Data Marketplace Insights and Trends: How Modern Marketers Are Winning With Audience Enrichment

The global data marketplace platform market was valued at $1.49 billion in 2024 and is on track to reach $5.73 billion by 2030, growing at a compound annual rate of 25.2% (Grand View Research, 2025). That pace reflects something most marketers already feel firsthand: the pressure to do more with data has never been greater, and the tools to act on it have never been more sophisticated.

Yet despite the opportunity, 98% of marketers and agencies report facing significant data challenges (Lotame State of Data Collaboration, 2024). First-party data is valuable but inherently limited in reach. Third-party cookies (once the default solution) now cover less of the internet every year. And AI-powered campaigns are only as good as the data you feed them.

Data marketplaces have emerged as a critical piece of the solution: a centralized way to access, enrich, and activate audience intelligence that goes beyond what any single brand can collect on its own. Understanding the modern data marketplace requires looking at the market’s primary drivers, the trends reshaping how marketplaces work, and the resulting impact on your audience strategy.

First, what is a data marketplace?

A data marketplace is a platform where marketers, agencies, and publishers can access, purchase, and activate curated third-party audience data segments, including demographic, behavioral, purchase intent, and lifestyle signals. They’re used to enrich first-party data, extend audience reach, and improve targeting precision.

Think of it as a bridge between the data you own and the insights you need. Your CRM knows who your customers are. A data marketplace helps you understand who they really are and helps you find more people like them.

Open Data Exchanges vs. Curated Marketplaces

Not all data marketplaces work the same way. The original open data exchange model allows any data provider to list segments for purchase with minimal vetting. It offers breadth, but quality is inconsistent and compliance is harder to guarantee.

The industry has been moving decisively toward curated marketplace models, where providers are vetted, segments are validated for accuracy and compliance, and buyers have far greater confidence in what they’re activating. This shift is being accelerated by stricter privacy regulation (GDPR, CCPA, and emerging global frameworks) and by programmatic buyers demanding cleaner supply paths. When your campaign performance depends on signal quality, the provenance of your data matters enormously.

What are the key trends shaping data marketplace use in 2026 and beyond? 

The data marketplace landscape is evolving fast. Here are five trends defining how marketers and advertisers will be expecting to leverage them:

Trend 1: The market is exploding and so are the stakes

The growth numbers reflect genuine momentum. The global data marketplace platform market is forecast to grow from $1.49 billion in 2024 to $5.73 billion by 2030 at a CAGR of 25.2% (Grand View Research, 2025), with B2B data marketplace platforms accounting for over 58% of current revenue share.

The performance gap between leaders and laggards is already stark: top-performing organizations derive 11% of total revenue from data monetization — five times more than their peers (McKinsey, 2025, via Digital Silk). Meanwhile, an estimated 68% of enterprise data remains unused, representing a significant untapped opportunity for brands willing to invest in the right infrastructure.

Trend 2: AI Is transforming audience intelligence

Artificial intelligence has moved from experimentation to everyday execution in data marketplace strategy. Rather than manually browsing and selecting audience segments, marketers are increasingly using AI to surface the most relevant signals for a given campaign objective. The broader shift is moving from manual segment selection to AI-powered signal matching and gaining speed across the industry.

The business case is clear: companies using AI for data enrichment report 25% higher conversion rates and 40% revenue increases (DemandLocal, 2025). Among marketers surveyed, 52% are already leaning into AI as a core part of their data strategy (Lotame State of Data Collaboration, 2024).

Trend 3: Data quality has become the true differentiator

As AI moves from hype to execution, a critical truth is emerging: your AI strategy is only as good as the data behind it. Poor data quality costs companies an average of $15 million annually, and errors compound quickly once flawed data enters automated workflows.

The market has taken notice. 83% of marketers now cite data quality as the single most important factor when choosing a third-party data provider (Experian, 2025). Quality in this context means more than accuracy as it encompasses freshness, interoperability, and privacy-safety. 

Trend 4: Retail Media Networks are reshaping the marketplace landscape

One of the most significant structural shifts in the data marketplace space right now is the rise of retail media networks (RMNs) as first-party data powerhouses. RMN ad spend was projected to reach approximately $62 billion in 2025, with its share of total digital ad spend expected to exceed 20% this year (Verkeer, March 2026). 35% of marketers plan to increase their RMN investment this year.

Driving this is data collaboration: retailers are packaging their purchase and behavioral data into media products, and brands are buying access to activate it programmatically. Instacart recently launched Data Hub, a clean room solution giving CPG brands and agencies privacy-safe access to its first-party grocery data (PR Newswire, 2025). Walmart is co-activating its audience segments with Disney streaming inventory and measuring performance via clean rooms.

The challenge: fewer than 48% of US retail media networks currently offer clean room capabilities (Skai, 2025), creating a gap between where marketers want to take their data strategy and where the infrastructure is today.

Trend 5: The cookieless shift Is accelerating demands for marketplace data

Despite Google reversing its plan to fully deprecate third-party cookies in Chrome, the functional impact is already material: 47% of the open internet is already unreachable via third-party cookies (Omega Trove, 2026). Safari and Firefox have blocked them for years. Only 15% of global marketers feel fully prepared for a cookieless environment (Deloitte, 2025, via Digital Applied).

For marketers, this creates durable, structural demand for cookieless audience solutions: hashed email-based targeting, contextual signals, privacy-safe data collaboration, and identity-resolved marketplace data that doesn’t depend on browser cookies. Data marketplaces powered by flexible, multi-signal identity graphics — with the ability to bridge audiences across environments using both deterministic and high-fidelity probabilistic data — are well-positioned to fill this gap.

How do data marketplaces help enrich audiences?

Audience enrichment is the process of layering third-party data attributes onto your existing first-party audiences to reveal richer behavioral, demographic, and intent signals. A data marketplace is the mechanism that makes this possible at scale.

In practice, enrichment unlocks two capabilities that are difficult to achieve with first-party data alone. The first is a deeper understanding of existing customers: who they are beyond their interactions with your brand, what else they’re buying, what their household looks like, what they’re likely to purchase next. The second is audience extension: identifying net-new prospects who share the attributes of your best customers but aren’t yet in your database.

61% of agencies currently use data enrichment as their primary external data strategy (Lotame State of Data Collaboration, 2024), and the performance case is clear: enriched audiences deliver 20–30% better conversion rates and 25% more sales-qualified leads compared to campaigns targeting unenriched first-party data (DemandLocal, 2025). Average deal sizes grow by 30% and customer lifetime value improves by 10%.

The categories of enrichment data available through modern marketplaces are broad: demographics, purchase intent, B2B firmographics, TV and CTV viewership, social interests, location behavior, and financial indicators. The most effective audience enrichment tools give buyers access to all of these through a single, vetted source network helping eliminate the operational overhead of managing relationships with dozens of individual data providers.

For media buyers, understanding the distinction between audience enrichment and audience extension is critical to building the right activation strategy. They serve different objectives and draw on different data types; confusing the two leads to misaligned campaigns and wasted spend.

What is the role of data collaboration in the marketplace era?

The most forward-looking data marketplaces are evolving beyond simple data transactions. They’re becoming collaboration platforms where brands, publishers, and data providers share permissioned data, model audiences together, and activate against a richer combined dataset than any single party could build alone.

71% of marketers and 64% of agencies are already using data collaboration platforms, and 62% of those not yet using one plan to adopt within the next 12 months (Lotame State of Data Collaboration, 2024).

It’s worth distinguishing data collaboration platforms from data clean rooms, which are frequently conflated. Clean rooms are primarily analytical environments allowing parties to match and measure data without exposing raw records, but they aren’t built for activation at scale. A full data collaboration platform like Lotame’s Spherica Platform goes further: enabling brands to onboard, enrich, analyze, and activate data within a single environment, connecting first-party data to 250+ online and offline sources without the friction of stitching together multiple tools.

For a practical breakdown of what this looks like in action, see data collaboration platform use cases for marketers. The implications for second and third-party data strategy are significant: collaboration-native platforms allow brands to build richer audience models, validate segments before activation, and measure results in a closed loop. 

Are marketers seeing an impact on business performance? 

The investment case for data marketplace strategy is backed by measurable outcomes across the funnel.

At the revenue level, personalization driven by enriched audience data yields a 10–15% revenue uplift on average, with high-performing brands reporting gains up to 25% (McKinsey, via Digital Silk). Companies that invest in superior data-driven customer experience achieve 190% greater revenue growth over three years versus peers. 

The scale of data-driven advertising activity reflects these results. Global remarketing spend — powered by enriched audience targeting — reached $31.3 billion in 2025, up 37% year over year (AppsFlyer Top Data Trends Report, 2025). Mobile video advertising spend is projected to surpass search for the first time in 2026 (AppsFlyer / Kantar Marketing Trends 2026), with audience data quality at the center of how that spend gets allocated and measured.

For media buyers looking to maximize enrichment ROI, the opportunity is clearest in reducing wasted impressions before a campaign launches — starting with a precisely defined, enriched audience rather than optimizing your way to one after the budget is already spent.

What does this mean for my business strategy? 

The data marketplace landscape in 2026 is no longer a supplemental tool for sophisticated marketers. It is increasingly the infrastructure that determines which brands can compete for attention — and which are flying blind.

Three things separate the marketers winning with data marketplace strategy from those still catching up: access to quality, vetted data sources; the enrichment capabilities to layer those signals onto first-party audiences at scale; and platform interoperability that unifies onboarding, enrichment, analysis, and activation.

The brands building these seamless partner connections and capabilities now (ahead of the AI curve, retail media land grab, and the identity resolution challenge) will have a big advantage as signal quality becomes the primary point of competition in digital advertising.

Data Marketplace FAQs for Modern Marketers

As data marketplace strategy evolves, many marketers still have practical questions about how these platforms support real campaign execution. Here are some of the most common.

What is a data marketplace in advertising?

A data marketplace is a platform where marketers can access curated third-party audience data to enrich first-party insights, extend campaign reach, and improve targeting precision across channels such as programmatic, CTV, and retail media.

What is the difference between audience enrichment and audience extension?

Audience enrichment enhances existing customer profiles by layering additional behavioral, demographic, or purchase-intent signals. Audience extension focuses on identifying net-new prospects who share characteristics with high-value customers, enabling brands to scale targeting beyond their owned data.

Why is data quality critical for AI-driven marketing?

AI models rely on accurate, privacy-safe signals to make optimization decisions. Poor data quality can lead to wasted impressions, flawed audience modeling, and reduced campaign performance. High-quality, vetted data sources improve targeting efficiency and help marketers achieve stronger ROI.

How are retail media networks influencing data marketplace strategy?

Retail media networks provide access to valuable first-party purchase and behavioral data. By activating this intelligence through data marketplaces or collaboration platforms, brands can reach consumers closer to the point of purchase and improve campaign measurement.

Are third-party cookies still relevant for audience targeting?

While cookies still exist in some environments, their declining reach across browsers has accelerated demand for cookieless identity solutions such as deterministic ID matching, contextual targeting, and privacy-safe data collaboration.

What is the difference between a data clean room and a data collaboration platform?

Data clean rooms are designed primarily for secure analysis and measurement of audience overlap. Data collaboration platforms go further by enabling marketers to onboard, enrich, model, and activate audiences within a unified environment.

As data marketplaces become foundational to modern audience strategy, the ability to enrich, collaborate, and activate data within a single platform is becoming a key competitive advantage.

Ready to see how Lotame’s audience data marketplace and Spherical platformcan power your enrichment strategy? Explore Lotame’s addressable audience solutions →