAs due to public holidays or weekends alone can take products offline. Leaving support operations unstructured while investing in listings and ads creates a compounding risk.
• Around 90% of marketplace support queries are standard and automatable — order status, cancellations, tracking, returns. Automation handles the volume; human agents handle everything else.
• Responding to pre-sale questions within 15 minutes can drive a 40–50% conversion uplift, according to eDesk’s platform data. Same-day response — the current standard for most sellers — is not fast enough.
• Multi-lingual support is a structural requirement in Europe. AI-assisted translation, properly configured, allows teams to cover far more markets than language-specific headcount would permit.
• Customer support is business intelligence. When the team has enough capacity to pay attention, the inbox surfaces product problems, carrier failures, and assortment issues before they show up anywhere else in the business.
• Start by measuring response time. If actual response times across channels are not being tracked today, that is the first metric to surface. It will tell you more than almost anything else about the state of the support operation.

Missed the live webinar? Watch the full recording here. For the full Pertemba story in their own words, listen to the Let’s Talk Marketplace podcast episode Automation at Scale: How to handle 1,000+ Daily Support Tickets #LTM145.

eDesk is a customer support platform built for e-commerce sellers, handling more than 3 million customer conversations monthly across thousands of seller accounts globally. Learn more or start a free two-week trial at edesk.com.

15.06.2026 – Written by Ricarda Eichler, Journalist and Author for OHN

Der Beitrag Why Your Marketplace Inbox Is Costing You More Than You Think erschien zuerst auf Marketplace Universe.

German e-commerce is back on the (cautious) growth track 

After the difficult post-pandemic years, German e-commerce has found its rhythm again. According to the new HDE Online Monitor 2026, online retail sales in Germany grew by 3.9% in 2025, reaching €92.3 billion net. That follows growth of 3.8% in 2024 and marks a further step away from the correction phase of 2022 and 2023.

For 2026, the HDE expects the market to grow by another 4.3%, reaching €96.3 billion. That is not a return to pandemic-style acceleration. But it is a steady recovery – and probably the healthier kind. Since 2020, German online sales have increased by €19.3 billion.

The more interesting question is where this growth comes from. Last year, the headline was simple: marketplaces drove the entire growth. This year, the story is more nuanced. Marketplaces are still ahead, but the gap to other online formats has narrowed.

All categories are growing again

For the second year in a row, all major online retail categories recorded growth. The striking part: growth rates have moved closer together. The weak patches of previous years, especially in categories like fashion, seem to be largely over.

The clear exception is FMCG. Online sales of fast-moving consumer goods grew by 10.4% in 2025 – more than 2.5 times the market average. In 2024, FMCG was already the fastest-growing category with 7.3%. This year, the category pulled even further ahead.

Other categories grew at a much more moderate pace: Health & Wellness by 4.9%, Jewelry & Watches by 3.1%, Consumer Electronics and Leisure & Hobby by 2.9% each, Fashion & Accessories by 2.8%, Office Supplies by 2.4%, DIY & Garden by 2.1%, and Home & Living by 1.8%.

Fashion and Electronics remain Germany’s two largest online categories. Fashion & Accessories reached €21.2 billion, accounting for 22.9% of total online sales. Consumer Electronics followed with €19.7 billion, or 21.3% of the market. Together, the two categories still make up 44.2% of German online retail – but their combined share is slowly declining. In 2024, it stood at 44.7%.

FMCG is the category to watch. Its share of total online sales rose from 13.7% to 14.5%, reaching €13.4 billion. The online penetration is still low, but the direction is clear: groceries, drugstore products and everyday consumer goods are becoming a much more important part of German e-commerce.

Marketplaces still lead – but they no longer own the whole growth story

In 2024, the message was brutal for many retailers: all online growth came from marketplaces, while other online channels declined. In 2025, the picture looks less one-sided.

Sales via marketplaces and platforms grew by 5.4%. That is still above the total online market growth of 3.9%. But other formats also grew: providers with online DNA by 3.9%, stationary retailers by 4.0%, and manufacturers by 3.8%.

So yes, marketplaces remain the strongest growth format. But the simplistic “marketplaces win, everyone else loses” narrative no longer works. Own shops, retailer shops and manufacturer-led models are not dead. They just need a much clearer role: brand experience, customer relationship, loyalty, better margins, exclusive assortments – something beyond simply listing products online.

Amazon gains share again

Germany remains an Amazon market.

According to the HDE Online Monitor 2026, Amazon.de accounted for 63.3% of German online sales in 2025, up from 62.7% in 2024. Amazon’s own retail business remained stable at 17.2%, while the Amazon marketplace grew from 45.5% to 46.1%.

That may sound like a small increase. It is not. When a player already controls more than 60% of the market, even half a percentage point matters.

Other marketplaces also gained slightly. The combined share of marketplaces outside Amazon – including eBay, Zalando/About You, Otto, TikTok Shop and specialist platforms such as ManoMano, Moebel.de or Chrono24- rose from 10.6% to 10.8%. Overall, marketplaces accounted for 56.7% of German online sales in 2025.

The uncomfortable truth remains: Germany is not a highly fragmented marketplace market. It is an Amazon-dominated market with a relevant, but much smaller, platform landscape around it.

Temu and Shein are big – but not as big as you think

Temu and Shein are now structurally relevant in Germany. The HDE estimates their combined German sales at around €4.7 billion in 2025, up from roughly €3.0 billion in 2024. That equals about 5% of total German online retail.

That is impressive. But it is not market takeover.

The two platforms are large enough to put pressure on pricing, assortment expectations and customer acquisition. But they are still far from Amazon’s scale. The industry sometimes talks about Temu and Shein as if they had already rewritten the entire German market. The numbers are more sober: they are a serious force, not the whole market.

Their user base is growing, though. The HDE estimates that 16.0 million people in Germany bought from Temu and/or Shein in 2025, up from 14.4 million in 2024. Average order value rose sharply from €24.95 to €34.15, while order frequency increased slightly to 8.51 orders per year.

The reputation problem remains. Many non-buyers still associate Temu with poor product quality. But among actual buyers, the picture is more positive. That is the real risk for established players: Temu does not need to convince everyone. It only needs a large enough group to keep buying frequently.

TikTok Shop starts small – but not quietly

TikTok Shop is still tiny compared with Amazon, Zalando or even Temu and Shein. But the early numbers are worth watching.

Half a year after launch, 52% of German internet users already knew TikTok Shop, and 9% had already bought there. The top categories were Clothing & Accessories, Cosmetics & Care, Sports & Leisure, Consumer Electronics, and Drinks & Snacks. Average spending per purchase was €59, and PwC data cited by the HDE estimates TikTok Shop’s German 2025 sales at around €220 million.

That does not make TikTok Shop a must-have channel for every brand yet. But ignoring it would be lazy. Especially in categories where impulse, creators, entertainment and low-friction buying meet, TikTok Shop is becoming part of the platform conversation faster than many expected.

Amazon Haul brings the low-price fight into Amazon’s own ecosystem

The low-price battle is no longer just happening on Temu, Shein or AliExpress. Amazon is moving too.

Amazon Haul launched in Germany in June 2025. Four months later, it already had 47% awareness, 13% of respondents had purchased via the concept, and 59% of buyers ordered at least once a month.

This matters because Amazon Haul brings ultra-low-price mechanics into the most powerful commerce ecosystem in Germany. For brands and sellers, that means the pressure from low-price models is no longer somewhere else. It is moving closer to the mainstream.

Cross-border shopping keeps rising

German consumers are also becoming more comfortable buying from abroad. The share of online shoppers who say they consciously order from foreign providers increased from 24% to 26%. China remains by far the most important source country: 49% of those who bought abroad ordered from China.

This is one of the reasons why national market logic is becoming weaker. German brands and retailers are not only competing with German retailers anymore. They are competing with global supply chains, platform-funded reach, aggressive pricing and increasingly frictionless cross-border delivery.

Social media and AI are moving into the shopping journey

The customer journey is becoming less predictable. Social media is not just a place for inspiration anymore. It triggers purchases. On average, 13% of German internet users have bought a product after seeing it in a person’s social media post. Among 30- to 39-year-olds, the share reaches 23%.

AI is moving even faster into product research. 35% of consumers already use AI chatbots when researching products, mainly to compare product features, quality and prices.

For brands, this is more than a marketing side note. Product data, reviews, trust signals, price logic and content quality are becoming machine-readable sales assets. If shoppers start asking AI tools what to buy, where to buy it and which shop to trust, visibility will no longer depend only on Amazon search, Google rankings or marketplace filters.

Second-hand is now a €10.5 billion online market

Second-hand is still excluded from the HDE’s main online sales figure because the report focuses on new goods. But as a market, it has become too large to treat as a niche.

Online second-hand sales reached €10.5 billion in 2025, up 5.3% from the previous year. Since 2019, the market has grown from €5.7 billion, with a CAGR of 10.6%.

The strongest segments are Books, Fashion & Accessories and Consumer Electronics. What started as a sustainability story is increasingly also a price story. Consumers buy second-hand not only because it feels responsible, but because it helps reduce spending. That makes the market relevant far beyond vintage fashion or refurbished electronics.

Conclusion: Germany’s online market is stable – but the rules are shifting

The German online market is growing again. Not spectacularly, but steadily. That alone is good news.

But the real story is not the growth rate. It is the changing structure underneath.

Marketplaces remain the backbone of German e-commerce, and Amazon has strengthened its already dominant position. But the market is no longer as one-sided as last year’s figures suggested. Other formats are growing again, FMCG is becoming a stronger online category, second-hand is reaching serious scale, and low-price platforms are forcing everyone to rethink price perception and customer expectations.

At the same time, TikTok Shop, social commerce and AI-driven product research are changing how products are discovered and evaluated. The next phase of German e-commerce will not be won only through more listings, more ad spend or more marketplace presence. It will be won through better execution: sharper channel roles, cleaner data, stronger pricing discipline, operational excellence and a realistic understanding of where customers actually make decisions.

Germany is not in an e-commerce boom. But it is entering a more complex, more platform-driven and more competitive phase of online retail.

Key Learnings

• German e-commerce is growing steadily again: Online sales increased by 3.9% to €92.3 billion in 2025, with 4.3% growth forecast for 2026.
• FMCG is the strongest growth category: With 10.4% growth, FMCG is pulling far ahead of the market average, even though online penetration remains low.
• Marketplaces remain dominant, but the gap is narrowing: Marketplace sales grew by 5.4%, still above market average, but other online formats are growing again too.
• Amazon is still the central force in Germany: Amazon.de increased its share to 63.3% of German online sales, driven mainly by its marketplace business.
• Temu and Shein are serious, not all-powerful: Their estimated combined market share reached around 5%, making them releva- but not dominant.
• TikTok Shop and Amazon Haul show where the pressure is moving: Social commerce and ultra-low-price mechanics are entering the mainstream faster than many brands expected.
• Second-hand has become a structural market: At €10.5 billion, online second-hand is no longer a side topic.
• AI will reshape product discovery: If consumers use AI tools for product research, brands need better data, clearer trust signals and more machine-readable product content.

If you’d like to learn more about TikTok Shop, check out our in-depth guide How to Succeed on TikTok Shop or our podcast Just Being on TikTok Shop Is Not Enough: Philips’ 2-Year Playbook for Europe #LTM153

Enjoyed this article? The Marketplace Universe Weekly is our free newsletter – every Monday, the latest marketplace news, platform updates, our newest posts, and the insights that matter, delivered straight to your inbox. So you never miss a thing. Subscribe here: https://marketplace-universe.com/newsletter/

Der Beitrag The German Online Market 2026 erschien zuerst auf Marketplace Universe.

What Agentic Commerce Actually Is (and Isn’t)

Agentic commerce describes a model in which AI agents act autonomously, or semi-autonomously, on behalf of consumers across the full commerce journey: product discovery, comparison, negotiation, checkout, and post-purchase management. The user sets a goal. The agent executes.

Imagine a shopper who needs new running shoes. They tell their AI assistant: best options under €150, next-day delivery to Germany, size 43. By the time they finish their coffee, the agent has compared inventory across platforms, verified stock and pricing, applied any loyalty discounts, and placed the order — without the shopper ever visiting a brand’s website or marketplace listing.

That scenario is no longer hypothetical. The question now is whether your brand is ready to be found by AI agents when it happens.

The Numbers: How Fast This Is Moving

The commercetools Agentic Commerce Radar, published in May 2026, and supporting data from multiple analyst sources tell a consistent story. Consumer adoption at the discovery layer is already mainstream. The transaction layer is beginning to follow.

Consumer adoption — where we are today:

According to Riskified consumer research, compiled in the commercetools radar:

• 73% of consumers are already using AI in their shopping journey — for product ideas (45%), review summaries (37%), and price comparison (32%)
• 60% of shoppers expect to use AI agents for purchases within the next 12 months (Martech)
• 44% of users who have tried AI-powered search say it has become their primary and preferred source for internet searching (McKinsey)
• But only 13% have actually completed a purchase after being referred by an AI assistant — with 70% saying they are at least somewhat comfortable with an agent making purchases on their behalf (Riskified)

That last gap — between comfort and actual completion — is the defining dynamic of agentic commerce right now. The majority of consumers are using AI for research and discovery. Very few are completing purchases through agents yet. The infrastructure and habits needed for full transaction delegation are forming, but they are not there.

The downstream traffic and conversion impact:

According to Adobe Analytics data reported by Digital Commerce 360, AI-driven traffic to US retail sites surged 805% year-over-year on Black Friday 2025. More recent Adobe data from Q1 2026 shows that AI-referred shoppers now convert 42% better than non-AI traffic — a complete reversal from a year prior, when they converted 38% worse. Traditional search engine volume, meanwhile, is projected to decline 25% by 2026 as consumers shift to GenAI channels, according to Gartner.

Where the market is heading:

A Morgan Stanley forecast estimates that nearly 50% of online shoppers will use AI agents by 2030, accounting for approximately 25% of their spending and adding around $115 billion to the US e-commerce sector alone. For B2B, the trajectory is steeper still — Gartner projects that 90% of B2B buying will be AI agent-intermediated by 2028.

Why Consumers Are Adopting It — and What That Means for Brands

The adoption driver is not technology enthusiasm. It is genuine frustration with the existing shopping experience.

Comparison shopping across multiple platforms is tedious. Review synthesis is time-consuming. Inventory availability changes by the hour. Return policies differ by retailer. For high-frequency or research-heavy purchases, AI agents remove real friction — and consumers know it.

This matters for brands because it means the adoption curve will not reverse. The question is not whether agents will mediate more purchases, but how quickly.

Marketplace Universe Insight: When a consumer delegates their purchase decision to an AI agent, brand marketing — the campaign, the imagery, the emotional narrative — has no surface to land on. The agent does not read copy. It reads data: price, availability, delivery time, return policy, product attributes, ratings. If that data is incomplete, inconsistent, or missing from the sources agents query, the brand simply does not exist in that transaction.

The shift from the traditional sales funnel to an agent-mediated purchase does not eliminate brand relevance entirely — but it relocates where that relevance is built. It moves earlier, to the data layer, and later, to the post-purchase experience. The moment of selection increasingly belongs to the algorithm.

The Hard Limits: What’s Not Working Yet

The numbers above are real. So is the hype around them. And the hype tends to obscure the genuine structural limits that still apply in mid-2026.

Full transaction delegation remains thin. According to Riskified consumer research, 70% of consumers say they are comfortable with an AI agent making purchases on their behalf — but only 13% have actually done it. OpenAI’s Instant Checkout feature, launched in September 2025, quietly ran into this wall: users were asking plenty of shopping questions inside ChatGPT but not completing purchases. By early 2026, OpenAI had walked back the native checkout model and pivoted to a discovery-first approach, routing transactions to merchant-controlled checkout environments instead. The lesson: even where the infrastructure exists, habits and trust take time to follow.

Data fragmentation undermines agent reliability. AI agents can only act on information they trust. Inconsistent product data — different titles, attributes, and pricing across channels — creates uncertainty. Research from Rithum, referenced in commercetools’ white paper “Navigating the Agentic Commerce Era On Your Terms,” found that 75% of retail leaders say AI is advancing faster than their organizations can adopt it, and 49% of brand workflows still rely heavily on manual processes. Agents built on fragmented data produce fragmented recommendations.

The post-purchase experience is fully brand-owned — and fully exposed. An agent can surface and order a product. It cannot process a return. That interaction remains owned by the brand or retailer. Brands investing in agentic entry points while neglecting post-purchase experience are building on unstable ground.

Regulatory clarity is still forming. The EU AI Act and related consumer protection frameworks are still being interpreted in their application to autonomous commercial transactions. Consent frameworks for agent-mediated purchases are not yet standardized. European brands need to monitor this actively.

Three Protocol Standards Brands Need to Know

Protocols are the infrastructure that determines whether AI agents can find, evaluate, and transact with your products. Three distinct standards are currently live or emerging — and they are not yet converging.

These three are complementary, not competing. MCP provides the data access layer. ACP routes OpenAI/ChatGPT-adjacent transactions. UCP routes Google-adjacent transactions. In April 2026, Amazon, Meta, Microsoft, Salesforce, and Stripe all joined the UCP Tech Council — signaling that UCP is emerging as the open governance standard that major players are coalescing around.

Marketplace Universe Insight: Brands that want to be present across the full agentic landscape need to be thinking about all three. The good news: the foundation is the same for all of them — clean, structured, real-time product data. A brand that solves its data infrastructure problem is not solving it three times over. It is solving it once and becoming protocol-ready by default.

The Amazon Angle: Control, Then Integrate

Amazon’s relationship to agentic commerce is its own story — and a revealing one.

Amazon’s first move was defensive. The company blocked ChatGPT and other AI crawlers in its robots.txt file, preventing OpenAI’s agents from surfacing Amazon product listings in real time. The stated rationale: protecting against misrepresentation of automated traffic as human. The commercial logic: Amazon’s $4 billion advertising business depends on controlling who can access its product data and on what terms.

What followed suggests a strategic recalibration rather than a clean reversal. In May 2026, a job listing for a Principal Technical Program Manager to lead a dedicated 40-person agentic commerce team surfaced publicly — specifically tasked with building controlled integrations between Amazon’s marketplace and third-party AI platforms including ChatGPT. Reported by PPC.land and TechBriefly, the listing signals that Amazon is now building its own integration layer — on its own timeline, under its own commercial conditions. In April 2026, Amazon also joined the UCP Tech Council alongside Meta, Microsoft, Salesforce, and Stripe, bringing itself inside the governance structure of the open standard it had initially stood apart from.

Amazon’s “Buy for Me” feature — announced in early 2026 — takes this further: it allows Rufus, Amazon’s AI shopping assistant, to complete purchases from other brands’ websites when Amazon does not carry the product itself. Amazon is positioning itself not just as a marketplace, but as a shopping agent layer that captures purchase intent regardless of where the transaction ultimately happens.

For European brands, the implication is direct: Amazon is not absent from the agentic future. It is engineering the terms on which it participates. Brands with Amazon presence need to monitor this closely — because the data and integration requirements for Rufus-visibility may differ substantially from those for ACP or UCP.

Answer Engine Optimization: The Concrete Action Available Today

The question practitioners eventually arrive at: what can we actually do right now?

The answer may lie in Answer Engine Optimization — AEO. Because AI agents function as search engines that synthesize and act rather than list and rank, content and product data need to be structured in a way that makes them directly accessible to those systems.

As Aditya Sinha from Sanbi AI puts it: “This is the defining challenge for brands in 2026: if your data isn’t machine-readable, you don’t exist in the agentic shopping funnel.”

AEO is distinct from traditional SEO in one critical way: SEO optimizes for human click-through from a ranked list. AEO optimizes for agent comprehension and direct action. An agent does not present options for selection — it synthesizes available information and either recommends or executes. A brand not represented in the structured data sources an agent queries is simply not included.

Marketplace Universe Insight: The brands best positioned for agentic commerce are often not the largest brands, but the most data-disciplined ones. A mid-sized European outdoor brand with complete, structured, intent-rich product data will outperform a global conglomerate with a fragmented catalog in agent-mediated recommendations. That is a genuine competitive opportunity — available right now.

Key Learnings

• The consumer shift is already happening at the discovery layer. 73% of consumers use AI in their shopping journey. Traffic from AI sources to retail sites grew 805% year-over-year. The infrastructure is being built in real time.
• The agent doesn’t read your campaign. It reads your data. When an AI agent is the buyer, brand relevance is determined by the completeness and accuracy of structured product data — not by creative or messaging.
• Three protocols are emerging simultaneously: MCP, ACP, and UCP. They are complementary. A solid data foundation makes a brand protocol-ready across all three without solving the problem three times over.
• OpenAI’s Instant Checkout struggled — and the pivot is instructive. Native AI checkout didn’t convert at scale. The current model routes to merchant-controlled checkout. Post-purchase experience remains fully brand-owned, and it matters more than ever.
• Amazon’s strategy is: control first, integrate on your own terms. It blocked AI crawlers, established its own agent rules, then joined the UCP council and started building integrations. Its “Buy for Me” feature positions Amazon as a shopping agent layer across the entire web — not just its own marketplace.
• AEO is the concrete action available today. Structured, complete, machine-readable, intent-rich product data is what makes a brand reachable by AI agents. This is an ongoing data discipline, not a one-time implementation.
• Data discipline, not brand size, determines agentic visibility. The brands that will capture disproportionate share in agent-mediated commerce are the most data-disciplined ones — regardless of marketing budget.

Enjoyed this article? The Marketplace Universe Weekly is our free newsletter — every Monday, the latest marketplace news, platform updates, our newest posts, and the insights that matter, delivered straight to your inbox. So you never miss a thing. Subscribe here: https://marketplace-universe.com/newsletter/

29.05.2026 – Written by Ricarda Eichler, Journalist and Author for OHN

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When Amazon shows products that are not sold on Amazon

Amazon has been testing new models for external commerce with “Shop Direct” and “Buy for Me” for some time. It is still unclear whether or when Amazon will bring these models to Europe. It also remains open whether this would be so straightforward, or whether European law could put limits on Amazon and thereby better protect brands and sellers. We asked Sandra May, legal expert at the German e-commerce association Händlerbund, for her assessment.

What is this about?

With “Shop Direct”, Amazon integrates external online shops directly into its own product search. Users see products from third-party shops within the Amazon app and are then redirected to the respective shop page to complete the purchase. Amazon earns commissions in the process.

With “Buy for Me”, Amazon goes one step further: here, the customer remains entirely within the Amazon interface while Amazon automatically executes the order in the background at the respective shop.

Both models significantly change the previous separation between the Amazon marketplace and external commerce. Suddenly, products can become part of the Amazon ecosystem even though merchants or brands deliberately do not want to sell there. This is precisely what gives rise to numerous legal questions.

Product images, texts and data: where does the copyright problem begin?

One of the first questions concerns the automated use of product data. As part of such models, Amazon apparently takes product images, texts and prices from external shops – in some cases without the active consent of the merchants.

Sandra May, legal expert at the German e-commerce retailer association Händlerbund, states:

“If Amazon uses product photos and texts from other shops without permission, this legally constitutes reproduction – and that requires a licence.”

Product images in particular are legally sensitive, as they are generally protected by copyright. However, the issue goes beyond individual images. As platforms increasingly retrieve product data from external stores, a new question arises. To what extent will commerce platforms be able to access third-party store infrastructures in the future – both technically and legally?

Brands appear on Amazon without wanting to

The issue becomes particularly sensitive when it comes to trademark law. Many companies deliberately invest in their own distribution channels and try to control their brand presentation outside large platforms. Some brands even explicitly prohibit their distribution partners from selling on certain marketplaces or have deliberately withdrawn from Amazon. If products nevertheless appear within the Amazon app, this could become problematic.

Sandra puts it this way:

“If brands are presented in this way, it could constitute exploitation of reputation, because it creates the impression that a business relationship exists. For consumers, that is exactly the impression that will arise.”

From a consumer perspective in particular, it is often unlikely to be clear whether a brand is actually working with Amazon or not. This creates not only trademark-related questions. It also raises reputational risks for companies that deliberately want to keep their distance from the platform.

New questions around contracts and bots

The situation becomes even more complex with “Buy for Me”. Here, according to the current understanding, Amazon merely acts as an intermediary and purchases on external shop pages on behalf of the customer. Legally, the contract therefore continues to be formed between the shop and the customer.

At the same time, this model potentially conflicts with existing shop terms and conditions, as many merchants expressly prohibit automated orders or bot access. Whether such orders can be rejected, however, depends heavily on how the respective shop structures the conclusion of contracts.

Sandra explains:

“In the case of binding offers, the contract is concluded directly. Cancelling an existing purchase contract is not easy.”

In addition, another question arises: do consumers recognise with sufficient transparency who their actual contractual partner is? If not, this could become problematic from the perspective of EU consumer protection law.

A risk factor for Amazon: the DMA

Alongside copyright, trademark law and consumer protection, another aspect comes into focus: the Digital Markets Act (DMA). Through “Shop Direct”, Amazon would potentially gain access to data that previously existed outside its own platform:

• Prices
• Assortment
• Demand
• Product availability

As Amazon is considered a gatekeeper under the DMA, the company is subject to particularly strict rules when handling business data. However, the model currently appears to sit in a regulatory grey area.

Sandra says:

“The DMA tends to assume data that Amazon has because merchants trade on the platform. With Shop Direct, the constellation is different.”

Whether and how the DMA will apply here in the future is therefore likely to depend heavily on the specific design of such models.

Why this development is strategically significant

The real significance of “Shop Direct” and “Buy for Me” may lie less in individual legal questions than in the direction indicated behind them. Amazon is increasingly expanding its role in e-commerce from a traditional marketplace to a central commerce interface. Even if the actual purchase takes place outside Amazon, Amazon potentially remains the central entry point for product search, product selection and the purchase decision.

Marketplace Universe Insight: The key question in e-commerce may increasingly be less “Where is the purchase made?” and more “Who controls the entry point into the customer journey?”

For brands that have invested heavily in their own shops, communities and CRM structures, this could become relevant in the long term. Platform dependency would then no longer arise only through the transaction itself, but already through visibility, product search and customer access.

Key Learnings

• “Shop Direct” and “Buy for Me” raise numerous open legal questions in Europe.
• Potential conflicts around copyright, trademark law, consumer protection and the DMA are particularly relevant.
• The automated use of product images and brand presentations could be especially critical.
• “Buy for Me” also raises new questions around automated orders and contract law.
• Strategically, a larger development is emerging at the same time: Amazon is increasingly expanding its role from marketplace to central commerce interface.

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Why the Nordic market is underestimated

The Nordics tend to end up in the appendices of most expansion strategies – somewhere behind Germany, UK, France, Poland and other, bigger markets. That’s a mistake.

According to ECDB, annual e-commerce revenue across the region will reach 39.7 billion euros in 2026, growing to 52.6 billion euros by 2030. Internet penetration stands at 98.9 percent, with near-universal coverage expected by 2030. According to the PostNord study, 86 percent of Nordic consumers made an online purchase in the last 30 days, and more than seven in ten made a cross-border purchase in the past year. These are not emerging market numbers – this is a mature, high-spending market with highly digitalised consumers.

Marketplace Universe Insight: The Nordics are not an add-on to a DACH strategy. They are a distinct, fragmented market – with different marketplace preferences in each country that sellers and brands need to understand and address separately.

The top 3 international marketplaces by country

Three platforms define the Nordic cross-border marketplace space: Temu, Zalando and Amazon. Their relative weight differs significantly by country – and the shifts compared to 2025 are significant enough to warrant a strategic rethink.

Country	1st place	2nd place	3rd place
Sweden	Amazon 33% (34%)	Temu 27% (23%)	Zalando 25% (27%)
Denmark	Zalando 36% (35%)	Temu 30% (26%)	Amazon 20% (23%)
Finland	Temu 30% (25%)	Zalando 30% (29%)	Amazon 11% (16%)
Norway	Temu 36% (41%)	Zalando 34% (34%)	Amazon 12% (16%)

Source: PostNord, “E-commerce in the Nordics 2026 Spring”. Figures in brackets: 2025 comparison values.

Sweden

Sweden is the most mature e-commerce market in the Nordics: 88 percent of consumers made an online purchase in the last 30 days, while cross-border affinity at 57 percent is the lowest in the region. Amazon holds the top spot but is losing ground slightly. The real winner of the year is Temu, which climbs from 23 to 27 percent and pushes Zalando off second place. Price beats brand loyalty – even in the affluent Swedish market.

Denmark

Denmark is the strongest cross-border market in the Nordics: 80 percent of consumers made a purchase from abroad in the past year. Zalando leads comfortably, driven by the top purchase category of fashion and footwear. For DACH brands, the most strategically relevant number is a different one: Germany has maintained its position as the most popular country of origin for cross-border purchases, jumping from 35 to 42 percent – well ahead of China at 31 percent. This means that brands already active in the German market can often serve Danish demand without starting from scratch.

Finland

Finland is showing the most significant structural shifts. Temu has overtaken Zalando in first place, driven by persistent price sensitivity in an economically sluggish market. Even more striking: Amazon loses five percentage points, falling from 16 to 11 percent. That is not statistical noise – it is a structural signal.

Marketplace Universe Insight: Finland is the market where price-driven platforms are advancing most strongly. Not just Temu – second-hand platforms such as Vinted and the Finnish platform Tori are also gaining ground according to the study. This is reshaping the price landscape for every seller active in the market.

Norway

Norway is the only Nordic country showing a notable Temu decline in 2026: down five percentage points to 36 percent. At the same time, the cross-border geography is shifting – Sweden has replaced China as the most popular country of origin, and Denmark has entered the top three for the first time. The study attributes this to a growing preference for closer markets: faster delivery, easier returns, higher consumer trust. For brands already active in Sweden or Denmark, this represents an underestimated entry point into the Norwegian market.

What the shifts mean for brands and sellers

Temu is not a temporary phenomenon. In three out of four Nordic countries, Temu has gained ground or holds the top spot – even if Norway is showing an early countermovement. Brands that view the Nordics as a premium market and dismiss Temu as irrelevant are misreading the data.

Amazon is losing ground consistently across all four countries – most sharply in Finland and Norway. The scale of the declines varies, but the direction is the same everywhere. Brands that have built their Nordic strategy primarily around Amazon should take a hard look at where things are heading.

Zalando remains the structurally strongest fashion partner. It sits in the top two in all four countries and holds market leadership in Denmark. For fashion brands without a Nordic marketplace presence, Zalando remains the logical first step – and that remains true in 2026.

What has changed, however, is the need for a country-specific approach. Zalando-first works very differently in Denmark than it does in Finland. Amazon investments that make sense in Sweden follow a different return logic in Norway. A single Nordic strategy is not a strategy.

There is also a regulatory factor the study explicitly flags: the planned removal of the €150 customs duty exemption for goods shipped from third countries would structurally reduce the price advantage of Chinese platforms – and in doing so, reopen the competitive field for established sellers.

Key Learnings

• A single Nordic strategy is not a strategy. Country-specific marketplace prioritisation is non-negotiable.
• The Nordic e-commerce market is growing to 52.6 billion euros by 2030, with internet penetration at 98.9 percent. This is not a niche market.
• Temu is gaining in three out of four Nordic countries: in Finland it takes market leadership from Zalando, in Sweden it moves past Zalando into second place.
• Amazon is losing share in all four countries – most sharply in Finland with minus 5 percentage points and in Norway with minus 4 percentage points.
• Germany is the most popular cross-border country of origin in Denmark at 42 percent – ahead of China at 31 percent. A direct expansion signal for DACH brands.
• Finland shows the strongest price sensitivity in the Nordics and the most pronounced structural shifts in favour of price-driven platforms.
• Norway is the first Nordic country with a noticeable Temu decline – and a growing preference for Nordic neighbouring markets over China.

Would you like to learn more about the Nordic countries? Then check out this in-depth article: How to Successfully Sell to the Nordics

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The Silo Problem: Data That Doesn’t Lie – But Doesn’t Tell the Whole Truth Either

Platform-native data is not wrong – it is precise, but only within its own ecosystem. Amazon measures what happens on Amazon, Zalando measures what happens on Zalando, eBay measures what happens on eBay. The problem lies not in the quality of this data, but in its scope. Every marketplace captures a slice of business reality – namely its own slice. Anyone who mistakes that slice for the full picture is making decisions on a systematically incomplete foundation.

In practice, sellers optimise what their dashboard measures well: traffic, conversion rate, ROAS, Buy Box share. What native dashboards are far less equipped to answer is the question that actually matters: whether a SKU makes any money once all costs are accounted for, whether a campaign is generating genuine new demand or simply capturing purchases that would have happened organically anyway, and whether a channel is growing the business or just pulling volume from somewhere else.

Marketplace Universe Insight: Platform data shows what happened inside the channel – but not whether it was worth it from a business perspective.

As a multichannel platform for sellers and an integration specialist, our partner base encounters exactly this pattern every day. That is why we put together this joint overview of the most common blind spots and their consequences.

When KPIs Mislead

The KPIs that marketplaces prioritise make sense from a platform perspective – ROAS, conversion rate and Buy Box share all show what is happening inside the ecosystem. The problem lies in what they do not show.

• ROAS and margin are two different things. A campaign can post a strong ROAS and still contribute almost no profit once fees, shipping, returns and product margin are factored in.
• Conversion rate and profitability follow different logic. A price reduction typically improves the conversion rate. It can simultaneously damage margin and long-term brand positioning – the dashboard only shows the improvement, not the damage.
• And Buy Box share can grow at the expense of profitability. Aggressive price cuts win visibility and may lose money on every transaction.

The result is a systematic misunderstanding: sellers begin to equate marketplace efficiency with business success.

Marketplace Universe Insight: A campaign can perform perfectly within a platform and simultaneously direct budget towards the wrong products, channels or customer segments – without any of this showing up in a native dashboard.

When Multiple Channels Enter the Picture, Things Get Structurally Complex

For single-channel sellers, the limitations of native analytics are still manageable. But as soon as a second or third channel is added, the situation changes fundamentally. The data suddenly speaks different languages.

Every platform defines performance in its own way, with its own reporting structures, fee models and attribution rules. What counts as a “sale” on Amazon is recorded differently on Zalando. And a direct online shop maps an entirely different conversion path. The result is data that is individually correct but not mutually comparable – and conclusions that make sense within one platform’s logic but systematically mislead when applied across channels.

Marketplace Universe Insight: Selling on three channels means having three different definitions of success – unless you build a shared one yourself.

The Aha Moment: What the Data Actually Showed

A concrete example from practice, representing a pattern that repeats itself regularly:

A seller directed campaign budget towards the channel that performed best by units sold. Revenue grew , but contribution margin did not keep pace. The aha moment came when return rates were compared across channels for the first time: the supposedly best-performing channel had significantly higher return rates than all the others – a cost factor that had not been visible in any single platform dashboard.

As a result of this insight the seller shifted his budget towards a channel that had grown less strongly at the top line, but delivered considerably better profits once full cost accounting was applied. The best-performing channel in the dashboard is not necessarily the most profitable one in the business.

What Independent Multichannel Analytics Actually Changes

Independent multichannel analytics means analysing the business from a level above any individual channel. Instead of letting each marketplace define what performance means, a shared view emerges across channels, products, orders, inventory and pricing. Good multichannel-capable tools – such as the analytics product from base – bring these data sources together natively, without requiring a complex BI infrastructure to be built first.

Concretely, sellers can identify:

• Which channel is actually profitable – not just the one with the highest volume
• Which products generate revenue and which generate real profit – a distinction that platform-native reporting often blurs
• Whether a channel is creating genuine growth – or simply redirecting demand from another channel
• Whether operational issues such as fulfilment friction or inventory shortages are undermining commercial performance

Decision-making shifts from channel optimisation to business optimisation: Where should the next budget be invested? Which pricing strategy improves profit – not just conversion? Which channel is building sustainable growth?

Marketplace Universe Insight: The greatest value of independent analytics lies not in having more data, but in making visible the connections that remain structurally hidden in fragmented reporting.

Who Benefits – and Who Doesn’t

This should be said explicitly: not every seller needs independent multichannel analytics. Single-channel sellers will gain little from it. The value scales with complexity – with the number of channels, countries, SKUs and teams. The moment different people are making different decisions about the same business using different dashboards, the structural problem that independent analytics solves becomes unavoidable.

Comprehensive business analytics will always remain partly an internal task, even with the best external tools – cost structures and purchase prices are data that many companies prefer not to share with an external platform. Specialised tools can nonetheless deliver aggregated insights for the broader picture and significantly reduce the internal development effort required.

Key Learnings

• The approach is not right for everyone. The value scales with the number of channels, countries and operational complexity.
• Platform-native data is precise – but limited. What happens outside the channel remains structurally invisible.
• ROAS, conversion rate and Buy Box share measure platform efficiency, not business success. The distinction is systematically underestimated.
• Once multiple channels are in play, platform data is no longer directly comparable. Each platform speaks its own language.
• The most profitable channel is rarely the one with the highest volume. Return rates and operational costs shift the picture significantly.
• Independent multichannel analytics shifts decision-making from channel optimisation to business optimisation.

Der Beitrag Unlocking Data: Why Sellers Need Independent Multichannel Analytics erschien zuerst auf Marketplace Universe.

From a German setup to European expansion

Handyhuellen.de has been active on Kaufland Germany since 2019. For the smartphone accessories specialist, the marketplace had long ceased to be a test channel and had become a solid foundation for further growth. When Kaufland expanded its marketplace presence across Europe, Handyhuellen.de faced an obvious question: How quickly could the existing German setup be transferred to additional countries?

The basis was already in place: Handyhuellen.de had been working with the integrator ChannelEngine for some time. Product data, mapping, pricing logic, stock, and content were already connected. That became the lever for the rollout into the six additional Kaufland regions Slovakia, the Czech Republic, Poland, Austria, France, and Italy.

“We were able to simply reuse our existing setup and quickly activate new markets without adding operational complexity or additional resources. That made scaling across several regions much easier than we had expected.” – Krijn Twigt, Business Development Manager at handyhuellen.de

The challenge: Internationalising without operational fragmentation

Cross-border marketplace expansion quickly creates complexity: localised content, translations, consistent pricing and stock, VAT questions, regulatory requirements, and logistics processes all have to work across several countries.

For Handyhuellen.de, it was therefore crucial not to treat expansion as a series of separate country projects. This is where ChannelEngine and Kaufland Global Marketplace complemented each other:

• ChannelEngine provided single mapping, automation, and central management of pricing, stock, and content processes.
• Kaufland provided the country marketplaces, regional reach, and translation support.
• One particular feature of the Kaufland setup also helped: sellers can manage all seven country marketplaces through one account.
• Logistics and compliance remained lean: centralised fulfilment from the Dutch warehouse and a single VAT setup via EU OSS.

The key lever was single mapping. Because the products for Germany were already mapped in ChannelEngine, they could be used as the basis for the additional Kaufland markets. Kaufland handled the translations for the individual regions, while ChannelEngine enabled targeted adjustments, for example for images containing localised text.

This meant Handyhuellen.de did not have to rebuild listings market by market, while still being able to adapt its brand presentation.

“Handyhuellen.de is an excellent example of how sellers can unlock the full potential of cross-border expansion through Kaufland Global Marketplace. By combining Kaufland’s customer reach with ChannelEngine’s automation and centralised management, sellers can expand quickly into new markets while maintaining efficiency and control across regions. This setup gives sellers a scalable and agile way to accelerate their European growth.” – Matthias Kluth, Teamlead Sales DACH at Kaufland Global Marketplace

Two hours per market: When expansion becomes a process

Building on this foundation, Handyhuellen.de was able to activate new Kaufland regions very quickly. In individual markets, the technical setup took only around two hours. This allowed around 20,000 SKUs to be rolled out across several international markets without rebuilding the operational logic each time.

“ChannelEngine gave us one central control point for all Kaufland regions. We maintained full oversight of pricing, stock, and content while expanding across Europe. Centralised logistics and a single VAT setup also removed much of the typical friction of cross-border expansion. That allowed us to focus on scaling performance with control and efficiency.” – Krijn Twigt, Business Development Manager at handyhuellen.de

Italy shows the momentum of new markets

The expansion quickly developed positively for Handyhuellen.de – and, according to the company, was in line with the forecasts provided by Kaufland’s account manager.

“Within the first year, the new Kaufland markets generated around 50% of Germany’s sales volume. That confirmed that our expansion model works. With ChannelEngine, scaling across regions is no longer a complex project. It becomes a structured and repeatable process.” – Krijn Twigt, Business Development Manager at handyhuellen.de

Italy turned out to be a particular highlight: together with France, it was the most recent market to be added and has already become the strongest Kaufland market after Germany – even though Kaufland has only been active with its marketplace in Italy since September 2025.

For Handyhuellen.de, these data points are now more than just sales signals. Performance across the individual regions feeds into the broader e-commerce roadmap and helps assess where further investment may make sense, including potential future webshop launches.

Conclusion: Scaling starts before the next market

The Handyhuellen.de case shows that European marketplace expansion becomes most efficient when existing structures can grow with the business. ChannelEngine played the central role as the integration and automation layer. Kaufland complemented this operational basis with country marketplaces, translation support, and regional demand.

This turned a successful German setup into a scalable European model – not without operational work, but without having to rebuild each country from scratch.

Key Learnings

• Marketplace data is becoming strategic. It not only reveals sales potential, but also helps guide further e-commerce investment.
• The numbers show how strongly the setup scaled: Handyhuellen.de rolled out around 20,000 SKUs across all seven Kaufland regions; individual markets could be technically activated in around two hours, and the new countries generated around 50% of Germany’s sales volume within the first year.
• Single mapping accelerates internationalisation. Once product data is cleanly set up, new markets can be activated much faster.
• Marketplace reach needs operational scalability. Growth only becomes efficient when content, pricing, stock, VAT, and logistics work together.
• Young markets can become relevant quickly. Italy has already become Handyhuellen.de’s second-strongest Kaufland market after Germany.

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From Search to Discovery (and Why That Matters)

TikTok Shop is often described as “discovery commerce.” That’s partly true — but it’s not the whole picture.

Platforms like Instagram have already moved commerce closer to content. What TikTok changes is the consistency and speed at which discovery turns into transactions. The entire journey — from first impression to purchase — happens within one environment.

The numbers behind this shift are significant. According to the Marketplace Shopping Behavior Report 2026 by ChannelEngine — a multichannel integration platform that connects brands’ backend systems with over 1,300 marketplaces and sales channels, including TikTok Shop — social commerce is on track to hit $6.2 trillion globally by 2030, up from $575.8 billion in 2021, representing 25–30% of all ecommerce. Per-user spending via social channels is projected to double to $1,224 by 2027.

TikTok sits at the center of this: with an estimated 40 trillion minutes watched globally, it outpaces both Instagram (25 trillion) and Netflix (12 trillion). And 40% of Gen Z already use TikTok for search instead of Google — a signal that the platform has moved well beyond entertainment into active purchase intent.

The difference is subtle, but important: traditional marketplaces like Amazon capture existing demand, while TikTok increasingly creates demand in the moment. This doesn’t replace marketplaces — but it changes how brands need to think about visibility. And as ChannelEngine’s work with brands across markets consistently shows, it also changes what “being ready” actually means operationally.

How TikTok Shop Actually Works

TikTok Shop is not a single storefront, but a combination of different commerce entry points embedded into the platform. There are four core formats that define how products are surfaced and sold:

Most successful setups don’t rely on just one of these — they combine them. But the starting point matters: brands that try to activate all four formats simultaneously before establishing content traction tend to spread themselves too thin.

Where TikTok Shop Works Best

TikTok Shop is not category-neutral. Data presented by ChannelEngine and TikTok Shop at the E-Commerce Expo Berlin 2026 gives a clear picture of where consumer willingness to buy is strongest: clothing and footwear leads at 31%, followed by toys and books (23%), health and beauty (22%), homeware (21%), sporting goods (18%), electronics (17%), and fitness equipment (14%).

What the top-performing categories have in common is that they can be demonstrated easily, are visually understandable, and benefit from impulse-driven decisions.

Marketplace Universe Insight:
Product evaluation on TikTok shifts from static product pages to dynamic content. Products that need explanation — a skincare routine, a kitchen gadget, a fitness tool — benefit from this format because the content does the selling work that a listing never could. Products that rely on specs, technical comparison, or considered purchase logic tend to struggle. If your product needs a table to explain it, TikTok Shop is probably not your primary channel.

The Real Shift: From Catalog to Content

Traditional marketplaces reward structure. Clean product data, optimized listings, and pricing competitiveness are still necessary on TikTok Shop — products need to be correctly categorized, attributes mapped, and listings compliant to be visible at all. But that’s only the baseline.

Products don’t gain traction because they are well-listed — they gain traction because they are embedded in content that performs.

One of the most common mistakes ChannelEngine sees brands make is repurposing standard ecommerce creatives or marketplace listings directly into TikTok. The format requires native content — not adapted content. A product image optimized for Amazon is not a TikTok video. A listing description written for search indexing is not a creator brief. Brands that treat TikTok Shop like a traditional product feed channel consistently underperform against brands that build content strategies from scratch for the platform.

At the same time, catalog and content cannot be treated entirely separately. Product titles, descriptions, and attributes still influence indexing — but they need to align with how the product is presented in content. If content promises something the listing doesn’t reflect, or vice versa, performance suffers.

This introduces a different operational rhythm: visibility fluctuates with content performance, demand is created in cycles, and optimization shifts from listings to content iterations.

What Drives Success on TikTok Shop

Across different markets and brand setups, a few patterns consistently emerge — and they were a central theme in what ChannelEngine and TikTok Shop discussed at the Expo.

Hero Product Strategy.

Successful brands rarely start with their full assortment. Instead, they focus on a small number of highly visual, trend-relevant products that are easy to demonstrate. These products act as entry points into the algorithm. Once traction is established, brands expand from there — testing quickly, identifying early winners, and scaling based on content performance, not traditional sales logic. Brands that upload too many SKUs too early, before understanding what resonates on the platform, consistently struggle to build momentum.

A concrete example of this approach in practice is Creamy Fabrics, a fast-growing shapewear and lifestyle brand that ChannelEngine has worked with. Their model combines influencer-driven content, limited product drops, and trend-based activations — including Coachella-themed campaigns — to generate social momentum, and then converts that demand across channels including marketplaces and DTC. The TikTok presence doesn’t operate in isolation: it feeds the entire commerce ecosystem.

This points to something ChannelEngine increasingly observes across brands on the platform: a measurable halo effect. Viral TikTok products don’t just drive TikTok Shop sales — they create uplift on marketplaces and in branded search activity more broadly. TikTok Shop, in other words, is not just a sales channel. It functions as a demand-generation engine for the wider commerce mix.

Creator Strategy.

Creators are not just a marketing channel — they are a core distribution layer. According to TikTok’s own data, 75% of TikTok users find creator content believable, and 71% say creator authenticity directly motivated them to make a purchase. As Stephen Meade, Senior Regional Marketing Manager EMEA at ChannelEngine, puts it: “The brands winning on TikTok Shop are not necessarily the ones with the biggest budgets, but the ones creating the most culturally relevant content.”

Brands rely on creators to translate products into content formats that resonate with specific audiences — through affiliate collaborations, product seeding, and performance-based partnerships. Investing early in creator relationships, before there is obvious commercial pressure to do so, is one of the clearest differentiators between brands that scale and brands that stall.

LIVE Strategy.

LIVE commerce becomes relevant once there is enough traction. It works particularly well for bundles, limited offers, and campaign moments — but comes with clear requirements: dedicated resources, real-time stock visibility, and operational flexibility. Consistency matters here as much as quality: sporadic livestream activity produces far weaker results than a regular cadence.

Full Ecosystem Approach.

More mature brands combine all elements — content, creators, listings, and promotions — into a coordinated system. Crucially, this also means breaking down internal silos between ecommerce, marketing, and social teams. The brands that perform best on TikTok Shop are typically those where these functions operate in genuine alignment, not in parallel. At that point, TikTok Shop is no longer an experiment. It becomes a structured sales channel.

Where Things Break

The challenge with TikTok Shop is not getting started — it’s maintaining performance. This is one of the most consistent observations ChannelEngine makes working with brands across markets: the bottleneck is rarely demand. It’s operations.

Content is the most visible dependency. Without a steady stream of relevant content, visibility drops quickly — and because the algorithm rewards recency and engagement, there’s no coasting on past performance. Brands that treat TikTok Shop like a traditional channel, with periodic campaigns and stable listings, tend to plateau fast.

But content is only part of the picture. TikTok Shop’s operational requirements are stricter than many brands expect coming from other marketplaces. Shipping speed, stock accuracy, and consistent order handling all feed directly into the platform’s Shop Performance Score — the metric TikTok uses to determine how much visibility a seller receives. A fulfillment delay or a stock mismatch doesn’t just create a customer service problem. It quietly reduces your reach.

“Operational excellence becomes a competitive advantage very quickly on TikTok Shop,” notes Stephen Meade. “Viral demand is great — unless your backend systems can’t keep up.”

Creator management adds another layer of complexity that’s easy to underestimate at the start. Coordinating product seeding, tracking affiliate performance, and maintaining enough active creators to keep content flowing is a real operational workload — not a marketing task that runs itself.

And then there’s the cost structure. Platform fees, creator commissions, and promotional mechanics need to be modeled carefully before scaling, not after. Brands that treat TikTok Shop as a low-cost acquisition channel often find the unit economics look different once they’re operating at volume.

Scaling TikTok Shop: Why Infrastructure Becomes Critical

What starts as a content-driven growth channel quickly turns into an operational challenge. As brands scale, they need to manage product data across channels, synchronize inventory in real time, maintain pricing consistency, and route and fulfill orders reliably. Without a structured setup, the typical risks are overselling, inconsistent pricing, and growing manual effort.

This is where marketplace middleware becomes essential. ChannelEngine has built its TikTok Shop integration around five operational requirements that brands consistently underestimate:

For brands that want to scale beyond initial traction, this operational layer is what keeps the system from breaking.

TikTok Shop in the Channel Mix

One consistent message from ChannelEngine’s work with brands across markets: TikTok Shop works best when it’s treated as a revenue channel, not just an advertising surface. That means being present where consumers are, maintaining control over content, pricing, and monitoring — and building the multichannel infrastructure that makes diversification sustainable.

The halo effect makes this argument concrete: brands that go viral on TikTok don’t just see TikTok Shop sales increase. They see measurable uplift on Amazon, on their own DTC channels, and in branded search. The platform generates demand that flows across the entire commerce ecosystem — which also means that the operational infrastructure supporting that ecosystem needs to be robust enough to capture it.

“Successful TikTok Shop strategies require brands to think holistically,” says Stephen Meade. “Social commerce impacts marketplaces, DTC, brand awareness, and creator ecosystems simultaneously.“

TikTok Shop doesn’t replace marketplaces — but it adds a new and increasingly significant layer to them. The opportunity is real. But it only holds if the infrastructure behind it can keep pace.

Key Learnings

• TikTok Shop rewards content performance, not just listing quality — repurposing standard ecommerce creatives doesn’t work
• Start with hero products, not full assortments; scale what performs, not everything at once Creators are a core distribution layer, not a marketing add-on — invest in those relationships early
• The halo effect is real: TikTok virality drives measurable uplift on marketplaces and branded search beyond the platform itself
• Operational performance directly impacts visibility — shipping speed, stock accuracy, and order handling all affect reach through the Shop Performance Score
• Break down internal silos between ecommerce, marketing, and social teams before launching, not after
• Treat TikTok Shop as a revenue channel and demand-generation engine, not an ad surface — and build the multichannel infrastructure to support it

15.05.2026 – Written by Ricarda Eichler, Journalist and Author for OHN

Der Beitrag How to Succeed on Tiktok Shop erschien zuerst auf Marketplace Universe.

The Old Logic Is Breaking Down

For years, product content in fashion e-commerce was treated as a cost to be managed. Every SKU needed photography. Every market needed assets. Every new channel demanded more material. The cost scaled linearly with volume — and that meant brands constantly made trade-offs: fewer images, slower time-to-market, underfunded product pages.

That logic is now being dismantled.

AI has made it possible — for the first time — to scale content without scaling cost. The result is not just operational efficiency. It is a structural shift in how competition on fashion marketplaces works. And the brands and platforms that recognised this earliest are already pulling ahead.

Zalando: The Signal Everyone Should Be Reading

When Zalando reported its full-year outlook in March 2026, the headline numbers were strong: a forecast jump of 12–25 % in adjusted operating profit, a share buyback of up to 300 million euros, and shares leaping 12% on the day — their best performance since March 2024.

But the more significant signal was in how Zalando explained the growth. Co-CEO David Schröder attributed it directly to AI:

“We have 70 % more content now, basically at the same kind of cost.”

Seventy percent more content. Same cost. That is not incremental improvement — that is the unit economics of content production fundamentally resetting.

Zalando also pointed to AI-generated product images as a driver of efficiency in ad creation, and flagged AI virtual try-on as a tool for reducing returns — historically one of the most expensive structural problems in online fashion.

The takeaway is not that Zalando is doing something clever with technology. It is that content — long a fixed operational cost — is beginning to behave like a variable one.

Marketplace Universe Insight
When the marginal cost of an additional product image approaches zero, the competitive logic of a marketplace changes entirely. Content stops being a constraint and starts being a weapon.

Luxury Is Not Sitting This Out

One persistent assumption in the AI-and-fashion conversation is that the premium segment will resist. Brand DNA, heritage, creative control — these are real concerns. But the data from early adopters tells a different story.

Fabrizio Cardinali, CEO of Etro and former General Manager of Dolce & Gabbana, spoke at BoF VOICES 2025 about the brand’s results after partnering with AI content provider PIXELMODA:

“With PIXELMODA we have been growing e-comm sales close to 50% per year for 2 years — and we are spending less than what we did 3 years ago.”

50 % annual e-commerce growth. Lower cost than before. That is the kind of P&L impact that tends to end the philosophical debate about AI fairly quickly.

Cardinali was also candid about how the shift happened internally. Etro began by using AI to improve precision and consistency in product imagery, then expanded into campaign content — including the SS24 “Nowhere” campaign, which used AI to build imaginative visual worlds around products. The concern that AI would dilute brand DNA has not materialised. According to Cardinali:

“It’s very difficult, almost impossible, to see the difference between a non-AI image and an AI-assisted one.”

The human element — real photographers, real models, real stylists — remained central. What changed is how efficiently that human team works, and how many additional assets can be generated from each shoot. The freed-up budget and creative capacity then went into the work where human judgement genuinely cannot be replicated: editorial, campaign, storytelling.

How the Production Model Actually Works

To understand why this matters at scale, it helps to understand what modern AI content production actually looks like. The industry has largely converged on two complementary modes — and the combination of both is where the real economics shift happens.

Mode 1: AI-Assisted Production A human team — model, photographer, stylist — shoots on set, but guided in real time by AI that checks every frame against the brand’s specific visual guidelines. Nothing is generated or synthetic. The output is traditional photography, produced faster and with significantly less rework and waste. The AI acts as a quality layer, not a replacement for the shoot itself.

Mode 2: Generative AI Using AI-assisted images as inputs, generative AI then produces additional assets per SKU: body swaps, alternative backgrounds, different poses, video clips, editorial shots. Content that previously required separate shoots, separate locations, and separate budgets can now be generated in hours.

Providers like PIXELMODA have built their entire service model around this two-layer approach — using the assisted shoot as the foundation and the generative layer as a multiplier. The results, across a client base of over 900 brands, make the case for the model plainly.

The cost impact is significant:

• Photography costs reduced by up to 70 %
• Video production costs reduced by up to 90 %
• Time-to-online cut by up to 50 %

And the revenue impact is equally measurable. According to PIXELMODA’s data:

• Moving from 4 images to 7+ per SKU reduces returns by 22 % (Shopify data)
• Adding video drives sales up by +10–20 %
• Aligning model ethnicity with target consumer demographics adds a further +10–25 % in conversion

The Missed Opportunity Most Brands Don’t See

Gianni Serazzi, who leads PIXELMODA, put the business case bluntly at BoF VOICES 2025:

“If you look at your business and you’re creating content for online the same way you were creating it 5 years ago, you’re probably missing anything between 10 % and 30–40 % of sales — now, this month.”

The uncomfortable truth is that this gap does not show up on a P&L as a line item. It is invisible — the sales that never happened, the conversions that never came, because the product page wasn’t good enough to close the deal.

Marketplace Universe Insight
Content gaps don’t announce themselves. You don’t see the sales you’re missing — you only see the ones you make. That’s what makes AI-driven content so structurally important: it makes previously invisible losses recoverable.

What This Means for Marketplace Competition

Here is where the argument gets structural.

Content volume and quality are already major inputs into marketplace ranking algorithms, conversion rates, and retail media performance. As AI makes richer content dramatically cheaper to produce, the baseline expectation on platforms will rise. What is a differentiator today — more images, video, diverse model representation — becomes table stakes in a short window.

That changes the nature of competitive advantage. Once AI content tools are widely available and the cost advantages compound for everyone who adopts them, content quality alone ceases to be a moat.

The brands that pull ahead will be those that use the newly freed-up capacity — budget, time, creative talent — more intelligently. That might mean:

• Faster creative testing across markets
• Deeper localisation (language, model ethnicity, cultural context)
• Higher investment in the data capabilities needed to understand which content actually converts, and where

The Uncomfortable Conclusion

The structural argument cuts both ways. If AI makes content production dramatically cheaper and faster for everyone, then the brands and marketplaces that benefit most will not be those who simply adopt the technology. They will be those who move earliest and build operational and strategic capabilities around it before the window closes.

Zalando’s framing — AI as a catalyst for both efficiency and growth simultaneously — is the version of this story that should be landing in boardrooms. Not AI as cost-cutting. Not AI as a creative experiment. AI as the mechanism by which the economics of marketplace competition fundamentally reset.

For fashion brands still treating content as a linear cost to be managed, that reset is already underway.

Key Learnings

• AI has broken the linear relationship between content volume and content cost. 70 % more content at the same cost (Zalando) is not an edge case — it is the new direction of travel.
• Premium and luxury brands are adopting AI, not resisting it. The Etro example shows that AI-assisted content can preserve brand DNA while delivering significant commercial results.
• The production model has structurally changed. AI-assisted shooting + generative AI output means 30+ assets per SKU, at a fraction of traditional cost.
• The revenue impact of richer content is measurable and significant. More images reduce returns. Adding video lifts conversion. Localised models drive further uplift.
• The gap is invisible until it’s gone. Brands not optimising their PDP content are losing sales they cannot see — and won’t recover until they change the workflow.
• Content quality will become table stakes, not a differentiator. Competitive advantage will shift toward execution, data, and how freed-up resources are reinvested.

PIXELMODA is a global provider of AI-assisted and AI-generated content for fashion and luxury e-commerce, working with over 900 brands across Europe, the US and Asia. For more information see pixelmoda.net 

04.05.2026 – Written by Ricarda Eichler, Journalist and Author for OHN

Der Beitrag How AI Transforms Fashion Marketplaces — From Content Bottleneck to Business Engine erschien zuerst auf Marketplace Universe.