Marketplaces in 2026: why brands must move beyond distribution and start thinking orchestration

In 2026, the question is no longer whether brands should sell on marketplaces[cite: 462]. The real challenge is how to build a marketplace presence that is profitable, consistent and built to last[cite: 463].

The marketplace landscape has changed dramatically[cite: 464]. According to FEVAD, marketplaces now account for more than 50% of e-commerce transactions in France, making them a core pillar of today’s digital distribution strategies[cite: 464]. The same source also highlights the growing pressure on brands and retailers to manage product data quality, stock synchronisation, pricing consistency, order processing and channel profitability at the same time[cite: 465].

In this environment, success is no longer about simply being present on a handful of platforms[cite: 466]. It is about being able to orchestrate the entire value chain: product data, content enrichment, distribution, channel adaptation, operational execution and commercial performance[cite: 467].

What we are seeing is a clear shift[cite: 468]. The businesses making the biggest strides are not the ones stacking more tools, but the ones putting the right governance in place to scale their marketplace strategy effectively[cite: 468].

From marketplace distribution to marketplace management

For years, selling on marketplaces was often driven by opportunity[cite: 470]. A feed was connected, a product selection was pushed live, and adjustments were made over time[cite: 471]. For a while, that was enough[cite: 472]. It no longer is[cite: 473].

Every platform comes with its own requirements: taxonomy rules, mandatory attributes, content standards, logistics constraints, update frequencies and service expectations[cite: 474]. As highlighted in the article, managing multiple marketplaces creates a sharp rise in operational complexity, particularly around format inconsistencies, stock updates, pricing alignment, product listing quality and order centralisation[cite: 475].

That means the challenge is no longer simply to distribute a catalogue. Brands now need to manage: [cite: 476]

• which products should be sold on which channels[cite: 477];
• how content should be tailored to each platform’s requirements[cite: 478];
• how to maintain data quality over time[cite: 479];
• how to protect margins despite fees and competitive pressure[cite: 480];
• how to ensure reliable execution across orders, stock and service levels[cite: 481].

In other words, marketplace strategy has become an orchestration challenge[cite: 482].

Product data is still where it all starts

No marketplace strategy can perform at scale without a strong and reliable product data foundation[cite: 484]. When product data is poorly structured, everything slows down: content enrichment, distribution, localisation, quality control, international roll-out and performance tracking[cite: 485].

By contrast, well-governed product data makes it easier to meet marketplace requirements and significantly reduces manual workload[cite: 486]. The 2026 benchmark also underlines the central role of PIM in this model, alongside feed management tools and pricing and performance solutions[cite: 487]. This reflects a very real operational truth: marketplace performance starts with product data, content quality and omnichannel consistency[cite: 488].

Assortment strategy can no longer be treated as one-size-fits-all

Another important point: not every product belongs on every marketplace[cite: 490]. A mature marketplace strategy is not about replicating the full catalogue across every channel. It is about making deliberate choices[cite: 491].

Some products are better suited to broad, generalist marketplaces, while others perform better in more specialist environments[cite: 492]. Some support brand visibility, others drive profitability, while others help unlock international expansion or reduce time-to-market[cite: 493].

This is why a multi-channel assortment strategy matters[cite: 494]. Product data, category structures, pricing and content all need to be adapted to the realities of each platform[cite: 495]. Real maturity means answering which products should be listed, on which channel, with what level of enrichment, and for what business outcome[cite: 496].

Execution is where performance is won or lost

Marketplace success is often determined less by strategy on paper than by the quality of day-to-day execution[cite: 498]. That means being able to: [cite: 499]

• transform product data into the formats expected by each marketplace[cite: 500];
• adapt titles, descriptions, attributes and visuals[cite: 501];
• keep stock synchronised[cite: 502];
• centralise order flows[cite: 503];
• send back fulfilment and logistics statuses[cite: 504];
• track performance by platform, product category and SKU[cite: 505].

The strongest marketplace models go well beyond catalogue distribution. They also cover fulfilment, statuses, cancellations, returns and the measurement of real profitability[cite: 506]. This is often where the difference lies between a marketplace presence that is simply visible and one that is genuinely under control[cite: 507].

AI can accelerate marketplace execution — but only within the right framework

Another major shift in the market is the growing role of AI in marketplace optimisation[cite: 515]. The rise of AI-powered use cases such as title and description generation, attribute suggestion, translation and product listing completeness scoring is very real[cite: 516].

In a world where every channel has its own standards, AI has become a practical way to speed up enrichment, standardise content and reduce repetitive manual work[cite: 517]. But one thing remains true: AI is not a strategy in itself[cite: 518].

Integrated into the MaPS System PIM, AI goes far beyond simple content generation[cite: 521]. It can be used to improve the quality, reliability and usability of product data across marketplace operations[cite: 522]. For example, it can: [cite: 523]

• generate or enhance product titles and descriptions in line with channel expectations[cite: 524];
• recommend or complete missing attributes to improve listing quality[cite: 525];
• translate and adapt content for cross-border expansion[cite: 526];
• identify inconsistencies in weight, dimensions or units[cite: 527];
• extract key data from supplier documents, including PDFs[cite: 528];
• automatically classify products according to their type or logistics constraints[cite: 529];
• prioritise product enrichment by identifying references with strongest sales potential[cite: 530];
• analyse customer reviews to surface pain points[cite: 531];
• monitor data consistency across reseller websites and distribution channels[cite: 532].

The MaPS System approach ensures data security through a connection to the customer’s own account, rather than a shared publisher account[cite: 535]. That enables true data segregation[cite: 536].

In short, AI delivers real value when it is embedded in an already structured architecture[cite: 537]. That is when it can truly do what it promises: not replace the fundamentals, but accelerate enrichment, secure data flows and make marketplace strategy more effective and easier to manage[cite: 538].

Profitability is back at the centre of the conversation

For a long time, marketplace success was measured mainly in terms of revenue. That is no longer enough[cite: 540]. Today, businesses need a more realistic view of performance — one that takes into account commissions, logistics costs, competitive pressure, listing quality and, depending on the platform, Buy Box control[cite: 541].

This shift from a volume-led mindset to an economically managed model is one of the clearest signs of marketplace maturity in 2026[cite: 547].

What this means for e-commerce, data and IT teams

Marketplace management is a cross-functional business challenge involving: [cite: 549]

• e-commerce teams[cite: 550];
• product marketing[cite: 551];
• data governance[cite: 552];
• pricing teams[cite: 553];
• operations[cite: 554];
• customer service[cite: 555];
• IT and information systems[cite: 556].

The real question is no longer “which tool should we choose?” but rather: how do we build a connected framework across product data, enrichment, distribution, execution and performance management? [cite: 557, 558] This is where the MaPS System approach becomes particularly relevant: as a structuring layer that helps secure product data, accelerate go-to-market and make marketplace performance easier to control[cite: 559].

Our point of view

In 2026, marketplace performance will not be defined simply by channel presence, or even by catalogue depth[cite: 561]. It will be defined by the ability to make the right product repositories, the right flows and the right performance indicators work together[cite: 562].

The businesses that move ahead will be the ones that stop treating marketplaces as just another sales channel, and start managing them as a system in their own right, with distinct requirements in terms of content, execution, governance and profitability[cite: 563]. The Eminence case shows exactly that: performance does not come from adding more channels, but from building a stronger product data foundation and industrialising distribution[cite: 564].

At MaPS System, we believe the real challenge is not avoiding complexity, but making it manageable through the right foundation and the right governance model[cite: 565].