Classifieds and Marketplace Monetization in the Age of AI: New Models, Real Levers

For decades, digital marketplaces and classifieds platforms have monetized on the same principle: visibility for a fee, standardized listing packages at flat prices. That “post and pray” approach has reached a structural breaking point. Macro pressure is tightening inventory, generative AI is bypassing the classic filter interfaces platforms have relied on to capture value, and the compute costs behind AI-powered tools cannot simply be passed through. Legacy flat fees are no longer viable.

For our hy Classifieds Report 2026, we conducted 15 expert interviews with executives from European classifieds platforms and marketplaces, including The StepStone Group, Aviv Group, SMG (SMG Swiss Marketplace Group), Ringier, Chrono24 and others. The findings are clear: the future of monetization lies not in optimizing existing visibility models, but in a fundamental shift in strategy. This article summarizes the key takeaways.

Why Classic Pricing Models Are Reaching Their Limits

Marketplaces are success stories of the platform economy. But the underlying principle, intermediation for a commission, visibility for a flat fee, is coming under pressure on several fronts at once. The share prices of global classifieds platforms and marketplace companies make this clear: on average, they lost around 17% in value between January 2023 and April 2026, as an analysis of Yahoo Finance data for our Classifieds Report shows.

Shifting customer expectations and market dynamics. Traditional monetization models based on listings and visibility are increasingly challenged by changing customer expectations and growing pressure to deliver measurable outcomes. A consistent picture emerged across all interviews: customers demand more transparency about the value actually delivered, and are less and less willing to pay for pure exposure. As Georg Konjovic, CEO of karriere.at, puts it: “Traditional pricing models remain dominant because they eliminate cognitive load. The pay-per-listing model offers incredible strategic comfort because it provides a level of cost certainty and internal accountability that performance-driven alternatives have yet to simplify.” But the strategic comfort zone of the flat fee is narrowing.

AI disintermediation as a new threat. At the same time, AI is fundamentally changing platform dynamics. LLMs and AI agents are shifting the focus of the value chain away from pure lead generation toward active curation. The mass generation of low-quality leads by AI tools puts the “conversion” step under pressure and forces platforms to move further down the value chain, from reach supplier to active curator. The result: value shifts from awareness and visibility toward matching, qualification and transaction.

As Dominique Cerri, Senior Director Strategy & Transformation at Aviv Group, observes: “We are seeing a fundamental shift in user expectations. People are bypassing the traditional ‘IKEA model,’ the manual assembly of information, in favor of an AI-driven experience that delivers exactly what they seek with zero friction.” Platforms that continue to rely on static filters and listing lists risk being skipped by conversational AI interfaces and agents.

What matters is this: these developments are unfolding in parallel and reinforcing one another. Addressing only one of them means treating the symptom.

Three Monetization Approaches Now Taking Shape

The question is not whether AI will change marketplace monetization, but which model fits a given business. Our interviews reveal three dominating monetization approaches that are emerging across classifieds and marketplaces.

1. Pay for Visibility: Evolution, Not Elimination

Pay-for-visibility models, listing fees, slot packages, subscriptions, are still widely used. But leading platforms are evolving them: away from simple price lists, toward value-based packaging and usage-based pricing.

A concrete example: ImmoScout24 introduced “ImmoPunkte,” a digital currency used to bill AI-based features and platform services on a usage basis. Around 60% of B2B memberships already run on this model. ImmoScout24 thereby combines its static pay-for-visibility products as a base with ImmoPunkte as a variable surcharge, innovating how classifieds platforms monetize in the age of AI.

At the same time, platforms such as StepStone are betting on subscription-based list-all offerings with their “All Jobs” model: companies bundle all of their open positions into an annual contract at an individual price, a shift from premium single listings to inventory maximization.

2. Hybrid Models with an Outcome Component

The second pattern combines a predictable base fee with a variable, outcome-dependent component. The logic: customers want predictability, but they increasingly accept variable elements when the value delivered is demonstrable.

A concrete example: Chrono24 combines a volume-based monthly base fee (from €199 for up to 25 watches) with a transaction-based commission (from 3.5%) calculated individually per watch by brand, price and condition. Revenue scales with the realized transaction value, a model that links listing exposure to sales success.

Our interviews make one thing clear: pure performance models (pay per click, pay per lead) are being widely tested, but have not yet gained broad traction. As Christopher Ringvold, Chief Product Officer Jobs at Vend, puts it: “We intentionally moved away from our cost-per-applicant model after recognizing a gap in market readiness. Our priority is to align our commercial structures with our partners’ current maturity, ensuring we don’t outpace the industry’s ability to adopt new standards.” The future lies in hybrid approaches that combine predictability and value orientation. Axel Konjack, Head Global Marketplaces at Ringier AG, confirms: “As intentional search behavior becomes more diverse and fragmented, classifieds must evolve from destination platforms into distribution and matching engines. The future belongs to businesses that swiftly embed themselves wherever attention materialises in the new AI reality.”

3. Value-Based Pricing through Granular Segmentation

The third lever is not a new pricing metric but a new pricing logic: away from one-size-fits-all, toward value-based differentiation. Our report shows how leading platforms increasingly build their pricing architecture along customer segments, usage intensity, inventory quality and delivered business value.

A concrete example: AutoScout24.ch introduced a “Car Value Factor” that scales the monthly fee between 0.8 and 1.2 depending on the average vehicle value of the inventory. As Alberto Sanz, Managing Director Automotive at Swiss Marketplace Group, explains: “We managed the transition to value-based pricing by leading with incentives. By ensuring that one market segment paid less, we proved that the model was a recalibration of value, not just a price increase.”

Jasmin Hakenmüller, Pricing Lead at Kleinanzeigen, underscores the urgency: “One-size-fits-all pricing and product models are no longer sufficient. We observe clear limits to customers’ willingness to pay under traditional structures, making a shift toward more sophisticated, granular segmentation a strategic necessity for long-term viability.”

From Intermediation to Value Creation: Why Conversion Ownership Is the New Moat

Behind the new monetization models lies a fundamental paradigm shift: the value of a marketplace no longer resides primarily in intermediation, but in control over the conversion process and the data that comes with it. Proprietary data, deep customer relationships and transaction ownership are, according to our report, the ultimate defense against AI disintermediation.

What this means in concrete terms:

1. Proprietary data as a line of defense. Platforms that own transaction data, usage behavior and matching outcomes are not easily replicated by AI agents. Chrono24, for instance, draws on more than 600,000 analyzed transactions to offer “ChronoPulse,” the only watch-specific price index based on real sales data, a proprietary data advantage that simultaneously generates SEO traffic and draws buyers to the platform.
2. Seeker monetization as a new revenue pool. Traditionally, platforms monetize the supply side (advertisers). But in markets where demand exceeds supply, a new opportunity emerges: monetizing the seekers. ImmoScout24 already generates 179 million euros in revenue in its seeker segment (FY2025), 60% of it through seeker subscriptions. In the jobs space, Profession.hu has launched a candidate product that gives job seekers prioritized access and information advantages, an entirely new B2C revenue stream.
3. Conversion ownership as a shield. When AI agents generate leads en masse, the value of the individual lead falls. Platforms must move further down the value chain, from lead generation to lead curation, matching and qualification. As Georg Konjovic puts it: “Our revenue model is tied to the successful delivery of talent, not mere traffic. To remain relevant, we must own the conversion. If candidates begin bypassing our ecosystem, we effectively lose our position in the value chain.”

The five key takeaways platform operators should put on their monetization roadmap now, from hybrid outcome-based models and value-based strategy to seeker monetization, AI productization & GEO and conversion ownership, are set out in detail in our hy Classifieds Report 2026, based on our expert interviews.

Implementation: What Corporate Leaders Need to Decide Now

Marketplace monetization in the age of AI is not an optimization task, it is a strategic course-setting decision. From the findings of our report, we derive three concrete recommendations for action:

1. Quantify the platform’s value contribution. Before introducing a new pricing model, it must be clear what measurable value the platform creates for the customers. Without this baseline, there is no foundation for usage-based or outcome-based pricing. A Pricing Opportunity Check, as we conduct it at hy, identifies the biggest monetization levers within four to six weeks.
2. Pilot the monetization model. No model works perfectly from the start. We recommend a controlled pilot with a user cohort, clear KPIs (conversion rate, ARPU, churn) and a 90-day time frame. Crucially, the model must be technically supported by granular usage data.
3. Build conversion ownership. The decisive strategic question is not which pricing model comes next, but what the platform controls within the transaction and whether that position is defensible against AI disintermediation. Proprietary data, deep customer relationships and technical integrations form the shield.

What PE investors should additionally keep in mind: for portfolio companies with classifieds and marketplace models, the monetization strategy is a direct EBITDA lever. A structured shift toward value-based monetization strategies can significantly increase enterprise value, provided it is executed on a data-driven basis and with a clear implementation roadmap.